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1,803.06367
The supernova remnant population in the very-high-energy sky: prospects for CTA
The detection of very-high-energy gamma rays from supernova remnant shells testifies of the acceleration of particles at strong shocks. Many aspects of the particle acceleration remain however unclear. The study of individual objects is very helpful, but the study of the entire population of SNRs detected in this range and its characteristics can also bring valuable science. Using Monte-Carlo simulations, the population of shells bright in the TeV and multi-TeV range can be simulated. The results of these simulations aim at being compared with observations of in struments operating in these ranges, such as the Cherenkov Telescope Array (CTA). Our results suggest that CTA should be able to effectively constrain the slope of particles accelerated at SNRs and the electron-to-proton ratio.
astro-ph.HE
the detection of veryhighenergy gamma rays from supernova remnant shells testifies of the acceleration of particles at strong shocks many aspects of the particle acceleration remain however unclear the study of individual objects is very helpful but the study of the entire population of snrs detected in this range and its characteristics can also bring valuable science using montecarlo simulations the population of shells bright in the tev and multitev range can be simulated the results of these simulations aim at being compared with observations of in struments operating in these ranges such as the cherenkov telescope array cta our results suggest that cta should be able to effectively constrain the slope of particles accelerated at snrs and the electrontoproton ratio
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1,803.06368
Doppelg\"anger dark energy: modified gravity with non-universal couplings after GW170817
Gravitational Wave (GW) astronomy severely narrowed down the theoretical space for scalar-tensor theories. We propose a new class of attractor models for Horndeski action in which GWs propagate at the speed of light in the nearby universe but not in the past. To do so we derive new solutions to the interacting dark sector in which the ratio of dark energy and dark matter remains constant, which we refer to as doppelg\"anger dark energy (DDE). We then remove the interaction between dark matter and dark energy by a suitable change of variables. The accelerated expansion that (we) baryons observe is due to a conformal coupling to the dark energy scalar field. We show how in this context it is possible to find a non trivial subset of solutions in which GWs propagate at the speed of light only at low red-shifts. The model is an attractor, thus reaching the limit $c_{T}\to1$ relatively fast. However, the effect of baryons turns out to be non-negligible and severely constrains the form of the Lagrangian. In passing, we found that in the simplest DDE models the no-ghost conditions for perturbations require a non-universal coupling to gravity. In the end, we comment on possible ways to solve the lack of matter domination stage for DDE models.
gr-qc
gravitational wave gw astronomy severely narrowed down the theoretical space for scalartensor theories we propose a new class of attractor models for horndeski action in which gws propagate at the speed of light in the nearby universe but not in the past to do so we derive new solutions to the interacting dark sector in which the ratio of dark energy and dark matter remains constant which we refer to as doppelganger dark energy dde we then remove the interaction between dark matter and dark energy by a suitable change of variables the accelerated expansion that we baryons observe is due to a conformal coupling to the dark energy scalar field we show how in this context it is possible to find a non trivial subset of solutions in which gws propagate at the speed of light only at low redshifts the model is an attractor thus reaching the limit c_tto1 relatively fast however the effect of baryons turns out to be nonnegligible and severely constrains the form of the lagrangian in passing we found that in the simplest dde models the noghost conditions for perturbations require a nonuniversal coupling to gravity in the end we comment on possible ways to solve the lack of matter domination stage for dde models
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1,803.06369
A Family of Minimal and Renormalizable Rectangle Exchange Maps
A domain exchange map (DEM) is a dynamical system defined on a smooth Jordan domain which is a piecewise translation. We explain how to use cut-and-project sets to construct minimal DEMs. Specializing to the case in which the domain is a square and the cut-and-project set is associated to a Galois lattice, we construct an infinite family of DEMs in which each map is associated to a PV number. We develop a renormalization scheme for these DEMs. Certain DEMs in the family can be composed to create multistage, renormalizable DEMs.
math.DS
a domain exchange map dem is a dynamical system defined on a smooth jordan domain which is a piecewise translation we explain how to use cutandproject sets to construct minimal dems specializing to the case in which the domain is a square and the cutandproject set is associated to a galois lattice we construct an infinite family of dems in which each map is associated to a pv number we develop a renormalization scheme for these dems certain dems in the family can be composed to create multistage renormalizable dems
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1,803.0637
First Calorimetric Measurement of Electron Capture in ${}^{193}$Pt with a Transition Edge Sensor
The neutrino mass can be extracted from a high statistics, high resolution calorimetric spectrum of electron capture in ${}^{163}$Ho. In order to better understand the shape of the calorimetric electron capture spectrum, a second isotope was measured with a close to ideal absorber-source configuration. ${}^{193}$Pt was created by irradiating a ${}^{192}$Pt-enriched platinum foil in a nuclear reactor. This Pt-in-Pt absorber was designed to have a nearly ideal absorber-source configuration. The measured ${}^{193}$Pt calorimetric electron-capture spectrum provides an independent check on the corresponding theoretical calculations, which have thus far been compared only for ${}^{163}$Ho. The first experimental and theoretically-calculated spectra from this ${}^{193}$Pt-in-Pt absorber are presented and overlaid for preliminary comparison of theory with experiment.
physics.atom-ph physics.ins-det
the neutrino mass can be extracted from a high statistics high resolution calorimetric spectrum of electron capture in 163ho in order to better understand the shape of the calorimetric electron capture spectrum a second isotope was measured with a close to ideal absorbersource configuration 193pt was created by irradiating a 192ptenriched platinum foil in a nuclear reactor this ptinpt absorber was designed to have a nearly ideal absorbersource configuration the measured 193pt calorimetric electroncapture spectrum provides an independent check on the corresponding theoretical calculations which have thus far been compared only for 163ho the first experimental and theoreticallycalculated spectra from this 193ptinpt absorber are presented and overlaid for preliminary comparison of theory with experiment
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1,803.06371
Ludvig Lorenz (1867) on Light and Electricity
Independent of Maxwell, in 1867 the Danish physicist L. V. Lorenz proposed a theory in which he identified light with electrical oscillations propagating in a very poor conductor. Lorenz's electrodynamic theory of light, which formally was equivalent to Maxwell's theory but physically quite different from it, was published in well-known journals in German and English but soon fell into oblivion. In 1867 Lorenz also published a paper on his new theory in a semi-popular Danish journal which has generally been overlooked. This other paper is here translated into English and provided with the necessary annotations.
physics.hist-ph
independent of maxwell in 1867 the danish physicist l v lorenz proposed a theory in which he identified light with electrical oscillations propagating in a very poor conductor lorenzs electrodynamic theory of light which formally was equivalent to maxwells theory but physically quite different from it was published in wellknown journals in german and english but soon fell into oblivion in 1867 lorenz also published a paper on his new theory in a semipopular danish journal which has generally been overlooked this other paper is here translated into english and provided with the necessary annotations
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1,803.06372
Stochastic basins of attraction and generalized committor functions
We generalize the concept of basin of attraction of a stable state in order to facilitate the analysis of dynamical systems with noise and to assess stability properties of metastable states and long transients. To this end we examine the notions of mean sojourn times and absorption probabilities for Markov chains and study their relation to the basins of attraction. Our approach is applicable to a large variety of problems since in most cases the transfer operator associated to a dynamical system can be approximated by a Markov chain.
math.DS nlin.CD
we generalize the concept of basin of attraction of a stable state in order to facilitate the analysis of dynamical systems with noise and to assess stability properties of metastable states and long transients to this end we examine the notions of mean sojourn times and absorption probabilities for markov chains and study their relation to the basins of attraction our approach is applicable to a large variety of problems since in most cases the transfer operator associated to a dynamical system can be approximated by a markov chain
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1,803.06373
Adversarial Logit Pairing
In this paper, we develop improved techniques for defending against adversarial examples at scale. First, we implement the state of the art version of adversarial training at unprecedented scale on ImageNet and investigate whether it remains effective in this setting - an important open scientific question (Athalye et al., 2018). Next, we introduce enhanced defenses using a technique we call logit pairing, a method that encourages logits for pairs of examples to be similar. When applied to clean examples and their adversarial counterparts, logit pairing improves accuracy on adversarial examples over vanilla adversarial training; we also find that logit pairing on clean examples only is competitive with adversarial training in terms of accuracy on two datasets. Finally, we show that adversarial logit pairing achieves the state of the art defense on ImageNet against PGD white box attacks, with an accuracy improvement from 1.5% to 27.9%. Adversarial logit pairing also successfully damages the current state of the art defense against black box attacks on ImageNet (Tramer et al., 2018), dropping its accuracy from 66.6% to 47.1%. With this new accuracy drop, adversarial logit pairing ties with Tramer et al.(2018) for the state of the art on black box attacks on ImageNet.
cs.LG stat.ML
in this paper we develop improved techniques for defending against adversarial examples at scale first we implement the state of the art version of adversarial training at unprecedented scale on imagenet and investigate whether it remains effective in this setting an important open scientific question athalye et al 2018 next we introduce enhanced defenses using a technique we call logit pairing a method that encourages logits for pairs of examples to be similar when applied to clean examples and their adversarial counterparts logit pairing improves accuracy on adversarial examples over vanilla adversarial training we also find that logit pairing on clean examples only is competitive with adversarial training in terms of accuracy on two datasets finally we show that adversarial logit pairing achieves the state of the art defense on imagenet against pgd white box attacks with an accuracy improvement from 15 to 279 adversarial logit pairing also successfully damages the current state of the art defense against black box attacks on imagenet tramer et al 2018 dropping its accuracy from 666 to 471 with this new accuracy drop adversarial logit pairing ties with tramer et al2018 for the state of the art on black box attacks on imagenet
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1,803.06374
Ab Initio Electron-Phonon Interactions Using Atomic Orbital Wavefunctions
The interaction between electrons and lattice vibrations determines key physical properties of materials, including their electrical and heat transport, excited electron dynamics, phase transitions, and superconductivity. We present a new ab initio method that employs atomic orbital (AO) wavefunctions to compute the electron-phonon (e-ph) interactions in materials and interpolate the e-ph coupling matrix elements to fine Brillouin zone grids. We detail the numerical implementation of such AO-based e-ph calculations, and benchmark them against direct density functional theory calculations and Wannier function (WF) interpolation. The key advantages of AOs over WFs for e-ph calculations are outlined. Since AOs are fixed basis functions associated with the atoms, they circumvent the need to generate a material-specific localized basis set with a trial-and-error approach, as is needed in WFs. Therefore, AOs are ideal to compute e-ph interactions in chemically and structurally complex materials for which WFs are challenging to generate, and are also promising for high-throughput materials discovery. While our results focus on AOs, the formalism we present generalizes e-ph calculations to arbitrary localized basis sets, with WFs recovered as a special case.
cond-mat.mtrl-sci
the interaction between electrons and lattice vibrations determines key physical properties of materials including their electrical and heat transport excited electron dynamics phase transitions and superconductivity we present a new ab initio method that employs atomic orbital ao wavefunctions to compute the electronphonon eph interactions in materials and interpolate the eph coupling matrix elements to fine brillouin zone grids we detail the numerical implementation of such aobased eph calculations and benchmark them against direct density functional theory calculations and wannier function wf interpolation the key advantages of aos over wfs for eph calculations are outlined since aos are fixed basis functions associated with the atoms they circumvent the need to generate a materialspecific localized basis set with a trialanderror approach as is needed in wfs therefore aos are ideal to compute eph interactions in chemically and structurally complex materials for which wfs are challenging to generate and are also promising for highthroughput materials discovery while our results focus on aos the formalism we present generalizes eph calculations to arbitrary localized basis sets with wfs recovered as a special case
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1,803.06375
Mobile phone records to feed activity-based travel demand models: MATSim for studying a cordon toll policy in Barcelona
Activity-based models appeared as an answer to the limitations of the traditional trip-based and tour-based four-stage models. The fundamental assumption of activity-based models is that travel demand is originated from people performing their daily activities. This is why they include a consistent representation of time, of the persons and households, time-dependent routing, and microsimulation of travel demand and traffic. In spite of their potential to simulate traffic demand management policies, their practical application is still limited. One of the main reasons is that these models require a huge amount of very detailed input data hard to get with surveys. However, the pervasive use of mobile devices has brought a valuable new source of data. The work presented here has a twofold objective: first, to demonstrate the capability of mobile phone records to feed activity-based transport models, and, second, to assert the advantages of using activity-based models to estimate the effects of traffic demand management policies. Activity diaries for the metropolitan area of Barcelona are reconstructed from mobile phone records. This information is then employed as input for building a transport MATSim model of the city. The model calibration and validation process proves the quality of the activity diaries obtained. The possible impacts of a cordon toll policy applied to two different areas of the city and at different times of the day is then studied. Our results show the way in which the modal share is modified in each of the considered scenario. The possibility of evaluating the effects of the policy at both aggregated and traveller level, together with the ability of the model to capture policy impacts beyond the cordon toll area confirm the advantages of activity-based models for the evaluation of traffic demand management policies.
physics.soc-ph cs.SI
activitybased models appeared as an answer to the limitations of the traditional tripbased and tourbased fourstage models the fundamental assumption of activitybased models is that travel demand is originated from people performing their daily activities this is why they include a consistent representation of time of the persons and households timedependent routing and microsimulation of travel demand and traffic in spite of their potential to simulate traffic demand management policies their practical application is still limited one of the main reasons is that these models require a huge amount of very detailed input data hard to get with surveys however the pervasive use of mobile devices has brought a valuable new source of data the work presented here has a twofold objective first to demonstrate the capability of mobile phone records to feed activitybased transport models and second to assert the advantages of using activitybased models to estimate the effects of traffic demand management policies activity diaries for the metropolitan area of barcelona are reconstructed from mobile phone records this information is then employed as input for building a transport matsim model of the city the model calibration and validation process proves the quality of the activity diaries obtained the possible impacts of a cordon toll policy applied to two different areas of the city and at different times of the day is then studied our results show the way in which the modal share is modified in each of the considered scenario the possibility of evaluating the effects of the policy at both aggregated and traveller level together with the ability of the model to capture policy impacts beyond the cordon toll area confirm the advantages of activitybased models for the evaluation of traffic demand management policies
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1,803.06376
A Generalised Method for Empirical Game Theoretic Analysis
This paper provides theoretical bounds for empirical game theoretical analysis of complex multi-agent interactions. We provide insights in the empirical meta game showing that a Nash equilibrium of the meta-game is an approximate Nash equilibrium of the true underlying game. We investigate and show how many data samples are required to obtain a close enough approximation of the underlying game. Additionally, we extend the meta-game analysis methodology to asymmetric games. The state-of-the-art has only considered empirical games in which agents have access to the same strategy sets and the payoff structure is symmetric, implying that agents are interchangeable. Finally, we carry out an empirical illustration of the generalised method in several domains, illustrating the theory and evolutionary dynamics of several versions of the AlphaGo algorithm (symmetric), the dynamics of the Colonel Blotto game played by human players on Facebook (symmetric), and an example of a meta-game in Leduc Poker (asymmetric), generated by the PSRO multi-agent learning algorithm.
cs.GT cs.MA
this paper provides theoretical bounds for empirical game theoretical analysis of complex multiagent interactions we provide insights in the empirical meta game showing that a nash equilibrium of the metagame is an approximate nash equilibrium of the true underlying game we investigate and show how many data samples are required to obtain a close enough approximation of the underlying game additionally we extend the metagame analysis methodology to asymmetric games the stateoftheart has only considered empirical games in which agents have access to the same strategy sets and the payoff structure is symmetric implying that agents are interchangeable finally we carry out an empirical illustration of the generalised method in several domains illustrating the theory and evolutionary dynamics of several versions of the alphago algorithm symmetric the dynamics of the colonel blotto game played by human players on facebook symmetric and an example of a metagame in leduc poker asymmetric generated by the psro multiagent learning algorithm
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1,803.06377
Spread of Information with Confirmation Bias in Cyber-Social Networks
This paper provides a model to investigate information spreading over cyber-social network of agents communicating with each other. The cyber-social network considered here comprises individuals and news agencies. Each individual holds a belief represented by a scalar. Individuals receive information from news agencies that are closer to their belief, confirmation bias is explicitly incorporated into the model. The proposed dynamics of cyber-social networks is adopted from DeGroot-Friedkin model, where the individual's opinion update mechanism is a convex combination of his innate opinion, his neighbors' opinions at the previous time step (obtained from the social network), and the opinions passed along by news agencies from cyber layer which he follows. The characteristics of the interdependent social and cyber networks are radically different here: the social network relies on trust and hence static while the news agencies are highly dynamic since they are weighted as a function of the distance between an individual state and the state of news agency to account for confirmation bias. The conditions for convergence of the aforementioned dynamics to a unique equilibrium are characterized. The estimation and exact computation of the steady-state values under non-linear and linear state-dependent weight functions are provided. Finally, the impact of polarization in the opinions of news agencies on the public opinion evolution is numerically analyzed in the context of the well-known Krackhardt's advice network.
cs.SI cs.MA cs.SY math.OC
this paper provides a model to investigate information spreading over cybersocial network of agents communicating with each other the cybersocial network considered here comprises individuals and news agencies each individual holds a belief represented by a scalar individuals receive information from news agencies that are closer to their belief confirmation bias is explicitly incorporated into the model the proposed dynamics of cybersocial networks is adopted from degrootfriedkin model where the individuals opinion update mechanism is a convex combination of his innate opinion his neighbors opinions at the previous time step obtained from the social network and the opinions passed along by news agencies from cyber layer which he follows the characteristics of the interdependent social and cyber networks are radically different here the social network relies on trust and hence static while the news agencies are highly dynamic since they are weighted as a function of the distance between an individual state and the state of news agency to account for confirmation bias the conditions for convergence of the aforementioned dynamics to a unique equilibrium are characterized the estimation and exact computation of the steadystate values under nonlinear and linear statedependent weight functions are provided finally the impact of polarization in the opinions of news agencies on the public opinion evolution is numerically analyzed in the context of the wellknown krackhardts advice network
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1,803.06378
Characterizing Ion Flows Across a Dipolarization Jet
The structure of dipolarization jets with finite width in the dawn-dusk direction relevant to magnetic reconnection in the Earth's magnetotail is explored with particle-in-cell simulations. We carry out Riemann simulations of the evolution of the jet in the dawn-dusk, north-south plane to investigate the dependence of the jet structure on the jet width in the dawn-dusk direction. We find that the magnetic field and Earth-directed ion flow structure depend on the dawn-dusk width. A reversal in the usual Hall magnetic field near the center of the current sheet on the dusk side of larger jets is observed. For small widths, the maximum velocity of the Earthward flow is significantly reduced below the theoretical limit of the upstream Alfv\'en speed. However, the ion flow speed approaches this limit once the width exceeds the ion Larmor radius based on the normal magnetic field, $B_z$.
physics.space-ph physics.plasm-ph
the structure of dipolarization jets with finite width in the dawndusk direction relevant to magnetic reconnection in the earths magnetotail is explored with particleincell simulations we carry out riemann simulations of the evolution of the jet in the dawndusk northsouth plane to investigate the dependence of the jet structure on the jet width in the dawndusk direction we find that the magnetic field and earthdirected ion flow structure depend on the dawndusk width a reversal in the usual hall magnetic field near the center of the current sheet on the dusk side of larger jets is observed for small widths the maximum velocity of the earthward flow is significantly reduced below the theoretical limit of the upstream alfven speed however the ion flow speed approaches this limit once the width exceeds the ion larmor radius based on the normal magnetic field b_z
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1,803.06379
Photon detector system timing performance in the DUNE 35-ton prototype liquid argon time projection chamber
The 35-ton prototype for the Deep Underground Neutrino Experiment far detector was a single-phase liquid argon time projection chamber with an integrated photon detector system, all situated inside a membrane cryostat. The detector took cosmic-ray data for six weeks during the period of February 1, 2016 to March 12, 2016. The performance of the photon detection system was checked with these data. An installed photon detector was demonstrated to measure the arrival times of cosmic-ray muons with a resolution better than 32 ns, limited by the timing of the trigger system. A measurement of the timing resolution using closely-spaced calibration pulses yielded a resolution of 15 ns for pulses at a level of 6 photo-electrons. Scintillation light from cosmic-ray muons was observed to be attenuated with increasing distance with a characteristic length of $155 \pm 28$ cm.
