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1,803.06567
A Dual Approach to Scalable Verification of Deep Networks
This paper addresses the problem of formally verifying desirable properties of neural networks, i.e., obtaining provable guarantees that neural networks satisfy specifications relating their inputs and outputs (robustness to bounded norm adversarial perturbations, for example). Most previous work on this topic was limited in its applicability by the size of the network, network architecture and the complexity of properties to be verified. In contrast, our framework applies to a general class of activation functions and specifications on neural network inputs and outputs. We formulate verification as an optimization problem (seeking to find the largest violation of the specification) and solve a Lagrangian relaxation of the optimization problem to obtain an upper bound on the worst case violation of the specification being verified. Our approach is anytime i.e. it can be stopped at any time and a valid bound on the maximum violation can be obtained. We develop specialized verification algorithms with provable tightness guarantees under special assumptions and demonstrate the practical significance of our general verification approach on a variety of verification tasks.
cs.LG stat.ML
this paper addresses the problem of formally verifying desirable properties of neural networks ie obtaining provable guarantees that neural networks satisfy specifications relating their inputs and outputs robustness to bounded norm adversarial perturbations for example most previous work on this topic was limited in its applicability by the size of the network network architecture and the complexity of properties to be verified in contrast our framework applies to a general class of activation functions and specifications on neural network inputs and outputs we formulate verification as an optimization problem seeking to find the largest violation of the specification and solve a lagrangian relaxation of the optimization problem to obtain an upper bound on the worst case violation of the specification being verified our approach is anytime ie it can be stopped at any time and a valid bound on the maximum violation can be obtained we develop specialized verification algorithms with provable tightness guarantees under special assumptions and demonstrate the practical significance of our general verification approach on a variety of verification tasks
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1,803.06568
Splittable and unsplittable graphs and configurations
We prove that there exist infinitely many splittable and also infinitely many unsplittable cyclic $(n_3)$ configurations. We also present a complete study of trivalent cyclic Haar graphs on at most 60 vertices with respect to splittability. Finally, we show that all cyclic flag-transitive configurations with the exception of the Fano plane and the M\"obius-Kantor configuration are splittable.
math.CO
we prove that there exist infinitely many splittable and also infinitely many unsplittable cyclic n_3 configurations we also present a complete study of trivalent cyclic haar graphs on at most 60 vertices with respect to splittability finally we show that all cyclic flagtransitive configurations with the exception of the fano plane and the mobiuskantor configuration are splittable
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1,803.06569
On-Demand Generation of Neutral and Negatively-Charged Silicon-Vacancy Centers in Diamond
Point defects in wide-bandgap semiconductors are emerging as versatile resources for nanoscale sensing and quantum information science but our understanding of the photo-ionization dynamics is presently incomplete. Here we use two-color confocal microscopy to investigate the dynamics of charge in Type 1b diamond hosting nitrogen-vacancy (NV) and silicon-vacancy (SiV) centers. By examining the non-local fluorescence patterns emerging from local laser excitation, we show that in the simultaneous presence of photo-generated electrons and holes, SiV (NV) centers selectively transform into the negative (neutral) charge state. Unlike NVs, 532 nm illumination ionizes SiV- via a single photon process thus hinting at a comparatively shallower ground state. In particular, slower ionization rates at longer wavelengths suggest the latter lies approximately ~1.9 eV below the conduction band minimum. Building on the above observations we demonstrate on-demand SiV and NV charge initialization over large areas via green laser illumination of variable intensity.
cond-mat.mes-hall
point defects in widebandgap semiconductors are emerging as versatile resources for nanoscale sensing and quantum information science but our understanding of the photoionization dynamics is presently incomplete here we use twocolor confocal microscopy to investigate the dynamics of charge in type 1b diamond hosting nitrogenvacancy nv and siliconvacancy siv centers by examining the nonlocal fluorescence patterns emerging from local laser excitation we show that in the simultaneous presence of photogenerated electrons and holes siv nv centers selectively transform into the negative neutral charge state unlike nvs 532 nm illumination ionizes siv via a single photon process thus hinting at a comparatively shallower ground state in particular slower ionization rates at longer wavelengths suggest the latter lies approximately 19 ev below the conduction band minimum building on the above observations we demonstrate ondemand siv and nv charge initialization over large areas via green laser illumination of variable intensity
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1,803.0657
Local Quantum Criticality of a One-Dimensional Kondo Insulator Model
The continuous quantum phase transition and the nature of quantum critical point (QCP) in a modified Kondo lattice model with Ising anisotropic exchange interactions is studied within the density-matrix renormalization group algorithm. We investigate the effect of quantum fluctuations on critical Kondo destruction QCP, by probing static and dynamic properties of the magnetic order and the Kondo effect. In particular, we identify that local Kondo physics itself becomes critical at the magnetic phase transition point, providing unbiased evidences for local quantum criticality between two insulators without resorting to the change of Fermi surface.
cond-mat.str-el
the continuous quantum phase transition and the nature of quantum critical point qcp in a modified kondo lattice model with ising anisotropic exchange interactions is studied within the densitymatrix renormalization group algorithm we investigate the effect of quantum fluctuations on critical kondo destruction qcp by probing static and dynamic properties of the magnetic order and the kondo effect in particular we identify that local kondo physics itself becomes critical at the magnetic phase transition point providing unbiased evidences for local quantum criticality between two insulators without resorting to the change of fermi surface
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1,803.06571
Orthogonal Representations for Output System Pairs
A new class of canonical forms is given proposed in which $(A, C)$ is in Hessenberg observer or Schur form and output normal: $\bf{I} - A^*A =C^*C$. Here, $C$ is the $d \times n$ measurement matrix and $A$ is the advance matrix. The $(C, A)$ stack is expressed as the product of $n$ orthogonal matrices, each of which depends on $d$ parameters. State updates require only ${\cal O}(nd)$ operations and derivatives of the system with respect to the parameters are fast and convenient to compute. Restrictions are given such that these models are generically identifiable. Since the observability Grammian is the identity matrix, system identification is better conditioned than other classes of models with fast updates.
stat.ME cs.SY eess.SY math.ST stat.TH
a new class of canonical forms is given proposed in which a c is in hessenberg observer or schur form and output normal bfi aa cc here c is the d times n measurement matrix and a is the advance matrix the c a stack is expressed as the product of n orthogonal matrices each of which depends on d parameters state updates require only cal ond operations and derivatives of the system with respect to the parameters are fast and convenient to compute restrictions are given such that these models are generically identifiable since the observability grammian is the identity matrix system identification is better conditioned than other classes of models with fast updates
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1,803.06572
Non-hyperbolic ergodic measures and horseshoes in partially hyperbolic homoclinic classes
We study a rich family of robustly non-hyperbolic transitive diffeomorphisms and we show that each ergodic measure is approached by hyperbolic sets in weak$*$-topology and in entropy. For hyperbolic ergodic measures, it is a classical result of A. Katok. The novelty here is to deal with non-hyperbolic ergodic measures.
math.DS
we study a rich family of robustly nonhyperbolic transitive diffeomorphisms and we show that each ergodic measure is approached by hyperbolic sets in weaktopology and in entropy for hyperbolic ergodic measures it is a classical result of a katok the novelty here is to deal with nonhyperbolic ergodic measures
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1,803.06573
On the Fenchel Duality between Strong Convexity and Lipschitz Continuous Gradient
We provide a simple proof for the Fenchel duality between strong convexity and Lipschitz continuous gradient. To this end, we first establish equivalent conditions of convexity for a general function that may not be differentiable. By utilizing these equivalent conditions, we can directly obtain equivalent conditions for strong convexity and Lipschitz continuous gradient. Based on these results, we can easily prove Fenchel duality. Beside this main result, we also identify several conditions that are implied by strong convexity or Lipschitz continuous gradient, but are not necessarily equivalent to them. This means that these conditions are more general than strong convexity or Lipschitz continuous gradient themselves.
math.OC
we provide a simple proof for the fenchel duality between strong convexity and lipschitz continuous gradient to this end we first establish equivalent conditions of convexity for a general function that may not be differentiable by utilizing these equivalent conditions we can directly obtain equivalent conditions for strong convexity and lipschitz continuous gradient based on these results we can easily prove fenchel duality beside this main result we also identify several conditions that are implied by strong convexity or lipschitz continuous gradient but are not necessarily equivalent to them this means that these conditions are more general than strong convexity or lipschitz continuous gradient themselves
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1,803.06574
Dynamical Localization in $\mathbb{Z}_2$ Lattice Gauge Theories
We study quantum quenches in two-dimensional lattice gauge theories with fermions coupled to dynamical $\mathbb{Z}_2$ gauge fields. Through the identification of an extensive set of conserved quantities, we propose a generic mechanism of charge localization in the absence of quenched disorder both in the Hamiltonian and in the initial states. We provide diagnostics of this localization through a set of experimentally relevant dynamical measures, entanglement measures, as well as spectral properties of the model. One of the defining features of the models that we study is a binary nature of emergent disorder, related to $\mathbb{Z}_2$ degrees of freedom. This results in a qualitatively different behaviour in the strong disorder limit compared to typically studied models of localization. For example it gives rise to a possibility of a delocalization transition via a mechanism of quantum percolation in dimensions higher than 1D. We highlight the importance of our general phenomenology to questions related to dynamics of defects in Kitaev's toric code, and to quantum quenches in Hubbard models. While the simplest models we consider are effectively non-interacting, we also include interactions leading to many-body localization-like logarithmic entanglement growth. Finally, we consider effects of interactions that generate dynamics for conserved charges, which gives rise to only transient localization behaviour, or quasi-many-body-localization.
cond-mat.str-el
we study quantum quenches in twodimensional lattice gauge theories with fermions coupled to dynamical mathbbz_2 gauge fields through the identification of an extensive set of conserved quantities we propose a generic mechanism of charge localization in the absence of quenched disorder both in the hamiltonian and in the initial states we provide diagnostics of this localization through a set of experimentally relevant dynamical measures entanglement measures as well as spectral properties of the model one of the defining features of the models that we study is a binary nature of emergent disorder related to mathbbz_2 degrees of freedom this results in a qualitatively different behaviour in the strong disorder limit compared to typically studied models of localization for example it gives rise to a possibility of a delocalization transition via a mechanism of quantum percolation in dimensions higher than 1d we highlight the importance of our general phenomenology to questions related to dynamics of defects in kitaevs toric code and to quantum quenches in hubbard models while the simplest models we consider are effectively noninteracting we also include interactions leading to manybody localizationlike logarithmic entanglement growth finally we consider effects of interactions that generate dynamics for conserved charges which gives rise to only transient localization behaviour or quasimanybodylocalization
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1,803.06575
Dynamics of a Lattice Gauge Theory with Fermionic Matter -- Minimal Quantum Simulator with Time-Dependent Impurities in Ultracold Gases
We propose a minimal model to study the real-time dynamics of a $\mathbb{Z}_2$ lattice gauge theory coupled to fermionic matter in a cold atom quantum simulator setup. We show that dynamical correlators of the gauge fields can be measured in experiments studying the time-evolution of two pairs of impurities, and suggest the protocol for implementing the model in cold atom experiments. Further, we discuss a number of unexpected features found in the integrable limit of the model, as well as its extensions to a non-integrable case. A potential experimental implementation of our model in the latter regime would allow one to simulate strongly-interacting lattice gauge theories beyond current capabilities of classical computers.
cond-mat.quant-gas cond-mat.str-el
we propose a minimal model to study the realtime dynamics of a mathbbz_2 lattice gauge theory coupled to fermionic matter in a cold atom quantum simulator setup we show that dynamical correlators of the gauge fields can be measured in experiments studying the timeevolution of two pairs of impurities and suggest the protocol for implementing the model in cold atom experiments further we discuss a number of unexpected features found in the integrable limit of the model as well as its extensions to a nonintegrable case a potential experimental implementation of our model in the latter regime would allow one to simulate stronglyinteracting lattice gauge theories beyond current capabilities of classical computers
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1,803.06576
Projection-Based Finite Elements for Nonlinear Function Spaces
We introduce a novel type of approximation spaces for functions with values in a nonlinear manifold. The discrete functions are constructed by piecewise polynomial interpolation in a Euclidean embedding space, and then projecting pointwise onto the manifold. We show optimal interpolation error bounds with respect to Lebesgue and Sobolev norms. Additionally, we show similar bounds for the test functions, i.e., variations of discrete functions. Combining these results with a nonlinear C\'ea lemma, we prove optimal $L^2$ and $H^1$ discretization error bounds for harmonic maps from a planar domain into a smooth manifold. All these error bounds are also verified numerically.
math.NA
we introduce a novel type of approximation spaces for functions with values in a nonlinear manifold the discrete functions are constructed by piecewise polynomial interpolation in a euclidean embedding space and then projecting pointwise onto the manifold we show optimal interpolation error bounds with respect to lebesgue and sobolev norms additionally we show similar bounds for the test functions ie variations of discrete functions combining these results with a nonlinear cea lemma we prove optimal l2 and h1 discretization error bounds for harmonic maps from a planar domain into a smooth manifold all these error bounds are also verified numerically
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1,803.06577
Multi-user Multi-task Offloading and Resource Allocation in Mobile Cloud Systems
We consider a general multi-user Mobile Cloud Computing (MCC) system where each mobile user has multiple independent tasks. These mobile users share the computation and communication resources while offloading tasks to the cloud. We study both the conventional MCC where tasks are offloaded to the cloud through a wireless access point, and MCC with a computing access point (CAP), where the CAP serves both as the network access gateway and a computation service provider to the mobile users. We aim to jointly optimize the offloading decisions of all users as well as the allocation of computation and communication resources, to minimize the overall cost of energy, computation, and delay for all users. The optimization problem is formulated as a non-convex quadratically constrained quadratic program, which is NP-hard in general. For the case without a CAP, an efficient approximate solution named MUMTO is proposed by using separable semidefinite relaxation (SDR), followed by recovery of the binary offloading decision and optimal allocation of the communication resource. To solve the more complicated problem with a CAP, we further propose an efficient three-step algorithm named MUMTO-C comprising of generalized MUMTO SDR with CAP, alternating optimization, and sequential tuning, which always computes a locally optimal solution. For performance benchmarking, we further present numerical lower bounds of the minimum system cost with and without the CAP. By comparison with this lower bound, our simulation results show that the proposed solutions for both scenarios give nearly optimal performance under various parameter settings, and the resultant efficient utilization of a CAP can bring substantial cost benefit.
cs.IT math.IT
we consider a general multiuser mobile cloud computing mcc system where each mobile user has multiple independent tasks these mobile users share the computation and communication resources while offloading tasks to the cloud we study both the conventional mcc where tasks are offloaded to the cloud through a wireless access point and mcc with a computing access point cap where the cap serves both as the network access gateway and a computation service provider to the mobile users we aim to jointly optimize the offloading decisions of all users as well as the allocation of computation and communication resources to minimize the overall cost of energy computation and delay for all users the optimization problem is formulated as a nonconvex quadratically constrained quadratic program which is nphard in general for the case without a cap an efficient approximate solution named mumto is proposed by using separable semidefinite relaxation sdr followed by recovery of the binary offloading decision and optimal allocation of the communication resource to solve the more complicated problem with a cap we further propose an efficient threestep algorithm named mumtoc comprising of generalized mumto sdr with cap alternating optimization and sequential tuning which always computes a locally optimal solution for performance benchmarking we further present numerical lower bounds of the minimum system cost with and without the cap by comparison with this lower bound our simulation results show that the proposed solutions for both scenarios give nearly optimal performance under various parameter settings and the resultant efficient utilization of a cap can bring substantial cost benefit
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1,803.06578
A two-stage estimation procedure for non-linear structural equation models
Applications of structural equation models (SEMs) are often restricted to linear associations between variables. Maximum likelihood (ML) estimation in non-linear models may be complex and require numerical integration. Furthermore, ML inference is sensitive to distributional assumptions. In this paper, we introduce a simple two-stage estimation technique for estimation of non-linear associations between latent variables. Here both steps are based on fitting linear SEMs: first a linear model is fitted to data on the latent predictor and terms describing the non-linear effect are predicted by their conditional means. In the second step, the predictions are included in a linear model for the latent outcome variable. We show that this procedure is consistent and identifies its asymptotic distribution. We also illustrate how this framework easily allows the association between latent variables to be modelled using restricted cubic splines and we develop a modified estimator which is robust to non-normality of the latent predictor. In a simulation study, we compare the proposed method to MLE and alternative two-stage estimation techniques.
stat.ME
applications of structural equation models sems are often restricted to linear associations between variables maximum likelihood ml estimation in nonlinear models may be complex and require numerical integration furthermore ml inference is sensitive to distributional assumptions in this paper we introduce a simple twostage estimation technique for estimation of nonlinear associations between latent variables here both steps are based on fitting linear sems first a linear model is fitted to data on the latent predictor and terms describing the nonlinear effect are predicted by their conditional means in the second step the predictions are included in a linear model for the latent outcome variable we show that this procedure is consistent and identifies its asymptotic distribution we also illustrate how this framework easily allows the association between latent variables to be modelled using restricted cubic splines and we develop a modified estimator which is robust to nonnormality of the latent predictor in a simulation study we compare the proposed method to mle and alternative twostage estimation techniques
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1,803.06579
A Multi-perspective Approach To Anomaly Detection For Self-aware Embodied Agents
This paper focuses on multi-sensor anomaly detection for moving cognitive agents using both external and private first-person visual observations. Both observation types are used to characterize agents' motion in a given environment. The proposed method generates locally uniform motion models by dividing a Gaussian process that approximates agents' displacements on the scene and provides a Shared Level (SL) self-awareness based on Environment Centered (EC) models. Such models are then used to train in a semi-unsupervised way a set of Generative Adversarial Networks (GANs) that produce an estimation of external and internal parameters of moving agents. Obtained results exemplify the feasibility of using multi-perspective data for predicting and analyzing trajectory information.
cs.CV
this paper focuses on multisensor anomaly detection for moving cognitive agents using both external and private firstperson visual observations both observation types are used to characterize agents motion in a given environment the proposed method generates locally uniform motion models by dividing a gaussian process that approximates agents displacements on the scene and provides a shared level sl selfawareness based on environment centered ec models such models are then used to train in a semiunsupervised way a set of generative adversarial networks gans that produce an estimation of external and internal parameters of moving agents obtained results exemplify the feasibility of using multiperspective data for predicting and analyzing trajectory information
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1,803.0658
Aging is a log-Poisson Process, not a Renewal Process
Aging is a ubiquitous relaxation dynamic in disordered materials. It ensues after a rapid quench from an equilibrium "fluid" state into a non-equilibrium, history-dependent jammed state. We propose a physically motivated description that contrasts sharply with a continuous-time random walk (CTRW) with broadly distributed trapping times commonly used to fit aging data. A renewal process like CTRW proves irreconcilable with the log-Poisson statistic exhibited, for example, by jammed colloids as well as by disordered magnets. A log-Poisson process is characteristic of the intermittent and decelerating dynamics of jammed matter usually activated by record-breaking fluctuations ("quakes"). We show that such a record dynamics (RD) provides a universal model for aging, physically grounded in generic features of free-energy landscapes of disordered systems.
