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1,802.0566
Fidelity based Measurement Induced Nonlocality over two-sided measurements
In this paper, we introduce quantum fidelity based measurement induced nonlocality for the bipartite state over two-sided von Neumann projective measurements. While all the properties of this quantity are reflected from that of one-sided measurement, the latter one is shown to set an upper bound for arbitrary bipartite state. As an illustration, we have studied the nonlocality of Bell diagonal state.
quant-ph
in this paper we introduce quantum fidelity based measurement induced nonlocality for the bipartite state over twosided von neumann projective measurements while all the properties of this quantity are reflected from that of onesided measurement the latter one is shown to set an upper bound for arbitrary bipartite state as an illustration we have studied the nonlocality of bell diagonal state
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1,802.05661
LISA sources in Milky Way globular clusters
We explore the formation of double-compact-object binaries in Milky Way (MW) globular clusters (GCs) that may be detectable by the Laser Interferometer Space Antenna (LISA). We use a set of 137 fully evolved GC models that, overall, effectively match the properties of the observed GCs in the MW. We estimate that, in total, the MW GCs contain $\sim21$ sources that will be detectable by LISA. These detectable sources contain all combinations of black hole (BH), neutron star, and white dwarf components. We predict $\sim7$ of these sources will be BH-BH binaries. Furthermore, we show that some of these BH-BH binaries can have signal-to-noise ratios large enough to be detectable at the distance of the Andromeda galaxy or even the Virgo cluster.
astro-ph.HE astro-ph.GA
we explore the formation of doublecompactobject binaries in milky way mw globular clusters gcs that may be detectable by the laser interferometer space antenna lisa we use a set of 137 fully evolved gc models that overall effectively match the properties of the observed gcs in the mw we estimate that in total the mw gcs contain sim21 sources that will be detectable by lisa these detectable sources contain all combinations of black hole bh neutron star and white dwarf components we predict sim7 of these sources will be bhbh binaries furthermore we show that some of these bhbh binaries can have signaltonoise ratios large enough to be detectable at the distance of the andromeda galaxy or even the virgo cluster
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1,802.05662
List Heaps
This paper presents a simple extension of the binary heap, the List Heap. We use List Heaps to demonstrate the idea of adaptive heaps: heaps whose performance is a function of both the size of the problem instance and the disorder of the problem instance. We focus on the presortedness of the input sequence as a measure of disorder for the problem instance. A number of practical applications that rely on heaps deal with input that is not random. Even random input contains presorted subsequences. Devising heaps that exploit this structure may provide a means for improving practical performance. We present some basic empirical tests to support this claim. Additionally, adaptive heaps may provide an interesting direction for theoretical investigation.
cs.DS
this paper presents a simple extension of the binary heap the list heap we use list heaps to demonstrate the idea of adaptive heaps heaps whose performance is a function of both the size of the problem instance and the disorder of the problem instance we focus on the presortedness of the input sequence as a measure of disorder for the problem instance a number of practical applications that rely on heaps deal with input that is not random even random input contains presorted subsequences devising heaps that exploit this structure may provide a means for improving practical performance we present some basic empirical tests to support this claim additionally adaptive heaps may provide an interesting direction for theoretical investigation
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1,802.05663
Imaging the Developing Heart: Synchronized Timelapse Microscopy During Developmental Changes
How do you use imaging to analyse the development of the heart, which not only changes shape but also undergoes constant, high-speed, quasi-periodic changes? We have integrated ideas from prospective and retrospective optical gating to capture long-term, phase-locked developmental time-lapse videos. In this paper we demonstrate the success of this approach over a key developmental time period: heart looping, where large changes in heart shape prevent previous prospective gating approaches from capturing phase-locked videos. We use the comparison with other approaches to in vivo heart imaging to highlight the importance of collecting the most appropriate data for the biological question.
q-bio.TO
how do you use imaging to analyse the development of the heart which not only changes shape but also undergoes constant highspeed quasiperiodic changes we have integrated ideas from prospective and retrospective optical gating to capture longterm phaselocked developmental timelapse videos in this paper we demonstrate the success of this approach over a key developmental time period heart looping where large changes in heart shape prevent previous prospective gating approaches from capturing phaselocked videos we use the comparison with other approaches to in vivo heart imaging to highlight the importance of collecting the most appropriate data for the biological question
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1,802.05664
DeepMatch: Balancing Deep Covariate Representations for Causal Inference Using Adversarial Training
We study optimal covariate balance for causal inferences from observational data when rich covariates and complex relationships necessitate flexible modeling with neural networks. Standard approaches such as propensity weighting and matching/balancing fail in such settings due to miscalibrated propensity nets and inappropriate covariate representations, respectively. We propose a new method based on adversarial training of a weighting and a discriminator network that effectively addresses this methodological gap. This is demonstrated through new theoretical characterizations of the method as well as empirical results using both fully connected architectures to learn complex relationships and convolutional architectures to handle image confounders, showing how this new method can enable strong causal analyses in these challenging settings.
stat.ML
we study optimal covariate balance for causal inferences from observational data when rich covariates and complex relationships necessitate flexible modeling with neural networks standard approaches such as propensity weighting and matchingbalancing fail in such settings due to miscalibrated propensity nets and inappropriate covariate representations respectively we propose a new method based on adversarial training of a weighting and a discriminator network that effectively addresses this methodological gap this is demonstrated through new theoretical characterizations of the method as well as empirical results using both fully connected architectures to learn complex relationships and convolutional architectures to handle image confounders showing how this new method can enable strong causal analyses in these challenging settings
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1,802.05665
Solar-System Studies with Pulsar Timing Arrays
High-precision pulsar timing is central to a wide range of astrophysics and fundamental physics applications. When timing an ensemble of millisecond pulsars in different sky positions, known as a pulsar timing array (PTA), one can search for ultra-low-frequency gravitational waves (GWs) through the spatial correlations that spacetime deformations by passing GWs are predicted to induce on the pulses' times-of-arrival (TOAs). A pulsar-timing model, requires the use of a solar-system ephemeris (SSE) to properly predict the position of the solar-system barycentre, the (quasi-)inertial frame where all TOAs are referred. Here, I discuss how while errors in SSEs can introduce correlations in the TOAs that may interfere with GW searches, one can make use of PTAs to study the solar system. I discuss work done within the context of the European Pulsar Timing Array and the International Pulsar Timing Array collaborations. These include new updates on the masses of planets from PTA data, first limits on masses of the most massive asteroids, and comparisons between SSEs from independent groups. Finally, I discuss a new approach in setting limits on the masses of unknown bodies in the solar system and calculate mass sensitivity curves for PTA data.
astro-ph.IM astro-ph.EP
highprecision pulsar timing is central to a wide range of astrophysics and fundamental physics applications when timing an ensemble of millisecond pulsars in different sky positions known as a pulsar timing array pta one can search for ultralowfrequency gravitational waves gws through the spatial correlations that spacetime deformations by passing gws are predicted to induce on the pulses timesofarrival toas a pulsartiming model requires the use of a solarsystem ephemeris sse to properly predict the position of the solarsystem barycentre the quasiinertial frame where all toas are referred here i discuss how while errors in sses can introduce correlations in the toas that may interfere with gw searches one can make use of ptas to study the solar system i discuss work done within the context of the european pulsar timing array and the international pulsar timing array collaborations these include new updates on the masses of planets from pta data first limits on masses of the most massive asteroids and comparisons between sses from independent groups finally i discuss a new approach in setting limits on the masses of unknown bodies in the solar system and calculate mass sensitivity curves for pta data
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1,802.05666
Adversarial Risk and the Dangers of Evaluating Against Weak Attacks
This paper investigates recently proposed approaches for defending against adversarial examples and evaluating adversarial robustness. We motivate 'adversarial risk' as an objective for achieving models robust to worst-case inputs. We then frame commonly used attacks and evaluation metrics as defining a tractable surrogate objective to the true adversarial risk. This suggests that models may optimize this surrogate rather than the true adversarial risk. We formalize this notion as 'obscurity to an adversary,' and develop tools and heuristics for identifying obscured models and designing transparent models. We demonstrate that this is a significant problem in practice by repurposing gradient-free optimization techniques into adversarial attacks, which we use to decrease the accuracy of several recently proposed defenses to near zero. Our hope is that our formulations and results will help researchers to develop more powerful defenses.
cs.LG cs.CR stat.ML
this paper investigates recently proposed approaches for defending against adversarial examples and evaluating adversarial robustness we motivate adversarial risk as an objective for achieving models robust to worstcase inputs we then frame commonly used attacks and evaluation metrics as defining a tractable surrogate objective to the true adversarial risk this suggests that models may optimize this surrogate rather than the true adversarial risk we formalize this notion as obscurity to an adversary and develop tools and heuristics for identifying obscured models and designing transparent models we demonstrate that this is a significant problem in practice by repurposing gradientfree optimization techniques into adversarial attacks which we use to decrease the accuracy of several recently proposed defenses to near zero our hope is that our formulations and results will help researchers to develop more powerful defenses
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1,802.05667
Calculating the similarity between words and sentences using a lexical database and corpus statistics
Calculating the semantic similarity between sentences is a long dealt problem in the area of natural language processing. The semantic analysis field has a crucial role to play in the research related to the text analytics. The semantic similarity differs as the domain of operation differs. In this paper, we present a methodology which deals with this issue by incorporating semantic similarity and corpus statistics. To calculate the semantic similarity between words and sentences, the proposed method follows an edge-based approach using a lexical database. The methodology can be applied in a variety of domains. The methodology has been tested on both benchmark standards and mean human similarity dataset. When tested on these two datasets, it gives highest correlation value for both word and sentence similarity outperforming other similar models. For word similarity, we obtained Pearson correlation coefficient of 0.8753 and for sentence similarity, the correlation obtained is 0.8794.
cs.CL
calculating the semantic similarity between sentences is a long dealt problem in the area of natural language processing the semantic analysis field has a crucial role to play in the research related to the text analytics the semantic similarity differs as the domain of operation differs in this paper we present a methodology which deals with this issue by incorporating semantic similarity and corpus statistics to calculate the semantic similarity between words and sentences the proposed method follows an edgebased approach using a lexical database the methodology can be applied in a variety of domains the methodology has been tested on both benchmark standards and mean human similarity dataset when tested on these two datasets it gives highest correlation value for both word and sentence similarity outperforming other similar models for word similarity we obtained pearson correlation coefficient of 08753 and for sentence similarity the correlation obtained is 08794
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1,802.05668
Model compression via distillation and quantization
Deep neural networks (DNNs) continue to make significant advances, solving tasks from image classification to translation or reinforcement learning. One aspect of the field receiving considerable attention is efficiently executing deep models in resource-constrained environments, such as mobile or embedded devices. This paper focuses on this problem, and proposes two new compression methods, which jointly leverage weight quantization and distillation of larger teacher networks into smaller student networks. The first method we propose is called quantized distillation and leverages distillation during the training process, by incorporating distillation loss, expressed with respect to the teacher, into the training of a student network whose weights are quantized to a limited set of levels. The second method, differentiable quantization, optimizes the location of quantization points through stochastic gradient descent, to better fit the behavior of the teacher model. We validate both methods through experiments on convolutional and recurrent architectures. We show that quantized shallow students can reach similar accuracy levels to full-precision teacher models, while providing order of magnitude compression, and inference speedup that is linear in the depth reduction. In sum, our results enable DNNs for resource-constrained environments to leverage architecture and accuracy advances developed on more powerful devices.
cs.NE cs.LG
deep neural networks dnns continue to make significant advances solving tasks from image classification to translation or reinforcement learning one aspect of the field receiving considerable attention is efficiently executing deep models in resourceconstrained environments such as mobile or embedded devices this paper focuses on this problem and proposes two new compression methods which jointly leverage weight quantization and distillation of larger teacher networks into smaller student networks the first method we propose is called quantized distillation and leverages distillation during the training process by incorporating distillation loss expressed with respect to the teacher into the training of a student network whose weights are quantized to a limited set of levels the second method differentiable quantization optimizes the location of quantization points through stochastic gradient descent to better fit the behavior of the teacher model we validate both methods through experiments on convolutional and recurrent architectures we show that quantized shallow students can reach similar accuracy levels to fullprecision teacher models while providing order of magnitude compression and inference speedup that is linear in the depth reduction in sum our results enable dnns for resourceconstrained environments to leverage architecture and accuracy advances developed on more powerful devices
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1,802.05669
Minimum Energy Paths and Transition States by Curve Optimization
Transition states and minimum energy paths are essential to understand and predict chemical reactivity. Double-ended methods represent a standard approach for their determination. We introduce a new double-ended method that optimizes reaction paths described by curves. Unlike other methods, our approach optimizes the curve parameters rather than distinct structures along the path. With molecular paths represented as continuous curves, the optimization can benefit from the advantages of an integral-based formulation. We call this approach ReaDuct and demonstrate its applicability for molecular paths parametrized by B-spline curves.
physics.chem-ph physics.comp-ph
transition states and minimum energy paths are essential to understand and predict chemical reactivity doubleended methods represent a standard approach for their determination we introduce a new doubleended method that optimizes reaction paths described by curves unlike other methods our approach optimizes the curve parameters rather than distinct structures along the path with molecular paths represented as continuous curves the optimization can benefit from the advantages of an integralbased formulation we call this approach readuct and demonstrate its applicability for molecular paths parametrized by bspline curves
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1,802.0567
Breaking of Large Amplitude Relativistically Intense Electron Plasma Waves in a Warm Plasma
In this paper, the effect of finite electron temperature on the space-time evolution and breaking of a large amplitude relativistically intense electron plasma wave has been studied, using a 1-D relativistic Particle-in-Cell (PIC) code. We have found that for phase velocities for which $\gamma _\phi \ll 1 + \frac{k_BT_e}{mc^2}$, the wave damps within a few plasma period and essentially follows the relativistic Landau Damping rate predicted by Buti. In the opposite regime (i.e. for $\gamma _\phi \gg 1 + \frac{k_BT_e}{mc^2}$) we have observed that waves propagate through the system for a long period of time and in small amplitude limit follow the relativistic warm plasma dispersion relation. Further we have demonstrated that in the same regime (i.e. for $\gamma _\phi \gg 1 + \frac{k_BT_e}{mc^2}$), for the phase velocities less than the velocity of light $c$, like the cold plasma Akhiezer - Polovin wave, in a warm plasma also, relativistically intense waves break via phase mixing when perturbed by an arbitrarily small amplitude longitudinal perturbation. Using the simulation results, we have also shown that the phase mixing time scale in a warm plasma can be interpreted using Dawson's formula for phase mixing time for a non-relativistic cold inhomogeneous plasma, which is based on out of phase motion of neighbouring oscillators constituting the wave.
physics.plasm-ph
in this paper the effect of finite electron temperature on the spacetime evolution and breaking of a large amplitude relativistically intense electron plasma wave has been studied using a 1d relativistic particleincell pic code we have found that for phase velocities for which gamma _phi ll 1 frack_bt_emc2 the wave damps within a few plasma period and essentially follows the relativistic landau damping rate predicted by buti in the opposite regime ie for gamma _phi gg 1 frack_bt_emc2 we have observed that waves propagate through the system for a long period of time and in small amplitude limit follow the relativistic warm plasma dispersion relation further we have demonstrated that in the same regime ie for gamma _phi gg 1 frack_bt_emc2 for the phase velocities less than the velocity of light c like the cold plasma akhiezer polovin wave in a warm plasma also relativistically intense waves break via phase mixing when perturbed by an arbitrarily small amplitude longitudinal perturbation using the simulation results we have also shown that the phase mixing time scale in a warm plasma can be interpreted using dawsons formula for phase mixing time for a nonrelativistic cold inhomogeneous plasma which is based on out of phase motion of neighbouring oscillators constituting the wave
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1,802.05671
Can a Fingerprint be Modelled by a Differential Equation ?
Some new directions to lay a rigorous mathematical foundation for the phase-portrait-based modelling of fingerprints are discussed in the present work. Couched in the language of dynamical systems, and preparing to a preliminary modelling, a back-to-basics analogy between Poincar\'{e}'s categories of equilibria of planar differential systems and the basic fingerprint singularities according to Purkyn\v{e}-Galton's standards is first investigated. Then, the problem of the global representation of a fingerprint's flow-like pattern as a smooth deformation of the phase portrait of a differential system is addressed. Unlike visualisation in fluid dynamics, where similarity between integral curves of smooth vector fields and flow streamline patterns is eye-catching, the case of an oriented texture like a fingerprint's stream of ridges proved to be a hard problem since, on the one hand, not all fingerprint singularities and nearby orientational behaviour can be modelled by canonical phase portraits on the plane, and on the other hand, even if it were the case, this should lead to a perplexing geometrical problem of connecting local phase portraits, a question which will be formulated within Poincar\'{e}'s index theory and addressed via a normal form approach as a bivariate Hermite interpolation problem. To a certain extent, the material presented herein is self-contained and provides a baseline for future work where, starting from a normal form as a source image, a transport via large deformation flows is envisaged to match the fingerprint as a target image.
math.DS
some new directions to lay a rigorous mathematical foundation for the phaseportraitbased modelling of fingerprints are discussed in the present work couched in the language of dynamical systems and preparing to a preliminary modelling a backtobasics analogy between poincares categories of equilibria of planar differential systems and the basic fingerprint singularities according to purkynvegaltons standards is first investigated then the problem of the global representation of a fingerprints flowlike pattern as a smooth deformation of the phase portrait of a differential system is addressed unlike visualisation in fluid dynamics where similarity between integral curves of smooth vector fields and flow streamline patterns is eyecatching the case of an oriented texture like a fingerprints stream of ridges proved to be a hard problem since on the one hand not all fingerprint singularities and nearby orientational behaviour can be modelled by canonical phase portraits on the plane and on the other hand even if it were the case this should lead to a perplexing geometrical problem of connecting local phase portraits a question which will be formulated within poincares index theory and addressed via a normal form approach as a bivariate hermite interpolation problem to a certain extent the material presented herein is selfcontained and provides a baseline for future work where starting from a normal form as a source image a transport via large deformation flows is envisaged to match the fingerprint as a target image
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1,802.05672
Event Nugget Detection with Forward-Backward Recurrent Neural Networks
Traditional event detection methods heavily rely on manually engineered rich features. Recent deep learning approaches alleviate this problem by automatic feature engineering. But such efforts, like tradition methods, have so far only focused on single-token event mentions, whereas in practice events can also be a phrase. We instead use forward-backward recurrent neural networks (FBRNNs) to detect events that can be either words or phrases. To the best our knowledge, this is one of the first efforts to handle multi-word events and also the first attempt to use RNNs for event detection. Experimental results demonstrate that FBRNN is competitive with the state-of-the-art methods on the ACE 2005 and the Rich ERE 2015 event detection tasks.