physics.ins-det hep-ex
the 35ton prototype for the deep underground neutrino experiment far detector was a singlephase liquid argon time projection chamber with an integrated photon detector system all situated inside a membrane cryostat the detector took cosmicray data for six weeks during the period of february 1 2016 to march 12 2016 the performance of the photon detection system was checked with these data an installed photon detector was demonstrated to measure the arrival times of cosmicray muons with a resolution better than 32 ns limited by the timing of the trigger system a measurement of the timing resolution using closelyspaced calibration pulses yielded a resolution of 15 ns for pulses at a level of 6 photoelectrons scintillation light from cosmicray muons was observed to be attenuated with increasing distance with a characteristic length of 155 pm 28 cm
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1,803.0638
Distributed Optimization for Second-Order Multi-Agent Systems with Dynamic Event-Triggered Communication
In this paper, we propose a fully distributed algorithm for second-order continuous-time multi-agent systems to solve the distributed optimization problem. The global objective function is a sum of private cost functions associated with the individual agents and the interaction between agents is described by a weighted undirected graph. We show the exponential convergence of the proposed algorithm if the underlying graph is connected, each private cost function is locally gradient-Lipschitz-continuous, and the global objective function is restricted strongly convex with respect to the global minimizer. Moreover, to reduce the overall need of communication, we then propose a dynamic event-triggered communication mechanism that is free of Zeno behavior. It is shown that the exponential convergence is achieved if the private cost functions are also globally gradient-Lipschitz-continuous. Numerical simulations are provided to illustrate the effectiveness of the theoretical results.
math.OC
in this paper we propose a fully distributed algorithm for secondorder continuoustime multiagent systems to solve the distributed optimization problem the global objective function is a sum of private cost functions associated with the individual agents and the interaction between agents is described by a weighted undirected graph we show the exponential convergence of the proposed algorithm if the underlying graph is connected each private cost function is locally gradientlipschitzcontinuous and the global objective function is restricted strongly convex with respect to the global minimizer moreover to reduce the overall need of communication we then propose a dynamic eventtriggered communication mechanism that is free of zeno behavior it is shown that the exponential convergence is achieved if the private cost functions are also globally gradientlipschitzcontinuous numerical simulations are provided to illustrate the effectiveness of the theoretical results
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1,803.06381
An Edge Computing Empowered Radio Access Network With UAV-Mounted FSO Fronthaul and Backhaul: Key Challenges and Approaches
One promising approach to address the supply-demand mismatch between the terrestrial infrastructure and the temporary and/or unexpected traffic demands is to leverage the unmanned aerial vehicle (UAV) technologies. Motivated by the recent advancement of UAV technologies and retromodulator based free space optical communication, we propose a novel edge-computing empowered radio access network architecture where the fronthaul and backhaul links are mounted on the UAVs for rapid event response and flexible deployment. The implementation of hardware and networking technologies for the proposed architecture are investigated. Due to the limited payload and endurance as well as the high mobility of UAVs, research challenges related to the communication resource management and recent research progress are reported.
cs.NI
one promising approach to address the supplydemand mismatch between the terrestrial infrastructure and the temporary andor unexpected traffic demands is to leverage the unmanned aerial vehicle uav technologies motivated by the recent advancement of uav technologies and retromodulator based free space optical communication we propose a novel edgecomputing empowered radio access network architecture where the fronthaul and backhaul links are mounted on the uavs for rapid event response and flexible deployment the implementation of hardware and networking technologies for the proposed architecture are investigated due to the limited payload and endurance as well as the high mobility of uavs research challenges related to the communication resource management and recent research progress are reported
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1,803.06382
Harmonic spinors on the Davis hyperbolic 4-manifold
In this paper we use the G-spin theorem to show that the Davis hyperbolic 4-manifold admits harmonic spinors. This is the first example of a closed hyperbolic 4-manifold that admits harmonic spinors. We also explicitly describe the Spinor bundle of a spin hyperbolic 2- or 4-manifold and show how to calculated the subtle sign terms in the G-spin theorem for an isometry, with isolated fixed points, of a closed spin hyperbolic 2- or 4-manifold.
math.GT math.DG
in this paper we use the gspin theorem to show that the davis hyperbolic 4manifold admits harmonic spinors this is the first example of a closed hyperbolic 4manifold that admits harmonic spinors we also explicitly describe the spinor bundle of a spin hyperbolic 2 or 4manifold and show how to calculated the subtle sign terms in the gspin theorem for an isometry with isolated fixed points of a closed spin hyperbolic 2 or 4manifold
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1,803.06383
A prediction criterion for working correlation structure selection in GEE
Generalized estimating equations (GEE) is one of the most commonly used methods for marginal regression analysis of longitudinal data, especially with discrete outcomes. The GEE method models the association among the responses of a subject through a working correlation matrix and correct specification of the working correlation structure ensures efficient estimation of the regression parameters. This study proposes a predicted residual sum of squares (PRESS) statistic as a working correlation selection criterion in GEE. An extensive simulation study is designed to assess the performance of the proposed GEE PRESS criterion and to compare its performance with well-known existing criteria in the literature. The results show that the GEE PRESS criterion has better performance than the weighted error sum of squares SC criterion in all cases and is comparable with that of other existing criteria when the true working correlation structure is AR(1) or exchangeable. Lastly, the working correlation selection criteria are illustrated with the Coronary Artery Risk Development in Young Adults study.
stat.ME
generalized estimating equations gee is one of the most commonly used methods for marginal regression analysis of longitudinal data especially with discrete outcomes the gee method models the association among the responses of a subject through a working correlation matrix and correct specification of the working correlation structure ensures efficient estimation of the regression parameters this study proposes a predicted residual sum of squares press statistic as a working correlation selection criterion in gee an extensive simulation study is designed to assess the performance of the proposed gee press criterion and to compare its performance with wellknown existing criteria in the literature the results show that the gee press criterion has better performance than the weighted error sum of squares sc criterion in all cases and is comparable with that of other existing criteria when the true working correlation structure is ar1 or exchangeable lastly the working correlation selection criteria are illustrated with the coronary artery risk development in young adults study
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1,803.06384
Star formation toward the H~II region IRAS 10427-6032
The formation and properties of star clusters formed at the edges of H II regions are poorly known. We study stellar content, physical conditions, and star formation processes around a relatively unknown young H II region IRAS 10427-6032, located in the southern outskirts of the Carina Nebula. We make use of near-IR data from VISTA, mid-IR from Spitzer and WISE, far-IR from Herschel, sub-mm from ATLASGAL, and 843 MHz radio-continuum data. Using multi-band photometry, we find a total of 5 Class I and 29 Class II young stellar object (YSO) candidates, most of which newly identified, in the 5'$\times$5' region centered on the IRAS source position. Modeling of the spectral energy distribution for selected YSO candidates using radiative transfer models shows that most of these candidates are intermediate mass YSOs in their early evolutionary stages. A majority of the YSO candidates are found to be coincident with the cold dense clump at the western rim of the H II region. Lyman continuum luminosity calculation using radio emission indicates the spectral type of the ionizing source to be earlier than B0.5-B1. We identified a candidate massive star possibly responsible for the H II region with an estimated spectral type B0-B0.5. The temperature and column density maps of the region constructed by performing pixel-wise modified blackbody fits to the thermal dust emission using the far-IR data show a high column density shell-like morphology around the H II region, and low column density (0.6 $\times$ 10$^{22}$ cm$^{-2}$) and high temperature ($\sim$21 K) matter within the H II region. Based on the morphology of the region in the ionized and the molecular gas, and the comparison between the estimated timescales of the H II region and the YSO candidates in the clump, we argue that the enhanced star-formation at the western rim of the H II region is likely due to compression by the ionized gas.
astro-ph.GA astro-ph.SR
the formation and properties of star clusters formed at the edges of h ii regions are poorly known we study stellar content physical conditions and star formation processes around a relatively unknown young h ii region iras 104276032 located in the southern outskirts of the carina nebula we make use of nearir data from vista midir from spitzer and wise farir from herschel submm from atlasgal and 843 mhz radiocontinuum data using multiband photometry we find a total of 5 class i and 29 class ii young stellar object yso candidates most of which newly identified in the 5times5 region centered on the iras source position modeling of the spectral energy distribution for selected yso candidates using radiative transfer models shows that most of these candidates are intermediate mass ysos in their early evolutionary stages a majority of the yso candidates are found to be coincident with the cold dense clump at the western rim of the h ii region lyman continuum luminosity calculation using radio emission indicates the spectral type of the ionizing source to be earlier than b05b1 we identified a candidate massive star possibly responsible for the h ii region with an estimated spectral type b0b05 the temperature and column density maps of the region constructed by performing pixelwise modified blackbody fits to the thermal dust emission using the farir data show a high column density shelllike morphology around the h ii region and low column density 06 times 1022 cm2 and high temperature sim21 k matter within the h ii region based on the morphology of the region in the ionized and the molecular gas and the comparison between the estimated timescales of the h ii region and the yso candidates in the clump we argue that the enhanced starformation at the western rim of the h ii region is likely due to compression by the ionized gas
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1,803.06385
The $\alpha$-normal labeling method for computing the $p$-spectral radii of uniform hypergraphs
Let $G$ be an $r$-uniform hypergraph of order $n$. For each $p\geq 1$, the $p$-spectral radius $\lambda^{(p)}(G)$ is defined as \[ \lambda^{(p)}(G):=\max_{|x_1|^p+\cdots+|x_n|^p=1} r\sum_{\{i_1,\ldots,i_r\}\in E(G)}x_{i_1}\cdots x_{i_r}. \] The $p$-spectral radius was introduced by Keevash-Lenz-Mubayi, and subsequently studied by Nikiforov in 2014. The most extensively studied case is when $p=r$, and $\lambda^{(r)}(G)$ is called the spectral radius of $G$. The $\alpha$-normal labeling method, which was introduced by Lu and Man in 2014, is effective method for computing the spectral radii of uniform hypergraphs. It labels each corner of an edge by a positive number so that the sum of the corner labels at any vertex is $1$ while the product of all corner labels at any edge is $\alpha$. Since then, this method has been used by many researchers in studying $\lambda^{(r)}(G)$. In this paper, we extend Lu and Man's $\alpha$-normal labeling method to the $p$-spectral radii of uniform hypergraphs for $p\ne r$; and find some applications.
math.CO
let g be an runiform hypergraph of order n for each pgeq 1 the pspectral radius lambdapg is defined as lambdapgmax_x_1pcdotsx_np1 rsum_i_1ldotsi_rin egx_i_1cdots x_i_r the pspectral radius was introduced by keevashlenzmubayi and subsequently studied by nikiforov in 2014 the most extensively studied case is when pr and lambdarg is called the spectral radius of g the alphanormal labeling method which was introduced by lu and man in 2014 is effective method for computing the spectral radii of uniform hypergraphs it labels each corner of an edge by a positive number so that the sum of the corner labels at any vertex is 1 while the product of all corner labels at any edge is alpha since then this method has been used by many researchers in studying lambdarg in this paper we extend lu and mans alphanormal labeling method to the pspectral radii of uniform hypergraphs for pne r and find some applications
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1,803.06386
Forecasting Economics and Financial Time Series: ARIMA vs. LSTM
Forecasting time series data is an important subject in economics, business, and finance. Traditionally, there are several techniques to effectively forecast the next lag of time series data such as univariate Autoregressive (AR), univariate Moving Average (MA), Simple Exponential Smoothing (SES), and more notably Autoregressive Integrated Moving Average (ARIMA) with its many variations. In particular, ARIMA model has demonstrated its outperformance in precision and accuracy of predicting the next lags of time series. With the recent advancement in computational power of computers and more importantly developing more advanced machine learning algorithms and approaches such as deep learning, new algorithms are developed to forecast time series data. The research question investigated in this article is that whether and how the newly developed deep learning-based algorithms for forecasting time series data, such as "Long Short-Term Memory (LSTM)", are superior to the traditional algorithms. The empirical studies conducted and reported in this article show that deep learning-based algorithms such as LSTM outperform traditional-based algorithms such as ARIMA model. More specifically, the average reduction in error rates obtained by LSTM is between 84 - 87 percent when compared to ARIMA indicating the superiority of LSTM to ARIMA. Furthermore, it was noticed that the number of training times, known as "epoch" in deep learning, has no effect on the performance of the trained forecast model and it exhibits a truly random behavior.
cs.LG q-fin.ST stat.ML
forecasting time series data is an important subject in economics business and finance traditionally there are several techniques to effectively forecast the next lag of time series data such as univariate autoregressive ar univariate moving average ma simple exponential smoothing ses and more notably autoregressive integrated moving average arima with its many variations in particular arima model has demonstrated its outperformance in precision and accuracy of predicting the next lags of time series with the recent advancement in computational power of computers and more importantly developing more advanced machine learning algorithms and approaches such as deep learning new algorithms are developed to forecast time series data the research question investigated in this article is that whether and how the newly developed deep learningbased algorithms for forecasting time series data such as long shortterm memory lstm are superior to the traditional algorithms the empirical studies conducted and reported in this article show that deep learningbased algorithms such as lstm outperform traditionalbased algorithms such as arima model more specifically the average reduction in error rates obtained by lstm is between 84 87 percent when compared to arima indicating the superiority of lstm to arima furthermore it was noticed that the number of training times known as epoch in deep learning has no effect on the performance of the trained forecast model and it exhibits a truly random behavior
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1,803.06387
Improving the efficiency and robustness of nested sampling using posterior repartitioning
In real-world Bayesian inference applications, prior assumptions regarding the parameters of interest may be unrepresentative of their actual values for a given dataset. In particular, if the likelihood is concentrated far out in the wings of the assumed prior distribution, this can lead to extremely inefficient exploration of the resulting posterior by nested sampling algorithms, with unnecessarily high associated computational costs. Simple solutions such as broadening the prior range in such cases might not be appropriate or possible in real-world applications, for example when one wishes to assume a single standardised prior across the analysis of a large number of datasets for which the true values of the parameters of interest may vary. This work therefore introduces a posterior repartitioning (PR) method for nested sampling algorithms, which addresses the problem by redefining the likelihood and prior while keeping their product fixed, so that the posterior inferences and evidence estimates remain unchanged but the efficiency of the nested sampling process is significantly increased. Numerical results show that the PR method provides a simple yet powerful refinement for nested sampling algorithms to address the issue of unrepresentative priors.
stat.CO astro-ph.IM
in realworld bayesian inference applications prior assumptions regarding the parameters of interest may be unrepresentative of their actual values for a given dataset in particular if the likelihood is concentrated far out in the wings of the assumed prior distribution this can lead to extremely inefficient exploration of the resulting posterior by nested sampling algorithms with unnecessarily high associated computational costs simple solutions such as broadening the prior range in such cases might not be appropriate or possible in realworld applications for example when one wishes to assume a single standardised prior across the analysis of a large number of datasets for which the true values of the parameters of interest may vary this work therefore introduces a posterior repartitioning pr method for nested sampling algorithms which addresses the problem by redefining the likelihood and prior while keeping their product fixed so that the posterior inferences and evidence estimates remain unchanged but the efficiency of the nested sampling process is significantly increased numerical results show that the pr method provides a simple yet powerful refinement for nested sampling algorithms to address the issue of unrepresentative priors
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1,803.06388
Pressure-Tunable Photonic Band Gaps in an Entropic Colloidal Crystal
Materials adopting the diamond structure possess useful properties in atomic and colloidal systems, and are a popular target for synthesis in colloids where a photonic band gap is possible. The desirable photonic properties of the diamond structure pose an interesting opportunity for reconfigurable matter: can we create a colloidal crystal able to switch reversibly to and from the diamond structure? Drawing inspiration from high-pressure transitions of diamond-forming atomic systems, we design a system of polyhedrally-shaped particles that transitions from diamond to a tetragonal diamond derivative upon a small pressure change. The transition can alternatively be triggered by changing the shape of the particle in-situ. We propose that the transition provides a reversible reconfiguration process for a potential new colloidal material, and draw parallels between this transition and phase behavior of the atomic transitions from which we take inspiration.
cond-mat.mtrl-sci cond-mat.mes-hall cond-mat.soft
materials adopting the diamond structure possess useful properties in atomic and colloidal systems and are a popular target for synthesis in colloids where a photonic band gap is possible the desirable photonic properties of the diamond structure pose an interesting opportunity for reconfigurable matter can we create a colloidal crystal able to switch reversibly to and from the diamond structure drawing inspiration from highpressure transitions of diamondforming atomic systems we design a system of polyhedrallyshaped particles that transitions from diamond to a tetragonal diamond derivative upon a small pressure change the transition can alternatively be triggered by changing the shape of the particle insitu we propose that the transition provides a reversible reconfiguration process for a potential new colloidal material and draw parallels between this transition and phase behavior of the atomic transitions from which we take inspiration
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1,803.06389
Mechanistic Regimes of Vibronic Transport in a Heterodimer and the Design Principle of Incoherent Vibronic Transport in Phycobiliproteins
Following the observation of coherent oscillations in non-linear spectra of photosynthetic pigment protein complexes, particularly phycobilliprotein such as PC645, coherent vibronic transport has been suggested as a design principle for novel light harvesting materials operating at room temperature. Vibronic transport between energetically remote pigments is coherent when the presence of a resonant vibration supports transient delocalization between the pair of electronic excited states. Here, we establish the mechanism of vibronic transport for a model heterodimer across a wide range of molecular parameter values. The resulting mechanistic map demonstrates that the molecular parameters of phycobiliproteins in fact support incoherent vibronic transport. This result points to an important design principle: incoherent vibronic transport is more efficient than a coherent mechanism when energetic disorder exceeds the coupling between the donor and vibrationally excited acceptor states. Finally, our results suggest that the role of coherent vibronic transport in pigment protein complexes should be reevaluated.
physics.chem-ph
following the observation of coherent oscillations in nonlinear spectra of photosynthetic pigment protein complexes particularly phycobilliprotein such as pc645 coherent vibronic transport has been suggested as a design principle for novel light harvesting materials operating at room temperature vibronic transport between energetically remote pigments is coherent when the presence of a resonant vibration supports transient delocalization between the pair of electronic excited states here we establish the mechanism of vibronic transport for a model heterodimer across a wide range of molecular parameter values the resulting mechanistic map demonstrates that the molecular parameters of phycobiliproteins in fact support incoherent vibronic transport this result points to an important design principle incoherent vibronic transport is more efficient than a coherent mechanism when energetic disorder exceeds the coupling between the donor and vibrationally excited acceptor states finally our results suggest that the role of coherent vibronic transport in pigment protein complexes should be reevaluated
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1,803.0639
Corpus Statistics in Text Classification of Online Data
Transformation of Machine Learning (ML) from a boutique science to a generally accepted technology has increased importance of reproduction and transportability of ML studies. In the current work, we investigate how corpus characteristics of textual data sets correspond to text classification results. We work with two data sets gathered from sub-forums of an online health-related forum. Our empirical results are obtained for a multi-class sentiment analysis application.