cond-mat.soft cond-mat.dis-nn cond-mat.mtrl-sci
aging is a ubiquitous relaxation dynamic in disordered materials it ensues after a rapid quench from an equilibrium fluid state into a nonequilibrium historydependent jammed state we propose a physically motivated description that contrasts sharply with a continuoustime random walk ctrw with broadly distributed trapping times commonly used to fit aging data a renewal process like ctrw proves irreconcilable with the logpoisson statistic exhibited for example by jammed colloids as well as by disordered magnets a logpoisson process is characteristic of the intermittent and decelerating dynamics of jammed matter usually activated by recordbreaking fluctuations quakes we show that such a record dynamics rd provides a universal model for aging physically grounded in generic features of freeenergy landscapes of disordered systems
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1,803.06581
Variational Knowledge Graph Reasoning
Inferring missing links in knowledge graphs (KG) has attracted a lot of attention from the research community. In this paper, we tackle a practical query answering task involving predicting the relation of a given entity pair. We frame this prediction problem as an inference problem in a probabilistic graphical model and aim at resolving it from a variational inference perspective. In order to model the relation between the query entity pair, we assume that there exists an underlying latent variable (paths connecting two nodes) in the KG, which carries the equivalent semantics of their relations. However, due to the intractability of connections in large KGs, we propose to use variation inference to maximize the evidence lower bound. More specifically, our framework (\textsc{Diva}) is composed of three modules, i.e. a posterior approximator, a prior (path finder), and a likelihood (path reasoner). By using variational inference, we are able to incorporate them closely into a unified architecture and jointly optimize them to perform KG reasoning. With active interactions among these sub-modules, \textsc{Diva} is better at handling noise and coping with more complex reasoning scenarios. In order to evaluate our method, we conduct the experiment of the link prediction task on multiple datasets and achieve state-of-the-art performances on both datasets.
cs.AI cs.CL
inferring missing links in knowledge graphs kg has attracted a lot of attention from the research community in this paper we tackle a practical query answering task involving predicting the relation of a given entity pair we frame this prediction problem as an inference problem in a probabilistic graphical model and aim at resolving it from a variational inference perspective in order to model the relation between the query entity pair we assume that there exists an underlying latent variable paths connecting two nodes in the kg which carries the equivalent semantics of their relations however due to the intractability of connections in large kgs we propose to use variation inference to maximize the evidence lower bound more specifically our framework textscdiva is composed of three modules ie a posterior approximator a prior path finder and a likelihood path reasoner by using variational inference we are able to incorporate them closely into a unified architecture and jointly optimize them to perform kg reasoning with active interactions among these submodules textscdiva is better at handling noise and coping with more complex reasoning scenarios in order to evaluate our method we conduct the experiment of the link prediction task on multiple datasets and achieve stateoftheart performances on both datasets
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1,803.06582
Contrasting Various Notions of Convergence in Geometric Analysis
We explore the distinctions between $L^p$ convergence of metric tensors on a fixed Riemannian manifold versus Gromov-Hausdorff, uniform, and intrinsic flat convergence of the corresponding sequence of metric spaces. We provide a number of examples which demonstrate these notions of convergence do not agree even for two dimensional warped product manifolds with warping functions converging in the $L^p$ sense. We then prove a theorem which requires $L^p$ bounds from above and $C^0$ bounds from below on the warping functions to obtain enough control for all these limits to agree.
math.MG math.DG
we explore the distinctions between lp convergence of metric tensors on a fixed riemannian manifold versus gromovhausdorff uniform and intrinsic flat convergence of the corresponding sequence of metric spaces we provide a number of examples which demonstrate these notions of convergence do not agree even for two dimensional warped product manifolds with warping functions converging in the lp sense we then prove a theorem which requires lp bounds from above and c0 bounds from below on the warping functions to obtain enough control for all these limits to agree
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1,803.06583
Circular orders, ultra-homogeneous order structures and their automorphism groups
We study topological groups $G$ for which the universal minimal $G$-system $M(G)$, or the universal irreducible affine $G$-system $IA(G)$ are tame. We call such groups intrinsically tame and convexly intrinsically tame. These notions are generalized versions of extreme amenability and amenability, respectively. When $M(G)$, as a $G$-system, admits a circular order we say that $G$ is intrinsically circularly ordered. This implies that $G$ is intrinsically tame. We show that for every circularly ultrahomogeneous action $G \curvearrowright X$ on a circularly ordered set $X$ the topological group $G$, in its pointwise convergence topology, is intrinsically circularly ordered. This result is a "circular" analog of Pestov's result about the extremal amenability of ultrahomogeneous actions on linearly ordered sets by linear order preserving transformations. In the case where $X$ is countable, the corresponding Polish group of circular automorphisms $G$ admits a concrete description. Using the Kechris-Pestov-Todorcevic construction we show that $M(G)$ is a circularly ordered compact space obtained by splitting the rational points on the circle. We show also that $G$ is Roelcke precompact, satisfies Kazhdan's property $T$ (using results of Evans-Tsankov) and has the automatic continuity property (using results of Rosendal-Solecki).
math.DS math.FA math.GN
we study topological groups g for which the universal minimal gsystem mg or the universal irreducible affine gsystem iag are tame we call such groups intrinsically tame and convexly intrinsically tame these notions are generalized versions of extreme amenability and amenability respectively when mg as a gsystem admits a circular order we say that g is intrinsically circularly ordered this implies that g is intrinsically tame we show that for every circularly ultrahomogeneous action g curvearrowright x on a circularly ordered set x the topological group g in its pointwise convergence topology is intrinsically circularly ordered this result is a circular analog of pestovs result about the extremal amenability of ultrahomogeneous actions on linearly ordered sets by linear order preserving transformations in the case where x is countable the corresponding polish group of circular automorphisms g admits a concrete description using the kechrispestovtodorcevic construction we show that mg is a circularly ordered compact space obtained by splitting the rational points on the circle we show also that g is roelcke precompact satisfies kazhdans property t using results of evanstsankov and has the automatic continuity property using results of rosendalsolecki
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1,803.06584
Linear Instability of the Peregrine Breather: Numerical and Analytical Investigations
We study the linear stability of the Peregrine breather both numerically and with analytical arguments based on its derivation as the singular limit of a single-mode spatially periodic breather as the spatial period becomes infinite. By constructing solutions of the linearization of the nonlinear Schr\"odinger equation in terms of quadratic products of components of the eigenfunctions of the Zakharov-Shabat system, we show that the Peregrine breather is linearly unstable. A numerical study employing a highly accurate Chebychev pseudo-spectral integrator confirms exponential growth of random initial perturbations of the Peregrine breather.
nlin.SI math-ph math.MP
we study the linear stability of the peregrine breather both numerically and with analytical arguments based on its derivation as the singular limit of a singlemode spatially periodic breather as the spatial period becomes infinite by constructing solutions of the linearization of the nonlinear schrodinger equation in terms of quadratic products of components of the eigenfunctions of the zakharovshabat system we show that the peregrine breather is linearly unstable a numerical study employing a highly accurate chebychev pseudospectral integrator confirms exponential growth of random initial perturbations of the peregrine breather
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1,803.06585
Learning Long Term Dependencies via Fourier Recurrent Units
It is a known fact that training recurrent neural networks for tasks that have long term dependencies is challenging. One of the main reasons is the vanishing or exploding gradient problem, which prevents gradient information from propagating to early layers. In this paper we propose a simple recurrent architecture, the Fourier Recurrent Unit (FRU), that stabilizes the gradients that arise in its training while giving us stronger expressive power. Specifically, FRU summarizes the hidden states $h^{(t)}$ along the temporal dimension with Fourier basis functions. This allows gradients to easily reach any layer due to FRU's residual learning structure and the global support of trigonometric functions. We show that FRU has gradient lower and upper bounds independent of temporal dimension. We also show the strong expressivity of sparse Fourier basis, from which FRU obtains its strong expressive power. Our experimental study also demonstrates that with fewer parameters the proposed architecture outperforms other recurrent architectures on many tasks.
cs.LG stat.ML
it is a known fact that training recurrent neural networks for tasks that have long term dependencies is challenging one of the main reasons is the vanishing or exploding gradient problem which prevents gradient information from propagating to early layers in this paper we propose a simple recurrent architecture the fourier recurrent unit fru that stabilizes the gradients that arise in its training while giving us stronger expressive power specifically fru summarizes the hidden states ht along the temporal dimension with fourier basis functions this allows gradients to easily reach any layer due to frus residual learning structure and the global support of trigonometric functions we show that fru has gradient lower and upper bounds independent of temporal dimension we also show the strong expressivity of sparse fourier basis from which fru obtains its strong expressive power our experimental study also demonstrates that with fewer parameters the proposed architecture outperforms other recurrent architectures on many tasks
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1,803.06586
Structural query-by-committee
In this work, we describe a framework that unifies many different interactive learning tasks. We present a generalization of the {\it query-by-committee} active learning algorithm for this setting, and we study its consistency and rate of convergence, both theoretically and empirically, with and without noise.
cs.LG stat.ML
in this work we describe a framework that unifies many different interactive learning tasks we present a generalization of the it querybycommittee active learning algorithm for this setting and we study its consistency and rate of convergence both theoretically and empirically with and without noise
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1,803.06587
Comparative Study of Approximate Multipliers
Approximate multipliers are widely being advocated for energy-efficient computing in applications that exhibit an inherent tolerance to inaccuracy. However, the inclusion of accuracy as a key design parameter, besides the performance, area and power, makes the identification of the most suitable approximate multiplier quite challenging. In this paper, we identify three major decision making factors for the selection of an approximate multipliers circuit: (1) the type of approximate full adder (FA) used to construct the multiplier, (2) the architecture, i.e., array or tree, of the multiplier and (3) the placement of sub-modules of approximate and exact multipliers in the main multiplier module. Based on these factors, we explored the design space for circuit level implementations of approximate multipliers. We used circuit level implementations of some of the most widely used approximate full adders, i.e., approximate mirror adders, XOR/XNOR based approximate full adders and Inexact adder cell. These FA cells are then used to develop circuits for the approximate high order compressors as building blocks for 8x8 array and tree multipliers. We then develop various implementations of higher bit multipliers by using a combination of exact and inaccurate 8x8 multiplier cells. All these implementations have been done using the Cadence's Spectre tool with the TSMC65nm technology. The design space of these multipliers is explored based on their power, area, delay and error and the best approximate multiplier designs are identified. The report also presents the validation of our results using an image blending application. An open source library of implemented cells and multiplier circuits are available online.
cs.ET
approximate multipliers are widely being advocated for energyefficient computing in applications that exhibit an inherent tolerance to inaccuracy however the inclusion of accuracy as a key design parameter besides the performance area and power makes the identification of the most suitable approximate multiplier quite challenging in this paper we identify three major decision making factors for the selection of an approximate multipliers circuit 1 the type of approximate full adder fa used to construct the multiplier 2 the architecture ie array or tree of the multiplier and 3 the placement of submodules of approximate and exact multipliers in the main multiplier module based on these factors we explored the design space for circuit level implementations of approximate multipliers we used circuit level implementations of some of the most widely used approximate full adders ie approximate mirror adders xorxnor based approximate full adders and inexact adder cell these fa cells are then used to develop circuits for the approximate high order compressors as building blocks for 8x8 array and tree multipliers we then develop various implementations of higher bit multipliers by using a combination of exact and inaccurate 8x8 multiplier cells all these implementations have been done using the cadences spectre tool with the tsmc65nm technology the design space of these multipliers is explored based on their power area delay and error and the best approximate multiplier designs are identified the report also presents the validation of our results using an image blending application an open source library of implemented cells and multiplier circuits are available online
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1,803.06588
Cultural Evolution of Categorization
Categorization is a fundamental function of minds, with wide ranging implications for the rest of the cognitive system. In humans, categories are shared and communicated between minds, thus requiring explanations at the population level. In this paper, we discuss the current state of research on the cultural evolution of categorization. We begin by delineating key properties of categories in need of evolutionary explanation. We then review computational modeling and laboratory studies of category evolution, including their major insights and limitations. Finally, we discuss remaining challenges for understanding the cultural evolution of categorization.
physics.soc-ph
categorization is a fundamental function of minds with wide ranging implications for the rest of the cognitive system in humans categories are shared and communicated between minds thus requiring explanations at the population level in this paper we discuss the current state of research on the cultural evolution of categorization we begin by delineating key properties of categories in need of evolutionary explanation we then review computational modeling and laboratory studies of category evolution including their major insights and limitations finally we discuss remaining challenges for understanding the cultural evolution of categorization
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1,803.06589
Early hospital mortality prediction using vital signals
Early hospital mortality prediction is critical as intensivists strive to make efficient medical decisions about the severely ill patients staying in intensive care units. As a result, various methods have been developed to address this problem based on clinical records. However, some of the laboratory test results are time-consuming and need to be processed. In this paper, we propose a novel method to predict mortality using features extracted from the heart signals of patients within the first hour of ICU admission. In order to predict the risk, quantitative features have been computed based on the heart rate signals of ICU patients. Each signal is described in terms of 12 statistical and signal-based features. The extracted features are fed into eight classifiers: decision tree, linear discriminant, logistic regression, support vector machine (SVM), random forest, boosted trees, Gaussian SVM, and K-nearest neighborhood (K-NN). To derive insight into the performance of the proposed method, several experiments have been conducted using the well-known clinical dataset named Medical Information Mart for Intensive Care III (MIMIC-III). The experimental results demonstrate the capability of the proposed method in terms of precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC). The decision tree classifier satisfies both accuracy and interpretability better than the other classifiers, producing an F1-score and AUC equal to 0.91 and 0.93, respectively. It indicates that heart rate signals can be used for predicting mortality in patients in the ICU, achieving a comparable performance with existing predictions that rely on high dimensional features from clinical records which need to be processed and may contain missing information.
cs.LG stat.ML
early hospital mortality prediction is critical as intensivists strive to make efficient medical decisions about the severely ill patients staying in intensive care units as a result various methods have been developed to address this problem based on clinical records however some of the laboratory test results are timeconsuming and need to be processed in this paper we propose a novel method to predict mortality using features extracted from the heart signals of patients within the first hour of icu admission in order to predict the risk quantitative features have been computed based on the heart rate signals of icu patients each signal is described in terms of 12 statistical and signalbased features the extracted features are fed into eight classifiers decision tree linear discriminant logistic regression support vector machine svm random forest boosted trees gaussian svm and knearest neighborhood knn to derive insight into the performance of the proposed method several experiments have been conducted using the wellknown clinical dataset named medical information mart for intensive care iii mimiciii the experimental results demonstrate the capability of the proposed method in terms of precision recall f1score and area under the receiver operating characteristic curve auc the decision tree classifier satisfies both accuracy and interpretability better than the other classifiers producing an f1score and auc equal to 091 and 093 respectively it indicates that heart rate signals can be used for predicting mortality in patients in the icu achieving a comparable performance with existing predictions that rely on high dimensional features from clinical records which need to be processed and may contain missing information
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1,803.0659
Cell Decompositions for Rank Two Quiver Grassmannians
We prove that all quiver Grassmannians for exceptional representations of a generalized Kronecker quiver admit a cell decomposition. In the process, we introduce a class of regular representations which arise as quotients of consecutive preprojective representations. Cell decompositions for quiver Grassmannians of these "truncated preprojectives" are also established. We also provide two natural combinatorial labelings for these cells. On the one hand, they are labeled by certain subsets of a so-called 2-quiver attached to a (truncated) preprojective representation. On the other hand, the cells are in bijection with compatible pairs in a maximal Dyck path as predicted by the theory of cluster algebras. The natural bijection between these two labelings gives a geometric explanation for the appearance of Dyck path combinatorics in the theory of quiver Grassmannians.
math.RT math.AG math.RA
we prove that all quiver grassmannians for exceptional representations of a generalized kronecker quiver admit a cell decomposition in the process we introduce a class of regular representations which arise as quotients of consecutive preprojective representations cell decompositions for quiver grassmannians of these truncated preprojectives are also established we also provide two natural combinatorial labelings for these cells on the one hand they are labeled by certain subsets of a socalled 2quiver attached to a truncated preprojective representation on the other hand the cells are in bijection with compatible pairs in a maximal dyck path as predicted by the theory of cluster algebras the natural bijection between these two labelings gives a geometric explanation for the appearance of dyck path combinatorics in the theory of quiver grassmannians
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1,803.06591
Recognizing number of communities and detecting community structures in complex networks
Recognizing number of communities and detecting community structures of complex network are discussed in this paper. As a visual and feasible algorithm, block model has been successfully applied to detect community structures in complex network. In order to measure the quality of the block model, we first define an objective function WQ value. For obtaining block model B of a network, GSA algorithm is applied to optimize WQ with the help of random keys. After executing processes AO (Adding Ones) and RO (Removing Ones) on block model B, the number of communities of a network can be recognized distinctly. Furthermore, based on the advantage of block model that its sort order of nodes is in correspondence with sort order of communities, so a new fuzzy boundary algorithm for detecting community structures is proposed and successfully applied to some representative networks. Finally, experimental results demonstrate the feasibility of the proposed algorithm.
physics.soc-ph cs.SI
recognizing number of communities and detecting community structures of complex network are discussed in this paper as a visual and feasible algorithm block model has been successfully applied to detect community structures in complex network in order to measure the quality of the block model we first define an objective function wq value for obtaining block model b of a network gsa algorithm is applied to optimize wq with the help of random keys after executing processes ao adding ones and ro removing ones on block model b the number of communities of a network can be recognized distinctly furthermore based on the advantage of block model that its sort order of nodes is in correspondence with sort order of communities so a new fuzzy boundary algorithm for detecting community structures is proposed and successfully applied to some representative networks finally experimental results demonstrate the feasibility of the proposed algorithm
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1,803.06592
Layer structure of irreducible Lie algebra modules
Let $\mathfrak{g}$ be a finite-dimensional simple complex Lie algebra. A layer sum is introduced as the sum of formal exponentials of the distinct weights appearing in an irreducible $\mathfrak{g}$-module. It is argued that the character of every finite-dimensional irreducible $\mathfrak{g}$-module admits a decomposition in terms of layer sums, with only non-negative integer coefficients. Ensuing results include a new approach to the computation of Weyl characters and weight multiplicities, and a closed-form expression for the number of distinct weights in a finite-dimensional irreducible $\mathfrak{g}$-module. The latter is given by a polynomial in the Dynkin labels, of degree equal to the rank of $\mathfrak{g}$.
math.RT hep-th math-ph math.CO math.MP
let mathfrakg be a finitedimensional simple complex lie algebra a layer sum is introduced as the sum of formal exponentials of the distinct weights appearing in an irreducible mathfrakgmodule it is argued that the character of every finitedimensional irreducible mathfrakgmodule admits a decomposition in terms of layer sums with only nonnegative integer coefficients ensuing results include a new approach to the computation of weyl characters and weight multiplicities and a closedform expression for the number of distinct weights in a finitedimensional irreducible mathfrakgmodule the latter is given by a polynomial in the dynkin labels of degree equal to the rank of mathfrakg
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1,803.06593
Bulk transport properties of Bismuth selenide thin films approaching the two-dimensional limit
We have investigated the transport properties of topological insulator Bi2Se3 thin films grown using magnetron sputtering with an emphasis on understanding the behavior as a function of thickness. We show that thickness has a strong influence on all aspects of transport as the two-dimensional limit is approached. Bulk resistivity and Hall mobility show disproportionately large changes below 6 quintuple layer which we directly correlate to an increase in the bulk band gap of few-layer Bi2Se3, an effect that is concomitant with surface gap opening. A tendency to crossover from a metallic to an insulating behavior in temperature-dependent resistivity measurements in ultra-thin Bi2Se3 is also consistent with an increase in the bulk band gap along with enhanced disorder at the film-substrate interface. Our work highlights that the properties of few-layer Bi2Se3 are tunable that may be attractive for a variety of device applications in areas such as optoelectronics, nanoelectronics and spintronics.