cs.CL
traditional event detection methods heavily rely on manually engineered rich features recent deep learning approaches alleviate this problem by automatic feature engineering but such efforts like tradition methods have so far only focused on singletoken event mentions whereas in practice events can also be a phrase we instead use forwardbackward recurrent neural networks fbrnns to detect events that can be either words or phrases to the best our knowledge this is one of the first efforts to handle multiword events and also the first attempt to use rnns for event detection experimental results demonstrate that fbrnn is competitive with the stateoftheart methods on the ace 2005 and the rich ere 2015 event detection tasks
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1,802.05673
Parallel magnetic field suppresses dissipation in superconducting nanostrips
The motion of Abrikosov vortices in type-II superconductors results in a finite resistance in the presence of an applied electric current. Elimination or reduction of the resistance via immobilization of vortices is the "holy grail" of superconductivity research. Common wisdom dictates that an increase in the magnetic field escalates the loss of energy since the number of vortices increases. Here we show that this is no longer true if the magnetic field and the current are applied parallel to each other.Our experimental studies on the resistive behavior of a superconducting Mo$_{0.79}$Ge$_{0.21}$ nanostrip reveal the emergence of a dissipative state with increasing magnetic field, followed by a pronounced resistance drop, signifying a reentrance to the superconducting state. Large-scale simulations of the 3D time-dependent Ginzburg-Landau model indicate that the intermediate resistive state is due to an unwinding of twisted vortices. When the magnetic field increases, this instability is suppressed due to a better accommodation of the vortex lattice to the pinning configuration. Our findings show that magnetic field and geometrical confinement can suppress the dissipation induced by vortex motion and thus radically improve the performance of superconducting materials.
cond-mat.mes-hall
the motion of abrikosov vortices in typeii superconductors results in a finite resistance in the presence of an applied electric current elimination or reduction of the resistance via immobilization of vortices is the holy grail of superconductivity research common wisdom dictates that an increase in the magnetic field escalates the loss of energy since the number of vortices increases here we show that this is no longer true if the magnetic field and the current are applied parallel to each otherour experimental studies on the resistive behavior of a superconducting mo_079ge_021 nanostrip reveal the emergence of a dissipative state with increasing magnetic field followed by a pronounced resistance drop signifying a reentrance to the superconducting state largescale simulations of the 3d timedependent ginzburglandau model indicate that the intermediate resistive state is due to an unwinding of twisted vortices when the magnetic field increases this instability is suppressed due to a better accommodation of the vortex lattice to the pinning configuration our findings show that magnetic field and geometrical confinement can suppress the dissipation induced by vortex motion and thus radically improve the performance of superconducting materials
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1,802.05674
Clustering and assembly dynamics of a one-dimensional microphase former
Both ordered and disordered microphases ubiquitously form in suspensions of particles that interact through competing short-range attraction and long-range repulsion (SALR). While ordered microphases are more appealing materials targets, understanding the rich structural and dynamical properties of their disordered counterparts is essential to controlling their mesoscale assembly. Here, we study the disordered regime of a one-dimensional (1D) SALR model, whose simplicity enables detailed analysis by transfer matrices and Monte Carlo simulations. We first characterize the signature of the clustering process on macroscopic observables, and then assess the equilibration dynamics of various simulation algorithms. We notably find that cluster moves markedly accelerate the mixing time, but that event chains are of limited help in the clustering regime. These insights will guide further study of three-dimensional microphase formers.
cond-mat.soft
both ordered and disordered microphases ubiquitously form in suspensions of particles that interact through competing shortrange attraction and longrange repulsion salr while ordered microphases are more appealing materials targets understanding the rich structural and dynamical properties of their disordered counterparts is essential to controlling their mesoscale assembly here we study the disordered regime of a onedimensional 1d salr model whose simplicity enables detailed analysis by transfer matrices and monte carlo simulations we first characterize the signature of the clustering process on macroscopic observables and then assess the equilibration dynamics of various simulation algorithms we notably find that cluster moves markedly accelerate the mixing time but that event chains are of limited help in the clustering regime these insights will guide further study of threedimensional microphase formers
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1,802.05675
Characterization of the X-ray Coherence Properties of an Undulator Beamline at the Advanced Photon Source
In anticipation of the increased use of coherent x-ray methods and the need to upgrade beamlines to match improved source quality, we have characterized the coherence properties of the x-rays delivered by beamline 12ID-D at the Advanced Photon Source. We compare the measured x-ray divergence, beam size, brightness, and coherent flux at energies up to 26 keV to the calculated values from the undulator source, and evaluate the effects of beamline optics such as a mirror, monochromator, and compound refractive lenses. Diffraction patterns from slits as a function of slit width are analyzed using wave propagation theory to obtain the beam divergence and thus coherence length. Imaging of the source using a compound refractive lens was found to be the most accurate method for determining the vertical divergence. While the brightness and coherent flux obtained without a monochromator ("pink beam") agree well with those calculated for the source, those measured with the monochromator were a factor of 3 to 6 lower than the source, primarily because of vertical divergence introduced by the monochromator. The methods we describe should be widely applicable for measuring the x-ray coherence properties of synchrotron beamlines.
physics.acc-ph
in anticipation of the increased use of coherent xray methods and the need to upgrade beamlines to match improved source quality we have characterized the coherence properties of the xrays delivered by beamline 12idd at the advanced photon source we compare the measured xray divergence beam size brightness and coherent flux at energies up to 26 kev to the calculated values from the undulator source and evaluate the effects of beamline optics such as a mirror monochromator and compound refractive lenses diffraction patterns from slits as a function of slit width are analyzed using wave propagation theory to obtain the beam divergence and thus coherence length imaging of the source using a compound refractive lens was found to be the most accurate method for determining the vertical divergence while the brightness and coherent flux obtained without a monochromator pink beam agree well with those calculated for the source those measured with the monochromator were a factor of 3 to 6 lower than the source primarily because of vertical divergence introduced by the monochromator the methods we describe should be widely applicable for measuring the xray coherence properties of synchrotron beamlines
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1,802.05676
Actinium hydrides $AcH_{10}$, $AcH_{12}$, $AcH_{16}$ as high-temperature conventional superconductors
Stability of numerous unexpected actinium hydrides was predicted via evolutionary algorithm USPEX. Electron-phonon interaction was investigated for the hydrogen-richest and most symmetric phases: R$\overline{3}$m-$AcH_{10}$, I4/mmm-$AcH_{12}$ and P$\overline{6}$m2-$AcH_{16}$. Predicted structures of actinium hydrides are consistent with all previously studied Ac-H phases and demonstrate phonon-mediated high-temperature superconductivity with Tc in the range 204-251 K for R$\overline{3}$m-$AcH_{10}$ at 200 GPa and 199-241 K for P$\overline{6}$m2-$AcH_{16}$ at 150 GPa which was estimated by directly solving of Eliashberg equation. Actinium belongs to the series of d1-elements (Sc-Y-La-Ac) that form high-Tc superconducting (HTSC) hydrides. Combining this observation with p0-HTSC hydrides ($MgH_{6}$ and $CaH_{6}$), we propose that p0- and d1-atoms with low-lying empty orbitals tend to form phonon-mediated HTSC metal polyhydrides.
cond-mat.supr-con
stability of numerous unexpected actinium hydrides was predicted via evolutionary algorithm uspex electronphonon interaction was investigated for the hydrogenrichest and most symmetric phases roverline3mach_10 i4mmmach_12 and poverline6m2ach_16 predicted structures of actinium hydrides are consistent with all previously studied ach phases and demonstrate phononmediated hightemperature superconductivity with tc in the range 204251 k for roverline3mach_10 at 200 gpa and 199241 k for poverline6m2ach_16 at 150 gpa which was estimated by directly solving of eliashberg equation actinium belongs to the series of d1elements scylaac that form hightc superconducting htsc hydrides combining this observation with p0htsc hydrides mgh_6 and cah_6 we propose that p0 and d1atoms with lowlying empty orbitals tend to form phononmediated htsc metal polyhydrides
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1,802.05677
Study of magnetized accretion flow with variable $\Gamma$ equation of state
We present here the solutions of magnetized accretion flows on to a compact object with hard surface such as neutron stars. The magnetic field of the central star is assumed dipolar and the magnetic axis is assumed to be aligned with the rotation axis of the star. We have used an equation of state for the accreting fluid in which the adiabatic index is dependent on temperature and composition of the flow. We have also included cooling processes like bremsstrahlung and cyclotron processes in the accretion flow. We found all possible accretion solutions. All accretion solutions terminate with a shock very near to the star surface and the height of this primary shock do not vary much with either the spin period or the Bernoulli parameter of the flow, although the strength of the shock may vary with the period. For moderately rotating central star there are possible formation of multiple sonic points in the flow and therefore, a second shock far away from the star surface may also form. However, the second shock is much weaker than the primary one near the surface. We found that if rotation period is below a certain value $(\pmin)$, then multiple critical points or multiple shocks are not possible and $\pmin$ depends upon the composition of the flow. We also found that cooling effect dominates after the shock and that the cyclotron and the bremsstrahlung cooling processes should be considered to obtain a consistent accretion solution.
astro-ph.HE
we present here the solutions of magnetized accretion flows on to a compact object with hard surface such as neutron stars the magnetic field of the central star is assumed dipolar and the magnetic axis is assumed to be aligned with the rotation axis of the star we have used an equation of state for the accreting fluid in which the adiabatic index is dependent on temperature and composition of the flow we have also included cooling processes like bremsstrahlung and cyclotron processes in the accretion flow we found all possible accretion solutions all accretion solutions terminate with a shock very near to the star surface and the height of this primary shock do not vary much with either the spin period or the bernoulli parameter of the flow although the strength of the shock may vary with the period for moderately rotating central star there are possible formation of multiple sonic points in the flow and therefore a second shock far away from the star surface may also form however the second shock is much weaker than the primary one near the surface we found that if rotation period is below a certain value pmin then multiple critical points or multiple shocks are not possible and pmin depends upon the composition of the flow we also found that cooling effect dominates after the shock and that the cyclotron and the bremsstrahlung cooling processes should be considered to obtain a consistent accretion solution
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1,802.05678
Maximum PBH Mass and Primordiality
In order to avoid unacceptable $\mu$-distortions inconsistent with observational data on the Cosmic Microwave Background, Primordial Black Holes (PBHs) must be less massive than $10^{12} M_{\odot}$, quite closely above the highest black hole mass yet observed. This comparableness leads us to posit that all supermassive black holes originate as PBHs.
gr-qc astro-ph.GA hep-ph hep-th
in order to avoid unacceptable mudistortions inconsistent with observational data on the cosmic microwave background primordial black holes pbhs must be less massive than 1012 m_odot quite closely above the highest black hole mass yet observed this comparableness leads us to posit that all supermassive black holes originate as pbhs
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1,802.05679
Experimental Demonstration of DDoS Mitigation over a Quantum Key Distribution (QKD) Network Using Software Defined Networking (SDN)
We experimentally demonstrate, for the first time, DDoS mitigation of QKD-based networks utilizing a software defined network application. Successful quantum-secured link allocation is achieved after a DDoS attack based on real-time monitoring of quantum parameters
cs.CR
we experimentally demonstrate for the first time ddos mitigation of qkdbased networks utilizing a software defined network application successful quantumsecured link allocation is achieved after a ddos attack based on realtime monitoring of quantum parameters
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1,802.0568
Constraining the Dynamics of Deep Probabilistic Models
We introduce a novel generative formulation of deep probabilistic models implementing "soft" constraints on their function dynamics. In particular, we develop a flexible methodological framework where the modeled functions and derivatives of a given order are subject to inequality or equality constraints. We then characterize the posterior distribution over model and constraint parameters through stochastic variational inference. As a result, the proposed approach allows for accurate and scalable uncertainty quantification on the predictions and on all parameters. We demonstrate the application of equality constraints in the challenging problem of parameter inference in ordinary differential equation models, while we showcase the application of inequality constraints on the problem of monotonic regression of count data. The proposed approach is extensively tested in several experimental settings, leading to highly competitive results in challenging modeling applications, while offering high expressiveness, flexibility and scalability.
stat.ML
we introduce a novel generative formulation of deep probabilistic models implementing soft constraints on their function dynamics in particular we develop a flexible methodological framework where the modeled functions and derivatives of a given order are subject to inequality or equality constraints we then characterize the posterior distribution over model and constraint parameters through stochastic variational inference as a result the proposed approach allows for accurate and scalable uncertainty quantification on the predictions and on all parameters we demonstrate the application of equality constraints in the challenging problem of parameter inference in ordinary differential equation models while we showcase the application of inequality constraints on the problem of monotonic regression of count data the proposed approach is extensively tested in several experimental settings leading to highly competitive results in challenging modeling applications while offering high expressiveness flexibility and scalability
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1,802.05681
Backward Differentiation Formula finite difference schemes for diffusion equations with an obstacle term
Finite difference schemes, using Backward Differentiation Formula (BDF), are studied for the approximation of one-dimensional diffusion equations with an obstacle term, of the form $$\min(v_t - a(t,x) v_{xx} + b(t,x) v_x + r(t,x) v, v- \varphi(t,x))= f(t,x).$$ For the scheme building on the second order BDF formula (BDF2), we discuss unconditional stability, prove an $L^2$-error estimate and show numerically second order convergence, in both space and time, unconditionally on the ratio of the mesh steps. In the analysis, an equivalence of the obstacle equation with a Hamilton-Jacobi-Bellman equation is mentioned, and a Crank-Nicolson scheme is tested in this context. Two academic problems for parabolic equations with an obstacle term with explicit solutions and the American option problem in mathematical finance are used for numerical tests.
math.NA cs.NA
finite difference schemes using backward differentiation formula bdf are studied for the approximation of onedimensional diffusion equations with an obstacle term of the form minv_t atx v_xx btx v_x rtx v v varphitx ftx for the scheme building on the second order bdf formula bdf2 we discuss unconditional stability prove an l2error estimate and show numerically second order convergence in both space and time unconditionally on the ratio of the mesh steps in the analysis an equivalence of the obstacle equation with a hamiltonjacobibellman equation is mentioned and a cranknicolson scheme is tested in this context two academic problems for parabolic equations with an obstacle term with explicit solutions and the american option problem in mathematical finance are used for numerical tests
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1,802.05682
Spin and charge pumping by steady or pulse current-driven magnetic domain wall: A self-consistent multiscale time-dependent-quantum/time-dependent-classical approach
We introduce a multiscale framework which combines time-dependent nonequilibrium Green function (TD-NEGF) algorithms, scaling linearly in the number of time steps and describing quantum-mechanically conduction electrons in the presence of time-dependent fields of arbitrary strength or frequency, with classical time evolution of localized magnetic moments described by the Landau-Lifshitz-Gilbert (LLG) equation. The TD-NEGF+LLG framework can be applied to a variety of problems where current-driven spin torque induces dynamics of magnetic moments as the key resource for next generation spintronics. Using magnetic domain wall (DW) as an example, we predict that its motion will pump time-dependent spin and charge currents (on the top of unpolarized DC charge current injected through normal metal leads to drive the DW motion). The conversion of AC components of spin current, whose amplitude increases (decreases) as the DW approaches (distances from) the normal metal lead, into AC voltage via the inverse spin Hall effect offers a tool to precisely track the DW position along magnetic nanowire. We also quantify the DW transient inertial displacement due to its acceleration and deceleration by pulse current and the entailed spin and charge pumping. Finally, TD-NEGF+LLG as a nonperturbative (i.e., numerically exact) framework allows us to establish the limits of validity of the so-called spin-motive force (SMF) theory for pumped charge current by time-dependent magnetic textures---the perturbative analytical formula of SMF theory becomes inapplicable for large frequencies (but unrealistic in magnetic system) and, more importantly, for increasing noncollinearity when the angles between neighboring magnetic moments exceed $\simeq 10^\circ$.
cond-mat.mes-hall
we introduce a multiscale framework which combines timedependent nonequilibrium green function tdnegf algorithms scaling linearly in the number of time steps and describing quantummechanically conduction electrons in the presence of timedependent fields of arbitrary strength or frequency with classical time evolution of localized magnetic moments described by the landaulifshitzgilbert llg equation the tdnegfllg framework can be applied to a variety of problems where currentdriven spin torque induces dynamics of magnetic moments as the key resource for next generation spintronics using magnetic domain wall dw as an example we predict that its motion will pump timedependent spin and charge currents on the top of unpolarized dc charge current injected through normal metal leads to drive the dw motion the conversion of ac components of spin current whose amplitude increases decreases as the dw approaches distances from the normal metal lead into ac voltage via the inverse spin hall effect offers a tool to precisely track the dw position along magnetic nanowire we also quantify the dw transient inertial displacement due to its acceleration and deceleration by pulse current and the entailed spin and charge pumping finally tdnegfllg as a nonperturbative ie numerically exact framework allows us to establish the limits of validity of the socalled spinmotive force smf theory for pumped charge current by timedependent magnetic texturesthe perturbative analytical formula of smf theory becomes inapplicable for large frequencies but unrealistic in magnetic system and more importantly for increasing noncollinearity when the angles between neighboring magnetic moments exceed simeq 10circ
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1,802.05683
Quantum Optimal Control: Landscape Structure and Topology
The core problem in optimal control theory applied to quantum systems is to determine the temporal shape of an applied field in order to maximize the expectation of value of some physical observable. The functional which maps the control field into a given value of the observable defines a Quantum Control Landscape (QCL). Studying the topological and structural features of these landscapes is of critical importance for understanding the process of finding the optimal fields required to effectively control the system, specially when external constraints are placed on both the field $\epsilon(t)$ and the available control duration $T$. In this work we analyze the rich structure of the $QCL$ of the paradigmatic Landau-Zener two-level model, studying several features of the optimized solutions, such as their abundance, spatial distribution and fidelities. We also inspect the optimization trajectories in parameter space. We are able rationalize several geometrical and topological aspects of the QCL of this simple model and the effects produced by the constraints. Our study opens the door for a deeper understanding of the QCL of general quantum systems.
quant-ph
the core problem in optimal control theory applied to quantum systems is to determine the temporal shape of an applied field in order to maximize the expectation of value of some physical observable the functional which maps the control field into a given value of the observable defines a quantum control landscape qcl studying the topological and structural features of these landscapes is of critical importance for understanding the process of finding the optimal fields required to effectively control the system specially when external constraints are placed on both the field epsilont and the available control duration t in this work we analyze the rich structure of the qcl of the paradigmatic landauzener twolevel model studying several features of the optimized solutions such as their abundance spatial distribution and fidelities we also inspect the optimization trajectories in parameter space we are able rationalize several geometrical and topological aspects of the qcl of this simple model and the effects produced by the constraints our study opens the door for a deeper understanding of the qcl of general quantum systems
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1,802.05684
Comparing Hecke Coefficients of Automorphic Representations
We prove a number of unconditional statistical results of the Hecke coefficients for unitary cuspidal representations of $\operatorname{GL}(2)$ over number fields. Using partial bounds on the size of the Hecke coefficients, instances of Langlands functoriality, and properties of Rankin-Selberg $L$-functions, we obtain bounds on the set of places where linear combinations of Hecke coefficients are negative. Under a mild functoriality assumption we extend these methods to $\operatorname{GL}(n)$. As an application, we obtain a result related to a question of Serre about the occurrence of large Hecke eigenvalues of Maass forms. Furthermore, in the cases where the Ramanujan conjecture is satisfied, we obtain distributional results of the Hecke coefficients at places varying in certain congruence or Galois classes.