cs.CL cs.IR cs.LG
transformation of machine learning ml from a boutique science to a generally accepted technology has increased importance of reproduction and transportability of ml studies in the current work we investigate how corpus characteristics of textual data sets correspond to text classification results we work with two data sets gathered from subforums of an online healthrelated forum our empirical results are obtained for a multiclass sentiment analysis application
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1,803.06391
The route to massive black hole formation via merger-driven direct collapse: a review
In this paper we review a new scenario for the formation of massive black hole seeds that relies on multi-scale gas inflows initiated by the merger of massive gas-rich galaxies at $z > 6$, where gas has already achieved solar composition. Hydrodynamical simulations undertaken to explore our scenario show that supermassive, gravitationally bound gaseous disks, weighing a billion solar masses and of a few pc in size, form in the nuclei of merger remnants in less than $10^5$ yr. These could later produce a supermassive protostar or supermassive star at their center via various mechanisms. Moreover, we present a new analytical model, based on angular momentum transport in mass-loaded gravitoturbulent disks. This naturally predicts that a nuclear disk accreting at rates exceeding $1000 M_{\odot}$/yr, as seen in the simulations, is stable against fragmentation irrespective of its metallicity. This is at variance with conventional direct collapse scenarios, which require the suppression of gas cooling in metal-free protogalaxies for gas collapse to take place. Such high accretion rates reflect the high free-fall velocities in massive halos appearing at $z < 10$, and occur naturally as a result of the efficient angular momentum loss provided by mergers. We discuss the implications of our scenario on the observed population of high-z quasars and on its evolution to lower redshifts using a semi-analytical galaxy formation model. Finally, we consider the intriguing possibility that the secondary gas inflows in the unstable disks might drive gas to collapse into a supermassive black hole directly via the General Relativistic radial instability. Such {\it dark collapse} route could generate gravitational wave emission detectable via the future Laser Interferometer Space Antenna (LISA). [Abridged]
astro-ph.GA
in this paper we review a new scenario for the formation of massive black hole seeds that relies on multiscale gas inflows initiated by the merger of massive gasrich galaxies at z 6 where gas has already achieved solar composition hydrodynamical simulations undertaken to explore our scenario show that supermassive gravitationally bound gaseous disks weighing a billion solar masses and of a few pc in size form in the nuclei of merger remnants in less than 105 yr these could later produce a supermassive protostar or supermassive star at their center via various mechanisms moreover we present a new analytical model based on angular momentum transport in massloaded gravitoturbulent disks this naturally predicts that a nuclear disk accreting at rates exceeding 1000 m_odotyr as seen in the simulations is stable against fragmentation irrespective of its metallicity this is at variance with conventional direct collapse scenarios which require the suppression of gas cooling in metalfree protogalaxies for gas collapse to take place such high accretion rates reflect the high freefall velocities in massive halos appearing at z 10 and occur naturally as a result of the efficient angular momentum loss provided by mergers we discuss the implications of our scenario on the observed population of highz quasars and on its evolution to lower redshifts using a semianalytical galaxy formation model finally we consider the intriguing possibility that the secondary gas inflows in the unstable disks might drive gas to collapse into a supermassive black hole directly via the general relativistic radial instability such it dark collapse route could generate gravitational wave emission detectable via the future laser interferometer space antenna lisa abridged
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1,803.06392
MESA Models of the Evolutionary State of the Interacting Binary epsilon Aurigae
Using MESA code (Modules for Experiments in Stellar Astrophysics, version 9575), an evaluation was made of the evolutionary state of the epsilon Aurigae binary system (HD 31964, F0Iap + disk). We sought to satisfy several observational constraints: 1) requiring evolutionary tracks to pass close to the current temperature and luminosity of the primary star; 2) obtaining a period near the observed value of 27.1 years; 3) matching a mass function of 3.0; 4) concurrent Roche lobe overflow and mass transfer; 5) an isotopic ratio 12 C/ 13 C = 5 and, (6) matching the interferometrically determined angular diameter. A MESA model starting with binary masses of 9.85 + 4.5 Msun , with a 100 day initial period, produces a 1.2 + 10.6 Msun result having a 547 day period, and a single digit 12 C/ 13 C ratio. These values were reached near an age of 20 Myr, when the donor star comes close to the observed luminosity and temperature for epsilon Aurigae A, as a post-RGB/pre-AGB star. Contemporaneously, the accretor then appears as an upper main sequence, early B-type star. This benchmark model can provide a basis for further exploration of this interacting binary, and other long period binary stars.
astro-ph.SR
using mesa code modules for experiments in stellar astrophysics version 9575 an evaluation was made of the evolutionary state of the epsilon aurigae binary system hd 31964 f0iap disk we sought to satisfy several observational constraints 1 requiring evolutionary tracks to pass close to the current temperature and luminosity of the primary star 2 obtaining a period near the observed value of 271 years 3 matching a mass function of 30 4 concurrent roche lobe overflow and mass transfer 5 an isotopic ratio 12 c 13 c 5 and 6 matching the interferometrically determined angular diameter a mesa model starting with binary masses of 985 45 msun with a 100 day initial period produces a 12 106 msun result having a 547 day period and a single digit 12 c 13 c ratio these values were reached near an age of 20 myr when the donor star comes close to the observed luminosity and temperature for epsilon aurigae a as a postrgbpreagb star contemporaneously the accretor then appears as an upper main sequence early btype star this benchmark model can provide a basis for further exploration of this interacting binary and other long period binary stars
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1,803.06393
Phylogeny-based tumor subclone identification using a Bayesian feature allocation model
Tumor cells acquire different genetic alterations during the course of evolution in cancer patients. As a result of competition and selection, only a few subgroups of cells with distinct genotypes survive. These subgroups of cells are often referred to as subclones. In recent years, many statistical and computational methods have been developed to identify tumor subclones, leading to biologically significant discoveries and shedding light on tumor progression, metastasis, drug resistance and other processes. However, most existing methods are either not able to infer the phylogenetic structure among subclones, or not able to incorporate copy number variations (CNV). In this article, we propose SIFA (tumor Subclone Identification by Feature Allocation), a Bayesian model which takes into account both CNV and tumor phylogeny structure to infer tumor subclones. We compare the performance of SIFA with two other commonly used methods using simulation studies with varying sequencing depth, evolutionary tree size, and tree complexity. SIFA consistently yields better results in terms of Rand Index and cellularity estimation accuracy. The usefulness of SIFA is also demonstrated through its application to whole genome sequencing (WGS) samples from four patients in a breast cancer study.
stat.AP q-bio.TO
tumor cells acquire different genetic alterations during the course of evolution in cancer patients as a result of competition and selection only a few subgroups of cells with distinct genotypes survive these subgroups of cells are often referred to as subclones in recent years many statistical and computational methods have been developed to identify tumor subclones leading to biologically significant discoveries and shedding light on tumor progression metastasis drug resistance and other processes however most existing methods are either not able to infer the phylogenetic structure among subclones or not able to incorporate copy number variations cnv in this article we propose sifa tumor subclone identification by feature allocation a bayesian model which takes into account both cnv and tumor phylogeny structure to infer tumor subclones we compare the performance of sifa with two other commonly used methods using simulation studies with varying sequencing depth evolutionary tree size and tree complexity sifa consistently yields better results in terms of rand index and cellularity estimation accuracy the usefulness of sifa is also demonstrated through its application to whole genome sequencing wgs samples from four patients in a breast cancer study
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1,803.06394
Combinatorial proofs of two Euler type identities due to Andrews
We prove combinatorially some identities related to Euler's partition identity (the number of partitions of $n$ into distinct parts equals the number of partitions of $n$ into odd parts). They were conjectured by Beck and proved by Andrews via generating functions. Let $a(n)$ be the number of partitions of $n$ such that the set of even parts has exactly one element, $b(n)$ be the difference between the number of parts in all odd partitions of $n$ and the number of parts in all distinct partitions of $n$, and $c(n)$ be the number of partitions of $n$ in which exactly one part is repeated. Then, $a(n)=b(n)=c(n)$. The identity $a(n)=c(n)$ was proved combinatorially (in greater generality) by Fu and Tang. We prove combinatorially that $a(n)=b(n)$ and $b(n)=c(n)$. Our proof relies on bijections between a set and a multiset, where the partitions in the multiset are decorated with bit strings. Let $c_1(n)$ be the number of partitions of $n$ such that there is exactly one part occurring three times while all other parts occur only once and let $b_1(n)$ to be the difference between the total number of parts in the partitions of $n$ into distinct parts and the total number of different parts in the partitions of $n$ into odd parts. We prove combinatorially that $c_1(n)=b_1(n)$. In addition to these results by Andrews, we prove combinatorially that $b_1(n)=a_1(n)$, where $a_1(n)$ counts partitions of $n$ such that the set of even parts has exactly one element and satisfying some additional conditions. We also treat the case when exactly one part occurs twice while all other parts occur only once.
math.CO math.NT
we prove combinatorially some identities related to eulers partition identity the number of partitions of n into distinct parts equals the number of partitions of n into odd parts they were conjectured by beck and proved by andrews via generating functions let an be the number of partitions of n such that the set of even parts has exactly one element bn be the difference between the number of parts in all odd partitions of n and the number of parts in all distinct partitions of n and cn be the number of partitions of n in which exactly one part is repeated then anbncn the identity ancn was proved combinatorially in greater generality by fu and tang we prove combinatorially that anbn and bncn our proof relies on bijections between a set and a multiset where the partitions in the multiset are decorated with bit strings let c_1n be the number of partitions of n such that there is exactly one part occurring three times while all other parts occur only once and let b_1n to be the difference between the total number of parts in the partitions of n into distinct parts and the total number of different parts in the partitions of n into odd parts we prove combinatorially that c_1nb_1n in addition to these results by andrews we prove combinatorially that b_1na_1n where a_1n counts partitions of n such that the set of even parts has exactly one element and satisfying some additional conditions we also treat the case when exactly one part occurs twice while all other parts occur only once
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1,803.06395
Singular genuine rigidity
We extend the concept of genuine rigidity of submanifolds by allowing mild singularities, mainly to obtain new global rigidity results and unify the known ones. As one of the consequences, we simultaneously extend and unify Sacksteder and Dajczer-Gromoll theorems by showing that any compact $n$-dimensional submanifold of ${\mathbb R}^{n+p}$ is singularly genuinely rigid in ${\mathbb R}^{n+q}$, for any $q < \min\{5,n\} - p$. Unexpectedly, the singular theory becomes much simpler and natural than the regular one, even though all technical codimension assumptions, needed in the regular case, are removed.
math.DG
we extend the concept of genuine rigidity of submanifolds by allowing mild singularities mainly to obtain new global rigidity results and unify the known ones as one of the consequences we simultaneously extend and unify sacksteder and dajczergromoll theorems by showing that any compact ndimensional submanifold of mathbb rnp is singularly genuinely rigid in mathbb rnq for any q min5n p unexpectedly the singular theory becomes much simpler and natural than the regular one even though all technical codimension assumptions needed in the regular case are removed
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1,803.06396
Reviving and Improving Recurrent Back-Propagation
In this paper, we revisit the recurrent back-propagation (RBP) algorithm, discuss the conditions under which it applies as well as how to satisfy them in deep neural networks. We show that RBP can be unstable and propose two variants based on conjugate gradient on the normal equations (CG-RBP) and Neumann series (Neumann-RBP). We further investigate the relationship between Neumann-RBP and back propagation through time (BPTT) and its truncated version (TBPTT). Our Neumann-RBP has the same time complexity as TBPTT but only requires constant memory, whereas TBPTT's memory cost scales linearly with the number of truncation steps. We examine all RBP variants along with BPTT and TBPTT in three different application domains: associative memory with continuous Hopfield networks, document classification in citation networks using graph neural networks and hyperparameter optimization for fully connected networks. All experiments demonstrate that RBPs, especially the Neumann-RBP variant, are efficient and effective for optimizing convergent recurrent neural networks. Code is released at: \url{https://github.com/lrjconan/RBP}.
cs.LG stat.ML
in this paper we revisit the recurrent backpropagation rbp algorithm discuss the conditions under which it applies as well as how to satisfy them in deep neural networks we show that rbp can be unstable and propose two variants based on conjugate gradient on the normal equations cgrbp and neumann series neumannrbp we further investigate the relationship between neumannrbp and back propagation through time bptt and its truncated version tbptt our neumannrbp has the same time complexity as tbptt but only requires constant memory whereas tbptts memory cost scales linearly with the number of truncation steps we examine all rbp variants along with bptt and tbptt in three different application domains associative memory with continuous hopfield networks document classification in citation networks using graph neural networks and hyperparameter optimization for fully connected networks all experiments demonstrate that rbps especially the neumannrbp variant are efficient and effective for optimizing convergent recurrent neural networks code is released at urlhttpsgithubcomlrjconanrbp
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1,803.06397
Deep learning for affective computing: text-based emotion recognition in decision support
Emotions widely affect human decision-making. This fact is taken into account by affective computing with the goal of tailoring decision support to the emotional states of individuals. However, the accurate recognition of emotions within narrative documents presents a challenging undertaking due to the complexity and ambiguity of language. Performance improvements can be achieved through deep learning; yet, as demonstrated in this paper, the specific nature of this task requires the customization of recurrent neural networks with regard to bidirectional processing, dropout layers as a means of regularization, and weighted loss functions. In addition, we propose sent2affect, a tailored form of transfer learning for affective computing: here the network is pre-trained for a different task (i.e. sentiment analysis), while the output layer is subsequently tuned to the task of emotion recognition. The resulting performance is evaluated in a holistic setting across 6 benchmark datasets, where we find that both recurrent neural networks and transfer learning consistently outperform traditional machine learning. Altogether, the findings have considerable implications for the use of affective computing.
cs.CL
emotions widely affect human decisionmaking this fact is taken into account by affective computing with the goal of tailoring decision support to the emotional states of individuals however the accurate recognition of emotions within narrative documents presents a challenging undertaking due to the complexity and ambiguity of language performance improvements can be achieved through deep learning yet as demonstrated in this paper the specific nature of this task requires the customization of recurrent neural networks with regard to bidirectional processing dropout layers as a means of regularization and weighted loss functions in addition we propose sent2affect a tailored form of transfer learning for affective computing here the network is pretrained for a different task ie sentiment analysis while the output layer is subsequently tuned to the task of emotion recognition the resulting performance is evaluated in a holistic setting across 6 benchmark datasets where we find that both recurrent neural networks and transfer learning consistently outperform traditional machine learning altogether the findings have considerable implications for the use of affective computing
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1,803.06398
Parabolic semi-orthogonal decompositions and Kummer flat invariants of log schemes
We construct semi-orthogonal decompositions on triangulated categories of parabolic sheaves on certain kinds of logarithmic schemes. This provides a categorification of the decomposition theorems in Kummer flat K-theory due to Hagihara and Nizio{\l}. Our techniques allow us to generalize Hagihara and Nizio{\l}'s results to a much larger class of invariants in addition to K-theory, and also to extend them to more general logarithmic stacks.
math.AG
we construct semiorthogonal decompositions on triangulated categories of parabolic sheaves on certain kinds of logarithmic schemes this provides a categorification of the decomposition theorems in kummer flat ktheory due to hagihara and niziol our techniques allow us to generalize hagihara and niziols results to a much larger class of invariants in addition to ktheory and also to extend them to more general logarithmic stacks
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1,803.06399
Generation of Electron Whistler Waves at the Mirror Mode Magnetic Holes: MMS Observations and PIC Simulation
The Magnetospheric Multiscale (MMS) mission has observed electron whistler waves at the center and at the edges of magnetic holes in the dayside magnetosheath. The magnetic holes are nonlinear mirror structures since their magnitude is anti-correlated with particle density. In this article, we examine the growth mechanisms of these whistler waves and their interaction with the host magnetic hole. In the observations, as magnetic holes develop and get deeper, an electron population gets trapped and develops a temperature anisotropy favorable for whistler waves to be generated. In addition, the decrease in magnetic field magnitude and the increase in density reduces the electron resonance energy, which promotes the electron cyclotron resonance. To investigate this process, we used an expanding box particle-in-cell simulations to produce the mirror instability, which then evolves into magnetic holes. The simulation shows that whistler waves can be generated at the center and edges of magnetic holes, which reproduces the primary features of the MMS observations. The simulation shows that the electron temperature anisotropy develops in the center of the magnetic hole once the mirror instability reaches its nonlinear stage of evolution. The plasma is then unstable to whistler waves at the minimum of the magnetic field structures. In the saturation regime of mirror instability, when magnetic holes are developed, the electron temperature anisotropy appears at the edges of the holes and electron distributions become more isotropic at the magnetic field minimum. At the edges, the expansion of magnetic holes decelerates the electrons which leads to temperature anisotropies.
physics.space-ph
the magnetospheric multiscale mms mission has observed electron whistler waves at the center and at the edges of magnetic holes in the dayside magnetosheath the magnetic holes are nonlinear mirror structures since their magnitude is anticorrelated with particle density in this article we examine the growth mechanisms of these whistler waves and their interaction with the host magnetic hole in the observations as magnetic holes develop and get deeper an electron population gets trapped and develops a temperature anisotropy favorable for whistler waves to be generated in addition the decrease in magnetic field magnitude and the increase in density reduces the electron resonance energy which promotes the electron cyclotron resonance to investigate this process we used an expanding box particleincell simulations to produce the mirror instability which then evolves into magnetic holes the simulation shows that whistler waves can be generated at the center and edges of magnetic holes which reproduces the primary features of the mms observations the simulation shows that the electron temperature anisotropy develops in the center of the magnetic hole once the mirror instability reaches its nonlinear stage of evolution the plasma is then unstable to whistler waves at the minimum of the magnetic field structures in the saturation regime of mirror instability when magnetic holes are developed the electron temperature anisotropy appears at the edges of the holes and electron distributions become more isotropic at the magnetic field minimum at the edges the expansion of magnetic holes decelerates the electrons which leads to temperature anisotropies
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1,803.064
The Unruh effect for mixing neutrinos
Recently, the inverse $\beta$-decay rate calculated with respect to uniformly accelerated observers (experiencing the Unruh thermal bath) was revisited. Concerns have been raised regarding the compatibility of inertial and accelerated observers' results when neutrino mixing is taken into account. Here, we show that these concerns are unfounded by discussing the properties of the Unruh thermal bath with mixing neutrinos and explicitly calculating the decay rates according to both sets of observers and confirming that they are in agreement. The Unruh effect is perfectly valid for mixing neutrinos.
gr-qc hep-th
recently the inverse betadecay rate calculated with respect to uniformly accelerated observers experiencing the unruh thermal bath was revisited concerns have been raised regarding the compatibility of inertial and accelerated observers results when neutrino mixing is taken into account here we show that these concerns are unfounded by discussing the properties of the unruh thermal bath with mixing neutrinos and explicitly calculating the decay rates according to both sets of observers and confirming that they are in agreement the unruh effect is perfectly valid for mixing neutrinos
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1,803.06401
Evaluating Conditional Cash Transfer Policies with Machine Learning Methods
This paper presents an out-of-sample prediction comparison between major machine learning models and the structural econometric model. Over the past decade, machine learning has established itself as a powerful tool in many prediction applications, but this approach is still not widely adopted in empirical economic studies. To evaluate the benefits of this approach, I use the most common machine learning algorithms, CART, C4.5, LASSO, random forest, and adaboost, to construct prediction models for a cash transfer experiment conducted by the Progresa program in Mexico, and I compare the prediction results with those of a previous structural econometric study. Two prediction tasks are performed in this paper: the out-of-sample forecast and the long-term within-sample simulation. For the out-of-sample forecast, both the mean absolute error and the root mean square error of the school attendance rates found by all machine learning models are smaller than those found by the structural model. Random forest and adaboost have the highest accuracy for the individual outcomes of all subgroups. For the long-term within-sample simulation, the structural model has better performance than do all of the machine learning models. The poor within-sample fitness of the machine learning model results from the inaccuracy of the income and pregnancy prediction models. The result shows that the machine learning model performs better than does the structural model when there are many data to learn; however, when the data are limited, the structural model offers a more sensible prediction. The findings of this paper show promise for adopting machine learning in economic policy analyses in the era of big data.
econ.EM stat.ML
this paper presents an outofsample prediction comparison between major machine learning models and the structural econometric model over the past decade machine learning has established itself as a powerful tool in many prediction applications but this approach is still not widely adopted in empirical economic studies to evaluate the benefits of this approach i use the most common machine learning algorithms cart c45 lasso random forest and adaboost to construct prediction models for a cash transfer experiment conducted by the progresa program in mexico and i compare the prediction results with those of a previous structural econometric study two prediction tasks are performed in this paper the outofsample forecast and the longterm withinsample simulation for the outofsample forecast both the mean absolute error and the root mean square error of the school attendance rates found by all machine learning models are smaller than those found by the structural model random forest and adaboost have the highest accuracy for the individual outcomes of all subgroups for the longterm withinsample simulation the structural model has better performance than do all of the machine learning models the poor withinsample fitness of the machine learning model results from the inaccuracy of the income and pregnancy prediction models the result shows that the machine learning model performs better than does the structural model when there are many data to learn however when the data are limited the structural model offers a more sensible prediction the findings of this paper show promise for adopting machine learning in economic policy analyses in the era of big data
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1,803.06402
Shadowing for nonautonomous dynamics
We prove that whenever a sequence of invertible and bounded operators $(A_m)_{m\in \mathbb{Z}}$ acting on a Banach space $X$ admits an exponential dichotomy and a sequence of differentiable maps $f_m \colon X\to X$, $m\in \mathbb{Z}$, has bounded and H\"{o}lder derivatives, the nonautonomous dynamics given by $x_{m+1}=A_mx_m+f_m(x_m)$, $m\in \mathbb{Z}$ has various shadowing properties. Hence, we extend recent results of Bernardes Jr. et al. in several directions. As a nontrivial application of our results, we give a new proof of the nonautonomous Grobman-Hartman theorem.
