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1,803.03767
Multi-Agent Submodular Optimization
Recent years have seen many algorithmic advances in the area of submodular optimization: (SO) $\min/\max~f(S): S \in \mathcal{F}$, where $\mathcal{F}$ is a given family of feasible sets over a ground set $V$ and $f:2^V \rightarrow \mathbb{R}$ is submodular. This progress has been coupled with a wealth of new applications for these models. Our focus is on a more general class of \emph{multi-agent submodular optimization} (MASO) which was introduced by Goel et al. in the minimization setting: $\min \sum_i f_i(S_i): S_1 \uplus S_2 \uplus \cdots \uplus S_k \in \mathcal{F}$. Here we use $\uplus$ to denote disjoint union and hence this model is attractive where resources are being allocated across $k$ agents, each with its own submodular cost function $f_i()$. In this paper we explore the extent to which the approximability of the multi-agent problems are linked to their single-agent {\em primitives}, referred to informally as the {\em multi-agent gap}. We present different reductions that transform a multi-agent problem into a single-agent one. For maximization we show that (MASO) admits an $O(\alpha)$-approximation whenever (SO) admits an $\alpha$-approximation over the multilinear formulation, and thus substantially expanding the family of tractable models. We also discuss several family classes (such as spanning trees, matroids, and $p$-systems) that have a provable multi-agent gap of 1. In the minimization setting we show that (MASO) has an $O(\alpha \cdot \min \{k, \log^2 (n)\})$-approximation whenever (SO) admits an $\alpha$-approximation over the convex formulation. In addition, we discuss the class of "bounded blocker" families where there is a provably tight O$(\log n)$ gap between (MASO) and (SO).
cs.DS
recent years have seen many algorithmic advances in the area of submodular optimization so minmaxfs s in mathcalf where mathcalf is a given family of feasible sets over a ground set v and f2v rightarrow mathbbr is submodular this progress has been coupled with a wealth of new applications for these models our focus is on a more general class of emphmultiagent submodular optimization maso which was introduced by goel et al in the minimization setting min sum_i f_is_i s_1 uplus s_2 uplus cdots uplus s_k in mathcalf here we use uplus to denote disjoint union and hence this model is attractive where resources are being allocated across k agents each with its own submodular cost function f_i in this paper we explore the extent to which the approximability of the multiagent problems are linked to their singleagent em primitives referred to informally as the em multiagent gap we present different reductions that transform a multiagent problem into a singleagent one for maximization we show that maso admits an oalphaapproximation whenever so admits an alphaapproximation over the multilinear formulation and thus substantially expanding the family of tractable models we also discuss several family classes such as spanning trees matroids and psystems that have a provable multiagent gap of 1 in the minimization setting we show that maso has an oalpha cdot min k log2 napproximation whenever so admits an alphaapproximation over the convex formulation in addition we discuss the class of bounded blocker families where there is a provably tight olog n gap between maso and so
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1,803.03768
Visco-Energetic solutions to some rate-independent systems in damage, delamination, and plasticity
This paper revolves around a newly introduced weak solvability concept for rate-independent systems, alternative to the notions of Energetic and Balanced Viscosity solutions. Visco-Energetic solutions have been recently obtained by passing to the time-continuous limit in a time-incremental scheme, akin to that for Energetic solutions, but perturbed by a `viscous' correction term, as in the case of Balanced Viscosity solutions. However, for Visco-Energetic solutions this viscous correction is tuned by a fixed parameter. The resulting solution notion turns out to describe a kind of evolution in between Energetic and Balanced Viscosity evolution. In this paper we aim to investigate the application of Visco-Energetic solutions to the paradigmatic example of perfect plasticity, and to nonsmooth rate-independent processes in solid mechanics such as damage and plasticity at finite strains. With the limit passage from adhesive contact to brittle delamination, we also provide a first result of Evolutionary Gamma-convergence for Visco-Energetic solutions. The analysis of these applications reveals the wide applicability of this solution concept and confirms its intermediate character.