math.NT
we prove a number of unconditional statistical results of the hecke coefficients for unitary cuspidal representations of operatornamegl2 over number fields using partial bounds on the size of the hecke coefficients instances of langlands functoriality and properties of rankinselberg lfunctions we obtain bounds on the set of places where linear combinations of hecke coefficients are negative under a mild functoriality assumption we extend these methods to operatornamegln as an application we obtain a result related to a question of serre about the occurrence of large hecke eigenvalues of maass forms furthermore in the cases where the ramanujan conjecture is satisfied we obtain distributional results of the hecke coefficients at places varying in certain congruence or galois classes
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1,802.05685
Origin of spin reorientation transitions in antiferromagnetic MnPt-based alloys
Antiferromagnetic MnPt exhibits a spin reorientation transition (SRT) as a function of temperature, and off-stoichiometric Mn-Pt alloys also display SRTs as a function of concentration. The magnetocrystalline anisotropy in these alloys is studied using first-principles calculations based on the coherent potential approximation and the disordered local moment method. The anisotropy is fairly small and sensitive to the variations in composition and temperature due to the cancellation of large contributions from different parts of the Brillouin zone. Concentration and temperature-driven SRTs are found in reasonable agreement with experimental data. Contributions from specific band-structure features are identified and used to explain the origin of the SRTs.
cond-mat.mtrl-sci
antiferromagnetic mnpt exhibits a spin reorientation transition srt as a function of temperature and offstoichiometric mnpt alloys also display srts as a function of concentration the magnetocrystalline anisotropy in these alloys is studied using firstprinciples calculations based on the coherent potential approximation and the disordered local moment method the anisotropy is fairly small and sensitive to the variations in composition and temperature due to the cancellation of large contributions from different parts of the brillouin zone concentration and temperaturedriven srts are found in reasonable agreement with experimental data contributions from specific bandstructure features are identified and used to explain the origin of the srts
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1,802.05686
A Bio-inspired Redundant Sensing Architecture
Sensing is the process of deriving signals from the environment that allows artificial systems to interact with the physical world. The Shannon theorem specifies the maximum rate at which information can be acquired. However, this upper bound is hard to achieve in many man-made systems. The biological visual systems, on the other hand, have highly efficient signal representation and processing mechanisms that allow precise sensing. In this work, we argue that redundancy is one of the critical characteristics for such superior performance. We show architectural advantages by utilizing redundant sensing, including correction of mismatch error and significant precision enhancement. For a proof-of-concept demonstration, we have designed a heuristic-based analog-to-digital converter - a zero-dimensional quantizer. Through Monte Carlo simulation with the error probabilistic distribution as a priori, the performance approaching the Shannon limit is feasible. In actual measurements without knowing the error distribution, we observe at least 2-bit extra precision. The results may also help explain biological processes including the dominance of binocular vision, the functional roles of the fixational eye movements, and the structural mechanisms allowing hyperacuity.
cs.NE cs.IT eess.SP math.IT
sensing is the process of deriving signals from the environment that allows artificial systems to interact with the physical world the shannon theorem specifies the maximum rate at which information can be acquired however this upper bound is hard to achieve in many manmade systems the biological visual systems on the other hand have highly efficient signal representation and processing mechanisms that allow precise sensing in this work we argue that redundancy is one of the critical characteristics for such superior performance we show architectural advantages by utilizing redundant sensing including correction of mismatch error and significant precision enhancement for a proofofconcept demonstration we have designed a heuristicbased analogtodigital converter a zerodimensional quantizer through monte carlo simulation with the error probabilistic distribution as a priori the performance approaching the shannon limit is feasible in actual measurements without knowing the error distribution we observe at least 2bit extra precision the results may also help explain biological processes including the dominance of binocular vision the functional roles of the fixational eye movements and the structural mechanisms allowing hyperacuity
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1,802.05687
Effect of Hilbert space truncation on Anderson localization
The 1-D Anderson model possesses a completely localized spectrum of eigenstates for all values of the disorder. We consider the effect of projecting the Hamiltonian to a truncated Hilbert space, destroying time reversal symmetry. We analyze the ensuing eigenstates using different measures such as inverse participation ratio and sample-averaged moments of the position operator. In addition, we examine amplitude fluctuations in detail to detect the possibility of multifractal behavior (characteristic of mobility edges) that may arise as a result of the truncation procedure.
cond-mat.dis-nn cond-mat.other quant-ph
the 1d anderson model possesses a completely localized spectrum of eigenstates for all values of the disorder we consider the effect of projecting the hamiltonian to a truncated hilbert space destroying time reversal symmetry we analyze the ensuing eigenstates using different measures such as inverse participation ratio and sampleaveraged moments of the position operator in addition we examine amplitude fluctuations in detail to detect the possibility of multifractal behavior characteristic of mobility edges that may arise as a result of the truncation procedure
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1,802.05688
Simulation assisted machine learning
Motivation: In a predictive modeling setting, if sufficient details of the system behavior are known, one can build and use a simulation for making predictions. When sufficient system details are not known, one typically turns to machine learning, which builds a black-box model of the system using a large dataset of input sample features and outputs. We consider a setting which is between these two extremes: some details of the system mechanics are known but not enough for creating simulations that can be used to make high quality predictions. In this context we propose using approximate simulations to build a kernel for use in kernelized machine learning methods, such as support vector machines. The results of multiple simulations (under various uncertainty scenarios) are used to compute similarity measures between every pair of samples: sample pairs are given a high similarity score if they behave similarly under a wide range of simulation parameters. These similarity values, rather than the original high dimensional feature data, are used to build the kernel. Results: We demonstrate and explore the simulation based kernel (SimKern) concept using four synthetic complex systems--three biologically inspired models and one network flow optimization model. We show that, when the number of training samples is small compared to the number of features, the SimKern approach dominates over no-prior-knowledge methods. This approach should be applicable in all disciplines where predictive models are sought and informative yet approximate simulations are available. Availability: The Python SimKern software, the demonstration models (in MATLAB, R), and the datasets are available at https://github.com/davidcraft/SimKern.
stat.ML cs.LG q-bio.QM
motivation in a predictive modeling setting if sufficient details of the system behavior are known one can build and use a simulation for making predictions when sufficient system details are not known one typically turns to machine learning which builds a blackbox model of the system using a large dataset of input sample features and outputs we consider a setting which is between these two extremes some details of the system mechanics are known but not enough for creating simulations that can be used to make high quality predictions in this context we propose using approximate simulations to build a kernel for use in kernelized machine learning methods such as support vector machines the results of multiple simulations under various uncertainty scenarios are used to compute similarity measures between every pair of samples sample pairs are given a high similarity score if they behave similarly under a wide range of simulation parameters these similarity values rather than the original high dimensional feature data are used to build the kernel results we demonstrate and explore the simulation based kernel simkern concept using four synthetic complex systemsthree biologically inspired models and one network flow optimization model we show that when the number of training samples is small compared to the number of features the simkern approach dominates over nopriorknowledge methods this approach should be applicable in all disciplines where predictive models are sought and informative yet approximate simulations are available availability the python simkern software the demonstration models in matlab r and the datasets are available at httpsgithubcomdavidcraftsimkern
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1,802.05689
Strongly Correlated Bosons on a Dynamical Lattice
We study a one-dimensional system of strongly correlated bosons on a dynamical lattice. To this end, we extend the standard Bose-Hubbard Hamiltonian to include extra degrees of freedom on the bonds of the lattice. We show that this minimal model exhibits phenomena reminiscent of fermion-phonon models. In particular, we discover a bosonic analog of the Peierls transition, where the translational symmetry of the underlying lattice is spontaneously broken. This provides a dynamical mechanism to obtain a topological insulator in the presence of interactions, analogous to the Su-Schrieffer-Heeger model for electrons. We characterize the phase diagram numerically, showing different types of bond order waves and topological solitons. Finally, we study the possibility of implementing the model using atomic systems.
cond-mat.quant-gas quant-ph
we study a onedimensional system of strongly correlated bosons on a dynamical lattice to this end we extend the standard bosehubbard hamiltonian to include extra degrees of freedom on the bonds of the lattice we show that this minimal model exhibits phenomena reminiscent of fermionphonon models in particular we discover a bosonic analog of the peierls transition where the translational symmetry of the underlying lattice is spontaneously broken this provides a dynamical mechanism to obtain a topological insulator in the presence of interactions analogous to the suschriefferheeger model for electrons we characterize the phase diagram numerically showing different types of bond order waves and topological solitons finally we study the possibility of implementing the model using atomic systems
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1,802.0569
Learning DNFs under product distributions via {\mu}-biased quantum Fourier sampling
We show that DNF formulae can be quantum PAC-learned in polynomial time under product distributions using a quantum example oracle. The best classical algorithm (without access to membership queries) runs in superpolynomial time. Our result extends the work by Bshouty and Jackson (1998) that proved that DNF formulae are efficiently learnable under the uniform distribution using a quantum example oracle. Our proof is based on a new quantum algorithm that efficiently samples the coefficients of a {\mu}-biased Fourier transform.
quant-ph cs.DM cs.LG
we show that dnf formulae can be quantum paclearned in polynomial time under product distributions using a quantum example oracle the best classical algorithm without access to membership queries runs in superpolynomial time our result extends the work by bshouty and jackson 1998 that proved that dnf formulae are efficiently learnable under the uniform distribution using a quantum example oracle our proof is based on a new quantum algorithm that efficiently samples the coefficients of a mubiased fourier transform
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1,802.05691
Landau level diagram and the continuous rotational symmetry breaking in trilayer graphene
The sequence of the zeroth Landau levels (LLs) between filling factors $\nu$=-6 to 6 in ABA-stacked trilayer graphene (TLG) is unknown because it depends sensitively on the non-uniform charge distribution on the three layers of ABA-stacked TLG. Using the sensitivity of quantum Hall data on the electric field and magnetic field, in an ultraclean ABA-stacked TLG sample, we quantitatively estimate the non-uniformity of the electric field and determine the sequence of the zeroth LLs. We also observe anticrossings between some LLs differing by 3 in LL index, which result from the breaking of the continuous rotational to \textit{C}$_3$ symmetry by the trigonal warping.
cond-mat.mes-hall
the sequence of the zeroth landau levels lls between filling factors nu6 to 6 in abastacked trilayer graphene tlg is unknown because it depends sensitively on the nonuniform charge distribution on the three layers of abastacked tlg using the sensitivity of quantum hall data on the electric field and magnetic field in an ultraclean abastacked tlg sample we quantitatively estimate the nonuniformity of the electric field and determine the sequence of the zeroth lls we also observe anticrossings between some lls differing by 3 in ll index which result from the breaking of the continuous rotational to textitc_3 symmetry by the trigonal warping
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1,802.05692
Asymptotics for scalar perturbations from a neighborhood of the bifurcation sphere
In our previous work [Y. Angelopoulos, S. Aretakis, and D. Gajic, Late-time asymptotics for the wave equation on spherically symmetric stationary backgrounds, in Advances in Mathematics 323 (2018), 529-621] we showed that the coefficient in the precise leading-order late-time asymptotics for solutions to the wave equation with smooth, compactly supported initial data on Schwarzschild backgrounds is proportional to the time-inverted Newman-Penrose constant (TINP), that is the Newman-Penrose constant of the associated time integral. The time integral (and hence the TINP constant) is canonically defined in the domain of dependence of any Cauchy hypersurface along which the stationary Killing field is non-vanishing. As a result, an explicit expression of the late-time polynomial tails was obtained in terms of initial data on Cauchy hypersurfaces intersecting the future event horizon to the future of the bifurcation sphere. In this paper, we extend the above result to Cauchy hypersurfaces intersecting the bifurcation sphere via a novel geometric interpretation of the TINP constant in terms of a modified gradient flux on Cauchy hypersurfaces. We show, without appealing to the time integral construction, that a general conservation law holds for these gradient fluxes. This allows us to express the TINP constant in terms of initial data on Cauchy hypersurfaces for which the time integral construction breaks down.
gr-qc math.AP
in our previous work y angelopoulos s aretakis and d gajic latetime asymptotics for the wave equation on spherically symmetric stationary backgrounds in advances in mathematics 323 2018 529621 we showed that the coefficient in the precise leadingorder latetime asymptotics for solutions to the wave equation with smooth compactly supported initial data on schwarzschild backgrounds is proportional to the timeinverted newmanpenrose constant tinp that is the newmanpenrose constant of the associated time integral the time integral and hence the tinp constant is canonically defined in the domain of dependence of any cauchy hypersurface along which the stationary killing field is nonvanishing as a result an explicit expression of the latetime polynomial tails was obtained in terms of initial data on cauchy hypersurfaces intersecting the future event horizon to the future of the bifurcation sphere in this paper we extend the above result to cauchy hypersurfaces intersecting the bifurcation sphere via a novel geometric interpretation of the tinp constant in terms of a modified gradient flux on cauchy hypersurfaces we show without appealing to the time integral construction that a general conservation law holds for these gradient fluxes this allows us to express the tinp constant in terms of initial data on cauchy hypersurfaces for which the time integral construction breaks down
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1,802.05693
Bandit Learning with Positive Externalities
In many platforms, user arrivals exhibit a self-reinforcing behavior: future user arrivals are likely to have preferences similar to users who were satisfied in the past. In other words, arrivals exhibit positive externalities. We study multiarmed bandit (MAB) problems with positive externalities. We show that the self-reinforcing preferences may lead standard benchmark algorithms such as UCB to exhibit linear regret. We develop a new algorithm, Balanced Exploration (BE), which explores arms carefully to avoid suboptimal convergence of arrivals before sufficient evidence is gathered. We also introduce an adaptive variant of BE which successively eliminates suboptimal arms. We analyze their asymptotic regret, and establish optimality by showing that no algorithm can perform better.
cs.LG stat.ML
in many platforms user arrivals exhibit a selfreinforcing behavior future user arrivals are likely to have preferences similar to users who were satisfied in the past in other words arrivals exhibit positive externalities we study multiarmed bandit mab problems with positive externalities we show that the selfreinforcing preferences may lead standard benchmark algorithms such as ucb to exhibit linear regret we develop a new algorithm balanced exploration be which explores arms carefully to avoid suboptimal convergence of arrivals before sufficient evidence is gathered we also introduce an adaptive variant of be which successively eliminates suboptimal arms we analyze their asymptotic regret and establish optimality by showing that no algorithm can perform better
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1,802.05694
Multinomial Adversarial Networks for Multi-Domain Text Classification
Many text classification tasks are known to be highly domain-dependent. Unfortunately, the availability of training data can vary drastically across domains. Worse still, for some domains there may not be any annotated data at all. In this work, we propose a multinomial adversarial network (MAN) to tackle the text classification problem in this real-world multidomain setting (MDTC). We provide theoretical justifications for the MAN framework, proving that different instances of MANs are essentially minimizers of various f-divergence metrics (Ali and Silvey, 1966) among multiple probability distributions. MANs are thus a theoretically sound generalization of traditional adversarial networks that discriminate over two distributions. More specifically, for the MDTC task, MAN learns features that are invariant across multiple domains by resorting to its ability to reduce the divergence among the feature distributions of each domain. We present experimental results showing that MANs significantly outperform the prior art on the MDTC task. We also show that MANs achieve state-of-the-art performance for domains with no labeled data.
cs.CL cs.LG stat.ML
many text classification tasks are known to be highly domaindependent unfortunately the availability of training data can vary drastically across domains worse still for some domains there may not be any annotated data at all in this work we propose a multinomial adversarial network man to tackle the text classification problem in this realworld multidomain setting mdtc we provide theoretical justifications for the man framework proving that different instances of mans are essentially minimizers of various fdivergence metrics ali and silvey 1966 among multiple probability distributions mans are thus a theoretically sound generalization of traditional adversarial networks that discriminate over two distributions more specifically for the mdtc task man learns features that are invariant across multiple domains by resorting to its ability to reduce the divergence among the feature distributions of each domain we present experimental results showing that mans significantly outperform the prior art on the mdtc task we also show that mans achieve stateoftheart performance for domains with no labeled data
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1,802.05695
Explainable Prediction of Medical Codes from Clinical Text
Clinical notes are text documents that are created by clinicians for each patient encounter. They are typically accompanied by medical codes, which describe the diagnosis and treatment. Annotating these codes is labor intensive and error prone; furthermore, the connection between the codes and the text is not annotated, obscuring the reasons and details behind specific diagnoses and treatments. We present an attentional convolutional network that predicts medical codes from clinical text. Our method aggregates information across the document using a convolutional neural network, and uses an attention mechanism to select the most relevant segments for each of the thousands of possible codes. The method is accurate, achieving precision@8 of 0.71 and a Micro-F1 of 0.54, which are both better than the prior state of the art. Furthermore, through an interpretability evaluation by a physician, we show that the attention mechanism identifies meaningful explanations for each code assignment
cs.CL cs.LG stat.ML
clinical notes are text documents that are created by clinicians for each patient encounter they are typically accompanied by medical codes which describe the diagnosis and treatment annotating these codes is labor intensive and error prone furthermore the connection between the codes and the text is not annotated obscuring the reasons and details behind specific diagnoses and treatments we present an attentional convolutional network that predicts medical codes from clinical text our method aggregates information across the document using a convolutional neural network and uses an attention mechanism to select the most relevant segments for each of the thousands of possible codes the method is accurate achieving precision8 of 071 and a microf1 of 054 which are both better than the prior state of the art furthermore through an interpretability evaluation by a physician we show that the attention mechanism identifies meaningful explanations for each code assignment
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1,802.05696
Identification of the Polaron measure I: Fixed coupling regime and the central limit theorem for large times
We consider the Fr\"ohlich model of the Polaron whose path integral formulation leads to the transformed path measure $$ \widehat{\mathbb P}_{\alpha,T}(\mathrm d\omega)= Z_{\alpha,T}^{-1}\,\, \exp\bigg\{\frac{\alpha}{2}\int_{-T}^T\int_{-T}^T\frac{e^{-|t-s|}}{|\omega(t)-\omega(s)|} \, d s \, d t\bigg\}\,\mathbb P(\mathrm d\omega) $$ with respect to $\mathbb P$ which governs the law of the increments of the three dimensional Brownian motion on a finite interval $[-T,T]$, and $ Z_{\alpha,T}$ is the partition function or the normalizing constant and $\alpha>0$ is a constant. The Polaron measure reflects a self attractive interaction. According to a conjecture of Pekar that was proved in [DV83] $$ g_0=\lim_{\alpha \to\infty}\frac{1}{\alpha^2}\bigg[\lim_{T\to\infty}\frac{\log Z_{\alpha,T}}{2T}\bigg] $$ exists and has a variational formula. In this article we show that for any $\alpha>0$, the infinite-volume limit $\widehat{\mathbb P}_{\alpha}=\lim_{T\to\infty}\widehat{\mathbb P}_{\alpha,T}$ exists which is also identified explicitly. As a corollary, we deduce the central limit theorem (for any $\alpha>0$ and as $T\to\infty$) for the distribution of $\frac{\omega(T)-\omega(-T)}{\sqrt{2T}}$ both under the finite-volume Polaron measure $\widehat{\mathbb P}_{\alpha,T}$ and its infinite-volume counterpart $\widehat{\mathbb P}_\alpha$, and obtain an expression for the limiting variance.