cond-mat.mtrl-sci
we have investigated the transport properties of topological insulator bi2se3 thin films grown using magnetron sputtering with an emphasis on understanding the behavior as a function of thickness we show that thickness has a strong influence on all aspects of transport as the twodimensional limit is approached bulk resistivity and hall mobility show disproportionately large changes below 6 quintuple layer which we directly correlate to an increase in the bulk band gap of fewlayer bi2se3 an effect that is concomitant with surface gap opening a tendency to crossover from a metallic to an insulating behavior in temperaturedependent resistivity measurements in ultrathin bi2se3 is also consistent with an increase in the bulk band gap along with enhanced disorder at the filmsubstrate interface our work highlights that the properties of fewlayer bi2se3 are tunable that may be attractive for a variety of device applications in areas such as optoelectronics nanoelectronics and spintronics
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1,803.06594
Efficient and accurate inversion of multiple scattering with deep learning
Image reconstruction under multiple light scattering is crucial in a number of applications such as diffraction tomography. The reconstruction problem is often formulated as a nonconvex optimization, where a nonlinear measurement model is used to account for multiple scattering and regularization is used to enforce prior constraints on the object. In this paper, we propose a powerful alternative to this optimization-based view of image reconstruction by designing and training a deep convolutional neural network that can invert multiple scattered measurements to produce a high-quality image of the refractive index. Our results on both simulated and experimental datasets show that the proposed approach is substantially faster and achieves higher imaging quality compared to the state-of-the-art methods based on optimization.
cs.CV
image reconstruction under multiple light scattering is crucial in a number of applications such as diffraction tomography the reconstruction problem is often formulated as a nonconvex optimization where a nonlinear measurement model is used to account for multiple scattering and regularization is used to enforce prior constraints on the object in this paper we propose a powerful alternative to this optimizationbased view of image reconstruction by designing and training a deep convolutional neural network that can invert multiple scattered measurements to produce a highquality image of the refractive index our results on both simulated and experimental datasets show that the proposed approach is substantially faster and achieves higher imaging quality compared to the stateoftheart methods based on optimization
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1,803.06595
New Nanoporous Graphyne Monolayer as Nodal Line Semimetal: Double Dirac Points with an Ultrahigh Fermi Velocity
Two-dimensional (2D) carbon materials play an important role in nanomaterials. We propose a new carbon monolayer, named hexagonal-4,4,4-graphyne (H4,4,4-graphyne), which is a nanoporous structure composed of rectangular carbon rings and triple bonds of carbon. Using first-principles calculations, we systematically studied the structure, stability, and band structure of this new material. We found that its energy is much lower than that of some experimental carbon materials and it is stable at least up to 1500 K. In contrast to the single Dirac point band structure of other 2D carbon monolayers, the band structure of H4,4,4-graphyne exhibits double Dirac points along the high symmetry points and the corresponding Fermi velocities (1.04~1.27 * 106 m/s) are asymmetric and higher than that of graphene. The origin of these double Dirac points is traced back to the nodal line states, which can be well explained by a tight-binding model. The H4,4,4-graphyne forms a moir\'e superstructure when placed on top of a BN substrate, while keeping the double Dirac points. These properties make H4,4,4-graphyne a promising semimetal material for applications in high-speed electronic devices.
cond-mat.mtrl-sci
twodimensional 2d carbon materials play an important role in nanomaterials we propose a new carbon monolayer named hexagonal444graphyne h444graphyne which is a nanoporous structure composed of rectangular carbon rings and triple bonds of carbon using firstprinciples calculations we systematically studied the structure stability and band structure of this new material we found that its energy is much lower than that of some experimental carbon materials and it is stable at least up to 1500 k in contrast to the single dirac point band structure of other 2d carbon monolayers the band structure of h444graphyne exhibits double dirac points along the high symmetry points and the corresponding fermi velocities 104127 106 ms are asymmetric and higher than that of graphene the origin of these double dirac points is traced back to the nodal line states which can be well explained by a tightbinding model the h444graphyne forms a moire superstructure when placed on top of a bn substrate while keeping the double dirac points these properties make h444graphyne a promising semimetal material for applications in highspeed electronic devices
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1,803.06596
Network Service Orchestration: A Survey
Business models of network service providers are undergoing an evolving transformation fueled by vertical customer demands and technological advances such as 5G, Software Defined Networking~(SDN), and Network Function Virtualization~(NFV). Emerging scenarios call for agile network services consuming network, storage, and compute resources across heterogeneous infrastructures and administrative domains. Coordinating resource control and service creation across interconnected domains and diverse technologies becomes a grand challenge. Research and development efforts are being devoted to enabling orchestration processes to automate, coordinate, and manage the deployment and operation of network services. In this survey, we delve into the topic of Network Service Orchestration~(NSO) by reviewing the historical background, relevant research projects, enabling technologies, and standardization activities. We define key concepts and propose a taxonomy of NSO approaches and solutions to pave the way towards a common understanding of the various ongoing efforts around the realization of diverse NSO application scenarios. Based on the analysis of the state of affairs, we present a series of open challenges and research opportunities, altogether contributing to a timely and comprehensive survey on the vibrant and strategic topic of network service orchestration.
cs.NI
business models of network service providers are undergoing an evolving transformation fueled by vertical customer demands and technological advances such as 5g software defined networkingsdn and network function virtualizationnfv emerging scenarios call for agile network services consuming network storage and compute resources across heterogeneous infrastructures and administrative domains coordinating resource control and service creation across interconnected domains and diverse technologies becomes a grand challenge research and development efforts are being devoted to enabling orchestration processes to automate coordinate and manage the deployment and operation of network services in this survey we delve into the topic of network service orchestrationnso by reviewing the historical background relevant research projects enabling technologies and standardization activities we define key concepts and propose a taxonomy of nso approaches and solutions to pave the way towards a common understanding of the various ongoing efforts around the realization of diverse nso application scenarios based on the analysis of the state of affairs we present a series of open challenges and research opportunities altogether contributing to a timely and comprehensive survey on the vibrant and strategic topic of network service orchestration
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1,803.06597
Schwinger-Dyson Equations in Coulomb Gauge Consistent with Numerical Simulation
In the present work we undertake a study of the Schwinger-Dyson equation (SDE) in the Euclidean formulation of local quantum gauge field theory, with Coulomb gauge condition $\partial_i A_i = 0$. We continue a previous study which kept only instantaneous terms in the SDE that are proportional to $\delta(t)$ in order to calculate the instantaneous part of the time component of the gluon propagator $D_{A_0 A_0}(t, R)$. We compare the results of that study with a numerical simulation of lattice gauge theory and find that the infrared critical exponents and related quantities agree to within 1\% to 3\%. This raises the question, "Why is the agreement so good, despite the systematic neglect of non-instantaneous terms?" We discovered the happy circumstance that all the non-instantaneous terms are in fact zero. They are forbidden by the symmetry of the local action in Coulomb gauge under time-dependent gauge transformations $g(t)$. This remnant gauge symmetry is not fixed by the Coulomb gauge condition. The numerical result of the present calculation is the same as in the previous study; the novelty is that we now demonstrate that all the non-instantaneous terms in the SDE vanish. We derive some elementary properties of propagators which are a consequence of the remnant gauge symmetry. In particular the time component of the gluon propagator is found to be purely instantaneous $D_{A_0 A_0}(t, R) = \delta(t) V(R)$, where $V(R)$ is the color-Coulomb potential. Our results support the simple physical scenario in which confinement is the result of a linearly rising color-Coulomb potential, $V(R) \sim \sigma R$ at large $R$.
hep-th
in the present work we undertake a study of the schwingerdyson equation sde in the euclidean formulation of local quantum gauge field theory with coulomb gauge condition partial_i a_i 0 we continue a previous study which kept only instantaneous terms in the sde that are proportional to deltat in order to calculate the instantaneous part of the time component of the gluon propagator d_a_0 a_0t r we compare the results of that study with a numerical simulation of lattice gauge theory and find that the infrared critical exponents and related quantities agree to within 1 to 3 this raises the question why is the agreement so good despite the systematic neglect of noninstantaneous terms we discovered the happy circumstance that all the noninstantaneous terms are in fact zero they are forbidden by the symmetry of the local action in coulomb gauge under timedependent gauge transformations gt this remnant gauge symmetry is not fixed by the coulomb gauge condition the numerical result of the present calculation is the same as in the previous study the novelty is that we now demonstrate that all the noninstantaneous terms in the sde vanish we derive some elementary properties of propagators which are a consequence of the remnant gauge symmetry in particular the time component of the gluon propagator is found to be purely instantaneous d_a_0 a_0t r deltat vr where vr is the colorcoulomb potential our results support the simple physical scenario in which confinement is the result of a linearly rising colorcoulomb potential vr sim sigma r at large r
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1,803.06598
Facial Landmarks Detection by Self-Iterative Regression based Landmarks-Attention Network
Cascaded Regression (CR) based methods have been proposed to solve facial landmarks detection problem, which learn a series of descent directions by multiple cascaded regressors separately trained in coarse and fine stages. They outperform the traditional gradient descent based methods in both accuracy and running speed. However, cascaded regression is not robust enough because each regressor's training data comes from the output of previous regressor. Moreover, training multiple regressors requires lots of computing resources, especially for deep learning based methods. In this paper, we develop a Self-Iterative Regression (SIR) framework to improve the model efficiency. Only one self-iterative regressor is trained to learn the descent directions for samples from coarse stages to fine stages, and parameters are iteratively updated by the same regressor. Specifically, we proposed Landmarks-Attention Network (LAN) as our regressor, which concurrently learns features around each landmark and obtains the holistic location increment. By doing so, not only the rest of regressors are removed to simplify the training process, but the number of model parameters is significantly decreased. The experiments demonstrate that with only 3.72M model parameters, our proposed method achieves the state-of-the-art performance.
cs.CV
cascaded regression cr based methods have been proposed to solve facial landmarks detection problem which learn a series of descent directions by multiple cascaded regressors separately trained in coarse and fine stages they outperform the traditional gradient descent based methods in both accuracy and running speed however cascaded regression is not robust enough because each regressors training data comes from the output of previous regressor moreover training multiple regressors requires lots of computing resources especially for deep learning based methods in this paper we develop a selfiterative regression sir framework to improve the model efficiency only one selfiterative regressor is trained to learn the descent directions for samples from coarse stages to fine stages and parameters are iteratively updated by the same regressor specifically we proposed landmarksattention network lan as our regressor which concurrently learns features around each landmark and obtains the holistic location increment by doing so not only the rest of regressors are removed to simplify the training process but the number of model parameters is significantly decreased the experiments demonstrate that with only 372m model parameters our proposed method achieves the stateoftheart performance
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1,803.06599
Single-Photon-Triggered Quantum Phase Transition
We propose a hybrid quantum model combining cavity QED and optomechanics, which allows the occurrence of equilibrium superradiant quantum phase transition (QPT) triggered by a single photon. This single-photon-triggered QPT exists both in the cases of ignoring and including the so-called $A^2$ term, i.e., it is immune to the no-go theorem. It originally comes from the photon-dependent quantum criticality featured by the proposed hybrid quantum model. Moreover, a reversed superradiant QPT is induced by the competition between the introduced $A^2$ term and the optomechanical interaction. This work offers an approach to manipulate QPT with a single photon, which should inspire the exploration of single-photon quantum-criticality physics and the engineering of new single-photon quantum devices.
quant-ph cond-mat.stat-mech
we propose a hybrid quantum model combining cavity qed and optomechanics which allows the occurrence of equilibrium superradiant quantum phase transition qpt triggered by a single photon this singlephotontriggered qpt exists both in the cases of ignoring and including the socalled a2 term ie it is immune to the nogo theorem it originally comes from the photondependent quantum criticality featured by the proposed hybrid quantum model moreover a reversed superradiant qpt is induced by the competition between the introduced a2 term and the optomechanical interaction this work offers an approach to manipulate qpt with a single photon which should inspire the exploration of singlephoton quantumcriticality physics and the engineering of new singlephoton quantum devices
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1,803.066
Optimizing the Efficiency of First-Order Methods for Decreasing the Gradient of Smooth Convex Functions
This paper optimizes the step coefficients of first-order methods for smooth convex minimization in terms of the worst-case convergence bound (i.e., efficiency) of the decrease in the gradient norm. This work is based on the performance estimation problem approach. The worst-case gradient bound of the resulting method is optimal up to a constant for large-dimensional smooth convex minimization problems, under the initial bounded condition on the cost function value. This paper then illustrates that the proposed method has a computationally efficient form that is similar to the optimized gradient method.
math.OC
this paper optimizes the step coefficients of firstorder methods for smooth convex minimization in terms of the worstcase convergence bound ie efficiency of the decrease in the gradient norm this work is based on the performance estimation problem approach the worstcase gradient bound of the resulting method is optimal up to a constant for largedimensional smooth convex minimization problems under the initial bounded condition on the cost function value this paper then illustrates that the proposed method has a computationally efficient form that is similar to the optimized gradient method
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1,803.06601
Convergence of Heisenberg Modules over Quantum 2-tori for the Modular Gromov-Hausdorff Propinquity
The modular Gromov-Hausdorff propinquity is a distance on classes of modules endowed with quantum metric information, in the form of a metric form of a connection and a left Hilbert module structure. This paper proves that the family of Heisenberg modules over quantum two tori, when endowed with their canonical connections, form a continuous family for the modular propinquity.
math.OA
the modular gromovhausdorff propinquity is a distance on classes of modules endowed with quantum metric information in the form of a metric form of a connection and a left hilbert module structure this paper proves that the family of heisenberg modules over quantum two tori when endowed with their canonical connections form a continuous family for the modular propinquity
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1,803.06602
Two new classes of quantum MDS codes
Let $p$ be a prime and let $q$ be a power of $p$. In this paper, by using generalized Reed-Solomon (GRS for short) codes and extended GRS codes, we construct two new classes of quantum maximum-distance- separable (MDS) codes with parameters \[ [[tq, tq-2d+2, d]]_{q} \] for any $1 \leq t \leq q, 2 \leq d \leq \lfloor \frac{tq+q-1}{q+1}\rfloor+1$, and \[ [[t(q+1)+2, t(q+1)-2d+4, d]]_{q} \] for any $1 \leq t \leq q-1, 2 \leq d \leq t+2$ with $(p,t,d) \neq (2, q-1, q)$. Our quantum codes have flexible parameters, and have minimum distances larger than $\frac{q}{2}+1$ when $t > \frac{q}{2}$. Furthermore, it turns out that our constructions generalize and improve some previous results.
cs.IT math.IT
let p be a prime and let q be a power of p in this paper by using generalized reedsolomon grs for short codes and extended grs codes we construct two new classes of quantum maximumdistance separable mds codes with parameters tq tq2d2 d_q for any 1 leq t leq q 2 leq d leq lfloor fractqq1q1rfloor1 and tq12 tq12d4 d_q for any 1 leq t leq q1 2 leq d leq t2 with ptd neq 2 q1 q our quantum codes have flexible parameters and have minimum distances larger than fracq21 when t fracq2 furthermore it turns out that our constructions generalize and improve some previous results
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1,803.06603
Energy-aware networked control systems under temporal logic specifications
In recent years, event and self-triggered control have been proposed as energy-aware control strategies to expand the life-time of battery powered devices in Networked Control Systems (NCSs). In contrast to the previous works in which their control objective is to achieve stability, this paper presents a novel energy-aware control scheme for achieving high level specifications, or more specifically, temporal logic specifications. Inspired by the standard hierarchical strategy that has been proposed in the field of formal control synthesis paradigm, we propose a new abstraction procedure for jointly synthesizing control and communication strategies, such that the communication reduction in NCSs and the satisfaction of the temporal logic specifications are guaranteed. The benefits of the proposal are illustrated through a numerical example.
math.OC
in recent years event and selftriggered control have been proposed as energyaware control strategies to expand the lifetime of battery powered devices in networked control systems ncss in contrast to the previous works in which their control objective is to achieve stability this paper presents a novel energyaware control scheme for achieving high level specifications or more specifically temporal logic specifications inspired by the standard hierarchical strategy that has been proposed in the field of formal control synthesis paradigm we propose a new abstraction procedure for jointly synthesizing control and communication strategies such that the communication reduction in ncss and the satisfaction of the temporal logic specifications are guaranteed the benefits of the proposal are illustrated through a numerical example
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1,803.06604
A Robust AUC Maximization Framework with Simultaneous Outlier Detection and Feature Selection for Positive-Unlabeled Classification
The positive-unlabeled (PU) classification is a common scenario in real-world applications such as healthcare, text classification, and bioinformatics, in which we only observe a few samples labeled as "positive" together with a large volume of "unlabeled" samples that may contain both positive and negative samples. Building robust classifier for the PU problem is very challenging, especially for complex data where the negative samples overwhelm and mislabeled samples or corrupted features exist. To address these three issues, we propose a robust learning framework that unifies AUC maximization (a robust metric for biased labels), outlier detection (for excluding wrong labels), and feature selection (for excluding corrupted features). The generalization error bounds are provided for the proposed model that give valuable insight into the theoretical performance of the method and lead to useful practical guidance, e.g., to train a model, we find that the included unlabeled samples are sufficient as long as the sample size is comparable to the number of positive samples in the training process. Empirical comparisons and two real-world applications on surgical site infection (SSI) and EEG seizure detection are also conducted to show the effectiveness of the proposed model.
cs.LG stat.ML
the positiveunlabeled pu classification is a common scenario in realworld applications such as healthcare text classification and bioinformatics in which we only observe a few samples labeled as positive together with a large volume of unlabeled samples that may contain both positive and negative samples building robust classifier for the pu problem is very challenging especially for complex data where the negative samples overwhelm and mislabeled samples or corrupted features exist to address these three issues we propose a robust learning framework that unifies auc maximization a robust metric for biased labels outlier detection for excluding wrong labels and feature selection for excluding corrupted features the generalization error bounds are provided for the proposed model that give valuable insight into the theoretical performance of the method and lead to useful practical guidance eg to train a model we find that the included unlabeled samples are sufficient as long as the sample size is comparable to the number of positive samples in the training process empirical comparisons and two realworld applications on surgical site infection ssi and eeg seizure detection are also conducted to show the effectiveness of the proposed model
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1,803.06605
An experimental and Ab-initio study of Electronic and Magnetic properties of FeGa3
Electronic structure of FeGa3 has been studied using experiments and ab-initio calculations. Magnetization measurements show that FeGa3 is inherently diamagnetic in nature. Our studies indicate that the previously reported magnetic moment on the Fe atoms in FeGa3 is not an intrinsic property of FeGa3, but is primarily due to the presence of disorder, defects, grain boundaries etc that break the symmetry about the Fe dimers. Analysis of the results obtained from magnetic measurements, photoelectron spectroscopy, Fe K-edge X-ray absorption near edge spectroscopy and ab-initio calculations clearly indicates that, the effects of on-site Coulomb repulsion between the Fe 3d electrons do not play any role in determining the electronic and magnetic properties of FeGa3. Detailed analysis of results of single crystal and poycrystalline FeGa3, helps to resolve the discrepancy in the electronic and magnetic properties in FeGa3 existing in the literature, consistently.