math.AP
this paper revolves around a newly introduced weak solvability concept for rateindependent systems alternative to the notions of energetic and balanced viscosity solutions viscoenergetic solutions have been recently obtained by passing to the timecontinuous limit in a timeincremental scheme akin to that for energetic solutions but perturbed by a viscous correction term as in the case of balanced viscosity solutions however for viscoenergetic solutions this viscous correction is tuned by a fixed parameter the resulting solution notion turns out to describe a kind of evolution in between energetic and balanced viscosity evolution in this paper we aim to investigate the application of viscoenergetic solutions to the paradigmatic example of perfect plasticity and to nonsmooth rateindependent processes in solid mechanics such as damage and plasticity at finite strains with the limit passage from adhesive contact to brittle delamination we also provide a first result of evolutionary gammaconvergence for viscoenergetic solutions the analysis of these applications reveals the wide applicability of this solution concept and confirms its intermediate character
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1,803.03769
A Minimax Surrogate Loss Approach to Conditional Difference Estimation
We present a new machine learning approach to estimate personalized treatment effects in the classical potential outcomes framework with binary outcomes. To overcome the problem that both treatment and control outcomes for the same unit are required for supervised learning, we propose surrogate loss functions that incorporate both treatment and control data. The new surrogates yield tighter bounds than the sum of losses for treatment and control groups. A specific choice of loss function, namely a type of hinge loss, yields a minimax support vector machine formulation. The resulting optimization problem requires the solution to only a single convex optimization problem, incorporating both treatment and control units, and it enables the kernel trick to be used to handle nonlinear (also non-parametric) estimation. Statistical learning bounds are also presented for the framework, and experimental results.
stat.ML cs.LG
we present a new machine learning approach to estimate personalized treatment effects in the classical potential outcomes framework with binary outcomes to overcome the problem that both treatment and control outcomes for the same unit are required for supervised learning we propose surrogate loss functions that incorporate both treatment and control data the new surrogates yield tighter bounds than the sum of losses for treatment and control groups a specific choice of loss function namely a type of hinge loss yields a minimax support vector machine formulation the resulting optimization problem requires the solution to only a single convex optimization problem incorporating both treatment and control units and it enables the kernel trick to be used to handle nonlinear also nonparametric estimation statistical learning bounds are also presented for the framework and experimental results
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1,803.0377
Continuous solutions of a second order iterative equation
In this paper we study the existence of continuous solutions and their constructions for a second order iterative functional equation, which involves iterate of the unknown function and a nonlinear term. Imposing Lipschitz conditions to those given functions, we prove the existence of continuous solutions on the whole $\mathbb{R}$ by applying the contraction principle. In the case without Lipschitz conditions we hardly use the contraction principle, but we construct continuous solutions on $\mathbb{R}$ recursively with a partition of $\mathbb{R}$.
math.CA
in this paper we study the existence of continuous solutions and their constructions for a second order iterative functional equation which involves iterate of the unknown function and a nonlinear term imposing lipschitz conditions to those given functions we prove the existence of continuous solutions on the whole mathbbr by applying the contraction principle in the case without lipschitz conditions we hardly use the contraction principle but we construct continuous solutions on mathbbr recursively with a partition of mathbbr
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1,803.03771
Noether and Abbott-Deser-Tekin conserved quantities in scalar-tensor theory of gravity both in Jordan and Einstein frames
We revisit the thermodynamic aspects of the scalar-tensor theory of gravity in the Jordan and in the Einstein frame. Examining the {\it missing links} of this theory carefully, we establish the thermodynamic descriptions from the conserved currents and potentials by following both the Noether and the Abbott-Deser-Tekin (ADT) formalism. With the help of conserved Noether current and potential, we define the thermodynamic quantities, which we show to be {\it conformally invariant}. Moreover, the defined quantities are shown to fit nicely in the laws of (the first and the second) black hole thermodynamics formulated by the Wald's method. We stretch the study of the conformal equivalence of the physical quantities in these two frames by following the ADT formalism. Our further study reveals that there is a connection between the ADT and the Noether conserved quantities, which signifies that the ADT approach provide the equivalent thermodynamic description in the two frames as obtained in Noether prescription. Our whole analysis is very general as the conserved Noether and ADT currents and potentials are formulated {\it off-shell} and the analysis is exempted from any prior assumption or boundary condition.