math.PR math-ph math.MP
we consider the frohlich model of the polaron whose path integral formulation leads to the transformed path measure widehatmathbb p_alphatmathrm domega z_alphat1 expbiggfracalpha2int_ttint_ttfracetsomegatomegas d s d tbiggmathbb pmathrm domega with respect to mathbb p which governs the law of the increments of the three dimensional brownian motion on a finite interval tt and z_alphat is the partition function or the normalizing constant and alpha0 is a constant the polaron measure reflects a self attractive interaction according to a conjecture of pekar that was proved in dv83 g_0lim_alpha toinftyfrac1alpha2bigglim_ttoinftyfraclog z_alphat2tbigg exists and has a variational formula in this article we show that for any alpha0 the infinitevolume limit widehatmathbb p_alphalim_ttoinftywidehatmathbb p_alphat exists which is also identified explicitly as a corollary we deduce the central limit theorem for any alpha0 and as ttoinfty for the distribution of fracomegatomegatsqrt2t both under the finitevolume polaron measure widehatmathbb p_alphat and its infinitevolume counterpart widehatmathbb p_alpha and obtain an expression for the limiting variance
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1,802.05697
Non-equilibrium quantum transport in presence of a defect: the non-interacting case
We study quantum transport after an inhomogeneous quantum quench in a free fermion lattice system in the presence of a localised defect. Using a new rigorous analytical approach for the calculation of large time and distance asymptotics of physical observables, we derive the exact profiles of particle density and current. Our analysis shows that the predictions of a semiclassical approach that has been extensively applied in similar problems match exactly with the correct asymptotics, except for possible finite distance corrections close to the defect. We generalise our formulas to an arbitrary non-interacting particle-conserving defect, expressing them in terms of its scattering properties.
cond-mat.stat-mech cond-mat.str-el math-ph math.MP
we study quantum transport after an inhomogeneous quantum quench in a free fermion lattice system in the presence of a localised defect using a new rigorous analytical approach for the calculation of large time and distance asymptotics of physical observables we derive the exact profiles of particle density and current our analysis shows that the predictions of a semiclassical approach that has been extensively applied in similar problems match exactly with the correct asymptotics except for possible finite distance corrections close to the defect we generalise our formulas to an arbitrary noninteracting particleconserving defect expressing them in terms of its scattering properties
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1,802.05698
A Machine Learning Approach for Virtual Flow Metering and Forecasting
We are concerned with robust and accurate forecasting of multiphase flow rates in wells and pipelines during oil and gas production. In practice, the possibility to physically measure the rates is often limited; besides, it is desirable to estimate future values of multiphase rates based on the previous behavior of the system. In this work, we demonstrate that a Long Short-Term Memory (LSTM) recurrent artificial network is able not only to accurately estimate the multiphase rates at current time (i.e., act as a virtual flow meter), but also to forecast the rates for a sequence of future time instants. For a synthetic severe slugging case, LSTM forecasts compare favorably with the results of hydrodynamical modeling. LSTM results for a realistic noizy dataset of a variable rate well test show that the model can also successfully forecast multiphase rates for a system with changing flow patterns.
cs.NE
we are concerned with robust and accurate forecasting of multiphase flow rates in wells and pipelines during oil and gas production in practice the possibility to physically measure the rates is often limited besides it is desirable to estimate future values of multiphase rates based on the previous behavior of the system in this work we demonstrate that a long shortterm memory lstm recurrent artificial network is able not only to accurately estimate the multiphase rates at current time ie act as a virtual flow meter but also to forecast the rates for a sequence of future time instants for a synthetic severe slugging case lstm forecasts compare favorably with the results of hydrodynamical modeling lstm results for a realistic noizy dataset of a variable rate well test show that the model can also successfully forecast multiphase rates for a system with changing flow patterns
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1,802.05699
Analysis of The Tailored Coupled-Cluster Method in Quantum Chemistry
In quantum chemistry, one of the most important challenges is the static correlation problem when solving the electronic Schr\"odinger equation for molecules in the Born--Oppenheimer approximation. In this article, we analyze the tailored coupled-cluster method (TCC), one particular and promising method for treating molecular electronic-structure problems with static correlation. The TCC method combines the single-reference coupled-cluster (CC) approach with an approximate reference calculation in a subspace [complete active space (CAS)] of the considered Hilbert space that covers the static correlation. A one-particle spectral gap assumption is introduced, separating the CAS from the remaining Hilbert space. This replaces the nonexisting or nearly nonexisting gap between the highest occupied molecular orbital and the lowest unoccupied molecular orbital usually encountered in standard single-reference quantum chemistry. The analysis covers, in particular, CC methods tailored by tensor-network states (TNS-TCC methods). The problem is formulated in a nonlinear functional analysis framework, and, under certain conditions such as the aforementioned gap, local uniqueness and existence are proved using Zarantonello's lemma. From the Aubin--Nitsche-duality method, a quadratic error bound valid for TNS-TCC methods is derived, e.g., for linear-tensor-network TCC schemes using the density matrix renormalization group method.
math.NA cond-mat.str-el cs.NA physics.chem-ph physics.comp-ph quant-ph
in quantum chemistry one of the most important challenges is the static correlation problem when solving the electronic schrodinger equation for molecules in the bornoppenheimer approximation in this article we analyze the tailored coupledcluster method tcc one particular and promising method for treating molecular electronicstructure problems with static correlation the tcc method combines the singlereference coupledcluster cc approach with an approximate reference calculation in a subspace complete active space cas of the considered hilbert space that covers the static correlation a oneparticle spectral gap assumption is introduced separating the cas from the remaining hilbert space this replaces the nonexisting or nearly nonexisting gap between the highest occupied molecular orbital and the lowest unoccupied molecular orbital usually encountered in standard singlereference quantum chemistry the analysis covers in particular cc methods tailored by tensornetwork states tnstcc methods the problem is formulated in a nonlinear functional analysis framework and under certain conditions such as the aforementioned gap local uniqueness and existence are proved using zarantonellos lemma from the aubinnitscheduality method a quadratic error bound valid for tnstcc methods is derived eg for lineartensornetwork tcc schemes using the density matrix renormalization group method
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1,802.057
Chang Palais-Smale condition and global inversion
Let f be local diffeomorphism between real Banach spaces. We prove that if the locally Lipschitz functional F(x)=1/2|f(x)-y|^2 satisfies the Chang Palais-Smale condition for all y in the target space of f, then f is a norm-coercive global diffeomorphism. We also give a version of this fact for a weighted Chang Palais-Smale condition. Finally, we study the relationship of this criterion to some classical global inversion conditions.
math.FA
let f be local diffeomorphism between real banach spaces we prove that if the locally lipschitz functional fx12fxy2 satisfies the chang palaissmale condition for all y in the target space of f then f is a normcoercive global diffeomorphism we also give a version of this fact for a weighted chang palaissmale condition finally we study the relationship of this criterion to some classical global inversion conditions
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1,802.05701
Inverting The Generator Of A Generative Adversarial Network (II)
Generative adversarial networks (GANs) learn a deep generative model that is able to synthesise novel, high-dimensional data samples. New data samples are synthesised by passing latent samples, drawn from a chosen prior distribution, through the generative model. Once trained, the latent space exhibits interesting properties, that may be useful for down stream tasks such as classification or retrieval. Unfortunately, GANs do not offer an "inverse model", a mapping from data space back to latent space, making it difficult to infer a latent representation for a given data sample. In this paper, we introduce a technique, inversion, to project data samples, specifically images, to the latent space using a pre-trained GAN. Using our proposed inversion technique, we are able to identify which attributes of a dataset a trained GAN is able to model and quantify GAN performance, based on a reconstruction loss. We demonstrate how our proposed inversion technique may be used to quantitatively compare performance of various GAN models trained on three image datasets. We provide code for all of our experiments, https://github.com/ToniCreswell/InvertingGAN.
cs.CV
generative adversarial networks gans learn a deep generative model that is able to synthesise novel highdimensional data samples new data samples are synthesised by passing latent samples drawn from a chosen prior distribution through the generative model once trained the latent space exhibits interesting properties that may be useful for down stream tasks such as classification or retrieval unfortunately gans do not offer an inverse model a mapping from data space back to latent space making it difficult to infer a latent representation for a given data sample in this paper we introduce a technique inversion to project data samples specifically images to the latent space using a pretrained gan using our proposed inversion technique we are able to identify which attributes of a dataset a trained gan is able to model and quantify gan performance based on a reconstruction loss we demonstrate how our proposed inversion technique may be used to quantitatively compare performance of various gan models trained on three image datasets we provide code for all of our experiments httpsgithubcomtonicreswellinvertinggan
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1,802.05702
Virtual Cartier divisors and blow-ups
We prove a universal property for blow-ups in regularly immersed subschemes, based on a notion we call "virtual effective Cartier divisor". We also construct blow-ups of quasi-smooth closed immersions in derived algebraic geometry.
math.AG
we prove a universal property for blowups in regularly immersed subschemes based on a notion we call virtual effective cartier divisor we also construct blowups of quasismooth closed immersions in derived algebraic geometry
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1,802.05703
$\aleph_0$-categoricity of semigroups
In this paper we initiate the study of $\aleph_0$-categorical semigroups, where a countable semigroup $S$ is $\aleph_0$-categorical if, for any natural number $n$, the action of its group of automorphisms Aut $S$ on $S^n$ has only finitely many orbits. We show that $\aleph_0$-categoricity transfers to certain important substructures such as maximal subgroups and principal factors. We examine the relationship between $\aleph_0$-categoricity and a number of semigroup and monoid constructions, namely direct sums, 0-direct unions, semidirect products and $\mathcal{P}$-semigroups. As a corollary, we determine the $\aleph_0$-categoricity of an $E$-unitary inverse semigroup with finite semilattice of idempotents in terms of that of the maximal group homomorphic image.
math.LO math.RA
in this paper we initiate the study of aleph_0categorical semigroups where a countable semigroup s is aleph_0categorical if for any natural number n the action of its group of automorphisms aut s on sn has only finitely many orbits we show that aleph_0categoricity transfers to certain important substructures such as maximal subgroups and principal factors we examine the relationship between aleph_0categoricity and a number of semigroup and monoid constructions namely direct sums 0direct unions semidirect products and mathcalpsemigroups as a corollary we determine the aleph_0categoricity of an eunitary inverse semigroup with finite semilattice of idempotents in terms of that of the maximal group homomorphic image
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1,802.05704
Dissipative flows, global attractors and shape theory
In this paper we study continuous parametrized families of dissipative flows, which are those flows having a global attractor. The main motivation for this study comes from the observation that, in general, global attractors are not robust, in the sense that small perturbations of the flow can destroy their globality. We give a necessary and sufficient condition for a global attractor to be continued to a global attractor. We also study, using shape theoretical methods and the Conley index, the bifurcation global to non-global.
math.DS
in this paper we study continuous parametrized families of dissipative flows which are those flows having a global attractor the main motivation for this study comes from the observation that in general global attractors are not robust in the sense that small perturbations of the flow can destroy their globality we give a necessary and sufficient condition for a global attractor to be continued to a global attractor we also study using shape theoretical methods and the conley index the bifurcation global to nonglobal
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1,802.05705
Relatively irreducible free subroups in Out($\mathbb{F}$)
We prove that given a finite rank free group $\mathbb{F}$ of rank $\geq 3$ and two exponentially growing outer automorphisms $\psi$ and $\phi$ with dual lamination pairs $\Lambda^\pm_\psi$ and $\Lambda^\pm_\phi$ associated to them, and given a free factor system $\mathcal{F}$ with co-edge number $\geq 2$, $\phi, \psi $ each preserving $\mathcal{F}$, so that the pair $(\phi, \Lambda^\pm_\phi), (\psi, \Lambda^\pm_\psi)$ is independent relative to $\mathcal{F}$, then there $\exists$ $M\geq 1$, such that for any integer $m,n \geq M$, the group $\langle \phi^m, \psi^n \rangle$ is a free group of rank 2, all of whose non-trivial elements except perhaps the powers of $\phi, \psi$ and their conjugates, are fully irreducible relative to $\mathcal{F}$ with a lamination pair which fills relative to $\mathcal{F}$. In addition if both $\Lambda^\pm_\phi, \Lambda^\pm_\psi$ are non-geometric then this lamination pair is also non-geometric. We also prove that the extension groups induced by such subgroups will be relatively hyperbolic under some natural conditions.
math.GR
we prove that given a finite rank free group mathbbf of rank geq 3 and two exponentially growing outer automorphisms psi and phi with dual lamination pairs lambdapm_psi and lambdapm_phi associated to them and given a free factor system mathcalf with coedge number geq 2 phi psi each preserving mathcalf so that the pair phi lambdapm_phi psi lambdapm_psi is independent relative to mathcalf then there exists mgeq 1 such that for any integer mn geq m the group langle phim psin rangle is a free group of rank 2 all of whose nontrivial elements except perhaps the powers of phi psi and their conjugates are fully irreducible relative to mathcalf with a lamination pair which fills relative to mathcalf in addition if both lambdapm_phi lambdapm_psi are nongeometric then this lamination pair is also nongeometric we also prove that the extension groups induced by such subgroups will be relatively hyperbolic under some natural conditions
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1,802.05706
Weak Lensing of Intensity Mapping: the Cosmic Infrared Background
Gravitational lensing deflects the paths of cosmic infrared background (CIB) photons, leaving a measurable imprint on CIB maps. The resulting statistical anisotropy can be used to reconstruct the matter distribution out to the redshifts of CIB sources. To this end, we generalize the CMB lensing quadratic estimator to any weakly non-Gaussian source field, by deriving the optimal lensing weights. We point out the additional noise and bias caused by the non-Gaussianity and the `self-lensing' of the source field. We propose methods to reduce, subtract or model these non-Gaussianities. We show that CIB lensing should be detectable with Planck data, and detectable at high significance for future CMB experiments like CCAT-Prime. The CIB thus constitutes a new source image for lensing studies, providing constraints on the amplitude of structure at intermediate redshifts between galaxies and the CMB. CIB lensing measurements will also give valuable information on the star formation history in the universe, constraining CIB halo models beyond the CIB power spectrum. By laying out a detailed treatment of lens reconstruction from a weakly non-Gaussian source field, this work constitutes a stepping stone towards lens reconstruction from continuum or line intensity mapping data, such as the Lyman-alpha emission, absorption, and the 21cm radiation.
astro-ph.CO
gravitational lensing deflects the paths of cosmic infrared background cib photons leaving a measurable imprint on cib maps the resulting statistical anisotropy can be used to reconstruct the matter distribution out to the redshifts of cib sources to this end we generalize the cmb lensing quadratic estimator to any weakly nongaussian source field by deriving the optimal lensing weights we point out the additional noise and bias caused by the nongaussianity and the selflensing of the source field we propose methods to reduce subtract or model these nongaussianities we show that cib lensing should be detectable with planck data and detectable at high significance for future cmb experiments like ccatprime the cib thus constitutes a new source image for lensing studies providing constraints on the amplitude of structure at intermediate redshifts between galaxies and the cmb cib lensing measurements will also give valuable information on the star formation history in the universe constraining cib halo models beyond the cib power spectrum by laying out a detailed treatment of lens reconstruction from a weakly nongaussian source field this work constitutes a stepping stone towards lens reconstruction from continuum or line intensity mapping data such as the lymanalpha emission absorption and the 21cm radiation
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1,802.05707
30-Fold Increase in Atom-Cavity Coupling Using a Parabolic Ring Cavity
Optical cavities are one of the best ways to increase atom-light coupling and will be a key ingredient for future quantum technologies that rely on light-matter interfaces. We demonstrate that traveling-wave "ring" cavities can achieve a greatly reduced mode waist $w$, leading to larger atom-cavity coupling strength, relative to conventional standing-wave cavities for given mirror separation and stability. Additionally, ring cavities can achieve arbitrary transverse-mode spacing simultaneously with the large mode-waist reductions. Following these principles, we build a parabolic atom-ring cavity system that achieves strong collective coupling $NC = 15(1)$ between $N=10^3$ Rb atoms and a ring cavity with a single-atom cooperativity $C$ that is a factor of $35(5)$ times greater than what could be achieved with a near-confocal standing-wave cavity with the same mirror separation and finesse. By using parabolic mirrors, we eliminate astigmatism--which can otherwise preclude stable operation--and increase optical access to the atoms. Cavities based on these principles, with enhanced coupling and large mirror separation, will be particularly useful for achieving strong coupling with ions, Rydberg atoms, or other strongly interacting particles, which often have undesirable interactions with nearby surfaces.
physics.atom-ph quant-ph
optical cavities are one of the best ways to increase atomlight coupling and will be a key ingredient for future quantum technologies that rely on lightmatter interfaces we demonstrate that travelingwave ring cavities can achieve a greatly reduced mode waist w leading to larger atomcavity coupling strength relative to conventional standingwave cavities for given mirror separation and stability additionally ring cavities can achieve arbitrary transversemode spacing simultaneously with the large modewaist reductions following these principles we build a parabolic atomring cavity system that achieves strong collective coupling nc 151 between n103 rb atoms and a ring cavity with a singleatom cooperativity c that is a factor of 355 times greater than what could be achieved with a nearconfocal standingwave cavity with the same mirror separation and finesse by using parabolic mirrors we eliminate astigmatismwhich can otherwise preclude stable operationand increase optical access to the atoms cavities based on these principles with enhanced coupling and large mirror separation will be particularly useful for achieving strong coupling with ions rydberg atoms or other strongly interacting particles which often have undesirable interactions with nearby surfaces
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1,802.05708
Kissing numbers and transference theorems from generalized tail bounds
We generalize Banaszczyk's seminal tail bound for the Gaussian mass of a lattice to a wide class of test functions. From this we obtain quite general transference bounds, as well as bounds on the number of lattice points contained in certain bodies. As applications, we bound the lattice kissing number in $\ell_p$ norms by $e^{(n+ o(n))/p}$ for $0 < p \leq 2$, and also give a proof of a new transference bound in the $\ell_1$ norm.
math.MG math.NT
we generalize banaszczyks seminal tail bound for the gaussian mass of a lattice to a wide class of test functions from this we obtain quite general transference bounds as well as bounds on the number of lattice points contained in certain bodies as applications we bound the lattice kissing number in ell_p norms by en onp for 0 p leq 2 and also give a proof of a new transference bound in the ell_1 norm
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1,802.05709
A physical framework for the Earth System, the Anthropocene Equation and the Great Acceleration
It is proposed, based on the Landau-Ginzburg Theory of phase transitions, that the transition of the Earth System from the stable conditions of the Holocene to the human driven condition of the Anthropocene is, actually, a phase transition, a qualitative change away from its Holocene equilibrium state. Based on this physical framework, one obtains the Anthropocene equation, the so-called Great Acceleration and shows that (i) the Earth System temperature on the new equilibrium state diverges from the average temperature of the Holocene as the cubic root of the human intervention, described by a parameter, $H$; (ii) the human induced departure from the Holocene can be as drastic as the ones due to natural, astronomical and geophysical causes; (iii) the susceptibility of the Earth System to human effects is much more relevant near the phase transition. The procedure to obtain numerical predictions from data is also exemplified through one of the existing proposals to account for human impact on the Earth's Holocene equilibrium.
physics.gen-ph physics.pop-ph
it is proposed based on the landauginzburg theory of phase transitions that the transition of the earth system from the stable conditions of the holocene to the human driven condition of the anthropocene is actually a phase transition a qualitative change away from its holocene equilibrium state based on this physical framework one obtains the anthropocene equation the socalled great acceleration and shows that i the earth system temperature on the new equilibrium state diverges from the average temperature of the holocene as the cubic root of the human intervention described by a parameter h ii the human induced departure from the holocene can be as drastic as the ones due to natural astronomical and geophysical causes iii the susceptibility of the earth system to human effects is much more relevant near the phase transition the procedure to obtain numerical predictions from data is also exemplified through one of the existing proposals to account for human impact on the earths holocene equilibrium
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1,802.0571
Symmetry and decoherence-free subspaces in quantum neural networks
Evolution of quantum states of array of quantum dots is analyzed by means of numerical solution of the von Neumann equation. For two qubit system with dipole-dipole interaction and common phonon bath the evolution of the symmetric state $\frac{\uparrow\downarrow+\downarrow\uparrow}{\sqrt{2}}$ leads to the mixture of the triplet states, leaving the singlet decoupled. For three qubit system ($D_{1/2}^{\otimes3}=D_{3/2}+2D_{1/2}$) with common phonon bath we observed similar effects within the quartet state $D_{3/2}$ if all qubits were symmetrically connected.