cond-mat.mtrl-sci
electronic structure of fega3 has been studied using experiments and abinitio calculations magnetization measurements show that fega3 is inherently diamagnetic in nature our studies indicate that the previously reported magnetic moment on the fe atoms in fega3 is not an intrinsic property of fega3 but is primarily due to the presence of disorder defects grain boundaries etc that break the symmetry about the fe dimers analysis of the results obtained from magnetic measurements photoelectron spectroscopy fe kedge xray absorption near edge spectroscopy and abinitio calculations clearly indicates that the effects of onsite coulomb repulsion between the fe 3d electrons do not play any role in determining the electronic and magnetic properties of fega3 detailed analysis of results of single crystal and poycrystalline fega3 helps to resolve the discrepancy in the electronic and magnetic properties in fega3 existing in the literature consistently
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1,803.06606
Stripes and honeycomb lattice of quantized vortices in rotating two-component Bose-Einstein condensates
We study numerically the structure of a vortex lattice in two-component Bose-Einstein condensates with equal atomic masses and equal intra- and inter-component coupling strengths. The numerical simulations of the Gross-Pitaevskii equation show that the quantized vortices form uncertain lattice configurations accompanying the vortex stripes, honeycomb lattices, and their complexes. This is a result of the degeneracy of the system for the SU(2) symmetric operation, which makes a continuous transformation between the above structures. In terms of the pseudospin representation, the complex lattice structures are identified to a hexagonal lattice of doubly-winding half-skyrmions.
cond-mat.quant-gas
we study numerically the structure of a vortex lattice in twocomponent boseeinstein condensates with equal atomic masses and equal intra and intercomponent coupling strengths the numerical simulations of the grosspitaevskii equation show that the quantized vortices form uncertain lattice configurations accompanying the vortex stripes honeycomb lattices and their complexes this is a result of the degeneracy of the system for the su2 symmetric operation which makes a continuous transformation between the above structures in terms of the pseudospin representation the complex lattice structures are identified to a hexagonal lattice of doublywinding halfskyrmions
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1,803.06607
Valley Hall Transport of Photon-Dressed Quasiparticles in 2D Dirac Semiconductors
We present a theory of the photovoltaic valley-dependent Hall effect in a two-dimensional Dirac semiconductor subject to an intense near-resonant electromagnetic field. Our theory captures and elucidates the influence of both the field-induced resonant interband transitions and the nonequilibrium carrier kinetics on the resulting valley Hall transport in terms of photon-dressed quasiparticles. The non-perturbative renormalization effect of the pump field manifests itself in the dynamics of the photon-dressed quasiparticles, with a quasienergy spectrum characterized by {dynamical gaps $\delta_\eta$ ($\eta$ is the valley index)} that strongly depend on field amplitude and polarization. Nonequilibrium carrier distribution functions are determined by the pump field frequency $\omega$ as well as the ratio of intraband relaxation time $\tau$ and interband recombination time $\tau_{\mathrm{rec}}$. We obtain analytic results in three regimes, when (I) all relaxation processes are negligible, (II) $\tau \ll \tau_{\mathrm{rec}}$, and (III) $\tau \gg \tau_{\mathrm{rec}}$, and display corresponding asymptotic dependences on $\delta_\eta$ and $\omega$. We then apply our theory to two-dimensional transition-metal dichalcogenides, and find a strong enhancement of valley-dependent Hall conductivity as the pump field frequency approaches the transition energies between the pair of spin-resolved conduction and valence bands at the two valleys.
cond-mat.mes-hall
we present a theory of the photovoltaic valleydependent hall effect in a twodimensional dirac semiconductor subject to an intense nearresonant electromagnetic field our theory captures and elucidates the influence of both the fieldinduced resonant interband transitions and the nonequilibrium carrier kinetics on the resulting valley hall transport in terms of photondressed quasiparticles the nonperturbative renormalization effect of the pump field manifests itself in the dynamics of the photondressed quasiparticles with a quasienergy spectrum characterized by dynamical gaps delta_eta eta is the valley index that strongly depend on field amplitude and polarization nonequilibrium carrier distribution functions are determined by the pump field frequency omega as well as the ratio of intraband relaxation time tau and interband recombination time tau_mathrmrec we obtain analytic results in three regimes when i all relaxation processes are negligible ii tau ll tau_mathrmrec and iii tau gg tau_mathrmrec and display corresponding asymptotic dependences on delta_eta and omega we then apply our theory to twodimensional transitionmetal dichalcogenides and find a strong enhancement of valleydependent hall conductivity as the pump field frequency approaches the transition energies between the pair of spinresolved conduction and valence bands at the two valleys
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1,803.06608
Information-Theoretic Security or Covert Communication
Information-theoretic secrecy, in particular the wiretap channel formulation, provides protection against interception of a message by adversary Eve and has been widely studied in the last two decades. In contrast, covert communications under an analogous formulation provides protection against even the detection of the presence of the message by an adversary, and it has drawn significant interest recently. These two security topics are generally applicable in different scenarios; however, here we explore what can be learned by studying them under a common framework. Under a similar but not identical mathematical formulation, we introduce power optimization problems for each of the secrecy and the covert communications scenario, and we exploit common aspects of the problems to employ similar tools in their respective optimizations. Moreover, due to the practical limitations, we assume only channel
cs.CR
informationtheoretic secrecy in particular the wiretap channel formulation provides protection against interception of a message by adversary eve and has been widely studied in the last two decades in contrast covert communications under an analogous formulation provides protection against even the detection of the presence of the message by an adversary and it has drawn significant interest recently these two security topics are generally applicable in different scenarios however here we explore what can be learned by studying them under a common framework under a similar but not identical mathematical formulation we introduce power optimization problems for each of the secrecy and the covert communications scenario and we exploit common aspects of the problems to employ similar tools in their respective optimizations moreover due to the practical limitations we assume only channel
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1,803.06609
Fundamental group of non-singular locus of Lauricella's $F_C$
In this paper, we give a set of generators and relations of the fundamental group of the non-singular locus of Lauricella's hypergeometric functions
math.AG
in this paper we give a set of generators and relations of the fundamental group of the nonsingular locus of lauricellas hypergeometric functions
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1,803.0661
Can You Pave the Plane Nicely with Identical Tiles
Every body knows that identical regular triangles or squares can tile the whole plane. Many people know that identical regular hexagons can tile the plane properly as well. In fact, even the bees know and use this fact! Is there any other convex domain which can tile the Euclidean plane? Yes, there is a long list of them! To find the list and to show the completeness of the list is a unique drama in mathematics, which has lasted for more than one century and the completeness of the list has been mistakenly announced not only once! Up to now, the list consists of triangles, quadrilaterals, three types of hexagons, and fifteen types of pentagons. In 2017, Michael Rao announced a computer proof for the completeness of the list. Meanwhile, Qi Yang and Chuanming Zong made a series of unexpected discoveries in multiple tilings in the Euclidean plane. For examples, besides parallelograms and centrally symmetric hexagons, there is no other convex domain which can form any two-, three- or four-fold translative tiling in the plane; there are only two types of octagons and one type of decagons which can form five-fold translative tilings.
math.MG math.HO
every body knows that identical regular triangles or squares can tile the whole plane many people know that identical regular hexagons can tile the plane properly as well in fact even the bees know and use this fact is there any other convex domain which can tile the euclidean plane yes there is a long list of them to find the list and to show the completeness of the list is a unique drama in mathematics which has lasted for more than one century and the completeness of the list has been mistakenly announced not only once up to now the list consists of triangles quadrilaterals three types of hexagons and fifteen types of pentagons in 2017 michael rao announced a computer proof for the completeness of the list meanwhile qi yang and chuanming zong made a series of unexpected discoveries in multiple tilings in the euclidean plane for examples besides parallelograms and centrally symmetric hexagons there is no other convex domain which can form any two three or fourfold translative tiling in the plane there are only two types of octagons and one type of decagons which can form fivefold translative tilings
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1,803.06611
Active Manipulation of Electromagnetically Induced Transparency in a Terahertz Hybrid Metamaterial
The metamaterial analogue of electromagnetically induced transparency (EIT) in terahertz (THz) regime holds fascinating prospects for filling the THz gap in various functional devices. In this paper, we propose a novel hybrid metamaterial to actively manipulate the resonance strength of EIT effect. By integrating a monolayer graphene into a THz metal metamaterial, an on-to-off modulation of the EIT transparency window is achieved under different Fermi levels of graphene. According to the classical two-particle model and the distributions of the electric field and surface charge density, the physical mechanism is attributable to the recombination effect of conductive graphene. This work reveals a novel manipulation mechanism of EIT resonance in the hybrid metamaterial and offers a new perspective towards designing THz functional devices.
physics.optics
the metamaterial analogue of electromagnetically induced transparency eit in terahertz thz regime holds fascinating prospects for filling the thz gap in various functional devices in this paper we propose a novel hybrid metamaterial to actively manipulate the resonance strength of eit effect by integrating a monolayer graphene into a thz metal metamaterial an ontooff modulation of the eit transparency window is achieved under different fermi levels of graphene according to the classical twoparticle model and the distributions of the electric field and surface charge density the physical mechanism is attributable to the recombination effect of conductive graphene this work reveals a novel manipulation mechanism of eit resonance in the hybrid metamaterial and offers a new perspective towards designing thz functional devices
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1,803.06612
New form of the exact NSVZ $\beta$-function: the three-loop verification for terms containing Yukawa couplings
We investigate a recently proposed new form of the exact NSVZ $\beta$-function, which relates the $\beta$-function to the anomalous dimensions of the quantum gauge superfield, of the Faddeev--Popov ghosts, and of the chiral matter superfields. Namely, for the general renormalizable ${\cal N}=1$ supersymmetric gauge theory, regularized by higher covariant derivatives, the sum of all three-loop contributions to the $\beta$-function containing the Yukawa couplings is compared with the corresponding two-loop contributions to the anomalous dimensions of the quantum superfields. It is demonstrated that for the considered terms both new and original forms of the NSVZ relation are valid independently of the subtraction scheme if the renormalization group functions are defined in terms of the bare couplings. This result is obtained from the equality relating the loop integrals, which, in turn, follows from the factorization of the integrals for the $\beta$-function into integrals of double total derivatives. For the renormalization group functions defined in terms of the renormalized couplings we verify that the NSVZ scheme is obtained with the higher covariant derivative regularization supplemented by the subtraction scheme in which only powers of $\ln\Lambda/\mu$ are included into the renormalization constants.
hep-th
we investigate a recently proposed new form of the exact nsvz betafunction which relates the betafunction to the anomalous dimensions of the quantum gauge superfield of the faddeevpopov ghosts and of the chiral matter superfields namely for the general renormalizable cal n1 supersymmetric gauge theory regularized by higher covariant derivatives the sum of all threeloop contributions to the betafunction containing the yukawa couplings is compared with the corresponding twoloop contributions to the anomalous dimensions of the quantum superfields it is demonstrated that for the considered terms both new and original forms of the nsvz relation are valid independently of the subtraction scheme if the renormalization group functions are defined in terms of the bare couplings this result is obtained from the equality relating the loop integrals which in turn follows from the factorization of the integrals for the betafunction into integrals of double total derivatives for the renormalization group functions defined in terms of the renormalized couplings we verify that the nsvz scheme is obtained with the higher covariant derivative regularization supplemented by the subtraction scheme in which only powers of lnlambdamu are included into the renormalization constants
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1,803.06613
Trajectory-based Scene Understanding using Dirichlet Process Mixture Model
Appropriate modeling of a surveillance scene is essential for detection of anomalies in road traffic. Learning usual paths can provide valuable insight into road traffic conditions and thus can help in identifying unusual routes taken by commuters/vehicles. If usual traffic paths are learned in a nonparametric way, manual interventions in road marking road can be avoided. In this paper, we propose an unsupervised and nonparametric method to learn frequently used paths from the tracks of moving objects in $\Theta(kn)$ time, where $k$ denotes the number of paths and $n$ represents the number of tracks. In the proposed method, temporal dependencies of the moving objects are considered to make the clustering meaningful using Temporally Incremental Gravity Model (TIGM). In addition, the distance-based scene learning makes it intuitive to estimate the model parameters. Further, we have extended TIGM hierarchically as Dynamically Evolving Model (DEM) to represent notable traffic dynamics of a scene. Experimental validation reveals that the proposed method can learn a scene quickly without prior knowledge about the number of paths ($k$). We have compared the results with various state-of-the-art methods. We have also highlighted the advantages of the proposed method over existing techniques popularly used for designing traffic monitoring applications. It can be used for administrative decision making to control traffic at junctions or crowded places and generate alarm signals, if necessary.
cs.CV
appropriate modeling of a surveillance scene is essential for detection of anomalies in road traffic learning usual paths can provide valuable insight into road traffic conditions and thus can help in identifying unusual routes taken by commutersvehicles if usual traffic paths are learned in a nonparametric way manual interventions in road marking road can be avoided in this paper we propose an unsupervised and nonparametric method to learn frequently used paths from the tracks of moving objects in thetakn time where k denotes the number of paths and n represents the number of tracks in the proposed method temporal dependencies of the moving objects are considered to make the clustering meaningful using temporally incremental gravity model tigm in addition the distancebased scene learning makes it intuitive to estimate the model parameters further we have extended tigm hierarchically as dynamically evolving model dem to represent notable traffic dynamics of a scene experimental validation reveals that the proposed method can learn a scene quickly without prior knowledge about the number of paths k we have compared the results with various stateoftheart methods we have also highlighted the advantages of the proposed method over existing techniques popularly used for designing traffic monitoring applications it can be used for administrative decision making to control traffic at junctions or crowded places and generate alarm signals if necessary
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1,803.06614
On existence of out-of-plane equilibrium points in restricted three-body problem with oblateness
We analyze in this paper the existence of the "out-of-plane" equilibrium points in the restricted three-body problem with oblateness. From the series expansion of the potential function of an oblate asteroid, we show analytically all equilibrium points locate on the orbital plane of primaries and how artificial equilibrium points may arise due to an inappropriate application of the potential function. Using the closed form of the potential of a triaxial ellipsoid, we analytically demonstrate that the gravitational acceleration in $z$-direction is always pointing toward the equatorial plane, thus it could not be balanced out at any value of $z\neq 0$ and the out-of-plane equilibrium points cannot exist. The out-of-plane equilibrium points appear only when additional acceleration other than the gravitation from primaries is taken into account. We suggest that special attention must be paid to the application of the spherical harmonics expansion of potential to find the equilibrium points, especially when these points may be very close to the celestial body.
astro-ph.EP
we analyze in this paper the existence of the outofplane equilibrium points in the restricted threebody problem with oblateness from the series expansion of the potential function of an oblate asteroid we show analytically all equilibrium points locate on the orbital plane of primaries and how artificial equilibrium points may arise due to an inappropriate application of the potential function using the closed form of the potential of a triaxial ellipsoid we analytically demonstrate that the gravitational acceleration in zdirection is always pointing toward the equatorial plane thus it could not be balanced out at any value of zneq 0 and the outofplane equilibrium points cannot exist the outofplane equilibrium points appear only when additional acceleration other than the gravitation from primaries is taken into account we suggest that special attention must be paid to the application of the spherical harmonics expansion of potential to find the equilibrium points especially when these points may be very close to the celestial body
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1,803.06615
Feature Selection of Post-Graduation Income of College Students in the United States
This study investigated the most important attributes of the 6-year post-graduation income of college graduates who used financial aid during their time at college in the United States. The latest data released by the United States Department of Education was used. Specifically, 1,429 cohorts of graduates from three years (2001, 2003, and 2005) were included in the data analysis. Three attribute selection methods, including filter methods, forward selection, and Genetic Algorithm, were applied to the attribute selection from 30 relevant attributes. Five groups of machine learning algorithms were applied to the dataset for classification using the best selected attribute subsets. Based on our findings, we discuss the role of neighborhood professional degree attainment, parental income, SAT scores, and family college education in post-graduation incomes and the implications for social stratification.
cs.CY
this study investigated the most important attributes of the 6year postgraduation income of college graduates who used financial aid during their time at college in the united states the latest data released by the united states department of education was used specifically 1429 cohorts of graduates from three years 2001 2003 and 2005 were included in the data analysis three attribute selection methods including filter methods forward selection and genetic algorithm were applied to the attribute selection from 30 relevant attributes five groups of machine learning algorithms were applied to the dataset for classification using the best selected attribute subsets based on our findings we discuss the role of neighborhood professional degree attainment parental income sat scores and family college education in postgraduation incomes and the implications for social stratification
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1,803.06616
Actively controlling the topological transition of dispersion based on electrically controllable metamaterials
Topological transition of the iso-frequency contour (IFC) from a closed ellipsoid to an open hyperboloid, will provide unique capabilities for controlling the propagation of light. However, the ability to actively tune these effects remains elusive and the related experimental observations are highly desirable. Here, tunable electric IFC in periodic structure which is composed of graphene/dielectric multilayers is investigated by tuning the chemical potential of graphene layer. Specially, we present the actively controlled transportation in two kinds of anisotropic zero-index media containing PEC/PMC impurities. At last, by adding variable capacitance diodes into two-dimensional transmission-line system, we present the experimental demonstration of the actively controlled magnetic topological transition of dispersion based on electrically controllable metamaterials. With the increase of voltage, we measure the different emission patterns from a point source inside the structure and observe the phase-transition process of IFCs. The realization of actively tuned topological transition will opens up a new avenue in the dynamical control of metamaterials.
physics.optics
topological transition of the isofrequency contour ifc from a closed ellipsoid to an open hyperboloid will provide unique capabilities for controlling the propagation of light however the ability to actively tune these effects remains elusive and the related experimental observations are highly desirable here tunable electric ifc in periodic structure which is composed of graphenedielectric multilayers is investigated by tuning the chemical potential of graphene layer specially we present the actively controlled transportation in two kinds of anisotropic zeroindex media containing pecpmc impurities at last by adding variable capacitance diodes into twodimensional transmissionline system we present the experimental demonstration of the actively controlled magnetic topological transition of dispersion based on electrically controllable metamaterials with the increase of voltage we measure the different emission patterns from a point source inside the structure and observe the phasetransition process of ifcs the realization of actively tuned topological transition will opens up a new avenue in the dynamical control of metamaterials
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1,803.06617
Towards an Area-Efficient Implementation of a High ILP EDGE Soft Processor
In-order scalar RISC architectures have been the dominant paradigm in FPGA soft processor design for twenty years. Prior out-of-order superscalar implementations have not exhibited competitive area or absolute performance. This paper describes a new way to build fast and area-efficient out-of-order superscalar soft processors by utilizing an Explicit Data Graph Execution (EDGE) instruction set architecture. By carefully mapping the EDGE microarchitecture, and in particular, its dataflow instruction scheduler, we demonstrate the feasibility of an out-of-order FPGA architecture. Two scheduler design alternatives are compared.