gr-qc hep-th
we revisit the thermodynamic aspects of the scalartensor theory of gravity in the jordan and in the einstein frame examining the it missing links of this theory carefully we establish the thermodynamic descriptions from the conserved currents and potentials by following both the noether and the abbottdesertekin adt formalism with the help of conserved noether current and potential we define the thermodynamic quantities which we show to be it conformally invariant moreover the defined quantities are shown to fit nicely in the laws of the first and the second black hole thermodynamics formulated by the walds method we stretch the study of the conformal equivalence of the physical quantities in these two frames by following the adt formalism our further study reveals that there is a connection between the adt and the noether conserved quantities which signifies that the adt approach provide the equivalent thermodynamic description in the two frames as obtained in noether prescription our whole analysis is very general as the conserved noether and adt currents and potentials are formulated it offshell and the analysis is exempted from any prior assumption or boundary condition
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1,803.03772
Generalization and Expressivity for Deep Nets
Along with the rapid development of deep learning in practice, the theoretical explanations for its success become urgent. Generalization and expressivity are two widely used measurements to quantify theoretical behaviors of deep learning. The expressivity focuses on finding functions expressible by deep nets but cannot be approximated by shallow nets with the similar number of neurons. It usually implies the large capacity. The generalization aims at deriving fast learning rate for deep nets. It usually requires small capacity to reduce the variance. Different from previous studies on deep learning, pursuing either expressivity or generalization, we take both factors into account to explore the theoretical advantages of deep nets. For this purpose, we construct a deep net with two hidden layers possessing excellent expressivity in terms of localized and sparse approximation. Then, utilizing the well known covering number to measure the capacity, we find that deep nets possess excellent expressive power (measured by localized and sparse approximation) without enlarging the capacity of shallow nets. As a consequence, we derive near optimal learning rates for implementing empirical risk minimization (ERM) on the constructed deep nets. These results theoretically exhibit the advantage of deep nets from learning theory viewpoints.
cs.LG
along with the rapid development of deep learning in practice the theoretical explanations for its success become urgent generalization and expressivity are two widely used measurements to quantify theoretical behaviors of deep learning the expressivity focuses on finding functions expressible by deep nets but cannot be approximated by shallow nets with the similar number of neurons it usually implies the large capacity the generalization aims at deriving fast learning rate for deep nets it usually requires small capacity to reduce the variance different from previous studies on deep learning pursuing either expressivity or generalization we take both factors into account to explore the theoretical advantages of deep nets for this purpose we construct a deep net with two hidden layers possessing excellent expressivity in terms of localized and sparse approximation then utilizing the well known covering number to measure the capacity we find that deep nets possess excellent expressive power measured by localized and sparse approximation without enlarging the capacity of shallow nets as a consequence we derive near optimal learning rates for implementing empirical risk minimization erm on the constructed deep nets these results theoretically exhibit the advantage of deep nets from learning theory viewpoints
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1,803.03773
Alloy engineering of topological semimetal phase transition in MgTa$_{2-x}$Nb$_x$N$_3$
Dirac, triple-point and Weyl fermions represent three topological semimetal phases, characterized with a descending degree of band degeneracy, which have been realized separately in specific crystalline materials with different lattice symmetries. Here we demonstrate an alloy engineering approach to realize all three types of fermions in one single material system of MgTa$_{2-x}$Nb$_x$N$_3$. Based on symmetry analysis and first-principles calculations, we map out a phase diagram of topological order in the parameter space of alloy concentration and crystalline symmetry, where the intrinsic MgTa$_2$N$_3$ with the highest symmetry hosts the Dirac semimetal phase which transforms into the triple-point and then the Weyl semimetal phase with the increasing Nb concentration that lowers the crystalline symmetries. Therefore, alloy engineering affords a unique approach for experimental investigation of topological transitions of semimetallic phases manifesting different fermionic behaviors.
cond-mat.mtrl-sci
dirac triplepoint and weyl fermions represent three topological semimetal phases characterized with a descending degree of band degeneracy which have been realized separately in specific crystalline materials with different lattice symmetries here we demonstrate an alloy engineering approach to realize all three types of fermions in one single material system of mgta_2xnb_xn_3 based on symmetry analysis and firstprinciples calculations we map out a phase diagram of topological order in the parameter space of alloy concentration and crystalline symmetry where the intrinsic mgta_2n_3 with the highest symmetry hosts the dirac semimetal phase which transforms into the triplepoint and then the weyl semimetal phase with the increasing nb concentration that lowers the crystalline symmetries therefore alloy engineering affords a unique approach for experimental investigation of topological transitions of semimetallic phases manifesting different fermionic behaviors
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1,803.03774
Long-period limit of exact periodic traveling wave solutions for the derivative nonlinear Schr\"{o}dinger equation
We study the periodic traveling wave solutions of the derivative nonlinear Schr\"{o}dinger equation (DNLS). It is known that DNLS has two types of solitons on the whole line; one has exponential decay and the other has algebraic decay. The latter corresponds to the soliton for the massless case. In the new global results recently obtained by Fukaya, Hayashi and Inui, the properties of two-parameter of the solitons are essentially used in the proof, and especially the soliton for the massless case plays an important role. To investigate further properties of the solitons, we construct exact periodic traveling wave solutions which yield the solitons on the whole line including the massless case in the long-period limit. Moreover, we study the regularity of the convergence of these exact solutions in the long-period limit. Throughout the paper, the theory of elliptic functions and elliptic integrals is used in the calculation.