quant-ph
evolution of quantum states of array of quantum dots is analyzed by means of numerical solution of the von neumann equation for two qubit system with dipoledipole interaction and common phonon bath the evolution of the symmetric state fracuparrowdownarrowdownarrowuparrowsqrt2 leads to the mixture of the triplet states leaving the singlet decoupled for three qubit system d_12otimes3d_322d_12 with common phonon bath we observed similar effects within the quartet state d_32 if all qubits were symmetrically connected
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1,802.05711
Modelling uncertainty using stochastic transport noise in a 2-layer quasi-geostrophic model
The stochastic variational approach for geophysical fluid dynamics was introduced by Holm (Proc Roy Soc A, 2015) as a framework for deriving stochastic parameterisations for unresolved scales. This paper applies the variational stochastic parameterisation in a two-layer quasi-geostrophic model for a beta-plane channel flow configuration. We present a new method for estimating the stochastic forcing (used in the parameterisation) to approximate unresolved components using data from the high resolution deterministic simulation, and describe a procedure for computing physically-consistent initial conditions for the stochastic model. We also quantify uncertainty of coarse grid simulations relative to the fine grid ones in homogeneous (teamed with small-scale vortices) and heterogeneous (featuring horizontally elongated large-scale jets) flows, and analyse how the spread of stochastic solutions depends on different parameters of the model. The parameterisation is tested by comparing it with the true eddy-resolving solution that has reached some statistical equilibrium and the deterministic solution modelled on a low-resolution grid. The results show that the proposed parameterisation significantly depends on the resolution of the stochastic model and gives good ensemble performance for both homogeneous and heterogeneous flows, and the parameterisation lays solid foundations for data assimilation.
physics.flu-dyn math-ph math.MP
the stochastic variational approach for geophysical fluid dynamics was introduced by holm proc roy soc a 2015 as a framework for deriving stochastic parameterisations for unresolved scales this paper applies the variational stochastic parameterisation in a twolayer quasigeostrophic model for a betaplane channel flow configuration we present a new method for estimating the stochastic forcing used in the parameterisation to approximate unresolved components using data from the high resolution deterministic simulation and describe a procedure for computing physicallyconsistent initial conditions for the stochastic model we also quantify uncertainty of coarse grid simulations relative to the fine grid ones in homogeneous teamed with smallscale vortices and heterogeneous featuring horizontally elongated largescale jets flows and analyse how the spread of stochastic solutions depends on different parameters of the model the parameterisation is tested by comparing it with the true eddyresolving solution that has reached some statistical equilibrium and the deterministic solution modelled on a lowresolution grid the results show that the proposed parameterisation significantly depends on the resolution of the stochastic model and gives good ensemble performance for both homogeneous and heterogeneous flows and the parameterisation lays solid foundations for data assimilation
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1,802.05712
Gravitational waves from vacuum first-order phase transitions: from the envelope to the lattice
We conduct large scale numerical simulations of gravitational wave production at a first order vacuum phase transition. We find a power law for the gravitational wave power spectrum at high wavenumber which falls off as $k^{-1.5}$ rather than the $k^{-1}$ produced by the envelope approximation. The peak of the power spectrum is shifted to slightly lower wave numbers from that of the envelope approximation. The envelope approximation reproduces our results for the peak power less well, agreeing only to within an order of magnitude. After the bubbles finish colliding the scalar field oscillates around the true vacuum. An additional feature is produced in the UV of the gravitational wave power spectrum, and this continues to grow linearly until the end of our simulation. The additional feature peaks at a length scale close to the bubble wall thickness and is shown to have a negligible contribution to the energy in gravitational waves, providing the scalar field mass is much smaller than the Planck mass.
astro-ph.CO hep-ph
we conduct large scale numerical simulations of gravitational wave production at a first order vacuum phase transition we find a power law for the gravitational wave power spectrum at high wavenumber which falls off as k15 rather than the k1 produced by the envelope approximation the peak of the power spectrum is shifted to slightly lower wave numbers from that of the envelope approximation the envelope approximation reproduces our results for the peak power less well agreeing only to within an order of magnitude after the bubbles finish colliding the scalar field oscillates around the true vacuum an additional feature is produced in the uv of the gravitational wave power spectrum and this continues to grow linearly until the end of our simulation the additional feature peaks at a length scale close to the bubble wall thickness and is shown to have a negligible contribution to the energy in gravitational waves providing the scalar field mass is much smaller than the planck mass
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1,802.05713
A Simple No-Scale Model of Modulus Fixing and Inflation
We construct a no-scale model of inflation with a single modulus whose real and imaginary parts are fixed by simple power-law corrections to the no-scale K{\" a}hler potential. Assuming an uplift of the minimum of the effective potential, the model yields a suitable number of e-folds of expansion and values of the tilt in the scalar cosmological density perturbations and of the ratio of tensor and scalar perturbations that are compatible with measurements of the cosmic microwave background radiation.
hep-ph astro-ph.CO gr-qc hep-th
we construct a noscale model of inflation with a single modulus whose real and imaginary parts are fixed by simple powerlaw corrections to the noscale k ahler potential assuming an uplift of the minimum of the effective potential the model yields a suitable number of efolds of expansion and values of the tilt in the scalar cosmological density perturbations and of the ratio of tensor and scalar perturbations that are compatible with measurements of the cosmic microwave background radiation
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1,802.05714
The Experimental Nuclear Reaction Data (EXFOR): Extended Computer Database and Web Retrieval System
The EXchange FORmat (EXFOR) experimental nuclear reaction database and the associated Web interface provide access to the wealth of low- and intermediate-energy nuclear reaction physics data. This resource is based on numerical data sets and bibliographical information of $\sim$22,000 experiments since the beginning of nuclear science. The principles of the Web and database applications development are described. New capabilities for the data sets uploads, renormalization, covariance matrix, and inverse reaction calculations are presented. The EXFOR database, updated monthly, provides an essential support for nuclear data evaluation, application development, and research activities. It is publicly available at the websites of the International Atomic Energy Agency Nuclear Data Section, {\it http://www-nds.iaea.org/exfor}, the U.S. National Nuclear Data Center, {\it http://www.nndc.bnl.gov/exfor}, and the mirror sites in China, India and Russian Federation.
physics.comp-ph math.NA
the exchange format exfor experimental nuclear reaction database and the associated web interface provide access to the wealth of low and intermediateenergy nuclear reaction physics data this resource is based on numerical data sets and bibliographical information of sim22000 experiments since the beginning of nuclear science the principles of the web and database applications development are described new capabilities for the data sets uploads renormalization covariance matrix and inverse reaction calculations are presented the exfor database updated monthly provides an essential support for nuclear data evaluation application development and research activities it is publicly available at the websites of the international atomic energy agency nuclear data section it httpwwwndsiaeaorgexfor the us national nuclear data center it httpwwwnndcbnlgovexfor and the mirror sites in china india and russian federation
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1,802.05715
An image-based array trigger for Imaging Atmospheric Cherenkov Telescope Arrays
It is anticipated that forthcoming, next generation, atmospheric Cherenkov telescope arrays will include a number of medium-sized telescopes that are constructed using a dual-mirror Schwarzschild-Couder configuration. These telescopes will sample a wide ($8^{\circ}$) field of view using a densely pixelated camera comprising over $10^{4}$ individual readout channels. A readout frequency congruent with the expected single-telescope trigger rates would result in substantial data rates. To ameliorate these data rates, a novel, hardware-level Distributed Intelligent Array Trigger (DIAT) is envisioned. A copy of the DIAT operates autonomously at each telescope and uses reduced resolution imaging data from a limited subset of nearby telescopes to veto events prior to camera readout {and any subsequent network transmission of camera data that is required for centralized storage or aggregation}. We present the results of Monte-Carlo simulations that evaluate the efficacy of a "Parallax width" discriminator that can be used by the DIAT to efficiently distinguish between genuine gamma-ray initiated events and unwanted background events that are initiated by hadronic cosmic rays.
astro-ph.IM astro-ph.HE
it is anticipated that forthcoming next generation atmospheric cherenkov telescope arrays will include a number of mediumsized telescopes that are constructed using a dualmirror schwarzschildcouder configuration these telescopes will sample a wide 8circ field of view using a densely pixelated camera comprising over 104 individual readout channels a readout frequency congruent with the expected singletelescope trigger rates would result in substantial data rates to ameliorate these data rates a novel hardwarelevel distributed intelligent array trigger diat is envisioned a copy of the diat operates autonomously at each telescope and uses reduced resolution imaging data from a limited subset of nearby telescopes to veto events prior to camera readout and any subsequent network transmission of camera data that is required for centralized storage or aggregation we present the results of montecarlo simulations that evaluate the efficacy of a parallax width discriminator that can be used by the diat to efficiently distinguish between genuine gammaray initiated events and unwanted background events that are initiated by hadronic cosmic rays
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1,802.05716
Secular dynamics of hierarchical multiple systems composed of nested binaries, with an arbitrary number of bodies and arbitrary hierarchical structure. II. External perturbations: flybys and supernovae
We extend the formalism of a previous paper to include the effects of flybys and instantaneous perturbations such as supernovae on the long-term secular evolution of hierarchical multiple systems with an arbitrary number of bodies and hierarchy, provided that the system is composed of nested binary orbits. To model secular encounters, we expand the Hamiltonian in terms of the ratio of the separation of the perturber with respect to the barycentre of the multiple system, to the separation of the widest orbit. Subsequently, we integrate over the perturber orbit numerically or analytically. We verify our method for secular encounters, and illustrate it with an example. Furthermore, we describe a method to compute instantaneous orbital changes to multiple systems, such as asymmetric supernovae and impulsive encounters. The secular code, with implementation of the extensions described in this paper, is publicly available within AMUSE, and we provide a number of simple example scripts to illustrate its usage for secular and impulsive encounters, and asymmetric supernovae. The extensions presented in this paper are a next step toward efficiently modeling the evolution of complex multiple systems embedded in star clusters.
astro-ph.SR astro-ph.EP
we extend the formalism of a previous paper to include the effects of flybys and instantaneous perturbations such as supernovae on the longterm secular evolution of hierarchical multiple systems with an arbitrary number of bodies and hierarchy provided that the system is composed of nested binary orbits to model secular encounters we expand the hamiltonian in terms of the ratio of the separation of the perturber with respect to the barycentre of the multiple system to the separation of the widest orbit subsequently we integrate over the perturber orbit numerically or analytically we verify our method for secular encounters and illustrate it with an example furthermore we describe a method to compute instantaneous orbital changes to multiple systems such as asymmetric supernovae and impulsive encounters the secular code with implementation of the extensions described in this paper is publicly available within amuse and we provide a number of simple example scripts to illustrate its usage for secular and impulsive encounters and asymmetric supernovae the extensions presented in this paper are a next step toward efficiently modeling the evolution of complex multiple systems embedded in star clusters
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1,802.05717
A model for AGN variability on multiple timescales
We present a framework to link and describe AGN variability on a wide range of timescales, from days to billions of years. In particular, we concentrate on the AGN variability features related to changes in black hole fuelling and accretion rate. In our framework, the variability features observed in different AGN at different timescales may be explained as realisations of the same underlying statistical properties. In this context, we propose a model to simulate the evolution of AGN light curves with time based on the probability density function (PDF) and power spectral density (PSD) of the Eddington ratio ($L/L_{\rm Edd}$) distribution. Motivated by general galaxy population properties, we propose that the PDF may be inspired by the $L/L_{\rm Edd}$ distribution function (ERDF), and that a single (or limited number of) ERDF+PSD set may explain all observed variability features. After outlining the framework and the model, we compile a set of variability measurements in terms of structure function (SF) and magnitude difference. We then combine the variability measurements on a SF plot ranging from days to Gyr. The proposed framework enables constraints on the underlying PSD and the ability to link AGN variability on different timescales, therefore providing new insights into AGN variability and black hole growth phenomena.
astro-ph.GA astro-ph.HE
we present a framework to link and describe agn variability on a wide range of timescales from days to billions of years in particular we concentrate on the agn variability features related to changes in black hole fuelling and accretion rate in our framework the variability features observed in different agn at different timescales may be explained as realisations of the same underlying statistical properties in this context we propose a model to simulate the evolution of agn light curves with time based on the probability density function pdf and power spectral density psd of the eddington ratio ll_rm edd distribution motivated by general galaxy population properties we propose that the pdf may be inspired by the ll_rm edd distribution function erdf and that a single or limited number of erdfpsd set may explain all observed variability features after outlining the framework and the model we compile a set of variability measurements in terms of structure function sf and magnitude difference we then combine the variability measurements on a sf plot ranging from days to gyr the proposed framework enables constraints on the underlying psd and the ability to link agn variability on different timescales therefore providing new insights into agn variability and black hole growth phenomena
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1,802.05718
An Analytical Portrait of Binary Mergers in Hierarchical Triple Systems
With better statistics and precision, eccentricity could prove to be a useful tool for understanding the origin and environment of binary black holes. Hierarchical triples in particular, which might be abundant in globular clusters and galactic nuclei, could generate observably large eccentricity at LIGO and future gravitational wave detectors. Measuring the eccentricity distribution accurately could help us probe the background and the formation of the mergers. In this paper we continue our previous investigation and improve our semi-analytical description of the eccentricity distribution of mergers hierarchical triple systems. Our result, which further reduces the reliance on numerical simulations, could be useful for statistically distinguishing different formation channels of observed binary mergers.
gr-qc astro-ph.HE hep-ph hep-th
with better statistics and precision eccentricity could prove to be a useful tool for understanding the origin and environment of binary black holes hierarchical triples in particular which might be abundant in globular clusters and galactic nuclei could generate observably large eccentricity at ligo and future gravitational wave detectors measuring the eccentricity distribution accurately could help us probe the background and the formation of the mergers in this paper we continue our previous investigation and improve our semianalytical description of the eccentricity distribution of mergers hierarchical triple systems our result which further reduces the reliance on numerical simulations could be useful for statistically distinguishing different formation channels of observed binary mergers
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1,802.05719
Generic emergence of objectivity of observables in infinite dimensions
Quantum Darwinism posits that information becomes objective whenever multiple observers indirectly probe a quantum system by each measuring a fraction of the environment. It was recently shown that objectivity of observables emerges generically from the mathematical structure of quantum mechanics, whenever the system of interest has finite dimensions and the number of environment fragments is large [F. G. S. L. Brand\~ao, M. Piani, and P. Horodecki, Nature Commun. 6, 7908 (2015)]. Despite the importance of this result, it necessarily excludes many practical systems of interest that are infinite-dimensional, including harmonic oscillators. Extending the study of Quantum Darwinism to infinite dimensions is a nontrivial task: we tackle it here by using a modified diamond norm, suitable to quantify the distinguishability of channels in infinite dimensions. We prove two theorems that bound the emergence of objectivity, first for finite energy systems, and then for systems that can only be prepared in states with an exponential energy cut-off. We show that the latter class of states includes any bounded-energy subset of single-mode Gaussian states.
quant-ph hep-th math-ph math.MP physics.hist-ph
quantum darwinism posits that information becomes objective whenever multiple observers indirectly probe a quantum system by each measuring a fraction of the environment it was recently shown that objectivity of observables emerges generically from the mathematical structure of quantum mechanics whenever the system of interest has finite dimensions and the number of environment fragments is large f g s l brandao m piani and p horodecki nature commun 6 7908 2015 despite the importance of this result it necessarily excludes many practical systems of interest that are infinitedimensional including harmonic oscillators extending the study of quantum darwinism to infinite dimensions is a nontrivial task we tackle it here by using a modified diamond norm suitable to quantify the distinguishability of channels in infinite dimensions we prove two theorems that bound the emergence of objectivity first for finite energy systems and then for systems that can only be prepared in states with an exponential energy cutoff we show that the latter class of states includes any boundedenergy subset of singlemode gaussian states
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1,802.0572
Obscured star-formation in bright z ~ 7 Lyman-break galaxies
We present Atacama Large Millimeter/Submillimeter Array observations of the rest-frame far-infrared (FIR) dust continuum emission of six bright Lyman-break galaxies (LBGs) at $z \simeq 7$. One LBG is detected ($5.2\sigma$ at peak emission), while the others remain individually undetected at the $3\sigma$ level. The average FIR luminosity of the sample is found to be $L_{\rm FIR} \simeq 2 \times 10^{11}\,{\rm L}_{\odot}$, corresponding to an obscured star-formation rate (SFR) that is comparable to that inferred from the unobscured UV emission. In comparison to the infrared excess (IRX$\,=L_{\rm FIR}/L_{\rm UV}$)-$\beta$ relation, our results are consistent with a Calzetti-like attenuation law (assuming a dust temperature of T = 40-50 K). We find a physical offset of 3 kpc between the dust continuum emission and the rest-frame UV light probed by Hubble Space Telescope imaging for galaxy ID65666 at $z = 7.17^{+0.09}_{-0.06}$. The offset is suggestive of an inhomogeneous dust distribution, where 75% of the total star formation activity (SFR$ \,\simeq 70\,{\rm M}_{\odot}/{\rm yr}$) of the galaxy is completely obscured. Our results provide direct evidence that dust obscuration plays a key role in shaping the bright-end of the observed rest-frame UV luminosity function at $z \simeq 7$, in agreement with cosmological galaxy formation simulations. The existence of a heavily-obscured component of galaxy ID65666 indicates that dusty star-forming regions, or even entire galaxies, that are "UV-dark" are significant even in the $z \simeq 7$ galaxy population.
astro-ph.GA
we present atacama large millimetersubmillimeter array observations of the restframe farinfrared fir dust continuum emission of six bright lymanbreak galaxies lbgs at z simeq 7 one lbg is detected 52sigma at peak emission while the others remain individually undetected at the 3sigma level the average fir luminosity of the sample is found to be l_rm fir simeq 2 times 1011rm l_odot corresponding to an obscured starformation rate sfr that is comparable to that inferred from the unobscured uv emission in comparison to the infrared excess irxl_rm firl_rm uvbeta relation our results are consistent with a calzettilike attenuation law assuming a dust temperature of t 4050 k we find a physical offset of 3 kpc between the dust continuum emission and the restframe uv light probed by hubble space telescope imaging for galaxy id65666 at z 717009_006 the offset is suggestive of an inhomogeneous dust distribution where 75 of the total star formation activity sfr simeq 70rm m_odotrm yr of the galaxy is completely obscured our results provide direct evidence that dust obscuration plays a key role in shaping the brightend of the observed restframe uv luminosity function at z simeq 7 in agreement with cosmological galaxy formation simulations the existence of a heavilyobscured component of galaxy id65666 indicates that dusty starforming regions or even entire galaxies that are uvdark are significant even in the z simeq 7 galaxy population
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1,802.05721
Single lepton charge asymmetries in $t \bar t$ and $t \bar t \gamma$ production at the LHC
We discuss lepton charge asymmetries in $t \bar t$ and $t \bar t \gamma$ production at the LHC, which can be measured in the semileptonic decay channel $t \bar t \to W^+ b \, W^- \bar b \to \ell^+ \nu b \, q \bar q' \bar b$ (or the charge conjugate). Considering several variants of a new physics scenario with a light colour octet, it is seen that for $t \bar t$ these asymmetries may have a sensitivity competitive with the dilepton asymmetry already measured. For $t \bar t \gamma$ the new leptonic asymmetries, as well as the $t \bar t$ charge asymmetry, will reach their full potential with the high luminosity LHC upgrade. These asymmetries can pinpoint deviations at the $3\sigma-4\sigma$ level for new physics scenarios where the charge asymmetries already measured in $t \bar t$ production agree within $1\sigma$.