cs.AR
inorder scalar risc architectures have been the dominant paradigm in fpga soft processor design for twenty years prior outoforder superscalar implementations have not exhibited competitive area or absolute performance this paper describes a new way to build fast and areaefficient outoforder superscalar soft processors by utilizing an explicit data graph execution edge instruction set architecture by carefully mapping the edge microarchitecture and in particular its dataflow instruction scheduler we demonstrate the feasibility of an outoforder fpga architecture two scheduler design alternatives are compared
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1,803.06618
Simple mechanisms that impede the Berry phase identification from magneto-oscillations
The phase of quantum magneto-oscillations is often associated with the Berry phase and is widely used to argue in favor of topological nontriviality of the system (Berry phase $2\pi n+\pi$). Nevertheless, the experimentally determined value may deviate from $2\pi n+\pi$ arbitrarily, therefore more care should be made analyzing the phase of magneto-oscillations to distinguish trivial systems from nontrivial. In this paper we suggest two simple mechanisms dramatically affecting the experimentally observed value of the phase in three-dimensional topological insulators: (i) magnetic field dependence of the chemical potential, and (ii) possible nonuniformity of the system. These mechanisms are not limited to topological insulators and can be extended to other topologically trivial and non-trivial systems.
cond-mat.str-el cond-mat.mes-hall
the phase of quantum magnetooscillations is often associated with the berry phase and is widely used to argue in favor of topological nontriviality of the system berry phase 2pi npi nevertheless the experimentally determined value may deviate from 2pi npi arbitrarily therefore more care should be made analyzing the phase of magnetooscillations to distinguish trivial systems from nontrivial in this paper we suggest two simple mechanisms dramatically affecting the experimentally observed value of the phase in threedimensional topological insulators i magnetic field dependence of the chemical potential and ii possible nonuniformity of the system these mechanisms are not limited to topological insulators and can be extended to other topologically trivial and nontrivial systems
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1,803.06619
The impact of Hubbard- and van der Waals-corrections on the DFT calculation of epsilon-zeta transition pressure in solid oxygen
The aim of this study is to clarify the physics which governs the transition from epsilon phase to zeta phase of solid oxygen observed experimentally at 96 GPa using density functional theory (DFT). The transition was predicted at 40 GPa with PBE functional. Then the Hubbard correction was added to enhance the localization of p-orbital of oxygen. The epsilon-zeta transition pressure was significantly improved to 70 GPa. Finally, we included the non-local van der Waals correction. The transition pressure slightly increases to 80 GPa. These results demonstrate that the contribution from Hubbard term is superior to van der Waals term.
cond-mat.mtrl-sci
the aim of this study is to clarify the physics which governs the transition from epsilon phase to zeta phase of solid oxygen observed experimentally at 96 gpa using density functional theory dft the transition was predicted at 40 gpa with pbe functional then the hubbard correction was added to enhance the localization of porbital of oxygen the epsilonzeta transition pressure was significantly improved to 70 gpa finally we included the nonlocal van der waals correction the transition pressure slightly increases to 80 gpa these results demonstrate that the contribution from hubbard term is superior to van der waals term
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1,803.0662
Characterizations of the Logistic and Related Distributions
It is known that few characterization results of the logistic distribution were available before, although it is similar in shape to the normal one whose characteristic properties have been well investigated. Fortunately, in the last decade, several authors have made great progress in this topic. Some interesting characterization results of the logistic distribution have been developed recently. In this paper, we further provide some new results by the distributional equalities in terms of order statistics of the underlying distribution and the random exponential shifts. The characterization of the closely related Pareto type II distribution is also investigated.
math.ST math.PR stat.TH
it is known that few characterization results of the logistic distribution were available before although it is similar in shape to the normal one whose characteristic properties have been well investigated fortunately in the last decade several authors have made great progress in this topic some interesting characterization results of the logistic distribution have been developed recently in this paper we further provide some new results by the distributional equalities in terms of order statistics of the underlying distribution and the random exponential shifts the characterization of the closely related pareto type ii distribution is also investigated
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1,803.06621
Future of Pulsar Research and Facilities
Radio pulsars have been responsible for many astonishing astrophysical and fundamental physics breakthroughs since their discovery 50 years ago. In this review I will discuss many of the highlights, most of which were only possible because of the provision of large-scale observing facilities. The next 50 years of pulsar astronomy can be very bright, but only if our governments properly plan and fund the infrastructure necessary to enable future discoveries. Being a small sub-field of astronomy places an onus on the pulsar community to have an open-source/open access approach to data, software, and major observing facilities to enable new groups to emerge to keep the field vibrant.
astro-ph.IM
radio pulsars have been responsible for many astonishing astrophysical and fundamental physics breakthroughs since their discovery 50 years ago in this review i will discuss many of the highlights most of which were only possible because of the provision of largescale observing facilities the next 50 years of pulsar astronomy can be very bright but only if our governments properly plan and fund the infrastructure necessary to enable future discoveries being a small subfield of astronomy places an onus on the pulsar community to have an opensourceopen access approach to data software and major observing facilities to enable new groups to emerge to keep the field vibrant
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1,803.06622
Learning recurrent dynamics in spiking networks
Spiking activity of neurons engaged in learning and performing a task show complex spatiotemporal dynamics. While the output of recurrent network models can learn to perform various tasks, the possible range of recurrent dynamics that emerge after learning remains unknown. Here we show that modifying the recurrent connectivity with a recursive least squares algorithm provides sufficient flexibility for synaptic and spiking rate dynamics of spiking networks to produce a wide range of spatiotemporal activity. We apply the training method to learn arbitrary firing patterns, stabilize irregular spiking activity of a balanced network, and reproduce the heterogeneous spiking rate patterns of cortical neurons engaged in motor planning and movement. We identify sufficient conditions for successful learning, characterize two types of learning errors, and assess the network capacity. Our findings show that synaptically-coupled recurrent spiking networks possess a vast computational capability that can support the diverse activity patterns in the brain.
q-bio.NC cs.AI cs.LG cs.NE
spiking activity of neurons engaged in learning and performing a task show complex spatiotemporal dynamics while the output of recurrent network models can learn to perform various tasks the possible range of recurrent dynamics that emerge after learning remains unknown here we show that modifying the recurrent connectivity with a recursive least squares algorithm provides sufficient flexibility for synaptic and spiking rate dynamics of spiking networks to produce a wide range of spatiotemporal activity we apply the training method to learn arbitrary firing patterns stabilize irregular spiking activity of a balanced network and reproduce the heterogeneous spiking rate patterns of cortical neurons engaged in motor planning and movement we identify sufficient conditions for successful learning characterize two types of learning errors and assess the network capacity our findings show that synapticallycoupled recurrent spiking networks possess a vast computational capability that can support the diverse activity patterns in the brain
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1,803.06623
The invariant subspaces of the shift plus integer multiple of Volterra operator on Hardy spaces
\v{C}u\v{c}kovi\'{c} and Paudyal recently characterized the lattice of invariant subspaces of the shift plus a complex Volterra operator on the Hilbert space $H^2$ on the unit disk. Motivated by the idea of Ong, in this paper, we give a complete characterization of the lattice of invariant subspaces of the shift operator plus a positive integer multiple of the Volterra operator on Hardy spaces $H^p$, which essentially extends their works to the more general cases when $1\leq p<\infty$.
math.CV
vcuvckovic and paudyal recently characterized the lattice of invariant subspaces of the shift plus a complex volterra operator on the hilbert space h2 on the unit disk motivated by the idea of ong in this paper we give a complete characterization of the lattice of invariant subspaces of the shift operator plus a positive integer multiple of the volterra operator on hardy spaces hp which essentially extends their works to the more general cases when 1leq pinfty
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1,803.06624
Blind quantum computing can always be made verifiable
Blind quantum computing enables a client, who does not have enough quantum technologies, to delegate her quantum computing to a remote quantum server in such a way that her privacy is protected against the server. Some blind quantum computing protocols can be made verifiable, which means that the client can check the correctness of server's quantum computing. Can any blind protocol always be made verifiable? In this paper, we answer to the open problem affirmatively. We propose a plug-in that makes any universal blind quantum computing protocol automatically verifiable. The idea is that the client blindly generates Feynman-Kitaev history states corresponding to the quantum circuit that solves client's problem and its complement circuit. The client can learn the solution of the problem and verify its correctness at the same time by measuring energies of local Hamiltonians on these states. Measuring energies of local Hamiltonians can be done with only single qubit measurements of Pauli operators.
quant-ph
blind quantum computing enables a client who does not have enough quantum technologies to delegate her quantum computing to a remote quantum server in such a way that her privacy is protected against the server some blind quantum computing protocols can be made verifiable which means that the client can check the correctness of servers quantum computing can any blind protocol always be made verifiable in this paper we answer to the open problem affirmatively we propose a plugin that makes any universal blind quantum computing protocol automatically verifiable the idea is that the client blindly generates feynmankitaev history states corresponding to the quantum circuit that solves clients problem and its complement circuit the client can learn the solution of the problem and verify its correctness at the same time by measuring energies of local hamiltonians on these states measuring energies of local hamiltonians can be done with only single qubit measurements of pauli operators
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1,803.06625
ShIFT: A Semi-haptic Interface for Flute Tutoring
Traditional instrument learning is time-consuming. It begins with learning music notation and necessitates layers of sophistication and abstraction. Haptic interfaces open another door to the music world for the vast majority of beginners when traditional training methods are not effective. However, existing haptic interfaces can only deal with specially designed pieces with great restrictions on performance duration and pitch range due to the fact that not all performance motions could be guided haptically for most instruments. Our system breaks such restrictions using a semi-haptic interface. For the first time, the pitch range of the haptically learned pieces goes beyond an octave (with the fingering motion covers most of the possible choices) and the duration of learned pieces cover a whole phrase. This significant change leads to a more realistic instrument learning process. Experiments show that our semi-haptic interface is effective as long as learners are not "tone deaf." Using our prototype device, the learning rate is about 30% faster compared to learning from videos.
cs.HC
traditional instrument learning is timeconsuming it begins with learning music notation and necessitates layers of sophistication and abstraction haptic interfaces open another door to the music world for the vast majority of beginners when traditional training methods are not effective however existing haptic interfaces can only deal with specially designed pieces with great restrictions on performance duration and pitch range due to the fact that not all performance motions could be guided haptically for most instruments our system breaks such restrictions using a semihaptic interface for the first time the pitch range of the haptically learned pieces goes beyond an octave with the fingering motion covers most of the possible choices and the duration of learned pieces cover a whole phrase this significant change leads to a more realistic instrument learning process experiments show that our semihaptic interface is effective as long as learners are not tone deaf using our prototype device the learning rate is about 30 faster compared to learning from videos
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1,803.06626
The Automatic Identification of Butterfly Species
The available butterfly data sets comprise a few limited species, and the images in the data sets are always standard patterns without the images of butterflies in their living environment. To overcome the aforementioned limitations in the butterfly data sets, we build a butterfly data set composed of all species of butterflies in China with 4270 standard pattern images of 1176 butterfly species, and 1425 images from living environment of 111 species. We propose to use the deep learning technique Faster-Rcnn to train an automatic butterfly identification system including butterfly position detection and species recognition. We delete those species with only one living environment image from data set, then partition the rest images from living environment into two subsets, one used as test subset, the other as training subset respectively combined with all standard pattern butterfly images or the standard pattern butterfly images with the same species of the images from living environment. In order to construct the training subset for FasterRcnn, nine methods were adopted to amplifying the images in the training subset including the turning of up and down, and left and right, rotation with different angles, adding noises, blurring, and contrast ratio adjusting etc. Three prediction models were trained. The mAP (Mean Average prediction) criterion was used to evaluate the performance of the prediction model. The experimental results demonstrate that our Faster-Rcnn based butterfly automatic identification system performed well, and its worst mAP is up to 60%, and can simultaneously detect the positions of more than one butterflies in one images from living environment and recognize the species of those butterflies as well.
cs.CV
the available butterfly data sets comprise a few limited species and the images in the data sets are always standard patterns without the images of butterflies in their living environment to overcome the aforementioned limitations in the butterfly data sets we build a butterfly data set composed of all species of butterflies in china with 4270 standard pattern images of 1176 butterfly species and 1425 images from living environment of 111 species we propose to use the deep learning technique fasterrcnn to train an automatic butterfly identification system including butterfly position detection and species recognition we delete those species with only one living environment image from data set then partition the rest images from living environment into two subsets one used as test subset the other as training subset respectively combined with all standard pattern butterfly images or the standard pattern butterfly images with the same species of the images from living environment in order to construct the training subset for fasterrcnn nine methods were adopted to amplifying the images in the training subset including the turning of up and down and left and right rotation with different angles adding noises blurring and contrast ratio adjusting etc three prediction models were trained the map mean average prediction criterion was used to evaluate the performance of the prediction model the experimental results demonstrate that our fasterrcnn based butterfly automatic identification system performed well and its worst map is up to 60 and can simultaneously detect the positions of more than one butterflies in one images from living environment and recognize the species of those butterflies as well
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1,803.06627
How to sheafify an elliptic quantum group
We give an introductory survey of the results in arXiv: 1708.01418. We discuss a sheafified elliptic quantum group associated to any symmetric Kac-Moody Lie algebra. The sheafification is obtained by applying the equivariant elliptic cohomological theory to the moduli space of representations of a preprojective algebra. By construction, the elliptic quantum group naturally acts on the equivariant elliptic cohomology of Nakajima quiver varieties. As an application, we obtain a relation between the sheafified elliptic quantum group and the global affine Grassmannian over an elliptic curve.
math.RT
we give an introductory survey of the results in arxiv 170801418 we discuss a sheafified elliptic quantum group associated to any symmetric kacmoody lie algebra the sheafification is obtained by applying the equivariant elliptic cohomological theory to the moduli space of representations of a preprojective algebra by construction the elliptic quantum group naturally acts on the equivariant elliptic cohomology of nakajima quiver varieties as an application we obtain a relation between the sheafified elliptic quantum group and the global affine grassmannian over an elliptic curve
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1,803.06628
A machine learning method to separate cosmic ray electrons from protons from 10 to 100 GeV using DAMPE data
DArk Matter Particle Explorer (DAMPE) is a general purpose high energy cosmic ray and gamma ray observatory, aiming to detect high energy electrons and gammas in the energy range 5 GeV to 10 TeV and hundreds of TeV for nuclei. This paper provides a method using machine learning to identify electrons and separate them from gammas,protons,helium and heavy nuclei with the DAMPE data from 2016 January 1 to 2017 June 30, in energy range from 10 to 100 GeV.
astro-ph.IM physics.ins-det
dark matter particle explorer dampe is a general purpose high energy cosmic ray and gamma ray observatory aiming to detect high energy electrons and gammas in the energy range 5 gev to 10 tev and hundreds of tev for nuclei this paper provides a method using machine learning to identify electrons and separate them from gammasprotonshelium and heavy nuclei with the dampe data from 2016 january 1 to 2017 june 30 in energy range from 10 to 100 gev
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1,803.06629
Cross-modality image synthesis from unpaired data using CycleGAN: Effects of gradient consistency loss and training data size
CT is commonly used in orthopedic procedures. MRI is used along with CT to identify muscle structures and diagnose osteonecrosis due to its superior soft tissue contrast. However, MRI has poor contrast for bone structures. Clearly, it would be helpful if a corresponding CT were available, as bone boundaries are more clearly seen and CT has standardized (i.e., Hounsfield) units. Therefore, we aim at MR-to-CT synthesis. The CycleGAN was successfully applied to unpaired CT and MR images of the head, these images do not have as much variation of intensity pairs as do images in the pelvic region due to the presence of joints and muscles. In this paper, we extended the CycleGAN approach by adding the gradient consistency loss to improve the accuracy at the boundaries. We conducted two experiments. To evaluate image synthesis, we investigated dependency of image synthesis accuracy on 1) the number of training data and 2) the gradient consistency loss. To demonstrate the applicability of our method, we also investigated a segmentation accuracy on synthesized images.
cs.CV
ct is commonly used in orthopedic procedures mri is used along with ct to identify muscle structures and diagnose osteonecrosis due to its superior soft tissue contrast however mri has poor contrast for bone structures clearly it would be helpful if a corresponding ct were available as bone boundaries are more clearly seen and ct has standardized ie hounsfield units therefore we aim at mrtoct synthesis the cyclegan was successfully applied to unpaired ct and mr images of the head these images do not have as much variation of intensity pairs as do images in the pelvic region due to the presence of joints and muscles in this paper we extended the cyclegan approach by adding the gradient consistency loss to improve the accuracy at the boundaries we conducted two experiments to evaluate image synthesis we investigated dependency of image synthesis accuracy on 1 the number of training data and 2 the gradient consistency loss to demonstrate the applicability of our method we also investigated a segmentation accuracy on synthesized images
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1,803.0663
Stellar Yields of Rotating First Stars. II. Pair Instability Supernovae and Comparison with Observations
Recent theory predicts that a first star is born with a massive initial mass of $\gtrsim$ 100 $M_\odot$. Pair instability supernova (PISN) is a common fate for such a massive star. Our final goal is to prove the existence of PISN and thus the high mass nature of the initial mass function in the early universe by conducting {\it abundance profiling}, in which properties of a hypothetical first star is constrained by metal-poor star abundances. In order to determine reliable and useful abundances, we investigate the PISN nucleosynthesis taking both rotating and non-rotating progenitors for the first time. We show that the initial and CO core mass ranges for PISNe depend on the envelope structures: non-magnetic rotating models developing inflated envelopes have a lower-shifted CO mass range of $\sim$ 70--125 $M_\odot$, while non-rotating and magnetic rotating models with deflated envelopes have a range of $\sim$ 80--135 $M_\odot$. However, we find no significant difference in explosive yields from rotating and non-rotating progenitors, except for large nitrogen production in non-magnetic rotating models. Furthermore, we conduct the first systematic comparison between theoretical yields and a large sample of metal-poor star abundances. We find that the predicted low [Na/Mg] $\sim$ $-1.5$ and high [Ca/Mg] $\sim$ $0.5$--$1.3$ abundance ratios are the most important to discriminate PISN signatures from normal metal-poor star abundances, and confirm that no currently observed metal-poor star matches with the PISN abundance. Extensive discussion on the non-detection is finally made.