math.DS
we prove that whenever a sequence of invertible and bounded operators a_m_min mathbbz acting on a banach space x admits an exponential dichotomy and a sequence of differentiable maps f_m colon xto x min mathbbz has bounded and holder derivatives the nonautonomous dynamics given by x_m1a_mx_mf_mx_m min mathbbz has various shadowing properties hence we extend recent results of bernardes jr et al in several directions as a nontrivial application of our results we give a new proof of the nonautonomous grobmanhartman theorem
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1,803.06403
Characterizing Earth Analogs in Reflected Light: Atmospheric Retrieval Studies for Future Space Telescopes
Space-based high contrast imaging mission concepts for studying rocky exoplanets in reflected light are currently under community study. We develop an inverse modeling framework to estimate the science return of such missions given different instrument design considerations. By combining an exoplanet albedo model, an instrument noise model, and an ensemble Markov chain Monte Carlo sampler, we explore retrievals of atmospheric and planetary properties for Earth twins as a function of signal-to-noise ratio (SNR) and resolution ($R$). Our forward model includes Rayleigh scattering, single-layer water clouds with patchy coverage, and pressure-dependent absorption due to water vapor, oxygen, and ozone. We simulate data at $R = 70$ and $R = 140$ from 0.4-1.0 $\mu$m with SNR $ = 5, 10, 15, 20$ at 550 nm (i.e., for HabEx/LUVOIR-type instruments). At these same SNR, we simulate data for WFIRST paired with a starshade, which includes two photometric points between 0.48-0.6 $\mu$m and $R = 50$ spectroscopy from 0.6-0.97 $\mu$m. Given our noise model for WFIRST-type detectors, we find that weak detections of water vapor, ozone, and oxygen can be achieved with observations with at least $R = 70$ / SNR$\ = 15$, or $R = 140$ / SNR$\ = 10$ for improved detections. Meaningful constraints are only achieved with $R = 140$ / SNR$\ = 20$ data. The WFIRST data offer limited diagnostic information, needing at least SNR = 20 to weakly detect gases. Most scenarios place limits on planetary radius, but cannot constrain surface gravity and, thus, planetary mass.
astro-ph.EP
spacebased high contrast imaging mission concepts for studying rocky exoplanets in reflected light are currently under community study we develop an inverse modeling framework to estimate the science return of such missions given different instrument design considerations by combining an exoplanet albedo model an instrument noise model and an ensemble markov chain monte carlo sampler we explore retrievals of atmospheric and planetary properties for earth twins as a function of signaltonoise ratio snr and resolution r our forward model includes rayleigh scattering singlelayer water clouds with patchy coverage and pressuredependent absorption due to water vapor oxygen and ozone we simulate data at r 70 and r 140 from 0410 mum with snr 5 10 15 20 at 550 nm ie for habexluvoirtype instruments at these same snr we simulate data for wfirst paired with a starshade which includes two photometric points between 04806 mum and r 50 spectroscopy from 06097 mum given our noise model for wfirsttype detectors we find that weak detections of water vapor ozone and oxygen can be achieved with observations with at least r 70 snr 15 or r 140 snr 10 for improved detections meaningful constraints are only achieved with r 140 snr 20 data the wfirst data offer limited diagnostic information needing at least snr 20 to weakly detect gases most scenarios place limits on planetary radius but cannot constrain surface gravity and thus planetary mass
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1,803.06404
Helical Network Model for Twisted Bilayer Graphene
In the presence of a finite interlayer displacement field bilayer graphene has an energy gap that is dependent on stacking and largest for the stable AB and BA stacking arrangements. When the relative orientations between layers are twisted through a small angle to form a moir$\mathrm{\acute{e}}$ pattern, the local stacking arrangement changes slowly. We show that for non-zero displacement fields the low-energy physics of twisted bilayers is captured by a phenomenological helical network model that describes electrons localized on domain walls separating regions with approximate AB and BA stacking. The network band structure is gapless and has of a series of two-dimensional bands with Dirac band-touching points and a density-of-states that is periodic in energy with one zero and one divergence per period.
cond-mat.mes-hall
in the presence of a finite interlayer displacement field bilayer graphene has an energy gap that is dependent on stacking and largest for the stable ab and ba stacking arrangements when the relative orientations between layers are twisted through a small angle to form a moirmathrmacutee pattern the local stacking arrangement changes slowly we show that for nonzero displacement fields the lowenergy physics of twisted bilayers is captured by a phenomenological helical network model that describes electrons localized on domain walls separating regions with approximate ab and ba stacking the network band structure is gapless and has of a series of twodimensional bands with dirac bandtouching points and a densityofstates that is periodic in energy with one zero and one divergence per period
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1,803.06405
Control of interlayer excitons in two-dimensional van der Waals heterostructures
Long-lived interlayer excitons with distinct spin-valley physics in van der Waals heterostructures based on transition metal dichalcogenides make them promising for information processing in next-generation devices. While the emission characteristics of interlayer excitons in different types of hetero stacks have been extensively studied, the manipulation of these excitons required to alter the valley-state or tune the emission energy and intensity is still lacking. Here, we demonstrate such control over interlayer excitons in MoSe2/WSe2 heterostructures. The encapsulation of our stack with h-BN ensures ultraclean interfaces, allowing us to resolve four separate narrow interlayer emission peaks. We observe two main interlayer transitions with opposite helicities under circularly polarized excitation, either conserving or inverting the polarization of incoming light. We further demonstrate control over the wavelength, intensity, and polarization of exciton emission by electrical and magnetic fields. Such ability to manipulate the interlayer excitons and their polarization could pave the way for novel excitonic and valleytronic device applications.
cond-mat.mes-hall
longlived interlayer excitons with distinct spinvalley physics in van der waals heterostructures based on transition metal dichalcogenides make them promising for information processing in nextgeneration devices while the emission characteristics of interlayer excitons in different types of hetero stacks have been extensively studied the manipulation of these excitons required to alter the valleystate or tune the emission energy and intensity is still lacking here we demonstrate such control over interlayer excitons in mose2wse2 heterostructures the encapsulation of our stack with hbn ensures ultraclean interfaces allowing us to resolve four separate narrow interlayer emission peaks we observe two main interlayer transitions with opposite helicities under circularly polarized excitation either conserving or inverting the polarization of incoming light we further demonstrate control over the wavelength intensity and polarization of exciton emission by electrical and magnetic fields such ability to manipulate the interlayer excitons and their polarization could pave the way for novel excitonic and valleytronic device applications
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1,803.06406
Self-Calibration of Mobile Manipulator Kinematic and Sensor Extrinsic Parameters Through Contact-Based Interaction
We present a novel approach for mobile manipulator self-calibration using contact information. Our method, based on point cloud registration, is applied to estimate the extrinsic transform between a fixed vision sensor mounted on a mobile base and an end effector. Beyond sensor calibration, we demonstrate that the method can be extended to include manipulator kinematic model parameters, which involves a non-rigid registration process. Our procedure uses on-board sensing exclusively and does not rely on any external measurement devices, fiducial markers, or calibration rigs. Further, it is fully automatic in the general case. We experimentally validate the proposed method on a custom mobile manipulator platform, and demonstrate centimetre-level post-calibration accuracy in positioning of the end effector using visual guidance only. We also discuss the stability properties of the registration algorithm, in order to determine the conditions under which calibration is possible.
cs.RO
we present a novel approach for mobile manipulator selfcalibration using contact information our method based on point cloud registration is applied to estimate the extrinsic transform between a fixed vision sensor mounted on a mobile base and an end effector beyond sensor calibration we demonstrate that the method can be extended to include manipulator kinematic model parameters which involves a nonrigid registration process our procedure uses onboard sensing exclusively and does not rely on any external measurement devices fiducial markers or calibration rigs further it is fully automatic in the general case we experimentally validate the proposed method on a custom mobile manipulator platform and demonstrate centimetrelevel postcalibration accuracy in positioning of the end effector using visual guidance only we also discuss the stability properties of the registration algorithm in order to determine the conditions under which calibration is possible
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1,803.06407
Deep Component Analysis via Alternating Direction Neural Networks
Despite a lack of theoretical understanding, deep neural networks have achieved unparalleled performance in a wide range of applications. On the other hand, shallow representation learning with component analysis is associated with rich intuition and theory, but smaller capacity often limits its usefulness. To bridge this gap, we introduce Deep Component Analysis (DeepCA), an expressive multilayer model formulation that enforces hierarchical structure through constraints on latent variables in each layer. For inference, we propose a differentiable optimization algorithm implemented using recurrent Alternating Direction Neural Networks (ADNNs) that enable parameter learning using standard backpropagation. By interpreting feed-forward networks as single-iteration approximations of inference in our model, we provide both a novel theoretical perspective for understanding them and a practical technique for constraining predictions with prior knowledge. Experimentally, we demonstrate performance improvements on a variety of tasks, including single-image depth prediction with sparse output constraints.
cs.LG cs.CV stat.ML
despite a lack of theoretical understanding deep neural networks have achieved unparalleled performance in a wide range of applications on the other hand shallow representation learning with component analysis is associated with rich intuition and theory but smaller capacity often limits its usefulness to bridge this gap we introduce deep component analysis deepca an expressive multilayer model formulation that enforces hierarchical structure through constraints on latent variables in each layer for inference we propose a differentiable optimization algorithm implemented using recurrent alternating direction neural networks adnns that enable parameter learning using standard backpropagation by interpreting feedforward networks as singleiteration approximations of inference in our model we provide both a novel theoretical perspective for understanding them and a practical technique for constraining predictions with prior knowledge experimentally we demonstrate performance improvements on a variety of tasks including singleimage depth prediction with sparse output constraints
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1,803.06408
Three \'Etudes on a sequence transformation pipeline
We study a sequence transformation pipeline that maps certain sequences with rational generating functions to permutation-based sequence families of combinatorial significance. Many of the number triangles we encounter can be related to simplicial objects such as the associahedron and the permutahedron. The linkages between these objects is facilitated by the use of the previously introduced $\mathcal{T}$ transform.
math.CO
we study a sequence transformation pipeline that maps certain sequences with rational generating functions to permutationbased sequence families of combinatorial significance many of the number triangles we encounter can be related to simplicial objects such as the associahedron and the permutahedron the linkages between these objects is facilitated by the use of the previously introduced mathcalt transform
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1,803.06409
Integral comparisons of nonnegative positive definite functions on LCA groups
In this paper we investigate the following questions. Let $\mu, \nu$ be two regular Borel measures of finite total variation. When do we have a constant $C$ satisfying $$\int f d\nu \le C \int f d\mu$$ whenever $f$ is a continuous nonnegative positive definite function? How the admissible constants $C$ can be characterized, and what is their optimal value? We first discuss the problem in locally compact abelian groups. Then we make further specializations when the Borel measures $\mu, \nu$ are both either purely atomic or absolutely continuous with respect to a reference Haar measure. In addition, we prove a duality conjecture posed in our former paper.
math.FA math.CA
in this paper we investigate the following questions let mu nu be two regular borel measures of finite total variation when do we have a constant c satisfying int f dnu le c int f dmu whenever f is a continuous nonnegative positive definite function how the admissible constants c can be characterized and what is their optimal value we first discuss the problem in locally compact abelian groups then we make further specializations when the borel measures mu nu are both either purely atomic or absolutely continuous with respect to a reference haar measure in addition we prove a duality conjecture posed in our former paper
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1,803.0641
Accurate evaluation of size and refractive index for spherical objects in quantitative phase imaging
Measuring the average refractive index (RI) of spherical objects, such as suspended cells, in quantitative phase imaging (QPI) requires a decoupling of RI and size from the QPI data. This has been commonly achieved by determining the object's radius with geometrical approaches, neglecting light-scattering. Here, we present a novel QPI fitting algorithm that reliably uncouples the RI using Mie theory and a semi-analytical, corrected Rytov approach. We assess the range of validity of this algorithm in silico and experimentally investigate various objects (oil and protein droplets, microgel beads, cells) and noise conditions. In addition, we provide important practical cues for future studies in cell biology.
q-bio.QM physics.bio-ph
measuring the average refractive index ri of spherical objects such as suspended cells in quantitative phase imaging qpi requires a decoupling of ri and size from the qpi data this has been commonly achieved by determining the objects radius with geometrical approaches neglecting lightscattering here we present a novel qpi fitting algorithm that reliably uncouples the ri using mie theory and a semianalytical corrected rytov approach we assess the range of validity of this algorithm in silico and experimentally investigate various objects oil and protein droplets microgel beads cells and noise conditions in addition we provide important practical cues for future studies in cell biology
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1,803.06411
The 21 reducible polars of Klein's quartic
We describe the singularities and related properties of the arrangement of 21 reducible polars of Klein's quartic, containing Klein's well-known arrangement of $21$ lines.
math.AG math.AC math.CO
we describe the singularities and related properties of the arrangement of 21 reducible polars of kleins quartic containing kleins wellknown arrangement of 21 lines
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1,803.06412
Symplectic invariance of rational surfaces on K\"{a}hler manifolds
Kollar and Ruan proved symplectic deformation invariance for uniruledness of Kaehler manifolds. Zhiyu Tian proved the same for rational connectedness in dimension < 4. Kollar conjectured this in all dimensions. We prove Kollar's conjecture, as well as existence of a covering family of rational surfaces, for all Kaehler manifolds that are symplectically deformation equivalent to G/P or to a low degree complete intersection in such.
math.AG
kollar and ruan proved symplectic deformation invariance for uniruledness of kaehler manifolds zhiyu tian proved the same for rational connectedness in dimension 4 kollar conjectured this in all dimensions we prove kollars conjecture as well as existence of a covering family of rational surfaces for all kaehler manifolds that are symplectically deformation equivalent to gp or to a low degree complete intersection in such
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1,803.06413
Thermal kinetic inductance detectors for ground-based millimeter-wave cosmology
We show measurements of thermal kinetic inductance detectors (TKID) intended for millimeter wave cosmology in the 200-300 GHz atmospheric window. The TKID is a type of bolometer which uses the kinetic inductance of a superconducting resonator to measure the temperature of the thermally isolated bolometer island. We measure bolometer thermal conductance, time constant and noise equivalent power. We also measure the quality factor of our resonators as the bath temperature varies to show they are limited by effects consistent with coupling to two level systems.
astro-ph.IM
we show measurements of thermal kinetic inductance detectors tkid intended for millimeter wave cosmology in the 200300 ghz atmospheric window the tkid is a type of bolometer which uses the kinetic inductance of a superconducting resonator to measure the temperature of the thermally isolated bolometer island we measure bolometer thermal conductance time constant and noise equivalent power we also measure the quality factor of our resonators as the bath temperature varies to show they are limited by effects consistent with coupling to two level systems
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1,803.06414
Learning to Segment via Cut-and-Paste
This paper presents a weakly-supervised approach to object instance segmentation. Starting with known or predicted object bounding boxes, we learn object masks by playing a game of cut-and-paste in an adversarial learning setup. A mask generator takes a detection box and Faster R-CNN features, and constructs a segmentation mask that is used to cut-and-paste the object into a new image location. The discriminator tries to distinguish between real objects, and those cut and pasted via the generator, giving a learning signal that leads to improved object masks. We verify our method experimentally using Cityscapes, COCO, and aerial image datasets, learning to segment objects without ever having seen a mask in training. Our method exceeds the performance of existing weakly supervised methods, without requiring hand-tuned segment proposals, and reaches 90% of supervised performance.
cs.CV
this paper presents a weaklysupervised approach to object instance segmentation starting with known or predicted object bounding boxes we learn object masks by playing a game of cutandpaste in an adversarial learning setup a mask generator takes a detection box and faster rcnn features and constructs a segmentation mask that is used to cutandpaste the object into a new image location the discriminator tries to distinguish between real objects and those cut and pasted via the generator giving a learning signal that leads to improved object masks we verify our method experimentally using cityscapes coco and aerial image datasets learning to segment objects without ever having seen a mask in training our method exceeds the performance of existing weakly supervised methods without requiring handtuned segment proposals and reaches 90 of supervised performance
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1,803.06415
Connection Blocking In Quotients of $Sol$
Let $G$ be a connected Lie group and $\Gamma \subset G$ a lattice. Connection curves of the homogeneous space $M=G/\Gamma$ are the orbits of one parameter subgroups of $G$. To $block$ a pair of points $m_1,m_2 \in M$ is to find a finite set $B \subset M\setminus \{m_1, m_2 \}$ such that every connecting curve joining $m_1$ and $m_2$ intersects $B$. The homogeneous space $M$ is $blockable$ if every pair of points in $M$ can be blocked, otherwise we call it $non-blockable$. $Sol$ is an important Lie group and one of the eight homogeneous Thurston 3-geometries. It is a unimodular solvable Lie group diffeomorphic to $R^3$, and together with the left invariant metric $ds^2=e^{-2z}dx^2+e^{2z}dy^2+dz^2$ includes copies of the hyperbolic plane, which makes studying its geometrical properties more interesting. In this paper we prove that all quotients of $Sol$ are non-blockable. In particular, we show that for any lattice $\Gamma \subset Sol$, the set of non-blockable pairs is a dense subset of $Sol/\Gamma \times Sol/\Gamma$.
math.DG
let g be a connected lie group and gamma subset g a lattice connection curves of the homogeneous space mggamma are the orbits of one parameter subgroups of g to block a pair of points m_1m_2 in m is to find a finite set b subset msetminus m_1 m_2 such that every connecting curve joining m_1 and m_2 intersects b the homogeneous space m is blockable if every pair of points in m can be blocked otherwise we call it nonblockable sol is an important lie group and one of the eight homogeneous thurston 3geometries it is a unimodular solvable lie group diffeomorphic to r3 and together with the left invariant metric ds2e2zdx2e2zdy2dz2 includes copies of the hyperbolic plane which makes studying its geometrical properties more interesting in this paper we prove that all quotients of sol are nonblockable in particular we show that for any lattice gamma subset sol the set of nonblockable pairs is a dense subset of solgamma times solgamma
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1,803.06416
Differential Privacy for Growing Databases
We study the design of differentially private algorithms for adaptive analysis of dynamically growing databases, where a database accumulates new data entries while the analysis is ongoing. We provide a collection of tools for machine learning and other types of data analysis that guarantee differential privacy and accuracy as the underlying databases grow arbitrarily large. We give both a general technique and a specific algorithm for adaptive analysis of dynamically growing databases. Our general technique is illustrated by two algorithms that schedule black box access to some algorithm that operates on a fixed database to generically transform private and accurate algorithms for static databases into private and accurate algorithms for dynamically growing databases. These results show that almost any private and accurate algorithm can be rerun at appropriate points of data growth with minimal loss of accuracy, even when data growth is unbounded. Our specific algorithm directly adapts the private multiplicative weights algorithm to the dynamic setting, maintaining the accuracy guarantee of the static setting through unbounded data growth. Along the way, we develop extensions of several other differentially private algorithms to the dynamic setting, which may be of independent interest for future work on the design of differentially private algorithms for growing databases.