math.AP math-ph math.MP
we study the periodic traveling wave solutions of the derivative nonlinear schrodinger equation dnls it is known that dnls has two types of solitons on the whole line one has exponential decay and the other has algebraic decay the latter corresponds to the soliton for the massless case in the new global results recently obtained by fukaya hayashi and inui the properties of twoparameter of the solitons are essentially used in the proof and especially the soliton for the massless case plays an important role to investigate further properties of the solitons we construct exact periodic traveling wave solutions which yield the solitons on the whole line including the massless case in the longperiod limit moreover we study the regularity of the convergence of these exact solutions in the longperiod limit throughout the paper the theory of elliptic functions and elliptic integrals is used in the calculation
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1,803.03775
Light Scattering by Fractal Dust Aggregates. II. Opacity and Asymmetry Parameter
Optical properties of dust aggregates are important at various astrophysical environments. To find a reliable approximation method for optical properties of dust aggregates, we calculate the opacity and the asymmetry parameter of dust aggregates by using a rigorous numerical method, the T-Matrix Method (TMM), and then the results are compared to those obtained by approximate methods; the Rayleigh-Gans-Debye (RGD) theory, the effective medium theory (EMT), and the distribution of hollow spheres method (DHS). First of all, we confirm that the RGD theory breaks down when multiple scattering is important. In addition, we find that both EMT and DHS fail to reproduce the optical properties of dust aggregates with fractal dimension of 2 when the incident wavelength is shorter than the aggregate radius. In order to solve these problems, we test the mean field theory (MFT), where multiple scattering can be taken into account. We show that the extinction opacity of dust aggregates can be well reproduced by MFT. However, it is also shown that MFT is not able to reproduce the scattering and absorption opacities when multiple scattering is important. We successfully resolve this weak point of MFT, by newly developing a modified mean field theory (MMF). Hence, we conclude that MMF can be a useful tool to investigate radiative transfer properties of various astrophysical environments. We also point out an enhancement of the absorption opacity of dust aggregates in the Rayleigh domain, which would be important to explain the large millimeter-wave opacity inferred from observations of protoplanetary disks.
astro-ph.EP
optical properties of dust aggregates are important at various astrophysical environments to find a reliable approximation method for optical properties of dust aggregates we calculate the opacity and the asymmetry parameter of dust aggregates by using a rigorous numerical method the tmatrix method tmm and then the results are compared to those obtained by approximate methods the rayleighgansdebye rgd theory the effective medium theory emt and the distribution of hollow spheres method dhs first of all we confirm that the rgd theory breaks down when multiple scattering is important in addition we find that both emt and dhs fail to reproduce the optical properties of dust aggregates with fractal dimension of 2 when the incident wavelength is shorter than the aggregate radius in order to solve these problems we test the mean field theory mft where multiple scattering can be taken into account we show that the extinction opacity of dust aggregates can be well reproduced by mft however it is also shown that mft is not able to reproduce the scattering and absorption opacities when multiple scattering is important we successfully resolve this weak point of mft by newly developing a modified mean field theory mmf hence we conclude that mmf can be a useful tool to investigate radiative transfer properties of various astrophysical environments we also point out an enhancement of the absorption opacity of dust aggregates in the rayleigh domain which would be important to explain the large millimeterwave opacity inferred from observations of protoplanetary disks
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1,803.03776
Yielding of a Model Glassformer: an Interpretation with an Effective System of Icosahedra
We consider the yielding under simple shear of a binary Lennard-Jones glassformer whose super-Arrhenius dynamics are correlated with the formation of icosahedral structures. We recast this glassformer as an effective system of icosahedra [Pinney et al. J. Chem. Phys. 143 244507 (2015)]. Looking at the small-strain region of sheared simulations, we observe that shear rates affect the shear localisation behavior particularly at temperatures below the glass transition as defined with a fit to the Vogel-Fulcher-Tamman equation. At higher temperature, shear localisation starts immediately upon shearing for all shear rates. At lower temperatures, faster shear rates can result in a delayed start in shear localisation; which begins close to the yield stress. Building from a previous work which considered steady-state shear [Pinney et al. J. Chem. Phys. 143 244507 (2016)], we interpret the response to shear and the shear localisation in terms of a \emph{local} effective temperature with our system of icosahedra. We find that the effective temperatures of the regions undergoing shear localisation increase significantly with increasing strain (before reaching a steady state plateau).