astro-ph.SR
recent theory predicts that a first star is born with a massive initial mass of gtrsim 100 m_odot pair instability supernova pisn is a common fate for such a massive star our final goal is to prove the existence of pisn and thus the high mass nature of the initial mass function in the early universe by conducting it abundance profiling in which properties of a hypothetical first star is constrained by metalpoor star abundances in order to determine reliable and useful abundances we investigate the pisn nucleosynthesis taking both rotating and nonrotating progenitors for the first time we show that the initial and co core mass ranges for pisne depend on the envelope structures nonmagnetic rotating models developing inflated envelopes have a lowershifted co mass range of sim 70125 m_odot while nonrotating and magnetic rotating models with deflated envelopes have a range of sim 80135 m_odot however we find no significant difference in explosive yields from rotating and nonrotating progenitors except for large nitrogen production in nonmagnetic rotating models furthermore we conduct the first systematic comparison between theoretical yields and a large sample of metalpoor star abundances we find that the predicted low namg sim 15 and high camg sim 0513 abundance ratios are the most important to discriminate pisn signatures from normal metalpoor star abundances and confirm that no currently observed metalpoor star matches with the pisn abundance extensive discussion on the nondetection is finally made
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1,803.06631
A Deal with the Devil: From Divergent Perturbation Theory to an Exponentially-Convergent Self-Consistent Expansion
For many nonlinear physical systems, approximate solutions are pursued by conventional perturbation theory in powers of the non-linear terms. Unfortunately, this often produces divergent asymptotic series, collectively dismissed by Abel as "an invention of the devil." An alternative method, the self-consistent expansion (SCE), has been introduced by Schwartz and Edwards. Its basic idea is a rescaling of the zeroth-order system around which the solution is expanded, to achieve optimal results. While low-order SCEs have been remarkably successful in describing the dynamics of non-equilibrium many-body systems (e.g., the Kardar-Parisi-Zhang equation), its convergence properties have not been elucidated before. To address this issue we apply this technique to the canonical partition function of the classical harmonic oscillator with a quartic $gx^{4}$ anharmonicity, for which perturbation theory's divergence is well-known. We obtain the $N$th order SCE for the partition function, which is rigorously found to converge exponentially fast in $N$, and uniformly in $g\ge0$. We use our results to elucidate the relation between the SCE and the class of approaches based on the so-called "order-dependent mapping." Moreover, we put the SCE to test against other methods that improve upon perturbation theory (Borel resummation, hyperasymptotics, Pad\'e approximants, and the Lanczos $\tau$-method), and find that it compares favorably with all of them for small $g$ and dominates over them for large $g$. The SCE is shown to successfully capture the correct partition function for the double-well potential case, where no perturbative expansion exists. Our treatment is generalized to the case of many oscillators, as well as to any nonlinearity of the form $g|x|^{q}$ with $q\ge0$ and complex $g$. These results allow us to treat the Airy function, and to see the fingerprints of Stokes lines in the SCE.
math-ph cond-mat.stat-mech hep-th math.MP
for many nonlinear physical systems approximate solutions are pursued by conventional perturbation theory in powers of the nonlinear terms unfortunately this often produces divergent asymptotic series collectively dismissed by abel as an invention of the devil an alternative method the selfconsistent expansion sce has been introduced by schwartz and edwards its basic idea is a rescaling of the zerothorder system around which the solution is expanded to achieve optimal results while loworder sces have been remarkably successful in describing the dynamics of nonequilibrium manybody systems eg the kardarparisizhang equation its convergence properties have not been elucidated before to address this issue we apply this technique to the canonical partition function of the classical harmonic oscillator with a quartic gx4 anharmonicity for which perturbation theorys divergence is wellknown we obtain the nth order sce for the partition function which is rigorously found to converge exponentially fast in n and uniformly in gge0 we use our results to elucidate the relation between the sce and the class of approaches based on the socalled orderdependent mapping moreover we put the sce to test against other methods that improve upon perturbation theory borel resummation hyperasymptotics pade approximants and the lanczos taumethod and find that it compares favorably with all of them for small g and dominates over them for large g the sce is shown to successfully capture the correct partition function for the doublewell potential case where no perturbative expansion exists our treatment is generalized to the case of many oscillators as well as to any nonlinearity of the form gxq with qge0 and complex g these results allow us to treat the airy function and to see the fingerprints of stokes lines in the sce
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1,803.06632
A Guided FP-growth algorithm for multitude-targeted mining of big data
In this paper we present the GFP-growth (Guided FP-growth) algorithm, a novel method for multitude-targeted mining: finding the count of a given large list of itemsets in large data. The GFP-growth algorithm is designed to focus on the specific multitude itemsets of interest and optimizes the time and memory costs. We prove that the GFP-growth algorithm yields the exact frequency-counts for the required itemsets. We show that for a number of different problems, a solution can be devised which takes advantage of the efficient implementation of multitude-targeted mining for boosting the performance. In particular, we study in detail the problem of generating the minority-class rules from imbalanced data, a scenario that appears in many real-life domains such as medical applications, failure prediction, network and cyber security, and maintenance. We develop the Minority-Report Algorithm that uses the GFP-growth for boosting performance. We prove some theoretical properties of the Minority-Report Algorithm and demonstrate its performance gain using simulations and real data.
cs.DB
in this paper we present the gfpgrowth guided fpgrowth algorithm a novel method for multitudetargeted mining finding the count of a given large list of itemsets in large data the gfpgrowth algorithm is designed to focus on the specific multitude itemsets of interest and optimizes the time and memory costs we prove that the gfpgrowth algorithm yields the exact frequencycounts for the required itemsets we show that for a number of different problems a solution can be devised which takes advantage of the efficient implementation of multitudetargeted mining for boosting the performance in particular we study in detail the problem of generating the minorityclass rules from imbalanced data a scenario that appears in many reallife domains such as medical applications failure prediction network and cyber security and maintenance we develop the minorityreport algorithm that uses the gfpgrowth for boosting performance we prove some theoretical properties of the minorityreport algorithm and demonstrate its performance gain using simulations and real data
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1,803.06633
Effects of the equation of state on the core-crust interface of slowly rotating neutron stars
We systematically study the symmetry energy effects of the transition density $n_{\rm t}$ and the transition pressure $P_{\rm t}$ around the crust-core interface of a neutron star in the framework of the dynamical and the thermodynamical method respectively. We employ both the parabolic approximation and the full expansion, for the definition of the symmetry energy. We use various theoretical nuclear models, which are suitable for reproducing the bulk properties of nuclear matter at low densities, close to saturation density as well as the maximum observational neutron star mass. Firstly we derive and present an approximation for the transition pressure $P_{\rm t}$ and crustal mass $M_{\rm crust}$. Secondly, we explore the effects of the Equation of State (EoS) on a few astrophysical applications which are sensitive to the values of $n_{\rm t}$ and $P_{\rm t}$ including neutron star oscillation frequencies, thermal relaxation of the crust, crustal fraction of the moment of inertia and the r-mode instability window of a rotating neutron star. We found that the above quantities are sensitive mainly on the applied approximation for the symmetry energy (confirming previous results). Furthermore, an additional sensitivity also exists, depending on the used method (dynamical or thermodynamical). The above findings lead us to claim that the determination of the $n_{\rm t}$ and $P_{\rm t}$ must be reliable and accurate before they are used to constrain relevant neutron star properties.
nucl-th astro-ph.HE
we systematically study the symmetry energy effects of the transition density n_rm t and the transition pressure p_rm t around the crustcore interface of a neutron star in the framework of the dynamical and the thermodynamical method respectively we employ both the parabolic approximation and the full expansion for the definition of the symmetry energy we use various theoretical nuclear models which are suitable for reproducing the bulk properties of nuclear matter at low densities close to saturation density as well as the maximum observational neutron star mass firstly we derive and present an approximation for the transition pressure p_rm t and crustal mass m_rm crust secondly we explore the effects of the equation of state eos on a few astrophysical applications which are sensitive to the values of n_rm t and p_rm t including neutron star oscillation frequencies thermal relaxation of the crust crustal fraction of the moment of inertia and the rmode instability window of a rotating neutron star we found that the above quantities are sensitive mainly on the applied approximation for the symmetry energy confirming previous results furthermore an additional sensitivity also exists depending on the used method dynamical or thermodynamical the above findings lead us to claim that the determination of the n_rm t and p_rm t must be reliable and accurate before they are used to constrain relevant neutron star properties
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1,803.06634
Detection of a Double Relic in the Torpedo Cluster: SPT-CL J0245-5302
The Torpedo cluster, SPT-CL J0245-5302 (S0295) is a massive, merging cluster at a redshift of z = 0.300, which exhibits a strikingly similar morphology to the Bullet cluster 1E 0657-55.8 (z = 0.296), including a classic bow shock in the cluster's intra-cluster medium revealed by Chandra X-ray observations. We present Australia Telescope Compact Array data centred at 2.1 GHz and Murchison Widefield Array data at frequencies between 72 MHz and 231 MHz which we use to study the properties of the cluster. We characterise a number of discrete and diffuse radio sources in the cluster, including the detection of two previously unknown radio relics on the cluster periphery. The average spectral index of the diffuse emission between 70 MHz and 3.1 GHz is $\alpha=-1.63_{-0.10}^{+0.10}$ and a radio-derived Mach number for the shock in the west of the cluster is calculated as M = 2.04. The Torpedo cluster is thus as a double relic system at moderate redshift.
astro-ph.GA
the torpedo cluster sptcl j02455302 s0295 is a massive merging cluster at a redshift of z 0300 which exhibits a strikingly similar morphology to the bullet cluster 1e 0657558 z 0296 including a classic bow shock in the clusters intracluster medium revealed by chandra xray observations we present australia telescope compact array data centred at 21 ghz and murchison widefield array data at frequencies between 72 mhz and 231 mhz which we use to study the properties of the cluster we characterise a number of discrete and diffuse radio sources in the cluster including the detection of two previously unknown radio relics on the cluster periphery the average spectral index of the diffuse emission between 70 mhz and 31 ghz is alpha163_010010 and a radioderived mach number for the shock in the west of the cluster is calculated as m 204 the torpedo cluster is thus as a double relic system at moderate redshift
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1,803.06635
A stabilized cut discontinuous Galerkin framework: I. Elliptic boundary value and interface problems
We develop a stabilized cut discontinuous Galerkin framework for the numerical solution of el- liptic boundary value and interface problems on complicated domains. The domain of interest is embedded in a structured, unfitted background mesh in R d , so that the boundary or interface can cut through it in an arbitrary fashion. The method is based on an unfitted variant of the classical symmetric interior penalty method using piecewise discontinuous polynomials defined on the back- ground mesh. Instead of the cell agglomeration technique commonly used in previously introduced unfitted discontinuous Galerkin methods, we employ and extend ghost penalty techniques from recently developed continuous cut finite element methods, which allows for a minimal extension of existing fitted discontinuous Galerkin software to handle unfitted geometries. Identifying four abstract assumptions on the ghost penalty, we derive geometrically robust a priori error and con- dition number estimates for the Poisson boundary value problem which hold irrespective of the particular cut configuration. Possible realizations of suitable ghost penalties are discussed. We also demonstrate how the framework can be elegantly applied to discretize high contrast interface problems. The theoretical results are illustrated by a number of numerical experiments for various approximation orders and for two and three-dimensional test problems.
math.NA cs.CE cs.NA
we develop a stabilized cut discontinuous galerkin framework for the numerical solution of el liptic boundary value and interface problems on complicated domains the domain of interest is embedded in a structured unfitted background mesh in r d so that the boundary or interface can cut through it in an arbitrary fashion the method is based on an unfitted variant of the classical symmetric interior penalty method using piecewise discontinuous polynomials defined on the back ground mesh instead of the cell agglomeration technique commonly used in previously introduced unfitted discontinuous galerkin methods we employ and extend ghost penalty techniques from recently developed continuous cut finite element methods which allows for a minimal extension of existing fitted discontinuous galerkin software to handle unfitted geometries identifying four abstract assumptions on the ghost penalty we derive geometrically robust a priori error and con dition number estimates for the poisson boundary value problem which hold irrespective of the particular cut configuration possible realizations of suitable ghost penalties are discussed we also demonstrate how the framework can be elegantly applied to discretize high contrast interface problems the theoretical results are illustrated by a number of numerical experiments for various approximation orders and for two and threedimensional test problems
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1,803.06636
Complexity problems in enumerative combinatorics
We give a broad survey of recent results in Enumerative Combinatorics and their complexity aspects.
math.CO cs.CC cs.DM math.HO math.PR
we give a broad survey of recent results in enumerative combinatorics and their complexity aspects
[['we', 'give', 'a', 'broad', 'survey', 'of', 'recent', 'results', 'in', 'enumerative', 'combinatorics', 'and', 'their', 'complexity', 'aspects']]
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1,803.06637
The nodal set of solutions to some elliptic problems: singular nonlinearities
This paper deals with solutions to the equation \begin{equation*} -\Delta u = \lambda_+ \left(u^+\right)^{q-1} - \lambda_- \left(u^-\right)^{q-1} \quad \text{in $B_1$} \end{equation*} where $\lambda_+,\lambda_- > 0$, $q \in (0,1)$, $B_1=B_1(0)$ is the unit ball in $\mathbb{R}^N$, $N \ge 2$, and $u^+:= \max\{u,0\}$, $u^-:= \max\{-u,0\}$ are the positive and the negative part of $u$, respectively. We extend to this class of \emph{singular} equations the results recently obtained in \cite{SoTe2018} for \emph{sublinear and discontinuous} equations, $1\leq q<2$, namely: (a) the finiteness of the vanishing order at every point and the complete characterization of the order spectrum; (b) a weak non-degeneracy property; (c) regularity of the nodal set of any solution: the nodal set is a locally finite collection of regular codimension one manifolds up to a residual singular set having Hausdorff dimension at most $N-2$ (locally finite when $N=2$). As an intermediate step, we establish the regularity of a class of \emph{not necessarily minimal} solutions. The proofs are based on a priori bounds, monotonicity formul\ae \ for a $2$-parameter family of Weiss-type functionals, blow-up arguments, and the classification of homogenous solutions.
math.AP
this paper deals with solutions to the equation beginequation delta u lambda_ lefturightq1 lambda_ lefturightq1 quad textin b_1 endequation where lambda_lambda_ 0 q in 01 b_1b_10 is the unit ball in mathbbrn n ge 2 and u maxu0 u maxu0 are the positive and the negative part of u respectively we extend to this class of emphsingular equations the results recently obtained in citesote2018 for emphsublinear and discontinuous equations 1leq q2 namely a the finiteness of the vanishing order at every point and the complete characterization of the order spectrum b a weak nondegeneracy property c regularity of the nodal set of any solution the nodal set is a locally finite collection of regular codimension one manifolds up to a residual singular set having hausdorff dimension at most n2 locally finite when n2 as an intermediate step we establish the regularity of a class of emphnot necessarily minimal solutions the proofs are based on a priori bounds monotonicity formulae for a 2parameter family of weisstype functionals blowup arguments and the classification of homogenous solutions
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1,803.06638
Adaptive Decision Making via Entropy Minimization
An agent choosing between various actions tends to take the one with the lowest cost. But this choice is arguably too rigid (not adaptive) to be useful in complex situations, e.g., where exploration-exploitation trade-off is relevant in creative task solving or when stated preferences differ from revealed ones. Here we study an agent who is willing to sacrifice a fixed amount of expected utility for adaptation. How can/ought our agent choose an optimal (in a technical sense) mixed action? We explore consequences of making this choice via entropy minimization, which is argued to be a specific example of risk-aversion. This recovers the $\epsilon$-greedy probabilities known in reinforcement learning. We show that the entropy minimization leads to rudimentary forms of intelligent behavior: (i) the agent assigns a non-negligible probability to costly events; but (ii) chooses with a sizable probability the action related to less cost (lesser of two evils) when confronted with two actions with comparable costs; (iii) the agent is subject to effects similar to cognitive dissonance and frustration. Neither of these features are shown by entropy maximization.
physics.data-an cond-mat.stat-mech cs.GT
an agent choosing between various actions tends to take the one with the lowest cost but this choice is arguably too rigid not adaptive to be useful in complex situations eg where explorationexploitation tradeoff is relevant in creative task solving or when stated preferences differ from revealed ones here we study an agent who is willing to sacrifice a fixed amount of expected utility for adaptation how canought our agent choose an optimal in a technical sense mixed action we explore consequences of making this choice via entropy minimization which is argued to be a specific example of riskaversion this recovers the epsilongreedy probabilities known in reinforcement learning we show that the entropy minimization leads to rudimentary forms of intelligent behavior i the agent assigns a nonnegligible probability to costly events but ii chooses with a sizable probability the action related to less cost lesser of two evils when confronted with two actions with comparable costs iii the agent is subject to effects similar to cognitive dissonance and frustration neither of these features are shown by entropy maximization
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1,803.06639
Stability of Energy Stable Flux Reconstruction for the Diffusion Problem using the Interior Penalty and Bassi and Rebay II Numerical Fluxes
Recovering some prominent high-order approaches such as the discontinuous Galerkin (DG) or the spectral difference (SD) methods, the flux reconstruction (FR) approach has been adopted by many individuals in the research community and is now commonly used to solve problems on unstructured grids over complex geometries. This approach relies on the use of correction functions to obtain a differential form for the discrete problem. A class of correction functions, named energy stable flux reconstruction (ESFR) functions, has been proven stable for the linear advection problem. This proof has then been extended for the diffusion equation using the local discontinuous Galerkin (LDG) scheme to compute the numerical fluxes. Although the LDG scheme is commonly used, many prefer the interior penalty (IP), as well as the Bassi and Rebay II (BR2) schemes. Similarly to the LDG proof, this article provides a stability analysis for the IP and the BR2 numerical fluxes. In fact, we obtain a theoretical condition on the penalty term to ensure stability. This result is then verified through numerical simulations. To complete this study, a von Neumann analysis is conducted to provide a combination of parameters producing the maximal time step while converging at the correct order. All things considered, this article has for purpose to provide the community with a stability condition while using the IP and the BR2 schemes.
math.NA
recovering some prominent highorder approaches such as the discontinuous galerkin dg or the spectral difference sd methods the flux reconstruction fr approach has been adopted by many individuals in the research community and is now commonly used to solve problems on unstructured grids over complex geometries this approach relies on the use of correction functions to obtain a differential form for the discrete problem a class of correction functions named energy stable flux reconstruction esfr functions has been proven stable for the linear advection problem this proof has then been extended for the diffusion equation using the local discontinuous galerkin ldg scheme to compute the numerical fluxes although the ldg scheme is commonly used many prefer the interior penalty ip as well as the bassi and rebay ii br2 schemes similarly to the ldg proof this article provides a stability analysis for the ip and the br2 numerical fluxes in fact we obtain a theoretical condition on the penalty term to ensure stability this result is then verified through numerical simulations to complete this study a von neumann analysis is conducted to provide a combination of parameters producing the maximal time step while converging at the correct order all things considered this article has for purpose to provide the community with a stability condition while using the ip and the br2 schemes
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1,803.0664
Invariant ultraviolet scale corrections to the thermodynamics of degenerate Fermi gas and its implications
We study the invariant Planck scale correction to the thermodynamics of the ideal Fermi gas. We have considered the modified dispersion relation and the cut-off to the maximum possible momentum/energy (Planck energy) of the non-interacting ideal degenerate Fermi gas particles. With such a modification the expression for the degenerate pressure and the total energy gets modified accordingly. We discuss the number density and mass dependence of the degenerate pressure. We found that the degenerate pressure is perturbative in the SR limit. We then take the example of white dwarfs to explore the possible implications. Using this modified degenerate pressure, we calculate the possible modification to the Chandrashekhar limit for white dwarfs using the Magueijo-Smolin (MS) modified dispersion relation. The mass-radius M-R plot shows that the modified/corrected radius of the white dwarf can be greater than, equal to and smaller than the usual special relativity (SR) value for particular masses. We found that the Chandrasekhar mass limit gets a positive correction. We note that the presence of observed white dwarfs having radius smaller than the SR Chandrasekhar limit may find an explanation if they are modeled using a modified dispersion relation. As the correction is perturbative in the SR limit, therefore this correction is solely because of the modified dispersion relation. The value of the obtained degenerate pressure for a given mass is found to be greater than, equal to and smaller than the usual special relativity (SR) value for particular masses as expected. We have also calculated the luminosity of the white dwarf by taking the model of partially degenerate gas and considering the modified radiative envelope equation. The luminosity also gets a negative correction. The correction to luminosity is nonperturbative as expected for such a theory.