hep-ph hep-ex
we discuss lepton charge asymmetries in t bar t and t bar t gamma production at the lhc which can be measured in the semileptonic decay channel t bar t to w b w bar b to ell nu b q bar q bar b or the charge conjugate considering several variants of a new physics scenario with a light colour octet it is seen that for t bar t these asymmetries may have a sensitivity competitive with the dilepton asymmetry already measured for t bar t gamma the new leptonic asymmetries as well as the t bar t charge asymmetry will reach their full potential with the high luminosity lhc upgrade these asymmetries can pinpoint deviations at the 3sigma4sigma level for new physics scenarios where the charge asymmetries already measured in t bar t production agree within 1sigma
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1,802.05722
Seesaw roadmap to neutrino mass and dark matter
We describe the many pathways to generate Majorana and Dirac neutrino mass through generalized dimension-5 operators a la Weinberg. The presence of new scalars beyond the Standard Model Higgs doublet implies new possible field contractions, which are required in the case of Dirac neutrinos. We also notice that, in the Dirac neutrino case, the extra symmetries needed to ensure the Dirac nature of neutrinos can also be made responsible for stability of dark matter.
hep-ph
we describe the many pathways to generate majorana and dirac neutrino mass through generalized dimension5 operators a la weinberg the presence of new scalars beyond the standard model higgs doublet implies new possible field contractions which are required in the case of dirac neutrinos we also notice that in the dirac neutrino case the extra symmetries needed to ensure the dirac nature of neutrinos can also be made responsible for stability of dark matter
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1,802.05723
Relativistic properties of a molecule: energy, linear momentum, angular momentum and boost momentum to order $1/c^2$
We give an explicit and general description of the energy, linear momentum, angular momentum and boost momentum of a molecule to order $1/c^2$, where it necessary to take account of kinetic contributions made by the electrons and nuclei as well as electromagnetic contributions made by the intramolecular field. A wealth of interesting subtleties are encountered that are not seen at order $1/c^0$, including relativistic Hall shifts, anomalous velocities and hidden momenta. Some of these have well known analogues in solid state physics.
physics.chem-ph quant-ph
we give an explicit and general description of the energy linear momentum angular momentum and boost momentum of a molecule to order 1c2 where it necessary to take account of kinetic contributions made by the electrons and nuclei as well as electromagnetic contributions made by the intramolecular field a wealth of interesting subtleties are encountered that are not seen at order 1c0 including relativistic hall shifts anomalous velocities and hidden momenta some of these have well known analogues in solid state physics
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1,802.05724
Dimension free properties of strong Muckenhoupt and Reverse H\"older weights for Radon measures
In this paper we prove self-improvement properties of strong Muckenhoupt and Reverse H\"older weights with respect to a general Radon measure on $\mathbb{R}^n$. We derive our result via a Bellman function argument. An important feature of our proof is that it uses only the Bellman function for the one-dimensional problem for Lebesgue measure; with this function in hand, we derive dimension free results for general measures and dimensions.
math.CA
in this paper we prove selfimprovement properties of strong muckenhoupt and reverse holder weights with respect to a general radon measure on mathbbrn we derive our result via a bellman function argument an important feature of our proof is that it uses only the bellman function for the onedimensional problem for lebesgue measure with this function in hand we derive dimension free results for general measures and dimensions
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1,802.05725
A New Catalogue of Galactic Novae: Investigation of the MMRD relation & Spatial Distribution
In this study, a new Galactic novae catalogue is introduced collecting important parameters of these sources such as their light curve parameters, classifications, full width half maximum (FWHM) of H$_\alpha$ line, distances and interstellar reddening estimates. The catalogue is also published on a website with a search option via a SQL query and an online tool to re-calculate the distance/reddening of a nova from the derived reddening-distance relations. Using the novae in the catalogue, the existence of a maximum magnitude-rate of decline (MMRD) relation in the Galaxy is investigated. Although an MMRD relation was obtained, a significant scattering in the resulting MMRD distribution still exists. We suggest that the MMRD relation likely depends on other parameters in addition to the decline time, as FWHM H$_\alpha$, the light curve shapes. Using two different samples depending on the distances in the catalogue and from the derived MMRD relation, the spatial distributions of Galactic novae as a function of their spectral and speed classes were studied. The investigation on the Galactic model parameters implies that best estimates for the local outburst density are 3.6 and 4.2 $\times 10^{-10}$ pc$^{-3}$ yr$^{-1}$ with a scale height of 148 and 175 pc, while the space density changes in the range of $0.4 - 16 \ \times 10^{-6}$ pc$^{-3}$. The local outburst density and scale height obtained in this study infer that the disk nova rate in the Galaxy is in the range of $\sim20$ to $\sim100$ yr$^{-1}$ with an average estimate $67^{+21}_{-17}$ yr$^{-1}$.
astro-ph.SR
in this study a new galactic novae catalogue is introduced collecting important parameters of these sources such as their light curve parameters classifications full width half maximum fwhm of h_alpha line distances and interstellar reddening estimates the catalogue is also published on a website with a search option via a sql query and an online tool to recalculate the distancereddening of a nova from the derived reddeningdistance relations using the novae in the catalogue the existence of a maximum magnituderate of decline mmrd relation in the galaxy is investigated although an mmrd relation was obtained a significant scattering in the resulting mmrd distribution still exists we suggest that the mmrd relation likely depends on other parameters in addition to the decline time as fwhm h_alpha the light curve shapes using two different samples depending on the distances in the catalogue and from the derived mmrd relation the spatial distributions of galactic novae as a function of their spectral and speed classes were studied the investigation on the galactic model parameters implies that best estimates for the local outburst density are 36 and 42 times 1010 pc3 yr1 with a scale height of 148 and 175 pc while the space density changes in the range of 04 16 times 106 pc3 the local outburst density and scale height obtained in this study infer that the disk nova rate in the galaxy is in the range of sim20 to sim100 yr1 with an average estimate 6721_17 yr1
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1,802.05726
Fixed points, bounded orbits and attractors of planar flows
In this paper we provide a dynamical characterization of isolated invariant continua which are global attractors for planar dissipative flows. As a consequence, a sufficient condition for an isolated invariant continuum to be either an attractor or a repeller is derived for general planar flows.
math.DS
in this paper we provide a dynamical characterization of isolated invariant continua which are global attractors for planar dissipative flows as a consequence a sufficient condition for an isolated invariant continuum to be either an attractor or a repeller is derived for general planar flows
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1,802.05727
Long-range Coulomb Interaction effects on Topological Phase Transitions between Semi-metals and Insulators
Topological states may be protected by a lattice symmetry in a class of topological semi-metals. In three spatial dimensions, the Berry flux around gapless excitations in momentum space defines a chirality concretely, so a protecting symmetry may be referred to as a chiral symmetry. Prime examples include Dirac semi-metal (DSM) in a distorted spinel, BiZnSiO$_4$, protected by a mirror symmetry and DSM in Na$_3$Bi, protected by a rotational symmetry. In these states, topology and a chiral symmetry are intrinsically tied. In this work, we investigate characteristics interplay between a chiral symmetry order parameter and instantaneous long-range Coulomb interaction with the standard renormalization group method. We show that a topological transition associated with a chiral symmetry is stable under the presence of the Coulomb interaction and the electron velocity always becomes faster than one of a chiral symmetry order parameter. Thus, the transition {\it must not} be relativistic, which implies a supersymmetry is intrinsically forbidden by the long-range Coulomb interaction. {Asymptotically exact} universal ratios of physical quantities such as energy gap ratio are obtained, and connections with experiments and recent theoretical proposals are also discussed.
cond-mat.str-el
topological states may be protected by a lattice symmetry in a class of topological semimetals in three spatial dimensions the berry flux around gapless excitations in momentum space defines a chirality concretely so a protecting symmetry may be referred to as a chiral symmetry prime examples include dirac semimetal dsm in a distorted spinel biznsio_4 protected by a mirror symmetry and dsm in na_3bi protected by a rotational symmetry in these states topology and a chiral symmetry are intrinsically tied in this work we investigate characteristics interplay between a chiral symmetry order parameter and instantaneous longrange coulomb interaction with the standard renormalization group method we show that a topological transition associated with a chiral symmetry is stable under the presence of the coulomb interaction and the electron velocity always becomes faster than one of a chiral symmetry order parameter thus the transition it must not be relativistic which implies a supersymmetry is intrinsically forbidden by the longrange coulomb interaction asymptotically exact universal ratios of physical quantities such as energy gap ratio are obtained and connections with experiments and recent theoretical proposals are also discussed
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1,802.05728
Synthesis of Insertion Functions to Enforce Decentralized and Joint Opacity Properties of Discrete-event Systems
Opacity is a confidentiality property that characterizes the non-disclosure of specified secret information of a system to an outside observer. In this paper, we consider the enforcement of opacity within the discrete-event system formalism in the presence of multiple intruders. We study two cases, one without coordination among the intruders and the other with coordination. We propose appropriate notions of opacity corresponding to the two cases, respectively, and propose enforcement mechanisms for these opacity properties based on the implementation of insertion functions, which manipulates the output of the system by inserting fictitious observable events whenever necessary. The insertion mechanism is adapted to the decentralized framework to enforce opacity when no coordination exists. Furthermore, we present a coordination and refinement procedure to synthesize appropriate insertion functions to enforce opacity when intruders may coordinate with each other by following an intersection-based coordination protocol. The effectiveness of the proposed opacity-enforcement approaches is validated through illustrative examples.
cs.CR
opacity is a confidentiality property that characterizes the nondisclosure of specified secret information of a system to an outside observer in this paper we consider the enforcement of opacity within the discreteevent system formalism in the presence of multiple intruders we study two cases one without coordination among the intruders and the other with coordination we propose appropriate notions of opacity corresponding to the two cases respectively and propose enforcement mechanisms for these opacity properties based on the implementation of insertion functions which manipulates the output of the system by inserting fictitious observable events whenever necessary the insertion mechanism is adapted to the decentralized framework to enforce opacity when no coordination exists furthermore we present a coordination and refinement procedure to synthesize appropriate insertion functions to enforce opacity when intruders may coordinate with each other by following an intersectionbased coordination protocol the effectiveness of the proposed opacityenforcement approaches is validated through illustrative examples
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1,802.05729
Linear discriminant analysis as an alternative method to investigate the interaction of a 1064 nm CW laser light with a cold inductively-coupled plasma
In this paper, the interaction of a 1064 nm continuum-wave laser with inductively-coupled plasma generated in a fluorescent light bulb has been studied both experimentally and theoretically. The absorption coefficients pertaining to the plasma medium were obtained for different power measurements. The results indicate that absorption coefficients decrease with the increase in laser power. The UV-Vis spectra of mercury plasma were recorded by the charge-coupled spectrometer device at different power levels of laser. The linear discriminant analysis (LDA) of plasma spectra reveals the plasma ion and electron oscillations. Fourier series modeling of electron oscillation results the Whistler mode frequency of wpe= 0.16 kHz with a density of ne=3.9x1013 cm^(-3). 3D representation of LDA coefficients shows that the increase of laser power leads the plasma species to form in Whistler mode structures. Plasma electron temperatures ( e T ) was inferred from the SPARTAN non-local thermal equilibrium (non-LTE) spectral code, and they were about 0.6 eV in the absence of laser light. However, there was a 0.05 eV increase in electron temperature when the laser power was absorbed by the plasma. Electron temperatures slightly increased with the increase in the power levels, which in turn resulted in smaller absorption coefficients since the absorption coefficients scales with Te^(-3/2).
physics.plasm-ph
in this paper the interaction of a 1064 nm continuumwave laser with inductivelycoupled plasma generated in a fluorescent light bulb has been studied both experimentally and theoretically the absorption coefficients pertaining to the plasma medium were obtained for different power measurements the results indicate that absorption coefficients decrease with the increase in laser power the uvvis spectra of mercury plasma were recorded by the chargecoupled spectrometer device at different power levels of laser the linear discriminant analysis lda of plasma spectra reveals the plasma ion and electron oscillations fourier series modeling of electron oscillation results the whistler mode frequency of wpe 016 khz with a density of ne39x1013 cm3 3d representation of lda coefficients shows that the increase of laser power leads the plasma species to form in whistler mode structures plasma electron temperatures e t was inferred from the spartan nonlocal thermal equilibrium nonlte spectral code and they were about 06 ev in the absence of laser light however there was a 005 ev increase in electron temperature when the laser power was absorbed by the plasma electron temperatures slightly increased with the increase in the power levels which in turn resulted in smaller absorption coefficients since the absorption coefficients scales with te32
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1,802.0573
Pedestrian-Robot Interaction Experiments in an Exit Corridor
The study of human-robot interaction (HRI) has received increasing research attention for robot navigation in pedestrian crowds. In this paper, we present empirical study of pedestrian-robot interaction in an uni-directional exit corridor. We deploy a mobile robot moving in a direction perpendicular to that of the pedestrian flow, and install a pedestrian motion tracking system to record the collective motion. We analyze both individual and collective motion of pedestrians, and measure the effect of the robot motion on the overall pedestrian flow. The experimental results show the effect of passive HRI, where the pedestrians' overall speed is slowed down in the presence of the robot, and the faster the robot moves, the lower the average pedestrian velocity becomes. Experiment results show qualitative consistency of the collective HRI effect with simulation results that was previously reported. The study can be used to guide future design of robot-assisted pedestrian evacuation algorithms.
cs.RO cs.SY
the study of humanrobot interaction hri has received increasing research attention for robot navigation in pedestrian crowds in this paper we present empirical study of pedestrianrobot interaction in an unidirectional exit corridor we deploy a mobile robot moving in a direction perpendicular to that of the pedestrian flow and install a pedestrian motion tracking system to record the collective motion we analyze both individual and collective motion of pedestrians and measure the effect of the robot motion on the overall pedestrian flow the experimental results show the effect of passive hri where the pedestrians overall speed is slowed down in the presence of the robot and the faster the robot moves the lower the average pedestrian velocity becomes experiment results show qualitative consistency of the collective hri effect with simulation results that was previously reported the study can be used to guide future design of robotassisted pedestrian evacuation algorithms
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1,802.05731
Ghosts- and Tachyon-Free Regions of the Randall-Sundrum Model Parameter Space
Model building within the Randall-Sundrum (RS) framework generally involves placing the Standard Model fields in the bulk. Such fields may possess non-zero values for their associated brane-localized kinetic terms (BLKTs) in addition to possible bulk mass parameters. In this paper we clearly identify the regions of the RS model parameter space where the presence of bulk mass terms and BLKTs yield a setup which is free from both ghost and tachyon instabilities. Such physically acceptable parameter space regions can then be used to construct realistic and phenomenologically viable RS models.
hep-ph
model building within the randallsundrum rs framework generally involves placing the standard model fields in the bulk such fields may possess nonzero values for their associated branelocalized kinetic terms blkts in addition to possible bulk mass parameters in this paper we clearly identify the regions of the rs model parameter space where the presence of bulk mass terms and blkts yield a setup which is free from both ghost and tachyon instabilities such physically acceptable parameter space regions can then be used to construct realistic and phenomenologically viable rs models
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1,802.05732
Distality for the asymptotic couple of the field of logarithmic transseries
We show that the theory $T_{\log}$ of the asymptotic couple of the field of logarithmic transseries is distal. As distal theories are NIP (= the non-independence property), this provides a new proof that $T_{\log}$ is NIP. Finally, we show that $T_{\log}$ is not strongly dependent, and in particular, it is not $\operatorname{dp}$-minimal and it does not have finite $\operatorname{dp}$-rank.
math.LO
we show that the theory t_log of the asymptotic couple of the field of logarithmic transseries is distal as distal theories are nip the nonindependence property this provides a new proof that t_log is nip finally we show that t_log is not strongly dependent and in particular it is not operatornamedpminimal and it does not have finite operatornamedprank
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1,802.05733
Fair Clustering Through Fairlets
We study the question of fair clustering under the {\em disparate impact} doctrine, where each protected class must have approximately equal representation in every cluster. We formulate the fair clustering problem under both the $k$-center and the $k$-median objectives, and show that even with two protected classes the problem is challenging, as the optimum solution can violate common conventions---for instance a point may no longer be assigned to its nearest cluster center! En route we introduce the concept of fairlets, which are minimal sets that satisfy fair representation while approximately preserving the clustering objective. We show that any fair clustering problem can be decomposed into first finding good fairlets, and then using existing machinery for traditional clustering algorithms. While finding good fairlets can be NP-hard, we proceed to obtain efficient approximation algorithms based on minimum cost flow. We empirically quantify the value of fair clustering on real-world datasets with sensitive attributes.
cs.LG stat.ML
we study the question of fair clustering under the em disparate impact doctrine where each protected class must have approximately equal representation in every cluster we formulate the fair clustering problem under both the kcenter and the kmedian objectives and show that even with two protected classes the problem is challenging as the optimum solution can violate common conventionsfor instance a point may no longer be assigned to its nearest cluster center en route we introduce the concept of fairlets which are minimal sets that satisfy fair representation while approximately preserving the clustering objective we show that any fair clustering problem can be decomposed into first finding good fairlets and then using existing machinery for traditional clustering algorithms while finding good fairlets can be nphard we proceed to obtain efficient approximation algorithms based on minimum cost flow we empirically quantify the value of fair clustering on realworld datasets with sensitive attributes
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1,802.05734
Reachability for infinite time Turing machines with long tapes
Infinite time Turing machine models with tape length $\alpha$, denoted $T_\alpha$, strengthen the machines of Hamkins and Kidder [HL00] with tape length $\omega$. A new phenomenon is that for some countable ordinals $\alpha$, some cells cannot be halting positions of $T_\alpha$ given trivial input. The main open question in [Rin14] asks about the size of the least such ordinal $\delta$. We answer this by providing various characterizations. For instance, $\delta$ is the least ordinal with any of the following properties: (a) For some $\xi<\alpha$, there is a $T_\xi$-writable but not $T_\alpha$-writable subset of $\omega$. (b) There is a gap in the $T_\alpha$-writable ordinals. (c) $\alpha$ is uncountable in $L_{\lambda_\alpha}$. Here $\lambda_\alpha$ denotes the supremum of $T_\alpha$-writable ordinals, i.e. those with a $T_\alpha$-writable code of length $\alpha$. We further use the above characterizations, and an analogue to Welch's submodel characterization of the ordinals $\lambda$, $\zeta$ and $\Sigma$, to show that $\delta$ is large in the sense that it is a closure point of the function $\alpha \mapsto \Sigma_\alpha$, where $\Sigma_\alpha$ denotes the supremum of the $T_\alpha$-accidentally writable ordinals.