cs.DS cs.DB
we study the design of differentially private algorithms for adaptive analysis of dynamically growing databases where a database accumulates new data entries while the analysis is ongoing we provide a collection of tools for machine learning and other types of data analysis that guarantee differential privacy and accuracy as the underlying databases grow arbitrarily large we give both a general technique and a specific algorithm for adaptive analysis of dynamically growing databases our general technique is illustrated by two algorithms that schedule black box access to some algorithm that operates on a fixed database to generically transform private and accurate algorithms for static databases into private and accurate algorithms for dynamically growing databases these results show that almost any private and accurate algorithm can be rerun at appropriate points of data growth with minimal loss of accuracy even when data growth is unbounded our specific algorithm directly adapts the private multiplicative weights algorithm to the dynamic setting maintaining the accuracy guarantee of the static setting through unbounded data growth along the way we develop extensions of several other differentially private algorithms to the dynamic setting which may be of independent interest for future work on the design of differentially private algorithms for growing databases
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1,803.06417
Coding for Channels with SNR Variation: Spatial Coupling and Efficient Interleaving
In magnetic-recording systems, consecutive sections experience different signal to noise ratios (SNRs). To perform error correction over these systems, one approach is to use an individual block code for each section. However, the performance over a section affected by a lower SNR is weaker compared to the performance over a section affected by a higher SNR. Spatially-coupled (SC) codes are a family of graph-based codes with capacity approaching performance and low latency decoding. An SC code is constructed by partitioning an underlying block code to several component matrices, and coupling copies of the component matrices together. The contribution of this paper is threefold. First, we present a new partitioning technique to efficiently construct SC codes with column weights 4 and 6. Second, we present an SC code construction for channels with SNR variation. Our SC code construction provides local error correction for each section by means of the underlying codes that cover one section each, and simultaneously, an added level of error correction by means of coupling among the underlying codes. Third, we introduce a low-complexity interleaving scheme specific to SC codes that further improves their performance over channels with SNR variation. Our simulation results show that our SC codes outperform individual block codes by more than 1 and 2 orders of magnitudes in the error floor region compared to the block codes with and without regular interleaving, respectively. This improvement is more pronounced by increasing the memory and column weight.
cs.IT math.IT
in magneticrecording systems consecutive sections experience different signal to noise ratios snrs to perform error correction over these systems one approach is to use an individual block code for each section however the performance over a section affected by a lower snr is weaker compared to the performance over a section affected by a higher snr spatiallycoupled sc codes are a family of graphbased codes with capacity approaching performance and low latency decoding an sc code is constructed by partitioning an underlying block code to several component matrices and coupling copies of the component matrices together the contribution of this paper is threefold first we present a new partitioning technique to efficiently construct sc codes with column weights 4 and 6 second we present an sc code construction for channels with snr variation our sc code construction provides local error correction for each section by means of the underlying codes that cover one section each and simultaneously an added level of error correction by means of coupling among the underlying codes third we introduce a lowcomplexity interleaving scheme specific to sc codes that further improves their performance over channels with snr variation our simulation results show that our sc codes outperform individual block codes by more than 1 and 2 orders of magnitudes in the error floor region compared to the block codes with and without regular interleaving respectively this improvement is more pronounced by increasing the memory and column weight
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1,803.06418
Leveraging Sparsity to Speed Up Polynomial Feature Expansions of CSR Matrices Using $K$-Simplex Numbers
An algorithm is provided for performing polynomial feature expansions that both operates on and produces compressed sparse row (CSR) matrices. Previously, no such algorithm existed, and performing polynomial expansions on CSR matrices required an intermediate densification step. The algorithm performs a $K$-degree expansion by using a bijective function involving $K$-simplex numbers of column indices in the original matrix to column indices in the expanded matrix. Not only is space saved by operating in CSR format, but the bijective function allows for only the nonzero elements to be iterated over and multiplied together during the expansion, greatly improving average time complexity. For a vector of dimensionality $D$ and density $0 \le d \le 1$, the algorithm has average time complexity $\Theta(d^KD^K)$ where $K$ is the polynomial-feature order; this is an improvement by a factor $d^K$ over the standard method. This work derives the required function for the cases of $K=2$ and $K=3$ and shows its use in the $K=2$ algorithm.
cs.DS cs.NA
an algorithm is provided for performing polynomial feature expansions that both operates on and produces compressed sparse row csr matrices previously no such algorithm existed and performing polynomial expansions on csr matrices required an intermediate densification step the algorithm performs a kdegree expansion by using a bijective function involving ksimplex numbers of column indices in the original matrix to column indices in the expanded matrix not only is space saved by operating in csr format but the bijective function allows for only the nonzero elements to be iterated over and multiplied together during the expansion greatly improving average time complexity for a vector of dimensionality d and density 0 le d le 1 the algorithm has average time complexity thetadkdk where k is the polynomialfeature order this is an improvement by a factor dk over the standard method this work derives the required function for the cases of k2 and k3 and shows its use in the k2 algorithm
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1,803.06419
Topological Wave-Guiding Near an Exceptional Point: Defect-Immune, Slow-Light, Loss-Immune Propagation
Electromagnetic waves propagating, at finite speeds, in conventional wave-guiding structures are reflected by discontinuities and decay in lossy regions. In this Letter, we drastically modify this typical guided-wave behavior by combining concepts from non-Hermitian physics and topological photonics. To this aim, we theoretically study, for the first time, the possibility of realizing an exceptional point between \emph{coupled topological modes in a non-Hermitian non-reciprocal waveguide}. Our proposed system is composed of oppositely-biased gyrotropic materials (e.g., biased plasmas or graphene layers) with a balanced loss/gain distribution. To study this complex wave-guiding problem, we put forward an exact analysis based on classical Green's function theory, and we illustrate the behavior of coupled topological modes and the nature of their non-Hermitian degeneracies. We find that, by operating near an exceptional point, we can realize anomalous topological wave propagation with, at the same time, low group-velocity, inherent immunity to back-scattering at discontinuities, and immunity to losses. These theoretical findings may open exciting research directions and stimulate further investigations of non-Hermitian topological waveguides to realize robust wave propagation in practical scenarios.
physics.optics
electromagnetic waves propagating at finite speeds in conventional waveguiding structures are reflected by discontinuities and decay in lossy regions in this letter we drastically modify this typical guidedwave behavior by combining concepts from nonhermitian physics and topological photonics to this aim we theoretically study for the first time the possibility of realizing an exceptional point between emphcoupled topological modes in a nonhermitian nonreciprocal waveguide our proposed system is composed of oppositelybiased gyrotropic materials eg biased plasmas or graphene layers with a balanced lossgain distribution to study this complex waveguiding problem we put forward an exact analysis based on classical greens function theory and we illustrate the behavior of coupled topological modes and the nature of their nonhermitian degeneracies we find that by operating near an exceptional point we can realize anomalous topological wave propagation with at the same time low groupvelocity inherent immunity to backscattering at discontinuities and immunity to losses these theoretical findings may open exciting research directions and stimulate further investigations of nonhermitian topological waveguides to realize robust wave propagation in practical scenarios
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1,803.0642
Exclusive vector meson production at an electron-ion collider
Coherent exclusive vector meson electroproduction is a key physics channel at an electron-ion collider. It probes the gluon structure of nuclei over a wide range of $Q^2$, and can be used to measure nuclear shadowing and to search for gluon saturation and/or the colored glass condensate. In this paper, we present calculations of the kinematic distributions for a variety of exclusive vector meson final states: the $\rho$, $\phi$, J/$\psi$, $\psi'$ and the $\Upsilon$ states. The cross-sections for light and $c\overline c$ mesons are large, while $\Upsilon$ states should be produced in moderate numbers at a medium energy EIC (the proposed U.S. designs) and in large numbers at the LHeC. We investigate the acceptances for these states, as a function of detector rapidity coverage. A large-acceptance detector is needed to cover the full range photon-nucleon collision energies produced at an EIC; a forward detector is required to observe vector mesons from the most energetic photon interactions, and thereby probe gluons at the lowest possible Bjorken-$x$ values.
nucl-ex hep-ph nucl-th
coherent exclusive vector meson electroproduction is a key physics channel at an electronion collider it probes the gluon structure of nuclei over a wide range of q2 and can be used to measure nuclear shadowing and to search for gluon saturation andor the colored glass condensate in this paper we present calculations of the kinematic distributions for a variety of exclusive vector meson final states the rho phi jpsi psi and the upsilon states the crosssections for light and coverline c mesons are large while upsilon states should be produced in moderate numbers at a medium energy eic the proposed us designs and in large numbers at the lhec we investigate the acceptances for these states as a function of detector rapidity coverage a largeacceptance detector is needed to cover the full range photonnucleon collision energies produced at an eic a forward detector is required to observe vector mesons from the most energetic photon interactions and thereby probe gluons at the lowest possible bjorkenx values
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1,803.06421
Uncertainties in permittivities computed from molecular dynamics simulations and temperature correction of dielectric properties of condensed polar systems
A robust, simple and fast procedure for the calculation of uncertainties in relative static dielectric permittivity ($\varepsilon_s$) computed via molecular dynamics (MD) is proposed. It arises as a direct application of well founded statistical methods for auto-correlated variables. Also, in order to deal with the lack of experimental data about $\varepsilon_s$ and relaxation times ($\tau$) at different temperatures, a method for their prediction is suggested. It requires one experimental value and at least two MD simulations. In the case of relaxation times, a theoretical justification is provided.
physics.chem-ph
a robust simple and fast procedure for the calculation of uncertainties in relative static dielectric permittivity varepsilon_s computed via molecular dynamics md is proposed it arises as a direct application of well founded statistical methods for autocorrelated variables also in order to deal with the lack of experimental data about varepsilon_s and relaxation times tau at different temperatures a method for their prediction is suggested it requires one experimental value and at least two md simulations in the case of relaxation times a theoretical justification is provided
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1,803.06422
A New Result on the Complexity of Heuristic Estimates for the A* Algorithm
Relaxed models are abstract problem descriptions generated by ignoring constraints that are present in base-level problems. They play an important role in planning and search algorithms, as it has been shown that the length of an optimal solution to a relaxed model yields a monotone heuristic for an A? search of a base-level problem. Optimal solutions to a relaxed model may be computed algorithmically or by search in a further relaxed model, leading to a search that explores a hierarchy of relaxed models. In this paper, we review the traditional definition of problem relaxation and show that searching in the abstraction hierarchy created by problem relaxation will not reduce the computational effort required to find optimal solutions to the base- level problem, unless the relaxed problem found in the hierarchy can be transformed by some optimization (e.g., subproblem factoring). Specifically, we prove that any A* search of the base-level using a heuristic h2 will largely dominate an A* search of the base-level using a heuristic h1, if h1 must be computed by an A* search of the relaxed model using h2.
cs.AI
relaxed models are abstract problem descriptions generated by ignoring constraints that are present in baselevel problems they play an important role in planning and search algorithms as it has been shown that the length of an optimal solution to a relaxed model yields a monotone heuristic for an a search of a baselevel problem optimal solutions to a relaxed model may be computed algorithmically or by search in a further relaxed model leading to a search that explores a hierarchy of relaxed models in this paper we review the traditional definition of problem relaxation and show that searching in the abstraction hierarchy created by problem relaxation will not reduce the computational effort required to find optimal solutions to the base level problem unless the relaxed problem found in the hierarchy can be transformed by some optimization eg subproblem factoring specifically we prove that any a search of the baselevel using a heuristic h2 will largely dominate an a search of the baselevel using a heuristic h1 if h1 must be computed by an a search of the relaxed model using h2
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1,803.06423
Relativistic Viscous Radiation Hydrodynamic Simulations of Geometrically Thin Disks: I. Thermal and Other Instabilities
We present results from two-dimensional, general relativistic, viscous, radiation hydrodynamic numerical simulations of Shakura-Sunyaev thin disks accreting onto stellar mass Schwarzschild black holes. We consider cases on both the gas- and radiation-pressure-dominated branches of the thermal equilibrium curve, with mass accretion rates spanning the range from $\dot{M} = 0.01 L_\mathrm{Edd}/c^2$ to $10 L_\mathrm{Edd}/c^2$. The simulations directly test the stability of this standard disk model on the different branches. We find clear evidence of thermal instability for all radiation-pressure-dominated disks, resulting universally in the vertical collapse of the disks, which in some cases then settle onto the stable, gas-pressure-dominated branch. Although these results are consistent with decades-old theoretical predictions, they appear to be in conflict with available observational data from black hole X-ray binaries. We also find evidence for a radiation-pressure-driven instability that breaks the unstable disks up into alternating rings of high and low surface density on a timescale comparable to the thermal collapse. Since radiation is included self-consistently in the simulations, we are able to calculate lightcurves and power density spectra (PDS). For the most part, we measure radiative efficiencies (ratio of luminosity to mass accretion rate) close to 6%, as expected for a non-rotating black hole. The PDS appear as broken power laws, with a break typically around 100 Hz. There is no evidence of significant excess power at any frequencies, i.e. no quasi-periodic oscillations are observed.
astro-ph.HE
we present results from twodimensional general relativistic viscous radiation hydrodynamic numerical simulations of shakurasunyaev thin disks accreting onto stellar mass schwarzschild black holes we consider cases on both the gas and radiationpressuredominated branches of the thermal equilibrium curve with mass accretion rates spanning the range from dotm 001 l_mathrmeddc2 to 10 l_mathrmeddc2 the simulations directly test the stability of this standard disk model on the different branches we find clear evidence of thermal instability for all radiationpressuredominated disks resulting universally in the vertical collapse of the disks which in some cases then settle onto the stable gaspressuredominated branch although these results are consistent with decadesold theoretical predictions they appear to be in conflict with available observational data from black hole xray binaries we also find evidence for a radiationpressuredriven instability that breaks the unstable disks up into alternating rings of high and low surface density on a timescale comparable to the thermal collapse since radiation is included selfconsistently in the simulations we are able to calculate lightcurves and power density spectra pds for the most part we measure radiative efficiencies ratio of luminosity to mass accretion rate close to 6 as expected for a nonrotating black hole the pds appear as broken power laws with a break typically around 100 hz there is no evidence of significant excess power at any frequencies ie no quasiperiodic oscillations are observed
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1,803.06424
Thermal entanglement in the mixed-spin Ising-Heisenberg double sawtooth frustrated ladder
The entanglement between spin-1/2 interstitial Heisenberg dimers in the mixed spin-(1,1/2) Ising-XXZ double sawtooth ladder is investigated at low temperature. Here, we consider a cyclic four-spin exchange interaction in square plaquette of each block, and investigate the effects of this amazing interaction on the bipartite entanglement between spin-1/2 interstitial dimers. Interestingly, we observe a remarkable difference in concurrence behavior with respect to the cyclic four-spin exchange interaction and magnetic field. Also, the critical points at which the concurrence vanishes are changed versus alteration of the anisotropic parameter of the interstitial Heisenberg dimers.
cond-mat.stat-mech
the entanglement between spin12 interstitial heisenberg dimers in the mixed spin112 isingxxz double sawtooth ladder is investigated at low temperature here we consider a cyclic fourspin exchange interaction in square plaquette of each block and investigate the effects of this amazing interaction on the bipartite entanglement between spin12 interstitial dimers interestingly we observe a remarkable difference in concurrence behavior with respect to the cyclic fourspin exchange interaction and magnetic field also the critical points at which the concurrence vanishes are changed versus alteration of the anisotropic parameter of the interstitial heisenberg dimers
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1,803.06425
Reinforcement Learning of Artificial Microswimmers
The behavior of living systems is based on the experience they gained through their interactions with the environment [1]. This experience is stored in the complex biochemical networks of cells and organisms to provide a relationship between a sensed situation and what to do in this situation [2-4]. An implementation of such processes in artificial systems has been achieved through different machine learning algorithms [5, 6]. However, for microscopic systems such as artificial microswimmers which mimic propulsion as one of the basic functionalities of living systems [7, 8] such adaptive behavior and learning processes have not been implemented so far. Here we introduce machine learning algorithms to the motion of artificial microswimmers with a hybrid approach. We employ self-thermophoretic artificial microswimmers in a real world environment [9, 10] which are controlled by a real-time microscopy system to introduce reinforcement learning [11-13]. We demonstrate the solution of a standard problem of reinforcement learning - the navigation in a grid world. Due to the size of the microswimmer, noise introduced by Brownian motion if found to contribute considerably to both the learning process and the actions within a learned behavior. We extend the learning process to multiple swimmers and sharing of information. Our work represents a first step towards the integration of learning strategies into microsystems and provides a platform for the study of the emergence of adaptive and collective behavior.
cond-mat.soft physics.bio-ph
the behavior of living systems is based on the experience they gained through their interactions with the environment 1 this experience is stored in the complex biochemical networks of cells and organisms to provide a relationship between a sensed situation and what to do in this situation 24 an implementation of such processes in artificial systems has been achieved through different machine learning algorithms 5 6 however for microscopic systems such as artificial microswimmers which mimic propulsion as one of the basic functionalities of living systems 7 8 such adaptive behavior and learning processes have not been implemented so far here we introduce machine learning algorithms to the motion of artificial microswimmers with a hybrid approach we employ selfthermophoretic artificial microswimmers in a real world environment 9 10 which are controlled by a realtime microscopy system to introduce reinforcement learning 1113 we demonstrate the solution of a standard problem of reinforcement learning the navigation in a grid world due to the size of the microswimmer noise introduced by brownian motion if found to contribute considerably to both the learning process and the actions within a learned behavior we extend the learning process to multiple swimmers and sharing of information our work represents a first step towards the integration of learning strategies into microsystems and provides a platform for the study of the emergence of adaptive and collective behavior
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1,803.06426
Entanglement in a fermionic spin chain containing a single mobile boson under decoherence
The concurrence between first and the last sites of a fermionic spin chain containing a single boson is rigorously investigated at finite low temperature in the vicinity of a weak homogeneous magnetic field. We consider the boson as a mobile spin-1 particle through the chain and study concurrence without/under decoherence and express some interesting phase flip and bit flip reactions of the pairwise entanglement between first and the last half-spins in the chain. Our investigations show that the concurrence between two considered half-spins has different behavior for various positions of the single boson along the chain. Indeed, we realize that the single boson mobility has an essential role to probe the pairwise entanglement intensity between two spins located at the opposite ends of a fermionic chain. Interestingly, the entanglement remains alive for higher temperatures when the boson is the nearest neighbor of the first fermion. When the boson is at the middle of chain, it is demonstrated that the threshold temperature (at which the concurrence vanishes) versus decoherence rate can be considered as a threshold temperature boundary. These results pave the way to set and interpret the numerical and analytical expressions for utilizing quantum information in realistic scenarios such as quantum state transmission, quantum communication science and quantum information processing, where the both fermion-fermion and fermion-boson correlations should be taken in to account.
cond-mat.stat-mech quant-ph
the concurrence between first and the last sites of a fermionic spin chain containing a single boson is rigorously investigated at finite low temperature in the vicinity of a weak homogeneous magnetic field we consider the boson as a mobile spin1 particle through the chain and study concurrence withoutunder decoherence and express some interesting phase flip and bit flip reactions of the pairwise entanglement between first and the last halfspins in the chain our investigations show that the concurrence between two considered halfspins has different behavior for various positions of the single boson along the chain indeed we realize that the single boson mobility has an essential role to probe the pairwise entanglement intensity between two spins located at the opposite ends of a fermionic chain interestingly the entanglement remains alive for higher temperatures when the boson is the nearest neighbor of the first fermion when the boson is at the middle of chain it is demonstrated that the threshold temperature at which the concurrence vanishes versus decoherence rate can be considered as a threshold temperature boundary these results pave the way to set and interpret the numerical and analytical expressions for utilizing quantum information in realistic scenarios such as quantum state transmission quantum communication science and quantum information processing where the both fermionfermion and fermionboson correlations should be taken in to account
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1,803.06427
Nonlinear nano-electromechanical lattices for high-frequency, tunable stress propagation
Active manipulation of mechanical waves at high frequencies opens opportunities in heat management, radio-frequency (RF) signal processing, and quantum technologies. Nanoelectromechanical systems (NEMS) are appropriate platforms for developing these technologies, offering energy transducibility between different physical domains, for example, converting optical or electrical signals into mechanical vibrations and viceversa. Existing NEMS platforms, however, are mostly linear, passive, and not dynamically controllable. Here, we report the realization of active manipulation of frequency band dispersion in one-dimensional (1D) nonlinear nanoelectromechanical lattices (NEML) in the RF domain (10-30 MHz). Our NEML is comprised of a periodic arrangement of mechanically coupled free-standing nano-membranes, with circular clamped boundaries. This design forms a flexural phononic crystals with a well-defined band gaps, 1.8 MHz wide. The application a DC gate voltage creates voltage-dependent on-site potentials, which can significantly shift the frequency bands of the device. Dynamic modulation of the voltage triggers nonlinear effects, which induce the formation of phononic band gaps in the acoustic branch. These devices could be used in tunable filters, ultrasonic delay lines and transducers for implantable medical devices.