gr-qc
we study the invariant planck scale correction to the thermodynamics of the ideal fermi gas we have considered the modified dispersion relation and the cutoff to the maximum possible momentumenergy planck energy of the noninteracting ideal degenerate fermi gas particles with such a modification the expression for the degenerate pressure and the total energy gets modified accordingly we discuss the number density and mass dependence of the degenerate pressure we found that the degenerate pressure is perturbative in the sr limit we then take the example of white dwarfs to explore the possible implications using this modified degenerate pressure we calculate the possible modification to the chandrashekhar limit for white dwarfs using the magueijosmolin ms modified dispersion relation the massradius mr plot shows that the modifiedcorrected radius of the white dwarf can be greater than equal to and smaller than the usual special relativity sr value for particular masses we found that the chandrasekhar mass limit gets a positive correction we note that the presence of observed white dwarfs having radius smaller than the sr chandrasekhar limit may find an explanation if they are modeled using a modified dispersion relation as the correction is perturbative in the sr limit therefore this correction is solely because of the modified dispersion relation the value of the obtained degenerate pressure for a given mass is found to be greater than equal to and smaller than the usual special relativity sr value for particular masses as expected we have also calculated the luminosity of the white dwarf by taking the model of partially degenerate gas and considering the modified radiative envelope equation the luminosity also gets a negative correction the correction to luminosity is nonperturbative as expected for such a theory
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1,803.06641
Zoom and Learn: Generalizing Deep Stereo Matching to Novel Domains
Despite the recent success of stereo matching with convolutional neural networks (CNNs), it remains arduous to generalize a pre-trained deep stereo model to a novel domain. A major difficulty is to collect accurate ground-truth disparities for stereo pairs in the target domain. In this work, we propose a self-adaptation approach for CNN training, utilizing both synthetic training data (with ground-truth disparities) and stereo pairs in the new domain (without ground-truths). Our method is driven by two empirical observations. By feeding real stereo pairs of different domains to stereo models pre-trained with synthetic data, we see that: i) a pre-trained model does not generalize well to the new domain, producing artifacts at boundaries and ill-posed regions; however, ii) feeding an up-sampled stereo pair leads to a disparity map with extra details. To avoid i) while exploiting ii), we formulate an iterative optimization problem with graph Laplacian regularization. At each iteration, the CNN adapts itself better to the new domain: we let the CNN learn its own higher-resolution output; at the meanwhile, a graph Laplacian regularization is imposed to discriminatively keep the desired edges while smoothing out the artifacts. We demonstrate the effectiveness of our method in two domains: daily scenes collected by smartphone cameras, and street views captured in a driving car.
cs.CV
despite the recent success of stereo matching with convolutional neural networks cnns it remains arduous to generalize a pretrained deep stereo model to a novel domain a major difficulty is to collect accurate groundtruth disparities for stereo pairs in the target domain in this work we propose a selfadaptation approach for cnn training utilizing both synthetic training data with groundtruth disparities and stereo pairs in the new domain without groundtruths our method is driven by two empirical observations by feeding real stereo pairs of different domains to stereo models pretrained with synthetic data we see that i a pretrained model does not generalize well to the new domain producing artifacts at boundaries and illposed regions however ii feeding an upsampled stereo pair leads to a disparity map with extra details to avoid i while exploiting ii we formulate an iterative optimization problem with graph laplacian regularization at each iteration the cnn adapts itself better to the new domain we let the cnn learn its own higherresolution output at the meanwhile a graph laplacian regularization is imposed to discriminatively keep the desired edges while smoothing out the artifacts we demonstrate the effectiveness of our method in two domains daily scenes collected by smartphone cameras and street views captured in a driving car
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1,803.06642
Enhancement of photon blockade effect via quantum interference
We study the photon blockade effect in a coupled cavity system, which is formed by a linear cavity coupled to a Kerr-type nonlinear cavity via a photon-hopping interaction. We explain the physical phenomenon from the viewpoint of the conventional and unconventional photon blockade effects. The corresponding physical mechanisms of the two kinds of photon blockade effects are based on the anharmonicity in the eigenenergy spectrum and the destructive quantum interference between two different transition paths, respectively. In particular, we find that the photon blockade via destructive quantum interference also exists in the conventional photon blockade regime, and that the unconventional photon blockade occurs in both the weak- and strong-Kerr nonlinearity cases. The photon blockade effect can be observed by calculating the second-order correlation function of the cavity field. This model is general and hence it can be implemented in various experimental setups such as coupled optical-cavity systems, coupled photon-magnon systems, and coupled superconducting-resonator systems. We present some discussions on the experimental feasibility.
quant-ph
we study the photon blockade effect in a coupled cavity system which is formed by a linear cavity coupled to a kerrtype nonlinear cavity via a photonhopping interaction we explain the physical phenomenon from the viewpoint of the conventional and unconventional photon blockade effects the corresponding physical mechanisms of the two kinds of photon blockade effects are based on the anharmonicity in the eigenenergy spectrum and the destructive quantum interference between two different transition paths respectively in particular we find that the photon blockade via destructive quantum interference also exists in the conventional photon blockade regime and that the unconventional photon blockade occurs in both the weak and strongkerr nonlinearity cases the photon blockade effect can be observed by calculating the secondorder correlation function of the cavity field this model is general and hence it can be implemented in various experimental setups such as coupled opticalcavity systems coupled photonmagnon systems and coupled superconductingresonator systems we present some discussions on the experimental feasibility
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1,803.06643
The Web as a Knowledge-base for Answering Complex Questions
Answering complex questions is a time-consuming activity for humans that requires reasoning and integration of information. Recent work on reading comprehension made headway in answering simple questions, but tackling complex questions is still an ongoing research challenge. Conversely, semantic parsers have been successful at handling compositionality, but only when the information resides in a target knowledge-base. In this paper, we present a novel framework for answering broad and complex questions, assuming answering simple questions is possible using a search engine and a reading comprehension model. We propose to decompose complex questions into a sequence of simple questions, and compute the final answer from the sequence of answers. To illustrate the viability of our approach, we create a new dataset of complex questions, ComplexWebQuestions, and present a model that decomposes questions and interacts with the web to compute an answer. We empirically demonstrate that question decomposition improves performance from 20.8 precision@1 to 27.5 precision@1 on this new dataset.
cs.CL cs.AI cs.LG
answering complex questions is a timeconsuming activity for humans that requires reasoning and integration of information recent work on reading comprehension made headway in answering simple questions but tackling complex questions is still an ongoing research challenge conversely semantic parsers have been successful at handling compositionality but only when the information resides in a target knowledgebase in this paper we present a novel framework for answering broad and complex questions assuming answering simple questions is possible using a search engine and a reading comprehension model we propose to decompose complex questions into a sequence of simple questions and compute the final answer from the sequence of answers to illustrate the viability of our approach we create a new dataset of complex questions complexwebquestions and present a model that decomposes questions and interacts with the web to compute an answer we empirically demonstrate that question decomposition improves performance from 208 precision1 to 275 precision1 on this new dataset
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1,803.06644
Computing and Testing Pareto Optimal Committees
Selecting a set of alternatives based on the preferences of agents is an important problem in committee selection and beyond. Among the various criteria put forth for the desirability of a committee, Pareto optimality is a minimal and important requirement. As asking agents to specify their preferences over exponentially many subsets of alternatives is practically infeasible, we assume that each agent specifies a weak order on single alternatives, from which a preference relation over subsets is derived using some preference extension. We consider five prominent extensions (responsive, downward lexicographic, upward lexicographic, best, and worst). For each of them, we consider the corresponding Pareto optimality notion, and we study the complexity of computing and verifying Pareto optimal outcomes. We also consider strategic issues: for four of the set extensions, we present a linear-time, Pareto optimal and strategyproof algorithm that even works for weak preferences.
cs.GT cs.AI cs.DS
selecting a set of alternatives based on the preferences of agents is an important problem in committee selection and beyond among the various criteria put forth for the desirability of a committee pareto optimality is a minimal and important requirement as asking agents to specify their preferences over exponentially many subsets of alternatives is practically infeasible we assume that each agent specifies a weak order on single alternatives from which a preference relation over subsets is derived using some preference extension we consider five prominent extensions responsive downward lexicographic upward lexicographic best and worst for each of them we consider the corresponding pareto optimality notion and we study the complexity of computing and verifying pareto optimal outcomes we also consider strategic issues for four of the set extensions we present a lineartime pareto optimal and strategyproof algorithm that even works for weak preferences
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1,803.06645
Approximating the Likelihood in Approximate Bayesian Computation
This chapter will appear in the forthcoming Handbook of Approximate Bayesian Computation (2018). The conceptual and methodological framework that underpins approximate Bayesian computation (ABC) is targetted primarily towards problems in which the likelihood is either challenging or missing. ABC uses a simulation-based non-parametric estimate of the likelihood of a summary statistic and assumes that the generation of data from the model is computationally cheap. This chapter reviews two alternative approaches for estimating the intractable likelihood, with the goal of reducing the necessary model simulations to produce an approximate posterior. The first of these is a Bayesian version of the synthetic likelihood (SL), initially developed by Wood (2010), which uses a multivariate normal approximation to the summary statistic likelihood. Using the parametric approximation as opposed to the non-parametric approximation of ABC, it is possible to reduce the number of model simulations required. The second likelihood approximation method we consider in this chapter is based on the empirical likelihood (EL), which is a non-parametric technique and involves maximising a likelihood constructed empirically under a set of moment constraints. Mengersen et al (2013) adapt the EL framework so that it can be used to form an approximate posterior for problems where ABC can be applied, that is, for models with intractable likelihoods. However, unlike ABC and the Bayesian SL (BSL), the Bayesian EL (BCel) approach can be used to completely avoid model simulations in some cases. The BSL and BCel methods are illustrated on models of varying complexity.
stat.CO stat.ME
this chapter will appear in the forthcoming handbook of approximate bayesian computation 2018 the conceptual and methodological framework that underpins approximate bayesian computation abc is targetted primarily towards problems in which the likelihood is either challenging or missing abc uses a simulationbased nonparametric estimate of the likelihood of a summary statistic and assumes that the generation of data from the model is computationally cheap this chapter reviews two alternative approaches for estimating the intractable likelihood with the goal of reducing the necessary model simulations to produce an approximate posterior the first of these is a bayesian version of the synthetic likelihood sl initially developed by wood 2010 which uses a multivariate normal approximation to the summary statistic likelihood using the parametric approximation as opposed to the nonparametric approximation of abc it is possible to reduce the number of model simulations required the second likelihood approximation method we consider in this chapter is based on the empirical likelihood el which is a nonparametric technique and involves maximising a likelihood constructed empirically under a set of moment constraints mengersen et al 2013 adapt the el framework so that it can be used to form an approximate posterior for problems where abc can be applied that is for models with intractable likelihoods however unlike abc and the bayesian sl bsl the bayesian el bcel approach can be used to completely avoid model simulations in some cases the bsl and bcel methods are illustrated on models of varying complexity
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1,803.06646
Toric geometry of $G_2$-manifolds
We consider $G_2$-manifolds with an effective torus action that is multi-Hamiltonian for one or more of the defining forms. The case of $T^3$-actions is found to be distinguished. For such actions multi-Hamiltonian with respect to both the three- and four-form, we derive a Gibbons-Hawking type ansatz giving the geometry on an open dense set in terms a symmetric $3\times 3$-matrix of functions. This leads to particularly simple examples of explicit metrics with holonomy equal to $G_2$. We prove that the multi-moment maps exhibit the full orbit space topologically as a smooth four-manifold containing a trivalent graph as the image of the set of special orbits and describe these graphs in some complete examples.
math.DG hep-th
we consider g_2manifolds with an effective torus action that is multihamiltonian for one or more of the defining forms the case of t3actions is found to be distinguished for such actions multihamiltonian with respect to both the three and fourform we derive a gibbonshawking type ansatz giving the geometry on an open dense set in terms a symmetric 3times 3matrix of functions this leads to particularly simple examples of explicit metrics with holonomy equal to g_2 we prove that the multimoment maps exhibit the full orbit space topologically as a smooth fourmanifold containing a trivalent graph as the image of the set of special orbits and describe these graphs in some complete examples
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1,803.06647
Line Artist: A Multiple Style Sketch to Painting Synthesis Scheme
Drawing a beautiful painting is a dream of many people since childhood. In this paper, we propose a novel scheme, Line Artist, to synthesize artistic style paintings with freehand sketch images, leveraging the power of deep learning and advanced algorithms. Our scheme includes three models. The Sketch Image Extraction (SIE) model is applied to generate the training data. It includes smoothing reality images and pencil sketch extraction. The Detailed Image Synthesis (DIS) model trains a conditional generative adversarial network to generate detailed real-world information. The Adaptively Weighted Artistic Style Transfer (AWAST) model is capable to combine multiple style images with a content with the VGG19 network and PageRank algorithm. The appealing artistic images are then generated by optimization iterations. Experiments are operated on the Kaggle Cats dataset and The Oxford Buildings Dataset. Our synthesis results are proved to be artistic, beautiful and robust.
cs.CV
drawing a beautiful painting is a dream of many people since childhood in this paper we propose a novel scheme line artist to synthesize artistic style paintings with freehand sketch images leveraging the power of deep learning and advanced algorithms our scheme includes three models the sketch image extraction sie model is applied to generate the training data it includes smoothing reality images and pencil sketch extraction the detailed image synthesis dis model trains a conditional generative adversarial network to generate detailed realworld information the adaptively weighted artistic style transfer awast model is capable to combine multiple style images with a content with the vgg19 network and pagerank algorithm the appealing artistic images are then generated by optimization iterations experiments are operated on the kaggle cats dataset and the oxford buildings dataset our synthesis results are proved to be artistic beautiful and robust
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1,803.06648
Charge migration mechanisms in the DNA at finite temperature revisited; from quasi-ballistic to subdiffusive transport
Various charge migration mechanisms in the DNA are studied within the framework of the Peyrard-Bishop-Holstein model which has been widely used to address charge dynamics in this macromolecule. To analyze these mechanisms we consider characteristic size and time scales of the fluctuations of the electronic and vibrational subsystems. It is shown, in particular, that due to substantial differences in these timescales polaron formation is unlikely within a broad range of temperatures. We demonstrate that at low temperatures electronic transport can be quasi-ballistic. For high temperatures, we propose an alternative to polaronic charge migration mechanism: the fluctuation-assisted one, in which the electron dynamics is governed by relatively slow fluctuations of the vibrational subsystem. We argue also that the discussed methods and mechanisms can be relevant for other organic macromolecular systems, such as conjugated polymers and molecular aggregates.
physics.bio-ph cond-mat.mes-hall
various charge migration mechanisms in the dna are studied within the framework of the peyrardbishopholstein model which has been widely used to address charge dynamics in this macromolecule to analyze these mechanisms we consider characteristic size and time scales of the fluctuations of the electronic and vibrational subsystems it is shown in particular that due to substantial differences in these timescales polaron formation is unlikely within a broad range of temperatures we demonstrate that at low temperatures electronic transport can be quasiballistic for high temperatures we propose an alternative to polaronic charge migration mechanism the fluctuationassisted one in which the electron dynamics is governed by relatively slow fluctuations of the vibrational subsystem we argue also that the discussed methods and mechanisms can be relevant for other organic macromolecular systems such as conjugated polymers and molecular aggregates
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1,803.06649
Cubical Assemblies, a Univalent and Impredicative Universe and a Failure of Propositional Resizing
We construct a model of cubical type theory with a univalent and impredicative universe in a category of cubical assemblies. We show that this impredicative universe in the cubical assembly model does not satisfy a form of propositional resizing.
cs.LO
we construct a model of cubical type theory with a univalent and impredicative universe in a category of cubical assemblies we show that this impredicative universe in the cubical assembly model does not satisfy a form of propositional resizing
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1,803.0665
A large and pristine sample of standard candles across the Milky Way: ~100,000 red clump stars with 3% contamination
Core helium-burning red clump (RC) stars are excellent standard candles in the Milky Way. These stars may have more precise distance estimates from spectrophotometry than from Gaia parallaxes beyond 3 kpc. However, RC stars have $T_{\rm eff}$ and log g very similar to some red giant branch (RGB) stars. Especially for low-resolution spectroscopic studies where $T_{\rm eff}$, log g, and [Fe/H] can only be estimated with limited precision, separating RC stars from RGB through established method can incur ~20% contamination. Recently, Hawkins et al. (2018) demonstrated that the additional information in single-epoch spectra, such as the C/N ratio, can be exploited to cleanly differentiate RC and RGB stars. In this second paper of the series, we establish a data-driven mapping from spectral flux space to independently determined asteroseismic parameters, the frequency and the period spacing. From this, we identify 210,371 RC stars from the publicly available LAMOST DR3 and APOGEE DR14 data, with ~9% of contamination. We provide an RC sample of 92,249 stars with a contamination of only ~3%, by restricting the combined analysis to LAMOST stars with ${\rm S/N}_{\rm pix}$ > 75. This demonstrates that high-S/N, low-resolution spectra covering a broad wavelength range can identify RC samples at least as pristine as their high-resolution counterparts. As coming and ongoing surveys such as TESS, DESI, and LAMOST will continue to improve the overlapping training spectroscopic-asteroseismic sample, the method presented in this study provides an efficient and straightforward way to derive a vast yet pristine RC stars to reveal the 3D structure of the Milky Way.
astro-ph.SR astro-ph.GA
core heliumburning red clump rc stars are excellent standard candles in the milky way these stars may have more precise distance estimates from spectrophotometry than from gaia parallaxes beyond 3 kpc however rc stars have t_rm eff and log g very similar to some red giant branch rgb stars especially for lowresolution spectroscopic studies where t_rm eff log g and feh can only be estimated with limited precision separating rc stars from rgb through established method can incur 20 contamination recently hawkins et al 2018 demonstrated that the additional information in singleepoch spectra such as the cn ratio can be exploited to cleanly differentiate rc and rgb stars in this second paper of the series we establish a datadriven mapping from spectral flux space to independently determined asteroseismic parameters the frequency and the period spacing from this we identify 210371 rc stars from the publicly available lamost dr3 and apogee dr14 data with 9 of contamination we provide an rc sample of 92249 stars with a contamination of only 3 by restricting the combined analysis to lamost stars with rm sn_rm pix 75 this demonstrates that highsn lowresolution spectra covering a broad wavelength range can identify rc samples at least as pristine as their highresolution counterparts as coming and ongoing surveys such as tess desi and lamost will continue to improve the overlapping training spectroscopicasteroseismic sample the method presented in this study provides an efficient and straightforward way to derive a vast yet pristine rc stars to reveal the 3d structure of the milky way
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1,803.06651
Limits in dagger categories
We develop a notion of limit for dagger categories, that we show is suitable in the following ways: it subsumes special cases known from the literature; dagger limits are unique up to unitary isomorphism; a wide class of dagger limits can be built from a small selection of them; dagger limits of a fixed shape can be phrased as dagger adjoints to a diagonal functor; dagger limits can be built from ordinary limits in the presence of polar decomposition; dagger limits commute with dagger colimits in many cases.