math.LO cs.LO
infinite time turing machine models with tape length alpha denoted t_alpha strengthen the machines of hamkins and kidder hl00 with tape length omega a new phenomenon is that for some countable ordinals alpha some cells cannot be halting positions of t_alpha given trivial input the main open question in rin14 asks about the size of the least such ordinal delta we answer this by providing various characterizations for instance delta is the least ordinal with any of the following properties a for some xialpha there is a t_xiwritable but not t_alphawritable subset of omega b there is a gap in the t_alphawritable ordinals c alpha is uncountable in l_lambda_alpha here lambda_alpha denotes the supremum of t_alphawritable ordinals ie those with a t_alphawritable code of length alpha we further use the above characterizations and an analogue to welchs submodel characterization of the ordinals lambda zeta and sigma to show that delta is large in the sense that it is a closure point of the function alpha mapsto sigma_alpha where sigma_alpha denotes the supremum of the t_alphaaccidentally writable ordinals
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1,802.05735
IBeaconMap: Automated Indoor Space Representation for Beacon-Based Wayfinding
Traditionally, there have been few options for navigational aids for the blind and visually impaired (BVI) in large indoor spaces. Some recent indoor navigation systems allow users equipped with smartphones to interact with low cost Bluetoothbased beacons deployed strategically within the indoor space of interest to navigate their surroundings. A major challenge in deploying such beacon-based navigation systems is the need to employ a time and labor-expensive beacon planning process to identify potential beacon placement locations and arrive at a topological structure representing the indoor space. This work presents a technique called IBeaconMap for creating such topological structures to use with beacon-based navigation that only needs the floor plans of the indoor spaces of interest. IBeaconMap employs a combination of computer vision and machine learning techniques to arrive at the required set of beacon locations and a weighted connectivity graph (with directional orientations) for subsequent navigational needs. Evaluations show IBeaconMap to be both fast and reasonably accurate, potentially proving to be an essential tool to be utilized before mass deployments of beacon-based indoor wayfinding systems of the future.
cs.HC
traditionally there have been few options for navigational aids for the blind and visually impaired bvi in large indoor spaces some recent indoor navigation systems allow users equipped with smartphones to interact with low cost bluetoothbased beacons deployed strategically within the indoor space of interest to navigate their surroundings a major challenge in deploying such beaconbased navigation systems is the need to employ a time and laborexpensive beacon planning process to identify potential beacon placement locations and arrive at a topological structure representing the indoor space this work presents a technique called ibeaconmap for creating such topological structures to use with beaconbased navigation that only needs the floor plans of the indoor spaces of interest ibeaconmap employs a combination of computer vision and machine learning techniques to arrive at the required set of beacon locations and a weighted connectivity graph with directional orientations for subsequent navigational needs evaluations show ibeaconmap to be both fast and reasonably accurate potentially proving to be an essential tool to be utilized before mass deployments of beaconbased indoor wayfinding systems of the future
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1,802.05736
Impact of Gas Giant Instabilities on Habitable Planets
The detection of many extrasolar gas giants with high eccentricities indicates that dynamical instabilities in planetary systems are common. These instabilities can alter the orbits of gas giants as well as the orbits of terrestrial planets and therefore eject or move a habitable planet out of the habitable zone. In this work 423 simulations with 153 different hypothetical planetary systems with gas giants and terrestrial planets have been modelled to explore the orbital stability of habitable planets. The initial parameter variations include the number, distances and masses of the giant planets and the star type. Linear correlations between the initial number and the initial distances of gas giants and the survival rate of habitable planets were found. Planetary systems consisting of two giant planets are fairly benign to terrestrial planets, whereas six giant planets very often lead to a complete clearing of the habitable zone. Systems with initial distances of five Hill Radii between the giant planets have a high chance to harbour a habitable planet, although more compact systems are very destructive. The giant planet masses have a smaller impact on the stability of habitable worlds. Additionally, a link between the present-day orbit of an observed giant exoplanet and the survival rate of habitable planets was established. As a rule of thumb, observed gas giants with eccentricities higher than 0.4 and inclinations higher than 20 degrees have experienced strong planet-planet scatterings and are unlikely to have a habitable planet in its system. Furthermore, it was found that habitable planets surrounding a K or M-star have a higher survival rate than those surrounding a G-star.
astro-ph.EP
the detection of many extrasolar gas giants with high eccentricities indicates that dynamical instabilities in planetary systems are common these instabilities can alter the orbits of gas giants as well as the orbits of terrestrial planets and therefore eject or move a habitable planet out of the habitable zone in this work 423 simulations with 153 different hypothetical planetary systems with gas giants and terrestrial planets have been modelled to explore the orbital stability of habitable planets the initial parameter variations include the number distances and masses of the giant planets and the star type linear correlations between the initial number and the initial distances of gas giants and the survival rate of habitable planets were found planetary systems consisting of two giant planets are fairly benign to terrestrial planets whereas six giant planets very often lead to a complete clearing of the habitable zone systems with initial distances of five hill radii between the giant planets have a high chance to harbour a habitable planet although more compact systems are very destructive the giant planet masses have a smaller impact on the stability of habitable worlds additionally a link between the presentday orbit of an observed giant exoplanet and the survival rate of habitable planets was established as a rule of thumb observed gas giants with eccentricities higher than 04 and inclinations higher than 20 degrees have experienced strong planetplanet scatterings and are unlikely to have a habitable planet in its system furthermore it was found that habitable planets surrounding a k or mstar have a higher survival rate than those surrounding a gstar
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1,802.05737
JU_KS@SAIL_CodeMixed-2017: Sentiment Analysis for Indian Code Mixed Social Media Texts
This paper reports about our work in the NLP Tool Contest @ICON-2017, shared task on Sentiment Analysis for Indian Languages (SAIL) (code mixed). To implement our system, we have used a machine learning algo-rithm called Multinomial Na\"ive Bayes trained using n-gram and SentiWordnet features. We have also used a small SentiWordnet for English and a small SentiWordnet for Bengali. But we have not used any SentiWordnet for Hindi language. We have tested our system on Hindi-English and Bengali-English code mixed social media data sets released for the contest. The performance of our system is very close to the best system participated in the contest. For both Bengali-English and Hindi-English runs, our system was ranked at the 3rd position out of all submitted runs and awarded the 3rd prize in the contest.
cs.CL
this paper reports about our work in the nlp tool contest icon2017 shared task on sentiment analysis for indian languages sail code mixed to implement our system we have used a machine learning algorithm called multinomial naive bayes trained using ngram and sentiwordnet features we have also used a small sentiwordnet for english and a small sentiwordnet for bengali but we have not used any sentiwordnet for hindi language we have tested our system on hindienglish and bengalienglish code mixed social media data sets released for the contest the performance of our system is very close to the best system participated in the contest for both bengalienglish and hindienglish runs our system was ranked at the 3rd position out of all submitted runs and awarded the 3rd prize in the contest
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1,802.05738
The spin of the second-born black hole in coalescing binary black holes
Various binary black hole formation channels have been proposed since the first gravitational event GW150914 was discovered by the Advanced Laser Interferometer Gravitational-Wave Observatory (AdLIGO). For all evolutionary channels based on the evolution of isolated binaries, the immediate progenitor of the binary black hole is a close binary system composed of a black hole and a helium star. We perform detailed binary evolution and systematically explore the parameter space of initial binary properties, including initial black hole and helium star masses, initial rotation of the helium star as well as metallicity. We argue that the spin of the first-born black hole at its birth is negligible ($\lesssim 0.1$), hence the second-born black hole's spin dominates the measured effective spin, $\chi_{\rm eff}$, from gravitational wave events of double black hole mergers. We find that tides can be important only when orbital periods are shorter than 2 days. Upon core collapse, the helium star produces a black hole (the second-born black hole in the system) with a spin that can span the entire range from zero to maximally spinning. We show that the bimodal distribution of the spin of the second-born black hole obtained in recent papers is mainly due to oversimplifying assumptions. We find an anti-correlation between the merging timescale of the two black holes, T$_{\rm merger}$, and the effective spin $\chi_{\rm eff}$. Finally, we provide new prescriptions for the tidal coefficient E$_2$ for both H-rich and the helium-rich stars. We predict that, with future improvements to AdLIGO's sensitivity, the sample of merging binary black hole systems will show an overdensity of sources with positive but small $\chi_{\rm eff}$. originating from lower mass black hole mergers born at low redshift.
astro-ph.SR hep-ph
various binary black hole formation channels have been proposed since the first gravitational event gw150914 was discovered by the advanced laser interferometer gravitationalwave observatory adligo for all evolutionary channels based on the evolution of isolated binaries the immediate progenitor of the binary black hole is a close binary system composed of a black hole and a helium star we perform detailed binary evolution and systematically explore the parameter space of initial binary properties including initial black hole and helium star masses initial rotation of the helium star as well as metallicity we argue that the spin of the firstborn black hole at its birth is negligible lesssim 01 hence the secondborn black holes spin dominates the measured effective spin chi_rm eff from gravitational wave events of double black hole mergers we find that tides can be important only when orbital periods are shorter than 2 days upon core collapse the helium star produces a black hole the secondborn black hole in the system with a spin that can span the entire range from zero to maximally spinning we show that the bimodal distribution of the spin of the secondborn black hole obtained in recent papers is mainly due to oversimplifying assumptions we find an anticorrelation between the merging timescale of the two black holes t_rm merger and the effective spin chi_rm eff finally we provide new prescriptions for the tidal coefficient e_2 for both hrich and the heliumrich stars we predict that with future improvements to adligos sensitivity the sample of merging binary black hole systems will show an overdensity of sources with positive but small chi_rm eff originating from lower mass black hole mergers born at low redshift
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1,802.05739
A Viscoelastic Catastrophe
We use a differential constitutive equation to model the flow of a viscoelastic flow in a cross-slot geometry, which is known to exhibit bistability above a critical flow rate. The novelty lies in two asymmetric modifications to the geometry, which causes a change in the bifurcation diagram such that one of the stable solutions becomes disconnected from the solution at low flow speeds. First we show that it is possible to mirror one of the modifications such that the system can be forced to the disconnected solution. Then we show that a slow decrease of the flow rate, can cause the system to go through a drastic change on a short time scale, also known as a catastrophe. The short time scale could lead to a precise and simple experimental measurement of the flow conditions at which the viscoelastic catastrophe occurs. Since the phenomena is intrinsically related to the extensional rheology of the fluid, we propose to exploit the phenomena for in-line extensional rheometry.
physics.flu-dyn cond-mat.soft cs.CE
we use a differential constitutive equation to model the flow of a viscoelastic flow in a crossslot geometry which is known to exhibit bistability above a critical flow rate the novelty lies in two asymmetric modifications to the geometry which causes a change in the bifurcation diagram such that one of the stable solutions becomes disconnected from the solution at low flow speeds first we show that it is possible to mirror one of the modifications such that the system can be forced to the disconnected solution then we show that a slow decrease of the flow rate can cause the system to go through a drastic change on a short time scale also known as a catastrophe the short time scale could lead to a precise and simple experimental measurement of the flow conditions at which the viscoelastic catastrophe occurs since the phenomena is intrinsically related to the extensional rheology of the fluid we propose to exploit the phenomena for inline extensional rheometry
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1,802.0574
Domain size polydispersity effects on the structural and dynamical properties in lipid monolayers with phase coexistence
Lipid monolayers with phase coexistence are a frequently used model for lipid membranes. In these systems, domains of the liquid-condensed phase always present size polydispersity. However, very few theoretical works consider size distribution effects on the monolayer properties. Because of the difference in surface densities, domains have excess dipolar density with respect to the surrounding liquid expanded phase, originating a dipolar inter-domain interaction. This interaction depends on the domain area, and hence the presence of a domain size distribution is associated with interaction polydispersity. Inter-domain interactions are fundamental to understanding the structure and dynamics of the monolayer. For this reason, it is expected that polydispersity significantly alters monolayer properties. By means of Brownian dynamics simulations, we study the radial distribution function (RDF), the average mean square displacement and the average time-dependent self-diffusion coefficient, D(t), of lipid monolayers with normal distributed size domains. It was found that polydispersity strongly affects the value of the interaction strength obtained, which is greatly underestimated if polydispersity is not considered. However, within a certain range of parameters, the RDF obtained from a polydisperse model can be well approximated by that of a monodisperse model, suitably fitting the interaction strength, even for 40% polydispersities. For small interaction strengths or small polydispersities, the polydisperse systems obtained from fitting the experimental RDF have an average mean square displacement and D(t) in good agreement with that of the monodisperse system.
physics.bio-ph cond-mat.soft
lipid monolayers with phase coexistence are a frequently used model for lipid membranes in these systems domains of the liquidcondensed phase always present size polydispersity however very few theoretical works consider size distribution effects on the monolayer properties because of the difference in surface densities domains have excess dipolar density with respect to the surrounding liquid expanded phase originating a dipolar interdomain interaction this interaction depends on the domain area and hence the presence of a domain size distribution is associated with interaction polydispersity interdomain interactions are fundamental to understanding the structure and dynamics of the monolayer for this reason it is expected that polydispersity significantly alters monolayer properties by means of brownian dynamics simulations we study the radial distribution function rdf the average mean square displacement and the average timedependent selfdiffusion coefficient dt of lipid monolayers with normal distributed size domains it was found that polydispersity strongly affects the value of the interaction strength obtained which is greatly underestimated if polydispersity is not considered however within a certain range of parameters the rdf obtained from a polydisperse model can be well approximated by that of a monodisperse model suitably fitting the interaction strength even for 40 polydispersities for small interaction strengths or small polydispersities the polydisperse systems obtained from fitting the experimental rdf have an average mean square displacement and dt in good agreement with that of the monodisperse system
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1,802.05741
Implementation of an efficient linear-optical quantum router
In this paper, we report on experimental implementation of a linear-optical quantum router. Our device allows single-photon polarization-encoded qubits to be routed coherently into two spatial output modes depending on the state of two identical control qubits. The polarization qubit state of the routed photon is maintained during the routing operation. The success probability of our scheme can be increased up to 25% making it the most efficient linear-optical quantum router known to this date.
quant-ph
in this paper we report on experimental implementation of a linearoptical quantum router our device allows singlephoton polarizationencoded qubits to be routed coherently into two spatial output modes depending on the state of two identical control qubits the polarization qubit state of the routed photon is maintained during the routing operation the success probability of our scheme can be increased up to 25 making it the most efficient linearoptical quantum router known to this date
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1,802.05742
Subaru High-z Exploration of Low-Luminosity Quasars (SHELLQs) III. Star formation properties of the host galaxies at $z \gtrsim 6$ studied with ALMA
We present our ALMA Cycle 4 measurements of the [CII] emission line and the underlying far-infrared (FIR) continuum emission from four optically low-luminosity ($M_{\rm 1450} > -25$) quasars at $z \gtrsim 6$ discovered by the Subaru Hyper Suprime Cam (HSC) survey. The [CII] line and FIR continuum luminosities lie in the ranges $L_{\rm [CII]} = (3.8-10.2) \times 10^8~L_\odot$ and $L_{\rm FIR} = (1.2-2.0) \times 10^{11}~L_\odot$, which are at least one order of magnitude smaller than those of optically-luminous quasars at $z \gtrsim 6$. We estimate the star formation rates (SFR) of our targets as $\simeq 23-40~M_\odot ~{\rm yr}^{-1}$. Their line and continuum-emitting regions are marginally resolved, and found to be comparable in size to those of optically luminous quasars, indicating that their SFR or likely gas mass surface densities (key controlling parameter of mass accretion) are accordingly different. The $L_{\rm [CII]}/L_{\rm FIR}$ ratios of the hosts, $\simeq (2.2-8.7) \times 10^{-3}$, are fully consistent with local star-forming galaxies. Using the [CII] dynamics, we derived their dynamical masses within a radius of 1.5-2.5 kpc as $\simeq (1.4-8.2) \times 10^{10}~M_\odot$. By interpreting these masses as stellar ones, we suggest that these faint quasar hosts are on or even below the star-forming main sequence at $z \sim 6$, i.e., they appear to be transforming into quiescent galaxies. This is in contrast to the optically luminous quasars at those redshifts, which show starburst-like properties. Finally, we find that the ratios of black hole mass to host galaxy dynamical mass of the most of low-luminosity quasars including the HSC ones are consistent with the local value. The mass ratios of the HSC quasars can be reproduced by a semi-analytical model that assumes merger-induced black hole-host galaxy evolution.
astro-ph.GA
we present our alma cycle 4 measurements of the cii emission line and the underlying farinfrared fir continuum emission from four optically lowluminosity m_rm 1450 25 quasars at z gtrsim 6 discovered by the subaru hyper suprime cam hsc survey the cii line and fir continuum luminosities lie in the ranges l_rm cii 38102 times 108l_odot and l_rm fir 1220 times 1011l_odot which are at least one order of magnitude smaller than those of opticallyluminous quasars at z gtrsim 6 we estimate the star formation rates sfr of our targets as simeq 2340m_odot rm yr1 their line and continuumemitting regions are marginally resolved and found to be comparable in size to those of optically luminous quasars indicating that their sfr or likely gas mass surface densities key controlling parameter of mass accretion are accordingly different the l_rm ciil_rm fir ratios of the hosts simeq 2287 times 103 are fully consistent with local starforming galaxies using the cii dynamics we derived their dynamical masses within a radius of 1525 kpc as simeq 1482 times 1010m_odot by interpreting these masses as stellar ones we suggest that these faint quasar hosts are on or even below the starforming main sequence at z sim 6 ie they appear to be transforming into quiescent galaxies this is in contrast to the optically luminous quasars at those redshifts which show starburstlike properties finally we find that the ratios of black hole mass to host galaxy dynamical mass of the most of lowluminosity quasars including the hsc ones are consistent with the local value the mass ratios of the hsc quasars can be reproduced by a semianalytical model that assumes mergerinduced black holehost galaxy evolution
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1,802.05743
A Multilevel Monte Carlo Ensemble Scheme for Solving Random Parabolic PDEs
A first-order, Monte Carlo ensemble method has been recently introduced for solving parabolic equations with random coefficients in [26], which is a natural synthesis of the ensemble-based, Monte Carlo sampling algorithm and the ensemble-based, first-order time stepping scheme. With the introduction of an ensemble average of the diffusion function, this algorithm leads to a single discrete system with multiple right-hand sides for a group of realizations, which could be solved more efficiently than a sequence of linear systems. In this paper, we pursue in the same direction and develop a new multilevel Monte Carlo ensemble method for solving random parabolic partial differential equations. Comparing with the approach in [26], this method possesses a high-order accuracy in time and further reduces the computational cost by using the multilevel Monte Carlo method. Rigorous numerical analysis shows the method achieves the optimal rate of convergence. Several numerical experiments are presented to illustrate the theoretical results.
math.NA
a firstorder monte carlo ensemble method has been recently introduced for solving parabolic equations with random coefficients in 26 which is a natural synthesis of the ensemblebased monte carlo sampling algorithm and the ensemblebased firstorder time stepping scheme with the introduction of an ensemble average of the diffusion function this algorithm leads to a single discrete system with multiple righthand sides for a group of realizations which could be solved more efficiently than a sequence of linear systems in this paper we pursue in the same direction and develop a new multilevel monte carlo ensemble method for solving random parabolic partial differential equations comparing with the approach in 26 this method possesses a highorder accuracy in time and further reduces the computational cost by using the multilevel monte carlo method rigorous numerical analysis shows the method achieves the optimal rate of convergence several numerical experiments are presented to illustrate the theoretical results
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1,802.05744
Material Scaling and Frequency-Selective Enhancement of Near-Field Radiative Heat Transfer for Lossy Metals in Two Dimensions via Inverse Design
The super-Planckian features of radiative heat transfer in the near-field are known to depend strongly on both material and geometric design properties. However, the relative importance and interplay of these two facets, and the degree to which they can be used to ultimately control energy flow, remains an open question. Recently derived bounds suggest that enhancements as large as $|\chi|^4 \lambda^{2} / \left(\left(4\pi\right)^{2} \Im\left[\chi\right]^{2} d^{2}\right)$ are possible between extended structures (compared to blackbody); but neither geometries reaching this bound, nor designs revealing the predicted material ($\chi$) scaling, have been previously reported. Here, exploiting inverse techniques, in combination with fast computational approaches enabled by the low-rank properties of elliptic operators for disjoint bodies, we investigate this relation between material and geometry on an enlarged space structures. Crucially, we find that the material proportionality given above does indeed emerge in realistic structures. In reaching this result, we also show that (in two dimensions) lossy metals such as tungsten, typically considered to be poor candidate materials for strongly enhancing heat transfer in the near infrared, can be structured to selectively realize flux rates that come within $50\%$ of those exhibited by an ideal pair of resonant lossless metals for separations as small as $2\%$ of a tunable design wavelength.