physics.app-ph
active manipulation of mechanical waves at high frequencies opens opportunities in heat management radiofrequency rf signal processing and quantum technologies nanoelectromechanical systems nems are appropriate platforms for developing these technologies offering energy transducibility between different physical domains for example converting optical or electrical signals into mechanical vibrations and viceversa existing nems platforms however are mostly linear passive and not dynamically controllable here we report the realization of active manipulation of frequency band dispersion in onedimensional 1d nonlinear nanoelectromechanical lattices neml in the rf domain 1030 mhz our neml is comprised of a periodic arrangement of mechanically coupled freestanding nanomembranes with circular clamped boundaries this design forms a flexural phononic crystals with a welldefined band gaps 18 mhz wide the application a dc gate voltage creates voltagedependent onsite potentials which can significantly shift the frequency bands of the device dynamic modulation of the voltage triggers nonlinear effects which induce the formation of phononic band gaps in the acoustic branch these devices could be used in tunable filters ultrasonic delay lines and transducers for implantable medical devices
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1,803.06428
Intrinsic spin-orbit torque in an antiferromagnet with a weakly noncollinear spin configuration
An antiferromagnet is a promising material for spin-orbit torque generation. Earlier studies of the spin-orbit torque in an antiferromagnet are limited to collinear spin configurations. We calculate the spin-orbit torque in an antiferromagnet whose spin ordering is weakly noncollinear. Such noncollinearity may be induced spontaneously during the magnetization dynamics even when the equilibrium spin configuration is perfectly collinear. It is shown that deviation from perfect collinearity can modify properties of the spin-orbit torque since noncollinearity generates extra Berry phase contributions to the spin-orbit torque, which are forbidden for collinear spin configurations. In sufficiently clean antiferromagnets, this modification can be significant. We estimate this effect to be of relevance for fast antiferromagnetic domain wall motion.
cond-mat.mes-hall
an antiferromagnet is a promising material for spinorbit torque generation earlier studies of the spinorbit torque in an antiferromagnet are limited to collinear spin configurations we calculate the spinorbit torque in an antiferromagnet whose spin ordering is weakly noncollinear such noncollinearity may be induced spontaneously during the magnetization dynamics even when the equilibrium spin configuration is perfectly collinear it is shown that deviation from perfect collinearity can modify properties of the spinorbit torque since noncollinearity generates extra berry phase contributions to the spinorbit torque which are forbidden for collinear spin configurations in sufficiently clean antiferromagnets this modification can be significant we estimate this effect to be of relevance for fast antiferromagnetic domain wall motion
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1,803.06429
How to automate a kinematic mount using a 3D printed Arduino-based system
We demonstrate a simple, flexible and cost-effective system to automatize most of the kinematic mounts available nowadays on the market. It combines 3D printed components, an Arduino board, stepper motors, and simple electronics. The system developed can control independently and simultaneously up to ten stepper motors using commands sent through the serial port, and it is suitable for applications where optical realignment using flat mirrors is required on a periodic basis.
physics.ins-det
we demonstrate a simple flexible and costeffective system to automatize most of the kinematic mounts available nowadays on the market it combines 3d printed components an arduino board stepper motors and simple electronics the system developed can control independently and simultaneously up to ten stepper motors using commands sent through the serial port and it is suitable for applications where optical realignment using flat mirrors is required on a periodic basis
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1,803.0643
The effects of metallicity and cooling physics on fragmentation: implications on direct-collapse black hole formation
A promising supermassive black hole seed formation channel is that of direct collapse from primordial gas clouds. We perform a suite of 3D hydrodynamics simulations of an isolated turbulent gas cloud to investigate conditions conducive to forming massive black hole seeds via direct collapse, probing the impact of cloud metallicity, gas temperature floor and cooling physics on cloud fragmentation. We find there is no threshold in metallicity which produces a sharp drop in fragmentation. When molecular cooling is not present, metallicity has little effect on fragmentation. When molecular cooling is present, fragmentation is suppressed by at most $\sim 25\%$, with the greatest suppression seen at metallicities below $2\%$ solar. A gas temperature floor $\sim 10^{4}$K produces the largest drop in fragmentation of any parameter choice, reducing fragmentation by $\sim 60\%$. At metallicities below $2\%$ solar or at temperatures $\sim 10^{3}$K we see a reduction in fragmentation $\sim 20-25 \%$. For a cloud of metallicity $2\%$ solar above and a temperature below $10^3$K, the detailed choices of temperature floor, metallicity, and cooling physics have little impact on fragmentation.
astro-ph.GA
a promising supermassive black hole seed formation channel is that of direct collapse from primordial gas clouds we perform a suite of 3d hydrodynamics simulations of an isolated turbulent gas cloud to investigate conditions conducive to forming massive black hole seeds via direct collapse probing the impact of cloud metallicity gas temperature floor and cooling physics on cloud fragmentation we find there is no threshold in metallicity which produces a sharp drop in fragmentation when molecular cooling is not present metallicity has little effect on fragmentation when molecular cooling is present fragmentation is suppressed by at most sim 25 with the greatest suppression seen at metallicities below 2 solar a gas temperature floor sim 104k produces the largest drop in fragmentation of any parameter choice reducing fragmentation by sim 60 at metallicities below 2 solar or at temperatures sim 103k we see a reduction in fragmentation sim 2025 for a cloud of metallicity 2 solar above and a temperature below 103k the detailed choices of temperature floor metallicity and cooling physics have little impact on fragmentation
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1,803.06431
Is Quintessence an Indication of a Time-Varying Gravitational Constant?
A model is presented where the quintessence parameter, w, is related to a time-varying gravitational constant. Assuming a present value of w equals -.98, we predict a current variation of G dot/G = -.06 H0. H0 is Hubbles parameter, G is Newtons constant and G dot is the derivative of G with respect to time. Thus, G has a cosmic origin, is decreasing with respect to cosmological time, and is proportional to H0, as originally proposed by the Dirac-Jordan hypothesis. Within our model, we can explain the cosmological constant fine-tuning problem, the discrepancy between the present very weak value of the cosmological constant, and the much greater vacuum energy found in earlier epochs. To formalize and solidify our model, we give two distinct functions of G(a), the cosmic scale parameter. We treat inverse G as an order parameter, which vanishes at high energies; at low temperatures, it reaches a saturation value, a value we are close to today. Our first function for inverse G is motivated by a charging capacitor; the second treats inverse G by analogy to a magnetic response. Both functions, even though very distinct, give a remarkably similar tracking behavior for w(a). Interestingly, both functions indicate the onset of G formation at a temperature of approximately 7 *1021 degrees Kelvin, in contrast to the concordance model. At the temperature of formation, we find that G has increased to roughly 4*1020 times its present value. For most of cosmic evolution, however, our variable G model gives results similar to the predictions of the concordance model, except in the very early universe, as we shall demonstrate. Within our framework, the weakening of G to its current value G0 is speculated as the true cause for the observed unanticipated acceleration of the universe.
gr-qc
a model is presented where the quintessence parameter w is related to a timevarying gravitational constant assuming a present value of w equals 98 we predict a current variation of g dotg 06 h0 h0 is hubbles parameter g is newtons constant and g dot is the derivative of g with respect to time thus g has a cosmic origin is decreasing with respect to cosmological time and is proportional to h0 as originally proposed by the diracjordan hypothesis within our model we can explain the cosmological constant finetuning problem the discrepancy between the present very weak value of the cosmological constant and the much greater vacuum energy found in earlier epochs to formalize and solidify our model we give two distinct functions of ga the cosmic scale parameter we treat inverse g as an order parameter which vanishes at high energies at low temperatures it reaches a saturation value a value we are close to today our first function for inverse g is motivated by a charging capacitor the second treats inverse g by analogy to a magnetic response both functions even though very distinct give a remarkably similar tracking behavior for wa interestingly both functions indicate the onset of g formation at a temperature of approximately 7 1021 degrees kelvin in contrast to the concordance model at the temperature of formation we find that g has increased to roughly 41020 times its present value for most of cosmic evolution however our variable g model gives results similar to the predictions of the concordance model except in the very early universe as we shall demonstrate within our framework the weakening of g to its current value g0 is speculated as the true cause for the observed unanticipated acceleration of the universe
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1,803.06432
Pseudo-differential operators with nonlinear quantizing functions
In this paper we develop the calculus of pseudo-differential operators corresponding to the quantizations of the form $$ Au(x)=\int_{\mathbb{R}^n}\int_{\mathbb{R}^n}e^{i(x-y)\cdot\xi}\sigma(x+\tau(y-x),\xi)u(y)dyd\xi, $$ where $\tau:\mathbb{R}^n\to\mathbb{R}^n$ is a general function. In particular, for the linear choices $\tau(x)=0$, $\tau(x)=x$, and $\tau(x)=\frac{x}{2}$ this covers the well-known Kohn-Nirenberg, anti-Kohn-Nirenberg, and Weyl quantizations, respectively. Quantizations of such type appear naturally in the analysis on nilpotent Lie groups for polynomial functions $\tau$ and here we investigate the corresponding calculus in the model case of $\mathbb{R}^n$. We also give examples of nonlinear $\tau$ appearing on the polarised and non-polarised Heisenberg groups, inspired by the recent joint work with Marius Mantoiu.
math.FA math.AP math.OA
in this paper we develop the calculus of pseudodifferential operators corresponding to the quantizations of the form auxint_mathbbrnint_mathbbrneixycdotxisigmaxtauyxxiuydydxi where taumathbbrntomathbbrn is a general function in particular for the linear choices taux0 tauxx and tauxfracx2 this covers the wellknown kohnnirenberg antikohnnirenberg and weyl quantizations respectively quantizations of such type appear naturally in the analysis on nilpotent lie groups for polynomial functions tau and here we investigate the corresponding calculus in the model case of mathbbrn we also give examples of nonlinear tau appearing on the polarised and nonpolarised heisenberg groups inspired by the recent joint work with marius mantoiu
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1,803.06433
Thermal conduction of one-dimensional carbon nanomaterials and nanoarchitectures
This review summarizes the current studies of the thermal transport properties of one-dimensional (1D) carbon nanomaterials and nanoarchitectures. Considering different hybridization states of carbon, emphases are laid on a variety of 1D carbon nanomaterials, such as diamond nanothreads, penta-graphene nanotubes, supernanotubes, and carbyne. Based on experimental measurements and simulation/calculation results, we discuss the dependence of the thermal conductivity of these 1D carbon nanomaterials on a wide range of factors, including the size effect, temperature influence, strain effect, and others. This review provides an overall understanding of the thermal transport properties of 1D carbon nanomaterials and nanoarchitectures, which paves the way for effective thermal management at nanoscale.
cond-mat.mtrl-sci physics.app-ph
this review summarizes the current studies of the thermal transport properties of onedimensional 1d carbon nanomaterials and nanoarchitectures considering different hybridization states of carbon emphases are laid on a variety of 1d carbon nanomaterials such as diamond nanothreads pentagraphene nanotubes supernanotubes and carbyne based on experimental measurements and simulationcalculation results we discuss the dependence of the thermal conductivity of these 1d carbon nanomaterials on a wide range of factors including the size effect temperature influence strain effect and others this review provides an overall understanding of the thermal transport properties of 1d carbon nanomaterials and nanoarchitectures which paves the way for effective thermal management at nanoscale
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1,803.06434
Probable Decay Modes at Limits of Nuclear Stability of the Superheavy Nuclei
The modes of decay for the even-even isotopes of superheavy nuclei of Z = 118 and 120 with neutron number $160 \leq N \leq 204$ are investigated in the framework of the axially deformed relativistic mean field model. The asymmetry parameter $\eta$ and the relative neutron-proton asymmetry of the surface to the center ($R_{\eta}$) are estimated from the ground state density distributions of the nucleus. We analyze the resulting asymmetry parameter $\eta$ and the relative neutron-proton asymmetry $R_{\eta}$ of the density play a crucial role in the mode(s) of decay and its half-life. Moreover, the excess neutron richness on the surface facets a superheavy nucleus for $\beta^-$ decays.
nucl-th
the modes of decay for the eveneven isotopes of superheavy nuclei of z 118 and 120 with neutron number 160 leq n leq 204 are investigated in the framework of the axially deformed relativistic mean field model the asymmetry parameter eta and the relative neutronproton asymmetry of the surface to the center r_eta are estimated from the ground state density distributions of the nucleus we analyze the resulting asymmetry parameter eta and the relative neutronproton asymmetry r_eta of the density play a crucial role in the modes of decay and its halflife moreover the excess neutron richness on the surface facets a superheavy nucleus for beta decays
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1,803.06435
Chapter 7 - Thermal Conductivity of Diamond Nanothread
This chapter introduces the thermal conductivity of a novel one-dimensional carbon nanostructure - diamond nanothread. It starts by introducing the family of the diamond nanothread as acquired from density functional theory calculations and also its successful experimental synthesisation. It then briefs the mechanical properties of the diamond nanothreads as a fundamental for their engineering applications. After that, it focuses on the thermal transport properties of the diamond nanothreads by examining the influences from various parameters such as size, geometry, and temperature. Then, the application of diamond nanothread as reinforcements for nanocomposites is discussed. By the end of the chapter, future directions and their potential applications are discussed.
cond-mat.mtrl-sci physics.app-ph
this chapter introduces the thermal conductivity of a novel onedimensional carbon nanostructure diamond nanothread it starts by introducing the family of the diamond nanothread as acquired from density functional theory calculations and also its successful experimental synthesisation it then briefs the mechanical properties of the diamond nanothreads as a fundamental for their engineering applications after that it focuses on the thermal transport properties of the diamond nanothreads by examining the influences from various parameters such as size geometry and temperature then the application of diamond nanothread as reinforcements for nanocomposites is discussed by the end of the chapter future directions and their potential applications are discussed
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1,803.06436
The Kepler Light Curves of AGN: A Detailed Analysis
We present a comprehensive analysis of 21 light curves of Type 1 AGN from the Kepler spacecraft. First, we describe the necessity and development of a customized pipeline for treating Kepler data of stochastically variable sources like AGN. We then present the light curves, power spectral density functions (PSDs), and flux histograms. The light curves display an astonishing variety of behaviors, many of which would not be detected in ground-based studies, including switching between distinct flux levels. Six objects exhibit PSD flattening at characteristic timescales which roughly correlate with black hole mass. These timescales are consistent with orbital timescales or freefall accretion timescales. We check for correlations of variability and high-frequency PSD slope with accretion rate, black hole mass, redshift and luminosity. We find that bolometric luminosity is anticorrelated with both variability and steepness of the PSD slope. We do not find evidence of the linear rms-flux relationships or lognormal flux distributions found in X-ray AGN light curves, indicating that reprocessing is not a significant contributor to optical variability at the 0.1-10% level.
astro-ph.HE
we present a comprehensive analysis of 21 light curves of type 1 agn from the kepler spacecraft first we describe the necessity and development of a customized pipeline for treating kepler data of stochastically variable sources like agn we then present the light curves power spectral density functions psds and flux histograms the light curves display an astonishing variety of behaviors many of which would not be detected in groundbased studies including switching between distinct flux levels six objects exhibit psd flattening at characteristic timescales which roughly correlate with black hole mass these timescales are consistent with orbital timescales or freefall accretion timescales we check for correlations of variability and highfrequency psd slope with accretion rate black hole mass redshift and luminosity we find that bolometric luminosity is anticorrelated with both variability and steepness of the psd slope we do not find evidence of the linear rmsflux relationships or lognormal flux distributions found in xray agn light curves indicating that reprocessing is not a significant contributor to optical variability at the 0110 level
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1,803.06437
Graphene and Carbon Nanotube Hybrid Structure: A Review
Graphene has been reported with record-breaking properties which have opened up huge potential applications. Considerable amount of researches have been devoted to manipulating or modify the properties of graphene to target a more smart nanoscale device. Graphene and carbon nanotube hybrid structure (GNHS) is one of the promising graphene derivate. The synthesis process and the mechanical properties are essential for the GNHS based devices. Therefore, this review will summarise the recent progress of the highly ordered GNHS synthesis/assembly, and discuss the mechanical properties of GNHS under various conditions as obtained from molecular dynamics simulations.
cond-mat.mtrl-sci physics.app-ph
graphene has been reported with recordbreaking properties which have opened up huge potential applications considerable amount of researches have been devoted to manipulating or modify the properties of graphene to target a more smart nanoscale device graphene and carbon nanotube hybrid structure gnhs is one of the promising graphene derivate the synthesis process and the mechanical properties are essential for the gnhs based devices therefore this review will summarise the recent progress of the highly ordered gnhs synthesisassembly and discuss the mechanical properties of gnhs under various conditions as obtained from molecular dynamics simulations
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1,803.06438
The morphology and temperature dependent tensile properties of diamond nanothreads
The ultrathin one-dimensional sp3 diamond nanothreads (NTHs), as successfully synthesised recently, have greatly augmented the interests from the carbon community. In principle, there can exist different stable NTH structures. In this work, we studied the mechanical behaviours of three representative NTHs using molecular dynamics simulations. It is found that the mechanical properties of NTH can vary significantly due to morphology differences, which are believed to originate from the different stress distributions determined by its structure. Further studies have shown that the temperature has a significant impact on the mechanical properties of the NTH. Specifically, the failure strength/strain decreases with increasing temperature, and the effective Young's modulus appears independent of temperature. The remarkable reduction of the failure strength/strain is believed to be resulted from the increased bond re-arrangement process and free lateral vibration at high temperatures. In addition, the NTH is found to have a relatively high bending rigidity, and behaves more like flexible elastic rod. This study highlights the importance of structure-property relation and provides a fundamental understanding of the tensile behaviours of different NTHs, which should shed light on the design and also application of the NTH-based nanostructures as strain sensors and mechanical connectors.
cond-mat.mtrl-sci
the ultrathin onedimensional sp3 diamond nanothreads nths as successfully synthesised recently have greatly augmented the interests from the carbon community in principle there can exist different stable nth structures in this work we studied the mechanical behaviours of three representative nths using molecular dynamics simulations it is found that the mechanical properties of nth can vary significantly due to morphology differences which are believed to originate from the different stress distributions determined by its structure further studies have shown that the temperature has a significant impact on the mechanical properties of the nth specifically the failure strengthstrain decreases with increasing temperature and the effective youngs modulus appears independent of temperature the remarkable reduction of the failure strengthstrain is believed to be resulted from the increased bond rearrangement process and free lateral vibration at high temperatures in addition the nth is found to have a relatively high bending rigidity and behaves more like flexible elastic rod this study highlights the importance of structureproperty relation and provides a fundamental understanding of the tensile behaviours of different nths which should shed light on the design and also application of the nthbased nanostructures as strain sensors and mechanical connectors
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1,803.06439
Global surfaces of section for dynamically convex Reeb flows on lens spaces
We show that a dynamically convex Reeb flow on the standard tight lens space $(L(p, 1),\xi_{\mathrm{std}})$, $p>1,$ admits a $p$-unknotted closed Reeb orbit $P$ which is the binding of a rational open book decomposition with disk-like pages. Each page is a rational global surface of section for the Reeb flow and the Conley-Zehnder index of the $p$-th iterate of $P$ is $3$. We also check dynamical convexity in the H\'enon-Heiles system for low positive energies. In this case the rational open book decomposition follows from the fact that the sphere-like component of the energy surface admits a $\mathbb{Z}_{3}$-symmetric periodic orbit and the flow descends to a Reeb flow on the standard tight $(L(3,2),\xi_{\mathrm{std}})$.