cond-mat.soft cond-mat.mtrl-sci cond-mat.stat-mech
we consider the yielding under simple shear of a binary lennardjones glassformer whose superarrhenius dynamics are correlated with the formation of icosahedral structures we recast this glassformer as an effective system of icosahedra pinney et al j chem phys 143 244507 2015 looking at the smallstrain region of sheared simulations we observe that shear rates affect the shear localisation behavior particularly at temperatures below the glass transition as defined with a fit to the vogelfulchertamman equation at higher temperature shear localisation starts immediately upon shearing for all shear rates at lower temperatures faster shear rates can result in a delayed start in shear localisation which begins close to the yield stress building from a previous work which considered steadystate shear pinney et al j chem phys 143 244507 2016 we interpret the response to shear and the shear localisation in terms of a emphlocal effective temperature with our system of icosahedra we find that the effective temperatures of the regions undergoing shear localisation increase significantly with increasing strain before reaching a steady state plateau
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1,803.03777
Deep Cross-media Knowledge Transfer
Cross-media retrieval is a research hotspot in multimedia area, which aims to perform retrieval across different media types such as image and text. The performance of existing methods usually relies on labeled data for model training. However, cross-media data is very labor consuming to collect and label, so how to transfer valuable knowledge in existing data to new data is a key problem towards application. For achieving the goal, this paper proposes deep cross-media knowledge transfer (DCKT) approach, which transfers knowledge from a large-scale cross-media dataset to promote the model training on another small-scale cross-media dataset. The main contributions of DCKT are: (1) Two-level transfer architecture is proposed to jointly minimize the media-level and correlation-level domain discrepancies, which allows two important and complementary aspects of knowledge to be transferred: intra-media semantic and inter-media correlation knowledge. It can enrich the training information and boost the retrieval accuracy. (2) Progressive transfer mechanism is proposed to iteratively select training samples with ascending transfer difficulties, via the metric of cross-media domain consistency with adaptive feedback. It can drive the transfer process to gradually reduce vast cross-media domain discrepancy, so as to enhance the robustness of model training. For verifying the effectiveness of DCKT, we take the largescale dataset XMediaNet as source domain, and 3 widelyused datasets as target domain for cross-media retrieval. Experimental results show that DCKT achieves promising improvement on retrieval accuracy.
cs.MM
crossmedia retrieval is a research hotspot in multimedia area which aims to perform retrieval across different media types such as image and text the performance of existing methods usually relies on labeled data for model training however crossmedia data is very labor consuming to collect and label so how to transfer valuable knowledge in existing data to new data is a key problem towards application for achieving the goal this paper proposes deep crossmedia knowledge transfer dckt approach which transfers knowledge from a largescale crossmedia dataset to promote the model training on another smallscale crossmedia dataset the main contributions of dckt are 1 twolevel transfer architecture is proposed to jointly minimize the medialevel and correlationlevel domain discrepancies which allows two important and complementary aspects of knowledge to be transferred intramedia semantic and intermedia correlation knowledge it can enrich the training information and boost the retrieval accuracy 2 progressive transfer mechanism is proposed to iteratively select training samples with ascending transfer difficulties via the metric of crossmedia domain consistency with adaptive feedback it can drive the transfer process to gradually reduce vast crossmedia domain discrepancy so as to enhance the robustness of model training for verifying the effectiveness of dckt we take the largescale dataset xmedianet as source domain and 3 widelyused datasets as target domain for crossmedia retrieval experimental results show that dckt achieves promising improvement on retrieval accuracy
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1,803.03778
Driving Scene Perception Network: Real-time Joint Detection, Depth Estimation and Semantic Segmentation
As the demand for enabling high-level autonomous driving has increased in recent years and visual perception is one of the critical features to enable fully autonomous driving, in this paper, we introduce an efficient approach for simultaneous object detection, depth estimation and pixel-level semantic segmentation using a shared convolutional architecture. The proposed network model, which we named Driving Scene Perception Network (DSPNet), uses multi-level feature maps and multi-task learning to improve the accuracy and efficiency of object detection, depth estimation and image segmentation tasks from a single input image. Hence, the resulting network model uses less than 850 MiB of GPU memory and achieves 14.0 fps on NVIDIA GeForce GTX 1080 with a 1024x512 input image, and both precision and efficiency have been improved over combination of single tasks.