math.CT
we develop a notion of limit for dagger categories that we show is suitable in the following ways it subsumes special cases known from the literature dagger limits are unique up to unitary isomorphism a wide class of dagger limits can be built from a small selection of them dagger limits of a fixed shape can be phrased as dagger adjoints to a diagonal functor dagger limits can be built from ordinary limits in the presence of polar decomposition dagger limits commute with dagger colimits in many cases
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1,803.06652
Hesperos: A geophysical mission to Venus
The Hesperos mission proposed in this paper is a mission to Venus to investigate the interior structure and the current level of activity. The main questions to be answered with this mission are whether Venus has an internal structure and composition similar to Earth and if Venus is still tectonically active. To do so the mission will consist of two elements: an orbiter to investigate the interior and changes over longer periods of time and a balloon floating at an altitude between 40 and 60\~km to investigate the composition of the atmosphere. The mission will start with the deployment of the balloon which will operate for about 25 days. During this time the orbiter acts as a relay station for data communication with Earth. Once the balloon phase is finished the orbiter will perform surface and gravity gradient mapping over the course of 7 Venus days. This mission proposal is the result of the Alpbach Summer School and the post-Alpbach week.
astro-ph.EP
the hesperos mission proposed in this paper is a mission to venus to investigate the interior structure and the current level of activity the main questions to be answered with this mission are whether venus has an internal structure and composition similar to earth and if venus is still tectonically active to do so the mission will consist of two elements an orbiter to investigate the interior and changes over longer periods of time and a balloon floating at an altitude between 40 and 60km to investigate the composition of the atmosphere the mission will start with the deployment of the balloon which will operate for about 25 days during this time the orbiter acts as a relay station for data communication with earth once the balloon phase is finished the orbiter will perform surface and gravity gradient mapping over the course of 7 venus days this mission proposal is the result of the alpbach summer school and the postalpbach week
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1,803.06653
Modeling stock markets through the reconstruction of market processes
There are two possible ways of interpreting the seemingly stochastic nature of financial markets: the Efficient Market Hypothesis (EMH) and a set of stylized facts that drive the behavior of the markets. We show evidence for some of the stylized facts such as memory-like phenomena in price volatility in the short term, a power-law behavior and non-linear dependencies on the returns. Given this, we construct a model of the market using Markov chains. Then, we develop an algorithm that can be generalized for any N-symbol alphabet and K-length Markov chain. Using this tool, we are able to show that it's, at least, always better than a completely random model such as a Random Walk. The code is written in MATLAB and maintained in GitHub.
q-fin.ST q-fin.CP
there are two possible ways of interpreting the seemingly stochastic nature of financial markets the efficient market hypothesis emh and a set of stylized facts that drive the behavior of the markets we show evidence for some of the stylized facts such as memorylike phenomena in price volatility in the short term a powerlaw behavior and nonlinear dependencies on the returns given this we construct a model of the market using markov chains then we develop an algorithm that can be generalized for any nsymbol alphabet and klength markov chain using this tool we are able to show that its at least always better than a completely random model such as a random walk the code is written in matlab and maintained in github
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1,803.06654
Inelastic scattering of microwave radiation in the dynamical Coulomb blockade
We study scattering of propagating microwave fields by a DC-voltage biased Josephson junction. At sub-gap voltages, a small Josephson junction works merely as a non-linear boundary that can absorb, amplify, and diversely convert propagating microwaves. In the leading-order perturbation theory of the Josephson coupling energy, the spectral density and quadrature fluctuations of scattered thermal and coherent radiation can be described in terms of the well-known $P(E)$ function. Applying this, we study how thermal and coherent radiation is absorbed and amplified in an Ohmic transmission line and in a circuit with a resonance frequency. We show when a coherent input can create a two-mode squeezed output. In addition, we evaluate scattering amplitudes between arbitrary photon-number (Fock) states, characterizing individual photon multiplication and absorption processes occuring at the junction.
cond-mat.supr-con cond-mat.mes-hall quant-ph
we study scattering of propagating microwave fields by a dcvoltage biased josephson junction at subgap voltages a small josephson junction works merely as a nonlinear boundary that can absorb amplify and diversely convert propagating microwaves in the leadingorder perturbation theory of the josephson coupling energy the spectral density and quadrature fluctuations of scattered thermal and coherent radiation can be described in terms of the wellknown pe function applying this we study how thermal and coherent radiation is absorbed and amplified in an ohmic transmission line and in a circuit with a resonance frequency we show when a coherent input can create a twomode squeezed output in addition we evaluate scattering amplitudes between arbitrary photonnumber fock states characterizing individual photon multiplication and absorption processes occuring at the junction
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1,803.06655
Ratio-Preserving Half-Cylindrical Warps for Natural Image Stitching
A novel warp for natural image stitching is proposed that utilizes the property of cylindrical warp and a horizontal pixel selection strategy. The proposed ratio-preserving half-cylindrical warp is a combination of homography and cylindrical warps which guarantees alignment by homography and possesses less projective distortion by cylindrical warp. Unlike previous approaches applying cylindrical warp before homography, we use partition lines to divide the image into different parts and apply homography in the overlapping region while a composition of homography and cylindrical warps in the non-overlapping region. The pixel selection strategy then samples the points in horizontal and reconstructs the image via interpolation to further reduce horizontal distortion by maintaining the ratio as similarity. With applying half-cylindrical warp and horizontal pixel selection, the projective distortion in vertical and horizontal is mitigated simultaneously. Experiments show that our warp is efficient and produces a more natural-looking stitched result than previous methods.
cs.CV
a novel warp for natural image stitching is proposed that utilizes the property of cylindrical warp and a horizontal pixel selection strategy the proposed ratiopreserving halfcylindrical warp is a combination of homography and cylindrical warps which guarantees alignment by homography and possesses less projective distortion by cylindrical warp unlike previous approaches applying cylindrical warp before homography we use partition lines to divide the image into different parts and apply homography in the overlapping region while a composition of homography and cylindrical warps in the nonoverlapping region the pixel selection strategy then samples the points in horizontal and reconstructs the image via interpolation to further reduce horizontal distortion by maintaining the ratio as similarity with applying halfcylindrical warp and horizontal pixel selection the projective distortion in vertical and horizontal is mitigated simultaneously experiments show that our warp is efficient and produces a more naturallooking stitched result than previous methods
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1,803.06656
Optical Property Study of Charge Compensated (Si, Na) Co-doped ZnO
ZnO is co-doped with Na+ and Si4+ in the ratio 2:1. The ratio was intentionally chosen so that net valence state of dopant theoretically matches that of host. This is to avoid dependence in the amount of oxygen vacancies/interstitials arising out of cationic valence state of the dopant. With such a combination, modifications in structural and optical properties do not depend on excess or deficit of the dopant charge state. For lower doping, Na+ ions behave as interstitial sites which enhance strain, lattice disorder and thereby creating defects. Formation of interstitial defects leads to reduction in bandgap energy and produce orange-red luminescence. For higher doping, Na+ starts substituting at Zn2+ site which helps in reducing strain and lattice disorder and thereby increases bandgap. Inspite of presence of Si4+ with higher charge, there is a gradual increase in oxygen vacancies due to lattice disorder.
cond-mat.mtrl-sci
zno is codoped with na and si4 in the ratio 21 the ratio was intentionally chosen so that net valence state of dopant theoretically matches that of host this is to avoid dependence in the amount of oxygen vacanciesinterstitials arising out of cationic valence state of the dopant with such a combination modifications in structural and optical properties do not depend on excess or deficit of the dopant charge state for lower doping na ions behave as interstitial sites which enhance strain lattice disorder and thereby creating defects formation of interstitial defects leads to reduction in bandgap energy and produce orangered luminescence for higher doping na starts substituting at zn2 site which helps in reducing strain and lattice disorder and thereby increases bandgap inspite of presence of si4 with higher charge there is a gradual increase in oxygen vacancies due to lattice disorder
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1,803.06657
Sdf-GAN: Semi-supervised Depth Fusion with Multi-scale Adversarial Networks
Refining raw disparity maps from different algorithms to exploit their complementary advantages is still challenging. Uncertainty estimation and complex disparity relationships among pixels limit the accuracy and robustness of existing methods and there is no standard method for fusion of different kinds of depth data. In this paper, we introduce a new method to fuse disparity maps from different sources, while incorporating supplementary information (intensity, gradient, etc.) into a refiner network to better refine raw disparity inputs. A discriminator network classifies disparities at different receptive fields and scales. Assuming a Markov Random Field for the refined disparity map produces better estimates of the true disparity distribution. Both fully supervised and semi-supervised versions of the algorithm are proposed. The approach includes a more robust loss function to inpaint invalid disparity values and requires much less labeled data to train in the semi-supervised learning mode. The algorithm can be generalized to fuse depths from different kinds of depth sources. Experiments explored different fusion opportunities: stereo-monocular fusion, stereo-ToF fusion and stereo-stereo fusion. The experiments show the superiority of the proposed algorithm compared with the most recent algorithms on public synthetic datasets (Scene Flow, SYNTH3, our synthetic garden dataset) and real datasets (Kitti2015 dataset and Trimbot2020 Garden dataset).
cs.CV
refining raw disparity maps from different algorithms to exploit their complementary advantages is still challenging uncertainty estimation and complex disparity relationships among pixels limit the accuracy and robustness of existing methods and there is no standard method for fusion of different kinds of depth data in this paper we introduce a new method to fuse disparity maps from different sources while incorporating supplementary information intensity gradient etc into a refiner network to better refine raw disparity inputs a discriminator network classifies disparities at different receptive fields and scales assuming a markov random field for the refined disparity map produces better estimates of the true disparity distribution both fully supervised and semisupervised versions of the algorithm are proposed the approach includes a more robust loss function to inpaint invalid disparity values and requires much less labeled data to train in the semisupervised learning mode the algorithm can be generalized to fuse depths from different kinds of depth sources experiments explored different fusion opportunities stereomonocular fusion stereotof fusion and stereostereo fusion the experiments show the superiority of the proposed algorithm compared with the most recent algorithms on public synthetic datasets scene flow synth3 our synthetic garden dataset and real datasets kitti2015 dataset and trimbot2020 garden dataset
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1,803.06658
Temperature dependent dynamics in water-ethanol liquid mixtures
Temperature dependent hydrogen bond energetics and dynamical features, such as the diffusion coefficient and reorientational times, have been determined for ethanol-water mixtures with 10, 20 and 30 mol % of ethanol. Concerning pairwise interaction energies between molecules, it is found that water-water interactions become stronger, while ethanol-ethanol ones become significantly weaker in the mixtures than the corresponding values characteristic to the pure substances. Concerning the diffusion processes, for all concentrations the activation barrier of water and ethanol molecule become very similar to each other. Reorientation motions of water and ethanol become slower as ethanol concentration is increasing. Characteristic reorientational times of water in the mixtures are substantially longer than these values in the pure substance. On the other hand, this change for ethanol is only moderate. The reorientation motions of water (especially the ones related to the H-bonded interaction) become very similar for those of ethanol in the mixtures.
physics.chem-ph cond-mat.soft
temperature dependent hydrogen bond energetics and dynamical features such as the diffusion coefficient and reorientational times have been determined for ethanolwater mixtures with 10 20 and 30 mol of ethanol concerning pairwise interaction energies between molecules it is found that waterwater interactions become stronger while ethanolethanol ones become significantly weaker in the mixtures than the corresponding values characteristic to the pure substances concerning the diffusion processes for all concentrations the activation barrier of water and ethanol molecule become very similar to each other reorientation motions of water and ethanol become slower as ethanol concentration is increasing characteristic reorientational times of water in the mixtures are substantially longer than these values in the pure substance on the other hand this change for ethanol is only moderate the reorientation motions of water especially the ones related to the hbonded interaction become very similar for those of ethanol in the mixtures
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1,803.06659
New characterizations of operator monotone functions
If $\sigma$ is a symmetric mean and $f$ is an operator monotone function on $[0, \infty)$, then $$f(2(A^{-1}+B^{-1})^{-1})\le f(A\sigma B)\le f((A+B)/2).$$ Conversely, Ando and Hiai showed that if $f$ is a function that satisfies either one of these inequalities for all positive operators $A$ and $B$ and a symmetric mean different than the arithmetic and the harmonic mean, then the function is operator monotone. In this paper, we show that the arithmetic and the harmonic means can be replaced by the geometric mean to obtain similar characterizations. Moreover, we give characterizations of operator monotone functions using self-adjoint means and general means subject to a constraint due to Kubo and Ando.
math.FA math.OA
if sigma is a symmetric mean and f is an operator monotone function on 0 infty then f2a1b11le fasigma ble fab2 conversely ando and hiai showed that if f is a function that satisfies either one of these inequalities for all positive operators a and b and a symmetric mean different than the arithmetic and the harmonic mean then the function is operator monotone in this paper we show that the arithmetic and the harmonic means can be replaced by the geometric mean to obtain similar characterizations moreover we give characterizations of operator monotone functions using selfadjoint means and general means subject to a constraint due to kubo and ando
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1,803.0666
Temperature dependent network stability in simple alcohols and pure water: the evolution of Laplace spectra
A number of computer-generated models of water, methanol and ethanol are considered at room temperature and ambient pressure, and also as a function of temperature (for water and ethanol), and the potential model (for water only). The Laplace matrices are determined, and various characteristics of this, such as eigenvalues and eigenvectors, and the corresponding Laplace spectra are calculated. It is revealed how the width of the spectral gap in the Laplace matrix of H-bonded networks may be applied for characterising the stability of the network. A novel method for detecting the presence percolated network in these systems is also introduced.
physics.chem-ph
a number of computergenerated models of water methanol and ethanol are considered at room temperature and ambient pressure and also as a function of temperature for water and ethanol and the potential model for water only the laplace matrices are determined and various characteristics of this such as eigenvalues and eigenvectors and the corresponding laplace spectra are calculated it is revealed how the width of the spectral gap in the laplace matrix of hbonded networks may be applied for characterising the stability of the network a novel method for detecting the presence percolated network in these systems is also introduced
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1,803.06661
New Approach To Fixed Point Theorems
In this article, we discuss a new version of metric fixed point theory especially of Banach Contraction Principle, Ran-Reurings Theorem and others.
math.FA
in this article we discuss a new version of metric fixed point theory especially of banach contraction principle ranreurings theorem and others
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1,803.06662
Fixed Point Theorems In Ordered Partial b-Metric Spaces With New Setting
The main purpose of this paper is to find the fixed point in such cases where existing literature remain silent. In this paper we introduce partial completeness, a new type of contraction and many other definitions. Using this approach the existence of fixed point can be proved in incomplete metric spaces with non-contraction map on it. We have reported an example in support our result.
math.FA
the main purpose of this paper is to find the fixed point in such cases where existing literature remain silent in this paper we introduce partial completeness a new type of contraction and many other definitions using this approach the existence of fixed point can be proved in incomplete metric spaces with noncontraction map on it we have reported an example in support our result
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1,803.06663
Direct Measurement of Focusing Fields in Active Plasma Lenses
Active plasma lenses have the potential to enable broad-ranging applications of plasma-based accelerators owing to their compact design and radially symmetric kT/m-level focusing fields, facilitating beam-quality preservation and compact beam transport. We report on the direct measurement of magnetic field gradients in active plasma lenses and demonstrate their impact on the emittance of a charged particle beam. This is made possible by the use of a well-characterized electron beam with 1.4 mm mrad normalized emittance from a conventional accelerator. Field gradients of up to 823 T/m are investigated. The observed emittance evolution is supported by numerical simulations, which suggest the potential for conservation of the core beam emittance in such a plasma lens setup.
physics.acc-ph
active plasma lenses have the potential to enable broadranging applications of plasmabased accelerators owing to their compact design and radially symmetric ktmlevel focusing fields facilitating beamquality preservation and compact beam transport we report on the direct measurement of magnetic field gradients in active plasma lenses and demonstrate their impact on the emittance of a charged particle beam this is made possible by the use of a wellcharacterized electron beam with 14 mm mrad normalized emittance from a conventional accelerator field gradients of up to 823 tm are investigated the observed emittance evolution is supported by numerical simulations which suggest the potential for conservation of the core beam emittance in such a plasma lens setup
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1,803.06664
An Introduction to the Moebius Function
This is an introduction to the M\"obius function of a poset. The chief novelty is in the exposition. We show how order-preserving maps from one poset to another can be used to relate their M\"obius functions. We derive the basic results on the M\"obius function, applying them in particular to geometric lattices.
math.CO
this is an introduction to the mobius function of a poset the chief novelty is in the exposition we show how orderpreserving maps from one poset to another can be used to relate their mobius functions we derive the basic results on the mobius function applying them in particular to geometric lattices
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1,803.06665
Les exposants de Liapounoff du flot de Teichm\"{u}ller
The purpose of the paper under review is to explain the main ideas and the main ingredients of the involved and delicate work of A. Eskin, M. Kontsevich and A. Zorich concerning the sum of the positive Lyapunov exponents of the so-called Kontsevich- Zorich cocycle acting on the first cohomology spaces of translation surfaces.
math.DS
the purpose of the paper under review is to explain the main ideas and the main ingredients of the involved and delicate work of a eskin m kontsevich and a zorich concerning the sum of the positive lyapunov exponents of the socalled kontsevich zorich cocycle acting on the first cohomology spaces of translation surfaces
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1,803.06666
Causality Aspects of Modified Kerr-Newman spacetimes
In this paper, we address the problem of causality violation in the solutions of Einstein equations and seek possible causality restoration mechanisms in modifed theories of gravity. We choose for the above problem, the causality violation due to the existence of closed time-like curves in the context of Kerr-Newman black hole. We first revisit and quantify the details of the causality violation in the Kerr-Newman spacetime. We then show that the issue is also existent in two of the modified solutions to the Kerr Newman spacetime: The Non-Commutativity inspired solution and the f(R)-Gravity modifed solution. We explore the possibility of mechanisms present within the model that prevent causality violation. We show that, in both the models, the model parameters can be chosen such that the causality violating region is eliminated. We argue that in the context of non commutativity inspired solution, the non commutativity parameter can be chosen such that the causality violating region is eliminated and the inner horizon is no longer the Cauchy horizon. We then discuss the geodesic connectivity of the causality violating region in both the scenarios and quantify the geodesics that have points in the causality violating regions. We also discuss the causal aspects of Kerr Newman deSitter/antideSitter spacetimes.
gr-qc
in this paper we address the problem of causality violation in the solutions of einstein equations and seek possible causality restoration mechanisms in modifed theories of gravity we choose for the above problem the causality violation due to the existence of closed timelike curves in the context of kerrnewman black hole we first revisit and quantify the details of the causality violation in the kerrnewman spacetime we then show that the issue is also existent in two of the modified solutions to the kerr newman spacetime the noncommutativity inspired solution and the frgravity modifed solution we explore the possibility of mechanisms present within the model that prevent causality violation we show that in both the models the model parameters can be chosen such that the causality violating region is eliminated we argue that in the context of non commutativity inspired solution the non commutativity parameter can be chosen such that the causality violating region is eliminated and the inner horizon is no longer the cauchy horizon we then discuss the geodesic connectivity of the causality violating region in both the scenarios and quantify the geodesics that have points in the causality violating regions we also discuss the causal aspects of kerr newman desitterantidesitter spacetimes
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