physics.optics
the superplanckian features of radiative heat transfer in the nearfield are known to depend strongly on both material and geometric design properties however the relative importance and interplay of these two facets and the degree to which they can be used to ultimately control energy flow remains an open question recently derived bounds suggest that enhancements as large as chi4 lambda2 leftleft4piright2 imleftchiright2 d2right are possible between extended structures compared to blackbody but neither geometries reaching this bound nor designs revealing the predicted material chi scaling have been previously reported here exploiting inverse techniques in combination with fast computational approaches enabled by the lowrank properties of elliptic operators for disjoint bodies we investigate this relation between material and geometry on an enlarged space structures crucially we find that the material proportionality given above does indeed emerge in realistic structures in reaching this result we also show that in two dimensions lossy metals such as tungsten typically considered to be poor candidate materials for strongly enhancing heat transfer in the near infrared can be structured to selectively realize flux rates that come within 50 of those exhibited by an ideal pair of resonant lossless metals for separations as small as 2 of a tunable design wavelength
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1,802.05745
Model reduction in chemical dynamics: slow invariant manifolds, singular perturbations, thermodynamic estimates, and analysis of reaction graph
The paper has two goals: It presents basic ideas, notions, and methods for reduction of reaction kinetics models: quasi-steady-state, quasi-equilibrium, slow invariant manifolds, and limiting steps. It describes briefly the current state of the art and some latest achievements in the broad area of model reduction in chemical and biochemical kinetics, including new results in methods of invariant manifolds, computation singular perturbation, bottleneck methods, asymptotology, tropical equilibration, and reaction mechanism skeletonisation.
physics.chem-ph
the paper has two goals it presents basic ideas notions and methods for reduction of reaction kinetics models quasisteadystate quasiequilibrium slow invariant manifolds and limiting steps it describes briefly the current state of the art and some latest achievements in the broad area of model reduction in chemical and biochemical kinetics including new results in methods of invariant manifolds computation singular perturbation bottleneck methods asymptotology tropical equilibration and reaction mechanism skeletonisation
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1,802.05746
Uniform boundedness in function spaces
We investigate several boundedness properties of function spaces considered as uniform spaces.
math.GN
we investigate several boundedness properties of function spaces considered as uniform spaces
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1,802.05747
Systematic Weight Pruning of DNNs using Alternating Direction Method of Multipliers
We present a systematic weight pruning framework of deep neural networks (DNNs) using the alternating direction method of multipliers (ADMM). We first formulate the weight pruning problem of DNNs as a constrained nonconvex optimization problem, and then adopt the ADMM framework for systematic weight pruning. We show that ADMM is highly suitable for weight pruning due to the computational efficiency it offers. We achieve a much higher compression ratio compared with prior work while maintaining the same test accuracy, together with a faster convergence rate. Our models are released at https://github.com/KaiqiZhang/admm-pruning
cs.LG cs.CV
we present a systematic weight pruning framework of deep neural networks dnns using the alternating direction method of multipliers admm we first formulate the weight pruning problem of dnns as a constrained nonconvex optimization problem and then adopt the admm framework for systematic weight pruning we show that admm is highly suitable for weight pruning due to the computational efficiency it offers we achieve a much higher compression ratio compared with prior work while maintaining the same test accuracy together with a faster convergence rate our models are released at httpsgithubcomkaiqizhangadmmpruning
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1,802.05748
Effects of Sound Suppressors on Muzzle Velocity, Bullet Yaw, and Drag
Little has been published regarding whether and how sound suppressors impact bullet flight, including velocity, bullet yaw, and drag. These parameters were compared for four different bullets fired from a .300 Winchester Magnum under four different muzzle conditions (no device and three different suppressors). While effects were not observed in all cases, results indicate that sound suppressors can have the effect of reducing bullet yaw and drag significantly, and can also have small effects on muzzle velocity. Results further suggest that bullets with a propensity to yaw demonstrate significant reductions in yaw and drag when shot through a two stage symmetric suppressor versus unsuppressed or with a conventional mouse-hole/K-baffle design.
physics.pop-ph
little has been published regarding whether and how sound suppressors impact bullet flight including velocity bullet yaw and drag these parameters were compared for four different bullets fired from a 300 winchester magnum under four different muzzle conditions no device and three different suppressors while effects were not observed in all cases results indicate that sound suppressors can have the effect of reducing bullet yaw and drag significantly and can also have small effects on muzzle velocity results further suggest that bullets with a propensity to yaw demonstrate significant reductions in yaw and drag when shot through a two stage symmetric suppressor versus unsuppressed or with a conventional mouseholekbaffle design
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1,802.05749
MHD stability of large scale liquid metal batteries
The aim of this paper is to develop a stability theory and a numerical model for the three density-stratified electrically conductive liquid layers. Using regular perturbation methods to reduce the full 3d problem to the shallow layer model, the coupled wave and electric current equations are derived. The problem set-up allows the weakly non-linear velocity field action and an arbitrary vertical magnetic field. Further linearisation of the coupled equations is used for the linear stability analysis in the case of uniform vertical magnetic field. New analytical stability criteria accounting for the viscous damping are derived for particular cases of practical interest and compared to the numerical solutions for variety of materials used in the batteries. The new criteria are equally applicable to the aluminium electrolysis cell MHD stability estimates.
physics.flu-dyn
the aim of this paper is to develop a stability theory and a numerical model for the three densitystratified electrically conductive liquid layers using regular perturbation methods to reduce the full 3d problem to the shallow layer model the coupled wave and electric current equations are derived the problem setup allows the weakly nonlinear velocity field action and an arbitrary vertical magnetic field further linearisation of the coupled equations is used for the linear stability analysis in the case of uniform vertical magnetic field new analytical stability criteria accounting for the viscous damping are derived for particular cases of practical interest and compared to the numerical solutions for variety of materials used in the batteries the new criteria are equally applicable to the aluminium electrolysis cell mhd stability estimates
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1,802.0575
Special subsets of the generalized Cantor space $2^\kappa$ and generalized Baire space $\kappa^\kappa$
In this paper, we are interested in parallels to the classical notions of special subsets in $\R$ defined in the generalized Cantor and Baire spaces ($2^\kappa$ and $\kappa^\kappa$). We consider generalizations of the well-known classes of special subsets, like Lusin sets, strongly null sets, concentrated sets, perfectly meagre sets, $\sigma$-sets, $\gamma$-sets, sets with Menger, Rothberger or Hurewicz property, but also of some less-know classes like $X$-small sets, meagre additive sets, Ramsey null sets, Marczewski, Silver, Miller and Laver-null sets. We notice that many classical theorems regarding these classes can be relatively easy generalized to higher cardinals although sometimes with some additional assumptions. This paper serves as a catalogue of such results along with some other generalizations and open problems.
math.LO
in this paper we are interested in parallels to the classical notions of special subsets in r defined in the generalized cantor and baire spaces 2kappa and kappakappa we consider generalizations of the wellknown classes of special subsets like lusin sets strongly null sets concentrated sets perfectly meagre sets sigmasets gammasets sets with menger rothberger or hurewicz property but also of some lessknow classes like xsmall sets meagre additive sets ramsey null sets marczewski silver miller and lavernull sets we notice that many classical theorems regarding these classes can be relatively easy generalized to higher cardinals although sometimes with some additional assumptions this paper serves as a catalogue of such results along with some other generalizations and open problems
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1,802.05751
Image Transformer
Image generation has been successfully cast as an autoregressive sequence generation or transformation problem. Recent work has shown that self-attention is an effective way of modeling textual sequences. In this work, we generalize a recently proposed model architecture based on self-attention, the Transformer, to a sequence modeling formulation of image generation with a tractable likelihood. By restricting the self-attention mechanism to attend to local neighborhoods we significantly increase the size of images the model can process in practice, despite maintaining significantly larger receptive fields per layer than typical convolutional neural networks. While conceptually simple, our generative models significantly outperform the current state of the art in image generation on ImageNet, improving the best published negative log-likelihood on ImageNet from 3.83 to 3.77. We also present results on image super-resolution with a large magnification ratio, applying an encoder-decoder configuration of our architecture. In a human evaluation study, we find that images generated by our super-resolution model fool human observers three times more often than the previous state of the art.
cs.CV
image generation has been successfully cast as an autoregressive sequence generation or transformation problem recent work has shown that selfattention is an effective way of modeling textual sequences in this work we generalize a recently proposed model architecture based on selfattention the transformer to a sequence modeling formulation of image generation with a tractable likelihood by restricting the selfattention mechanism to attend to local neighborhoods we significantly increase the size of images the model can process in practice despite maintaining significantly larger receptive fields per layer than typical convolutional neural networks while conceptually simple our generative models significantly outperform the current state of the art in image generation on imagenet improving the best published negative loglikelihood on imagenet from 383 to 377 we also present results on image superresolution with a large magnification ratio applying an encoderdecoder configuration of our architecture in a human evaluation study we find that images generated by our superresolution model fool human observers three times more often than the previous state of the art
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1,802.05752
Field-induced Ferrohastatic Order in Cubic Non-Kramers Doublet Systems
Cubic Pr-based compounds with $\Gamma_3$ non-Kramers doublet ground states can realize a novel heavy Fermi liquid with spinorial hybridization ('hastatic' order) that breaks time reversal symmetry. Several Pr-"1-2-20" materials exhibit a suggestive heavy Fermi liquid stabilized in intermediate magnetic fields; these provide key insight into the quadrupolar Kondo lattice. We develop a simple, yet realistic microscopic model of ferrohastatic order, and elaborate its experimental signatures and behavior in field, where it is a good candidate to explain the observed heavy Fermi liquids at intermediate fields in Pr(Ir,Rh)$_2$Zn$_{20}$. In addition, we develop the Landau theory of ferrohastatic order, which allows us to understand its behavior close to the transition and explore thermodynamic signatures from magnetic susceptibility to thermal expansion.
cond-mat.str-el
cubic prbased compounds with gamma_3 nonkramers doublet ground states can realize a novel heavy fermi liquid with spinorial hybridization hastatic order that breaks time reversal symmetry several pr1220 materials exhibit a suggestive heavy fermi liquid stabilized in intermediate magnetic fields these provide key insight into the quadrupolar kondo lattice we develop a simple yet realistic microscopic model of ferrohastatic order and elaborate its experimental signatures and behavior in field where it is a good candidate to explain the observed heavy fermi liquids at intermediate fields in prirrh_2zn_20 in addition we develop the landau theory of ferrohastatic order which allows us to understand its behavior close to the transition and explore thermodynamic signatures from magnetic susceptibility to thermal expansion
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1,802.05753
Bayesian variable selection in linear dynamical systems
We develop a method for reconstructing regulatory interconnection networks between variables evolving according to a linear dynamical system. The work is motivated by the problem of gene regulatory network inference, that is, finding causal effects between genes from gene expression time series data. In biological applications, the typical problem is that the sampling frequency is low, and consequentially the system identification problem is ill-posed. The low sampling frequency also makes it impossible to estimate derivatives directly from the data. We take a Bayesian approach to the problem, as it offers a natural way to incorporate prior information to deal with the ill-posedness, through the introduction of sparsity promoting prior for the underlying dynamics matrix. It also provides a framework for modelling both the process and measurement noises. We develop Markov Chain Monte Carlo samplers for the discrete-valued zero-structure of the dynamics matrix, and for the continuous-time trajectory of the system.
stat.ME math.OC q-bio.QM
we develop a method for reconstructing regulatory interconnection networks between variables evolving according to a linear dynamical system the work is motivated by the problem of gene regulatory network inference that is finding causal effects between genes from gene expression time series data in biological applications the typical problem is that the sampling frequency is low and consequentially the system identification problem is illposed the low sampling frequency also makes it impossible to estimate derivatives directly from the data we take a bayesian approach to the problem as it offers a natural way to incorporate prior information to deal with the illposedness through the introduction of sparsity promoting prior for the underlying dynamics matrix it also provides a framework for modelling both the process and measurement noises we develop markov chain monte carlo samplers for the discretevalued zerostructure of the dynamics matrix and for the continuoustime trajectory of the system
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1,802.05754
Extended Mean Field Control Problems: stochastic maximum principle and transport perspective
We study Mean Field stochastic control problems where the cost function and the state dynamics depend upon the joint distribution of the controlled state and the control process. We prove suitable versions of the Pontryagin stochastic maximum principle, both in necessary and in sufficient form, which extend the known conditions to this general framework. Furthermore, we suggest a variational approach to study a weak formulation of these control problems. We show a natural connection between this weak formulation and optimal transport on path space, which inspires a novel discretization scheme.
math.OC math.PR
we study mean field stochastic control problems where the cost function and the state dynamics depend upon the joint distribution of the controlled state and the control process we prove suitable versions of the pontryagin stochastic maximum principle both in necessary and in sufficient form which extend the known conditions to this general framework furthermore we suggest a variational approach to study a weak formulation of these control problems we show a natural connection between this weak formulation and optimal transport on path space which inspires a novel discretization scheme
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1,802.05755
Development of Highly Efficient Multi-invariable Wireless Sensor System Design for Energy Harvesting
Capillary wireless sensor networks devoted to air quality monitoring have provided vital information on dangerous air conditions. In adopting the environmentally generated energy as the fundamental energy source the main challenge is the implementation of capillary networks rather than replacing the batteries on a set period of times that leads to functional dilemma of devices management and high costs. In this paper we present a battery-less, self-governing, multi-parametric sensing platform for air quality monitoring that harvests environment energy for long run. Furthermore study on sensor section with their results have also been described in the paper. A customized process of calibration to check the sensors' sensitivity and a basic portfolio of variant energy sources over the power recovery section could productively improve air quality standards tracing in indoor and outdoor application, in a kind of 'set and forget' scenario.
eess.SP cs.CY cs.NI
capillary wireless sensor networks devoted to air quality monitoring have provided vital information on dangerous air conditions in adopting the environmentally generated energy as the fundamental energy source the main challenge is the implementation of capillary networks rather than replacing the batteries on a set period of times that leads to functional dilemma of devices management and high costs in this paper we present a batteryless selfgoverning multiparametric sensing platform for air quality monitoring that harvests environment energy for long run furthermore study on sensor section with their results have also been described in the paper a customized process of calibration to check the sensors sensitivity and a basic portfolio of variant energy sources over the power recovery section could productively improve air quality standards tracing in indoor and outdoor application in a kind of set and forget scenario
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1,802.05756
Inferring relevant features: from QFT to PCA
In many-body physics, renormalization techniques are used to extract aspects of a statistical or quantum state that are relevant at large scale, or for low energy experiments. Recent works have proposed that these features can be formally identified as those perturbations of the states whose distinguishability most resist coarse-graining. Here, we examine whether this same strategy can be used to identify important features of an unlabeled dataset. This approach indeed results in a technique very similar to kernel PCA (principal component analysis), but with a kernel function that is automatically adapted to the data, or "learned". We test this approach on handwritten digits, and find that the most relevant features are significantly better for classification than those obtained from a simple gaussian kernel.
cs.LG quant-ph stat.ML
in manybody physics renormalization techniques are used to extract aspects of a statistical or quantum state that are relevant at large scale or for low energy experiments recent works have proposed that these features can be formally identified as those perturbations of the states whose distinguishability most resist coarsegraining here we examine whether this same strategy can be used to identify important features of an unlabeled dataset this approach indeed results in a technique very similar to kernel pca principal component analysis but with a kernel function that is automatically adapted to the data or learned we test this approach on handwritten digits and find that the most relevant features are significantly better for classification than those obtained from a simple gaussian kernel
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1,802.05757
Stochastic Wasserstein Barycenters
We present a stochastic algorithm to compute the barycenter of a set of probability distributions under the Wasserstein metric from optimal transport. Unlike previous approaches, our method extends to continuous input distributions and allows the support of the barycenter to be adjusted in each iteration. We tackle the problem without regularization, allowing us to recover a sharp output whose support is contained within the support of the true barycenter. We give examples where our algorithm recovers a more meaningful barycenter than previous work. Our method is versatile and can be extended to applications such as generating super samples from a given distribution and recovering blue noise approximations.
cs.LG math.OC stat.ML
we present a stochastic algorithm to compute the barycenter of a set of probability distributions under the wasserstein metric from optimal transport unlike previous approaches our method extends to continuous input distributions and allows the support of the barycenter to be adjusted in each iteration we tackle the problem without regularization allowing us to recover a sharp output whose support is contained within the support of the true barycenter we give examples where our algorithm recovers a more meaningful barycenter than previous work our method is versatile and can be extended to applications such as generating super samples from a given distribution and recovering blue noise approximations
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1,802.05758
Cross-topic Argument Mining from Heterogeneous Sources Using Attention-based Neural Networks
Argument mining is a core technology for automating argument search in large document collections. Despite its usefulness for this task, most current approaches to argument mining are designed for use only with specific text types and fall short when applied to heterogeneous texts. In this paper, we propose a new sentential annotation scheme that is reliably applicable by crowd workers to arbitrary Web texts. We source annotations for over 25,000 instances covering eight controversial topics. The results of cross-topic experiments show that our attention-based neural network generalizes best to unseen topics and outperforms vanilla BiLSTM models by 6% in accuracy and 11% in F-score.
cs.CL
argument mining is a core technology for automating argument search in large document collections despite its usefulness for this task most current approaches to argument mining are designed for use only with specific text types and fall short when applied to heterogeneous texts in this paper we propose a new sentential annotation scheme that is reliably applicable by crowd workers to arbitrary web texts we source annotations for over 25000 instances covering eight controversial topics the results of crosstopic experiments show that our attentionbased neural network generalizes best to unseen topics and outperforms vanilla bilstm models by 6 in accuracy and 11 in fscore
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1,802.05759
A Krylov subspace method for the approximation of bivariate matrix functions
Bivariate matrix functions provide a unified framework for various tasks in numerical linear algebra, including the solution of linear matrix equations and the application of the Fr\'echet derivative. In this work, we propose a novel tensorized Krylov subspace method for approximating such bivariate matrix functions and analyze its convergence. While this method is already known for some instances, our analysis appears to result in new convergence estimates and insights for all but one instance, Sylvester matrix equations.
math.NA math.OA
bivariate matrix functions provide a unified framework for various tasks in numerical linear algebra including the solution of linear matrix equations and the application of the frechet derivative in this work we propose a novel tensorized krylov subspace method for approximating such bivariate matrix functions and analyze its convergence while this method is already known for some instances our analysis appears to result in new convergence estimates and insights for all but one instance sylvester matrix equations
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