math.SG math.DS
we show that a dynamically convex reeb flow on the standard tight lens space lp 1xi_mathrmstd p1 admits a punknotted closed reeb orbit p which is the binding of a rational open book decomposition with disklike pages each page is a rational global surface of section for the reeb flow and the conleyzehnder index of the pth iterate of p is 3 we also check dynamical convexity in the henonheiles system for low positive energies in this case the rational open book decomposition follows from the fact that the spherelike component of the energy surface admits a mathbbz_3symmetric periodic orbit and the flow descends to a reeb flow on the standard tight l32xi_mathrmstd
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1,803.0644
Failure mechanism of monolayer graphene under hypervelocity impact of spherical projectile
The excellent mechanical properties of graphene have enabled it as appealing candidate in the field of impact protection or protective shield. By considering a monolayer graphene membrane, in this work, we assessed its deformation mechanisms under hypervelocity impact (from 2 to 6 km/s), based on a serial of in silico studies. It is found that the cracks are formed preferentially in the zigzag directions which are consistent with that observed from tensile deformation. Specifically, the boundary condition is found to exert an obvious influence on the stress distribution and transmission during the impact process, which eventually influences the penetration energy and crack growth. For similar sample size, the circular shape graphene possesses the best impact resistance, followed by hexagonal graphene membrane. Moreover, it is found the failure shape of graphene membrane has a strong relationship with the initial kinetic energy of the projectile. The higher kinetic energy, the more number the cracks. This study provides a fundamental understanding of the deformation mechanisms of monolayer graphene under impact, which is crucial in order to facilitate their emerging future applications for impact protection, such as protective shield from orbital debris for spacecraft.
cond-mat.mtrl-sci physics.app-ph
the excellent mechanical properties of graphene have enabled it as appealing candidate in the field of impact protection or protective shield by considering a monolayer graphene membrane in this work we assessed its deformation mechanisms under hypervelocity impact from 2 to 6 kms based on a serial of in silico studies it is found that the cracks are formed preferentially in the zigzag directions which are consistent with that observed from tensile deformation specifically the boundary condition is found to exert an obvious influence on the stress distribution and transmission during the impact process which eventually influences the penetration energy and crack growth for similar sample size the circular shape graphene possesses the best impact resistance followed by hexagonal graphene membrane moreover it is found the failure shape of graphene membrane has a strong relationship with the initial kinetic energy of the projectile the higher kinetic energy the more number the cracks this study provides a fundamental understanding of the deformation mechanisms of monolayer graphene under impact which is crucial in order to facilitate their emerging future applications for impact protection such as protective shield from orbital debris for spacecraft
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1,803.06441
A Novel Blaschke Unwinding Adaptive Fourier Decomposition based Signal Compression Algorithm with Application on ECG Signals
This paper presents a novel signal compression algorithm based on the Blaschke unwinding adaptive Fourier decomposition (AFD). The Blaschke unwinding AFD is a newly developed signal decomposition theory. It utilizes the Nevanlinna factorization and the maximal selection principle in each decomposition step, and achieves a faster convergence rate with higher fidelity. The proposed compression algorithm is applied to the electrocardiogram signal. To assess the performance of the proposed compression algorithm, in addition to the generic assessment criteria, we consider the less discussed criteria related to the clinical needs -- for the heart rate variability analysis purpose, how accurate the R peak information is preserved is evaluated. The experiments are conducted on the MIT-BIH arrhythmia benchmark database. The results show that the proposed algorithm performs better than other state-of-the-art approaches. Meanwhile, it also well preserves the R peak information.
eess.SP physics.data-an stat.ML
this paper presents a novel signal compression algorithm based on the blaschke unwinding adaptive fourier decomposition afd the blaschke unwinding afd is a newly developed signal decomposition theory it utilizes the nevanlinna factorization and the maximal selection principle in each decomposition step and achieves a faster convergence rate with higher fidelity the proposed compression algorithm is applied to the electrocardiogram signal to assess the performance of the proposed compression algorithm in addition to the generic assessment criteria we consider the less discussed criteria related to the clinical needs for the heart rate variability analysis purpose how accurate the r peak information is preserved is evaluated the experiments are conducted on the mitbih arrhythmia benchmark database the results show that the proposed algorithm performs better than other stateoftheart approaches meanwhile it also well preserves the r peak information
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1,803.06442
Replica Symmetry Breaking in Bipartite Spin Glasses and Neural Networks
Some interesting recent advances in the theoretical understanding of neural networks have been informed by results from the physics of disordered many-body systems. Motivated by these findings, this work uses the replica technique to study the mathematically tractable bipartite Sherrington-Kirkpatrick (SK) spin glass model, which is formally similar to a Restricted Boltzmann Machine (RBM) neural network. The bipartite SK model has been previously studied assuming replica symmetry; here this assumption is relaxed and a replica symmetry breaking analysis is performed. The bipartite SK model is found to have many features in common with Parisi's solution of the original, unipartite SK model, including the existence of a multitude of pure states which are related in a hierarchical, ultrametric fashion. As an application of this analysis, the optimal cost for a graph partitioning problem is shown to be simply related to the ground state energy of the bipartite SK model. As a second application, empirical investigations reveal that the Gibbs sampled outputs of an RBM trained on the MNIST data set are more ultrametrically distributed than the input data itself.
cond-mat.dis-nn cs.LG
some interesting recent advances in the theoretical understanding of neural networks have been informed by results from the physics of disordered manybody systems motivated by these findings this work uses the replica technique to study the mathematically tractable bipartite sherringtonkirkpatrick sk spin glass model which is formally similar to a restricted boltzmann machine rbm neural network the bipartite sk model has been previously studied assuming replica symmetry here this assumption is relaxed and a replica symmetry breaking analysis is performed the bipartite sk model is found to have many features in common with parisis solution of the original unipartite sk model including the existence of a multitude of pure states which are related in a hierarchical ultrametric fashion as an application of this analysis the optimal cost for a graph partitioning problem is shown to be simply related to the ground state energy of the bipartite sk model as a second application empirical investigations reveal that the gibbs sampled outputs of an rbm trained on the mnist data set are more ultrametrically distributed than the input data itself
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1,803.06443
Communication Compression for Decentralized Training
Optimizing distributed learning systems is an art of balancing between computation and communication. There have been two lines of research that try to deal with slower networks: {\em communication compression} for low bandwidth networks, and {\em decentralization} for high latency networks. In this paper, We explore a natural question: {\em can the combination of both techniques lead to a system that is robust to both bandwidth and latency?} Although the system implication of such combination is trivial, the underlying theoretical principle and algorithm design is challenging: unlike centralized algorithms, simply compressing exchanged information, even in an unbiased stochastic way, within the decentralized network would accumulate the error and fail to converge. In this paper, we develop a framework of compressed, decentralized training and propose two different strategies, which we call {\em extrapolation compression} and {\em difference compression}. We analyze both algorithms and prove both converge at the rate of $O(1/\sqrt{nT})$ where $n$ is the number of workers and $T$ is the number of iterations, matching the convergence rate for full precision, centralized training. We validate our algorithms and find that our proposed algorithm outperforms the best of merely decentralized and merely quantized algorithm significantly for networks with {\em both} high latency and low bandwidth.
cs.LG cs.DC cs.SY stat.ML
optimizing distributed learning systems is an art of balancing between computation and communication there have been two lines of research that try to deal with slower networks em communication compression for low bandwidth networks and em decentralization for high latency networks in this paper we explore a natural question em can the combination of both techniques lead to a system that is robust to both bandwidth and latency although the system implication of such combination is trivial the underlying theoretical principle and algorithm design is challenging unlike centralized algorithms simply compressing exchanged information even in an unbiased stochastic way within the decentralized network would accumulate the error and fail to converge in this paper we develop a framework of compressed decentralized training and propose two different strategies which we call em extrapolation compression and em difference compression we analyze both algorithms and prove both converge at the rate of o1sqrtnt where n is the number of workers and t is the number of iterations matching the convergence rate for full precision centralized training we validate our algorithms and find that our proposed algorithm outperforms the best of merely decentralized and merely quantized algorithm significantly for networks with em both high latency and low bandwidth
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1,803.06444
Measurement of the branching fraction of $B \rightarrow D^{(*)}\pi \ell\nu$ at Belle using hadronic tagging in fully reconstructed events
We report a measurement of the branching fraction of the decay $B \rightarrow D^{(*)}\pi \ell\nu$. The analysis uses 772$\times 10^6$ $B\bar{B}$ pairs produced in $e^+e^-\rightarrow \Upsilon(4S)$ data recorded by the Belle experiment at the KEKB asymmetric-energy $e^+e^-$ collider. The tagging $B$ meson in the decay is fully reconstructed in a hadronic decay mode. On the signal side, we reconstruct the decay $B \rightarrow D^{(*)}\pi \ell\nu$ $(\ell=e,\mu)$. The measured branching fractions are $\mathcal{B}(B^+ \rightarrow D^-\pi^+ \ell^+\nu)$ = [4.55 $\pm$ 0.27 (stat.) $\pm$ 0.39 (syst.)]$\times 10^{-3}$, $\mathcal{B}(B^0 \rightarrow \bar{D}^0\pi^- \ell^+\nu)$ = [4.05 $\pm$ 0.36 (stat.) $\pm$ 0.41 (syst.)]$\times 10^{-3}$, $\mathcal{B}(B^+ \rightarrow D^{*-}\pi^+ \ell^+\nu)$ = [6.03 $\pm$ 0.43 (stat.) $\pm$ 0.38 (syst.)]$\times 10^{-3}$, and $\mathcal{B}(B^0 \rightarrow \bar{D}^{*0}\pi^- \ell^+\nu)$ = [6.46 $\pm$ 0.53 (stat.) $\pm$ 0.52 (syst.)]$\times 10^{-3}$. These are in good agreement with the current world average values.
hep-ex
we report a measurement of the branching fraction of the decay b rightarrow dpi ellnu the analysis uses 772times 106 bbarb pairs produced in eerightarrow upsilon4s data recorded by the belle experiment at the kekb asymmetricenergy ee collider the tagging b meson in the decay is fully reconstructed in a hadronic decay mode on the signal side we reconstruct the decay b rightarrow dpi ellnu ellemu the measured branching fractions are mathcalbb rightarrow dpi ellnu 455 pm 027 stat pm 039 systtimes 103 mathcalbb0 rightarrow bard0pi ellnu 405 pm 036 stat pm 041 systtimes 103 mathcalbb rightarrow dpi ellnu 603 pm 043 stat pm 038 systtimes 103 and mathcalbb0 rightarrow bard0pi ellnu 646 pm 053 stat pm 052 systtimes 103 these are in good agreement with the current world average values
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1,803.06445
Datalog: Bag Semantics via Set Semantics
Duplicates in data management are common and problematic. In this work, we present a translation of Datalog under bag semantics into a well-behaved extension of Datalog, the so-called {\em warded Datalog}$^\pm$, under set semantics. From a theoretical point of view, this allows us to reason on bag semantics by making use of the well-established theoretical foundations of set semantics. From a practical point of view, this allows us to handle the bag semantics of Datalog by powerful, existing query engines for the required extension of Datalog. This use of Datalog$^\pm$ is extended to give a set semantics to duplicates in Datalog$^\pm$ itself. We investigate the properties of the resulting Datalog$^\pm$ programs, the problem of deciding multiplicities, and expressibility of some bag operations. Moreover, the proposed translation has the potential for interesting applications such as to Multiset Relational Algebra and the semantic web query language SPARQL with bag semantics.
cs.DB cs.AI cs.LO
duplicates in data management are common and problematic in this work we present a translation of datalog under bag semantics into a wellbehaved extension of datalog the socalled em warded datalogpm under set semantics from a theoretical point of view this allows us to reason on bag semantics by making use of the wellestablished theoretical foundations of set semantics from a practical point of view this allows us to handle the bag semantics of datalog by powerful existing query engines for the required extension of datalog this use of datalogpm is extended to give a set semantics to duplicates in datalogpm itself we investigate the properties of the resulting datalogpm programs the problem of deciding multiplicities and expressibility of some bag operations moreover the proposed translation has the potential for interesting applications such as to multiset relational algebra and the semantic web query language sparql with bag semantics
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1,803.06446
On Polyhedral Estimation of Signals via Indirect Observations
We consider the problem of recovering linear image of unknown signal belonging to a given convex compact signal set from noisy observation of another linear image of the signal. We develop a simple generic efficiently computable nonlinear in observations "polyhedral" estimate along with computation-friendly techniques for its design and risk analysis. We demonstrate that under favorable circumstances the resulting estimate is provably near-optimal in the minimax sense, the "favorable circumstances" being less restrictive than the weakest known so far assumptions ensuring near-optimality of estimates which are linear in observations.
math.ST stat.TH
we consider the problem of recovering linear image of unknown signal belonging to a given convex compact signal set from noisy observation of another linear image of the signal we develop a simple generic efficiently computable nonlinear in observations polyhedral estimate along with computationfriendly techniques for its design and risk analysis we demonstrate that under favorable circumstances the resulting estimate is provably nearoptimal in the minimax sense the favorable circumstances being less restrictive than the weakest known so far assumptions ensuring nearoptimality of estimates which are linear in observations
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1,803.06447
Emergence of spin-orbit order in the spinel CuCr$_2$O$_4$
We determined the magnetic structure of CuCr$_2$O$_4$ using neutron diffraction and irreducible representation analysis. The measurements identified a new phase between 155 K and 125 K as nearly collinear magnetic ordering in the Cr pyrochlore lattice. Below 125 K, a Cu-Cr ferrimagnetic component develops the noncollinear order. Along with the simultaneously obtained O positions and the quantum effect of spin-orbit coupling, the magnetic structure is understood to involve spin-orbit ordering, accompanied by an appreciably deformed orbital of presumably spin-only Cu and Cr.
cond-mat.str-el
we determined the magnetic structure of cucr_2o_4 using neutron diffraction and irreducible representation analysis the measurements identified a new phase between 155 k and 125 k as nearly collinear magnetic ordering in the cr pyrochlore lattice below 125 k a cucr ferrimagnetic component develops the noncollinear order along with the simultaneously obtained o positions and the quantum effect of spinorbit coupling the magnetic structure is understood to involve spinorbit ordering accompanied by an appreciably deformed orbital of presumably spinonly cu and cr
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1,803.06448
Frequency-Domain Decoupling for MIMO-GFDM Spatial Multiplexing
Generalized frequency division multiplexing (GFDM) is considered a non-orthogonal waveform and known to encounter difficulties when using in the spatial multiplexing mode of multiple-input-multiple-output (MIMO) scenario. In this paper, a class of GFDM prototype filters, under which the GFDM system is free from inter-subcarrier interference, is investigated, enabling frequency-domain decoupling in the processing at the GFDM receiver. An efficient MIMO-GFDM detection method based on depth-first sphere decoding is then proposed with such class of filters. Numerical results confirm a significant reduction in complexity, especially when the number of subcarriers is large, compared with existing methods presented in recent years.
cs.IT math.IT
generalized frequency division multiplexing gfdm is considered a nonorthogonal waveform and known to encounter difficulties when using in the spatial multiplexing mode of multipleinputmultipleoutput mimo scenario in this paper a class of gfdm prototype filters under which the gfdm system is free from intersubcarrier interference is investigated enabling frequencydomain decoupling in the processing at the gfdm receiver an efficient mimogfdm detection method based on depthfirst sphere decoding is then proposed with such class of filters numerical results confirm a significant reduction in complexity especially when the number of subcarriers is large compared with existing methods presented in recent years
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1,803.06449
Note: Variational Encoding of Protein Dynamics Benefits from Maximizing Latent Autocorrelation
As deep Variational Auto-Encoder (VAE) frameworks become more widely used for modeling biomolecular simulation data, we emphasize the capability of the VAE architecture to concurrently maximize the timescale of the latent space while inferring a reduced coordinate, which assists in finding slow processes as according to the variational approach to conformational dynamics. We additionally provide evidence that the VDE framework (Hern\'andez et al., 2017), which uses this autocorrelation loss along with a time-lagged reconstruction loss, obtains a variationally optimized latent coordinate in comparison with related loss functions. We thus recommend leveraging the autocorrelation of the latent space while training neural network models of biomolecular simulation data to better represent slow processes.
physics.chem-ph cs.LG physics.bio-ph stat.ML
as deep variational autoencoder vae frameworks become more widely used for modeling biomolecular simulation data we emphasize the capability of the vae architecture to concurrently maximize the timescale of the latent space while inferring a reduced coordinate which assists in finding slow processes as according to the variational approach to conformational dynamics we additionally provide evidence that the vde framework hernandez et al 2017 which uses this autocorrelation loss along with a timelagged reconstruction loss obtains a variationally optimized latent coordinate in comparison with related loss functions we thus recommend leveraging the autocorrelation of the latent space while training neural network models of biomolecular simulation data to better represent slow processes
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1,803.0645
Measuring fluorescence into a nanofiber by observing field quadrature noise
We perform balanced homodyne detection of the electromagnetic field in a single-mode tapered optical nanofiber surrounded by rubidium atoms in a magneto-optical trap. Resonant fluorescence of atoms into the nanofiber mode manifests itself as increased quantum noise of the field quadratures. The autocorrelation function of the homodyne detector's output photocurrent exhibits exponential fall-off with a decay time constant of $26.3\pm 0.6$ ns, which is consistent with the theoretical expectation under our experimental conditions. To our knowledge, this is the first experiment in which fluorescence has been observed and measured by balanced optical homodyne detection.
physics.atom-ph
we perform balanced homodyne detection of the electromagnetic field in a singlemode tapered optical nanofiber surrounded by rubidium atoms in a magnetooptical trap resonant fluorescence of atoms into the nanofiber mode manifests itself as increased quantum noise of the field quadratures the autocorrelation function of the homodyne detectors output photocurrent exhibits exponential falloff with a decay time constant of 263pm 06 ns which is consistent with the theoretical expectation under our experimental conditions to our knowledge this is the first experiment in which fluorescence has been observed and measured by balanced optical homodyne detection
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1,803.06451
Instability of the solitary waves for the generalized derivative nonlinear Schr\"odinger equation in the degenerate case
In this paper, we develop the modulation analysis, the perturbation argument and the Virial identity similar as those in \cite{MartelM:Instab:gKdV} to show the orbital instability of the solitary waves $\Q\sts{x-ct}\e^{\i\omega t}$ of the generalized derivative nonlinear Schr\"odinger equation (gDNLS) in the degenerate case $c=2z_0\sqrt{\omega}$, where $z_0=z_0\sts{\sigma} $ is the unique zero point of $F\sts{z;~\sigma}$ in $\sts{-1, ~ 1}$. The new ingredients in the proof are the refined modulation decomposition of the solution near $\Q$ according to the spectrum property of the linearized operator $\Scal_{\omega, c}"\sts{\Q}$ and the refined construction of the Virial identity in the degenerate case. Our argument is qualitative, and we improve the result in \cite{Fukaya2017}.
math.AP
in this paper we develop the modulation analysis the perturbation argument and the virial identity similar as those in citemartelminstabgkdv to show the orbital instability of the solitary waves qstsxcteiomega t of the generalized derivative nonlinear schrodinger equation gdnls in the degenerate case c2z_0sqrtomega where z_0z_0stssigma is the unique zero point of fstszsigma in sts1 1 the new ingredients in the proof are the refined modulation decomposition of the solution near q according to the spectrum property of the linearized operator scal_omega cstsq and the refined construction of the virial identity in the degenerate case our argument is qualitative and we improve the result in citefukaya2017
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1,803.06452
Spectral Estimation of Plasma Fluctuations II: Nonstationary Analysis of ELM Spectra
Several analysis methods for nonstationary fluctuations are described and applied to the edge localized mode (ELM) instabilities of limiter H-mode plasmas. The microwave scattering diagnostic observes poloidal $k_{\theta}$ values of 3.3 cm$^{-1}$, averaged over a 20 cm region at the plasma edge.A short autoregressive filter enhances the nonstationary component of the plasma fluctuations by removing much of the background level of stationary fluctuations. Between ELMs, the spectrum predominantly consists of broad-banded 300-700 kHz fluctuations propagating in the electron diamagnetic drift direction, indicating the presence of a negative electric field near the plasma edge. The time-frequency spectrogram is computed with the multiple taper technique. By using the singular value decomposition of the spectrogram, it is shown that the spectrum during the ELM is broader and more symmetric than that of the stationary spectrum. The ELM period and the evolution of the spectrum between ELMs varies from discharge to discharge. For the discharge under consideration which has distinct ELMs with a 1 msec period, the spectrum has a maximum in the electron drift direction which relaxes to a near constant value %its characteristic shape in the first half millisecond after the end of the ELM and then grows slowly. In contrast, the level of the fluctuations in the ion drift direction increases exponentially by a factor of eight in the five milliseconds~after the ELM. High frequency precursors are found which occur one millisecond before the ELMs and propagate in the ion drift direction. These precursors are very short ($\sim 10 \mu$secs), coherent bursts, and they predict the occurrence of an ELM with a high success rate.
physics.plasm-ph eess.AS physics.data-an stat.AP
several analysis methods for nonstationary fluctuations are described and applied to the edge localized mode elm instabilities of limiter hmode plasmas the microwave scattering diagnostic observes poloidal k_theta values of 33 cm1 averaged over a 20 cm region at the plasma edgea short autoregressive filter enhances the nonstationary component of the plasma fluctuations by removing much of the background level of stationary fluctuations between elms the spectrum predominantly consists of broadbanded 300700 khz fluctuations propagating in the electron diamagnetic drift direction indicating the presence of a negative electric field near the plasma edge the timefrequency spectrogram is computed with the multiple taper technique by using the singular value decomposition of the spectrogram it is shown that the spectrum during the elm is broader and more symmetric than that of the stationary spectrum the elm period and the evolution of the spectrum between elms varies from discharge to discharge for the discharge under consideration which has distinct elms with a 1 msec period the spectrum has a maximum in the electron drift direction which relaxes to a near constant value its characteristic shape in the first half millisecond after the end of the elm and then grows slowly in contrast the level of the fluctuations in the ion drift direction increases exponentially by a factor of eight in the five millisecondsafter the elm high frequency precursors are found which occur one millisecond before the elms and propagate in the ion drift direction these precursors are very short sim 10 musecs coherent bursts and they predict the occurrence of an elm with a high success rate
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1,803.06453
Constrained Deep Learning using Conditional Gradient and Applications in Computer Vision
A number of results have recently demonstrated the benefits of incorporating various constraints when training deep architectures in vision and machine learning. The advantages range from guarantees for statistical generalization to better accuracy to compression. But support for general constraints within widely used libraries remains scarce and their broader deployment within many applications that can benefit from them remains under-explored. Part of the reason is that Stochastic gradient descent (SGD), the workhorse for training deep neural networks, does not natively deal with constraints with global scope very well. In this paper, we revisit a classical first order scheme from numerical optimization, Conditional Gradients (CG), that has, thus far had limited applicability in training deep models. We show via rigorous analysis how various constraints can be naturally handled by modifications of this algorithm. We provide convergence guarantees and show a suite of immediate benefits that are possible -- from training ResNets with fewer layers but better accuracy simply by substituting in our version of CG to faster training of GANs with 50% fewer epochs in image inpainting applications to provably better generalization guarantees using efficiently implementable forms of recently proposed regularizers.
cs.LG cs.CV stat.ML
a number of results have recently demonstrated the benefits of incorporating various constraints when training deep architectures in vision and machine learning the advantages range from guarantees for statistical generalization to better accuracy to compression but support for general constraints within widely used libraries remains scarce and their broader deployment within many applications that can benefit from them remains underexplored part of the reason is that stochastic gradient descent sgd the workhorse for training deep neural networks does not natively deal with constraints with global scope very well in this paper we revisit a classical first order scheme from numerical optimization conditional gradients cg that has thus far had limited applicability in training deep models we show via rigorous analysis how various constraints can be naturally handled by modifications of this algorithm we provide convergence guarantees and show a suite of immediate benefits that are possible from training resnets with fewer layers but better accuracy simply by substituting in our version of cg to faster training of gans with 50 fewer epochs in image inpainting applications to provably better generalization guarantees using efficiently implementable forms of recently proposed regularizers
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1,803.06454
Some Questions in $l-$adic Cohomology
The comparison theorem for a smooth projective variety $X$ over $\mathbb{C}$ tells us that the Betti numbers are independent of $l$. We aim to understand the $l$ independence of Betti numbers for smooth projective varieties $X$ over $k$, where $k$ is an algebraic extension of $\mathbb{F}_p$.
math.AG
the comparison theorem for a smooth projective variety x over mathbbc tells us that the betti numbers are independent of l we aim to understand the l independence of betti numbers for smooth projective varieties x over k where k is an algebraic extension of mathbbf_p
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1,803.06455
A-infinity algebras, strand algebras, and contact categories
In previous work we showed that the contact category algebra of a quadrangulated surface is isomorphic to the homology of a strand algebra from bordered sutured Floer theory. Being isomorphic to the homology of a differential graded algebra, this contact category algebra has an A-infinity structure, allowing us to combine contact structures not just by gluing, but also by higher-order operations. In this paper we investigate such A-infinity structures and higher order operations on contact structures. We give explicit constructions of such A-infinity structures, and establish some of their properties, including conditions for the vanishing and nonvanishing of A-infinity operations. Along the way we develop several related notions, including a detailed consideration of tensor products of strand diagrams.
math.GT math.AT math.SG
in previous work we showed that the contact category algebra of a quadrangulated surface is isomorphic to the homology of a strand algebra from bordered sutured floer theory being isomorphic to the homology of a differential graded algebra this contact category algebra has an ainfinity structure allowing us to combine contact structures not just by gluing but also by higherorder operations in this paper we investigate such ainfinity structures and higher order operations on contact structures we give explicit constructions of such ainfinity structures and establish some of their properties including conditions for the vanishing and nonvanishing of ainfinity operations along the way we develop several related notions including a detailed consideration of tensor products of strand diagrams
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1,803.06456
Experiments with Neural Networks for Small and Large Scale Authorship Verification
We propose two models for a special case of authorship verification problem. The task is to investigate whether the two documents of a given pair are written by the same author. We consider the authorship verification problem for both small and large scale datasets. The underlying small-scale problem has two main challenges: First, the authors of the documents are unknown to us because no previous writing samples are available. Second, the two documents are short (a few hundred to a few thousand words) and may differ considerably in the genre and/or topic. To solve it we propose transformation encoder to transform one document of the pair into the other. This document transformation generates a loss which is used as a recognizable feature to verify if the authors of the pair are identical. For the large scale problem where various authors are engaged and more examples are available with larger length, a parallel recurrent neural network is proposed. It compares the language models of the two documents. We evaluate our methods on various types of datasets including Authorship Identification datasets of PAN competition, Amazon reviews, and machine learning articles. Experiments show that both methods achieve stable and competitive performance compared to the baselines.
cs.CL
we propose two models for a special case of authorship verification problem the task is to investigate whether the two documents of a given pair are written by the same author we consider the authorship verification problem for both small and large scale datasets the underlying smallscale problem has two main challenges first the authors of the documents are unknown to us because no previous writing samples are available second the two documents are short a few hundred to a few thousand words and may differ considerably in the genre andor topic to solve it we propose transformation encoder to transform one document of the pair into the other this document transformation generates a loss which is used as a recognizable feature to verify if the authors of the pair are identical for the large scale problem where various authors are engaged and more examples are available with larger length a parallel recurrent neural network is proposed it compares the language models of the two documents we evaluate our methods on various types of datasets including authorship identification datasets of pan competition amazon reviews and machine learning articles experiments show that both methods achieve stable and competitive performance compared to the baselines
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1,803.06457
Generalization of a Real-Analysis Result to a Class of Topological Vector Spaces
In this paper, we generalize an elementary real-analysis result to a class of topological vector spaces. We also give an example of a topological vector space to which the result cannot be generalized.
math.FA math.PR
in this paper we generalize an elementary realanalysis result to a class of topological vector spaces we also give an example of a topological vector space to which the result cannot be generalized
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1,803.06458
A local $\psi$-epistemic retrocausal hidden-variable model of Bell correlations with wavefunctions in physical space
We construct a local $\psi$-epistemic hidden-variable model of Bell correlations by a retrocausal adaptation of the originally superdeterministic model given by Brans. In our model, for a pair of particles the joint quantum state $|\psi_e(t)\rangle$ as determined by preparation is epistemic. The model also assigns to the pair of particles a factorisable joint quantum state $|\psi_o(t)\rangle$ which is different from the prepared quantum state $|\psi_e(t)\rangle$ and has an ontic status. The ontic state of a single particle consists of two parts. First, a single particle ontic quantum state $\chi(\vec{x},t)|i\rangle$, where $\chi(\vec{x},t)$ is a 3-space wavepacket and $|i\rangle$ is a spin eigenstate of the future measurement setting. Second, a particle position in 3-space $\vec{x}(t)$, which evolves via a de Broglie-Bohm type guidance equation with the 3-space wavepacket $\chi(\vec{x},t)$ acting as a local pilot wave. The joint ontic quantum state $|\psi_o(t)\rangle$ fixes the measurement outcomes deterministically whereas the prepared quantum state $|\psi_e(t)\rangle$ determines the distribution of the $|\psi_o(t)\rangle$'s over an ensemble. Both $|\psi_o(t)\rangle$ and $|\psi_e(t)\rangle$ evolve via the Schrodinger equation. Our model exactly reproduces the Bell correlations for any pair of measurement settings. We also consider `non-equilibrium' extensions of the model with an arbitrary distribution of hidden variables. We show that, in non-equilibrium, the model generally violates no-signalling constraints while remaining local with respect to both ontology and interaction between particles. We argue that our model shares some structural similarities with the modal class of interpretations of quantum mechanics.
quant-ph
we construct a local psiepistemic hiddenvariable model of bell correlations by a retrocausal adaptation of the originally superdeterministic model given by brans in our model for a pair of particles the joint quantum state psi_etrangle as determined by preparation is epistemic the model also assigns to the pair of particles a factorisable joint quantum state psi_otrangle which is different from the prepared quantum state psi_etrangle and has an ontic status the ontic state of a single particle consists of two parts first a single particle ontic quantum state chivecxtirangle where chivecxt is a 3space wavepacket and irangle is a spin eigenstate of the future measurement setting second a particle position in 3space vecxt which evolves via a de brogliebohm type guidance equation with the 3space wavepacket chivecxt acting as a local pilot wave the joint ontic quantum state psi_otrangle fixes the measurement outcomes deterministically whereas the prepared quantum state psi_etrangle determines the distribution of the psi_otrangles over an ensemble both psi_otrangle and psi_etrangle evolve via the schrodinger equation our model exactly reproduces the bell correlations for any pair of measurement settings we also consider nonequilibrium extensions of the model with an arbitrary distribution of hidden variables we show that in nonequilibrium the model generally violates nosignalling constraints while remaining local with respect to both ontology and interaction between particles we argue that our model shares some structural similarities with the modal class of interpretations of quantum mechanics
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1,803.06459
Learning to Cluster for Proposal-Free Instance Segmentation
This work proposed a novel learning objective to train a deep neural network to perform end-to-end image pixel clustering. We applied the approach to instance segmentation, which is at the intersection of image semantic segmentation and object detection. We utilize the most fundamental property of instance labeling -- the pairwise relationship between pixels -- as the supervision to formulate the learning objective, then apply it to train a fully convolutional network (FCN) for learning to perform pixel-wise clustering. The resulting clusters can be used as the instance labeling directly. To support labeling of an unlimited number of instance, we further formulate ideas from graph coloring theory into the proposed learning objective. The evaluation on the Cityscapes dataset demonstrates strong performance and therefore proof of the concept. Moreover, our approach won the second place in the lane detection competition of 2017 CVPR Autonomous Driving Challenge, and was the top performer without using external data.
cs.CV cs.AI cs.LG
this work proposed a novel learning objective to train a deep neural network to perform endtoend image pixel clustering we applied the approach to instance segmentation which is at the intersection of image semantic segmentation and object detection we utilize the most fundamental property of instance labeling the pairwise relationship between pixels as the supervision to formulate the learning objective then apply it to train a fully convolutional network fcn for learning to perform pixelwise clustering the resulting clusters can be used as the instance labeling directly to support labeling of an unlimited number of instance we further formulate ideas from graph coloring theory into the proposed learning objective the evaluation on the cityscapes dataset demonstrates strong performance and therefore proof of the concept moreover our approach won the second place in the lane detection competition of 2017 cvpr autonomous driving challenge and was the top performer without using external data
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1,803.0646
Mean Reverting Portfolios via Penalized OU-Likelihood Estimation
We study an optimization-based approach to con- struct a mean-reverting portfolio of assets. Our objectives are threefold: (1) design a portfolio that is well-represented by an Ornstein-Uhlenbeck process with parameters estimated by maximum likelihood, (2) select portfolios with desirable characteristics of high mean reversion and low variance, and (3) select a parsimonious portfolio, i.e. find a small subset of a larger universe of assets that can be used for long and short positions. We present the full problem formulation, a specialized algorithm that exploits partial minimization, and numerical examples using both simulated and empirical price data.
q-fin.PM math.OC stat.ML
we study an optimizationbased approach to con struct a meanreverting portfolio of assets our objectives are threefold 1 design a portfolio that is wellrepresented by an ornsteinuhlenbeck process with parameters estimated by maximum likelihood 2 select portfolios with desirable characteristics of high mean reversion and low variance and 3 select a parsimonious portfolio ie find a small subset of a larger universe of assets that can be used for long and short positions we present the full problem formulation a specialized algorithm that exploits partial minimization and numerical examples using both simulated and empirical price data
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1,803.06461
Constraints on the cohomological correspondence associated to a self map
In this article we establish some constraints on the eigenvalues for the action of a self map of a proper variety on its $\ell$-adic cohomology. The essential ingredients are a trace formula due to Fujiwara, and the theory of weights.
math.AG
in this article we establish some constraints on the eigenvalues for the action of a self map of a proper variety on its elladic cohomology the essential ingredients are a trace formula due to fujiwara and the theory of weights
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1,803.06462
500MHz resonant photodetector for high-quantum-effciency, low-noise homodyne measurement
We design and demonstrate a resonant-type differential photodetector for low-noise quantum homodyne measurement at 500MHz optical sideband with 17MHz of bandwidth. By using a microwave monolithic amplifier and a discrete voltage buffer circuit, a low-noise voltage amplifier is realized and applied to our detector. 12dB of signal-to-noise ratio of the shot noise to the electric noise is obtained with 5mW of continuous-wave local oscillator. We analyze the frequency response and the noise characteristics of a resonant photodetector, and the theoretical model agrees with the shot noise measurement.
physics.app-ph quant-ph
we design and demonstrate a resonanttype differential photodetector for lownoise quantum homodyne measurement at 500mhz optical sideband with 17mhz of bandwidth by using a microwave monolithic amplifier and a discrete voltage buffer circuit a lownoise voltage amplifier is realized and applied to our detector 12db of signaltonoise ratio of the shot noise to the electric noise is obtained with 5mw of continuouswave local oscillator we analyze the frequency response and the noise characteristics of a resonant photodetector and the theoretical model agrees with the shot noise measurement
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1,803.06463
Multiplication formulas and semisimplicity for q-Schur superalgebras
We investigate products of certain double cosets for the symmetric group and use the findings to derive some multiplication formulas for q-Schur superalgebras. This gives a combinatorialisation of the relative norm approach developed by the first two authors. We then give several applications of the multiplication formulas, including the matrix representation of the regular representation and a semisimplicity criterion for q-Schur superalgebras. We also construct infinitesimal and little q-Schur superalgebras directly from the multiplication formulas and develop their semisimplicity criteria.
math.QA math.GR math.RA math.RT
we investigate products of certain double cosets for the symmetric group and use the findings to derive some multiplication formulas for qschur superalgebras this gives a combinatorialisation of the relative norm approach developed by the first two authors we then give several applications of the multiplication formulas including the matrix representation of the regular representation and a semisimplicity criterion for qschur superalgebras we also construct infinitesimal and little qschur superalgebras directly from the multiplication formulas and develop their semisimplicity criteria
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1,803.06464
Toward Understanding the Impact of User Participation in Autonomous Ridesharing Systems
Autonomous ridesharing systems (ARS) promise many societal and environmental benefits, including decreased accident rates, reduced energy consumption and pollutant emissions, and diminished land use for parking. To unleash ARS' potential, stakeholders must understand how the degree of passenger participation influences the ridesharing systems' efficiency. To date, however, a careful study that quantifies the impact of user participation on ARS' performance is missing. Here, we present the first simulation analysis to investigate how and to what extent user participation affects the efficiency of ARS. We demonstrate how specific configurations (e.g., fleet size, vehicle capacity, and the maximum waiting time) of a system can be identified to counter the performance loss due to users' uncoordinated behavior on ridesharing participation. Our results indicate that stakeholders of ARS should base decisions regarding system configurations on insights from data-driven simulations and make tradeoffs between system efficiency and price of anarchy for desired outcomes.
cs.CY cs.MA cs.SY
autonomous ridesharing systems ars promise many societal and environmental benefits including decreased accident rates reduced energy consumption and pollutant emissions and diminished land use for parking to unleash ars potential stakeholders must understand how the degree of passenger participation influences the ridesharing systems efficiency to date however a careful study that quantifies the impact of user participation on ars performance is missing here we present the first simulation analysis to investigate how and to what extent user participation affects the efficiency of ars we demonstrate how specific configurations eg fleet size vehicle capacity and the maximum waiting time of a system can be identified to counter the performance loss due to users uncoordinated behavior on ridesharing participation our results indicate that stakeholders of ars should base decisions regarding system configurations on insights from datadriven simulations and make tradeoffs between system efficiency and price of anarchy for desired outcomes
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1,803.06465
Local Continuity and Asymptotic Behaviour of Degenerate Parabolic Systems
We study the local H\"older continuity and the asymptotic behaviour of solution, $\mathbf{u}=(u^1,\cdots, u^k)$, of the degenerate system \begin{equation*} u^i_t=\nabla\cdot\left(m\,U^{m-1}\nabla u^i\right) \qquad \text{for $m>1$ and $i=1,\cdots,k$ } \end{equation*} which describes the populations density of $k$-species whose diffusion is determined by their total population density $U=u^1+\cdots+u^k$. For the local H\"older continuity, we adopt the intrinsic scaling and iteration arguments of DeGiorgi, Moser, and Dibenedetto. Under some regularity conditions, we also prove that the population density function of $i$-th species with the population $M_i$ converges in $C_s^{\infty}$ to $\frac{M_i}{M}\mathcal{B}_M(x,t)$ as $t\to \infty$ where $\mathcal{B}_M$ is the Barenblatt profile of the standard porous medium equation with $L^1$ mass $M=M_1+\cdots+M_k$. As a consequence of asymptotic behaviour, it is shown that each density function becomes a concave function after a finite time.
math.AP
we study the local holder continuity and the asymptotic behaviour of solution mathbfuu1cdots uk of the degenerate system beginequation ui_tnablacdotleftmum1nabla uiright qquad textfor m1 and i1cdotsk endequation which describes the populations density of kspecies whose diffusion is determined by their total population density uu1cdotsuk for the local holder continuity we adopt the intrinsic scaling and iteration arguments of degiorgi moser and dibenedetto under some regularity conditions we also prove that the population density function of ith species with the population m_i converges in c_sinfty to fracm_immathcalb_mxt as tto infty where mathcalb_m is the barenblatt profile of the standard porous medium equation with l1 mass mm_1cdotsm_k as a consequence of asymptotic behaviour it is shown that each density function becomes a concave function after a finite time
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1,803.06466
Example-based super-resolution for point-cloud video
We propose a mixed-resolution point-cloud representation and an example-based super-resolution framework, from which several processing tools can be derived, such as compression, denoising and error concealment. By inferring the high-frequency content of low-resolution frames based on the similarities between adjacent full-resolution frames, the proposed framework achieves an average 1.18 dB gain over low-pass versions of the point-cloud, for a projection-based distortion metric[1-2].
eess.SP
we propose a mixedresolution pointcloud representation and an examplebased superresolution framework from which several processing tools can be derived such as compression denoising and error concealment by inferring the highfrequency content of lowresolution frames based on the similarities between adjacent fullresolution frames the proposed framework achieves an average 118 db gain over lowpass versions of the pointcloud for a projectionbased distortion metric12
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