cs.CV
as the demand for enabling highlevel autonomous driving has increased in recent years and visual perception is one of the critical features to enable fully autonomous driving in this paper we introduce an efficient approach for simultaneous object detection depth estimation and pixellevel semantic segmentation using a shared convolutional architecture the proposed network model which we named driving scene perception network dspnet uses multilevel feature maps and multitask learning to improve the accuracy and efficiency of object detection depth estimation and image segmentation tasks from a single input image hence the resulting network model uses less than 850 mib of gpu memory and achieves 140 fps on nvidia geforce gtx 1080 with a 1024x512 input image and both precision and efficiency have been improved over combination of single tasks
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1,803.03779
Quantum Dimensional Transition in Spin-$\frac{1}{2}$ Antiferromagnetic Heisenberg Model on A Square Lattice and Space Reduction in Matrix Product State
We study the spin-$\frac{1}{2}$ antiferromagnetic Heisenberg model on an infinity-by-$N$ square lattice for even $N$'s up to $14$. Previously, the nonlinear sigma model perturbatively predicts that its spin rotational symmetry asymptotically breaks when $N\rightarrow \infty$, i.e., when it is two-dimensional (2D). However, we identified a critical width $N_c = 10$ for which this symmetry breaks spontaneously. It defines a dimensional transition from one-dimension (1D) including quasi-1D to 2D. The finite-size effect differs from that of the $N$-by-$N$ lattice. The ground state (GS) energy per site approaches the thermodynamic limit value, in agreement with the previously accepted value, by one order of $1/N$ faster than when using $N$-by-$N$ lattices in the literature. We build and variationally solve a matrix product state (MPS) on a chain, converting the $N$ sites in the rung into an effective site. We show that the area law of entanglement entropy does not apply when $N$ increases in our method, and show that the reduced density matrix of each effective site will have a saturating number of dominant diagonal elements with increasing $N$. These two characteristics make the MPS rank needed to obtain a demanded energy accuracy quickly saturate when $N$ is large, making our algorithm efficient for large $N$'s. And, the latter enables space reduction in MPS. Within the framework of MPS, we prove a theorem that the spin-spin correlation at infinite separation is the square of staggered magnetization and demonstrate that the eigenvalue structure of a building MPS unit of $\langle g\mid g\rangle$, $\mid g\rangle$ being the GS, is responsible for order, disorder and quasi-long-range order.
cond-mat.str-el
we study the spinfrac12 antiferromagnetic heisenberg model on an infinitybyn square lattice for even ns up to 14 previously the nonlinear sigma model perturbatively predicts that its spin rotational symmetry asymptotically breaks when nrightarrow infty ie when it is twodimensional 2d however we identified a critical width n_c 10 for which this symmetry breaks spontaneously it defines a dimensional transition from onedimension 1d including quasi1d to 2d the finitesize effect differs from that of the nbyn lattice the ground state gs energy per site approaches the thermodynamic limit value in agreement with the previously accepted value by one order of 1n faster than when using nbyn lattices in the literature we build and variationally solve a matrix product state mps on a chain converting the n sites in the rung into an effective site we show that the area law of entanglement entropy does not apply when n increases in our method and show that the reduced density matrix of each effective site will have a saturating number of dominant diagonal elements with increasing n these two characteristics make the mps rank needed to obtain a demanded energy accuracy quickly saturate when n is large making our algorithm efficient for large ns and the latter enables space reduction in mps within the framework of mps we prove a theorem that the spinspin correlation at infinite separation is the square of staggered magnetization and demonstrate that the eigenvalue structure of a building mps unit of langle gmid grangle mid grangle being the gs is responsible for order disorder and quasilongrange order
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1,803.0378
Energy and Delay Optimization for Cache-Enabled Dense Small Cell Networks
Caching popular files in small base stations (SBSs) has been proved to be an effective way to reduce bandwidth pressure on the backhaul links of dense small cell networks (DSCNs). Many existing studies on cache-enabled DSCNs attempt to improve user experience by optimizing end-to-end file delivery delay. However, under practical scenarios where files (e.g., video files) have diverse quality of service requirements, energy consumption at SBSs should also be concerned from the network perspective. In this paper,we attempt to optimize these two critical metrics in cache-enabled DSCNs. Firstly, we formulate the energy-delay optimization problem as a Mixed Integer Programming (MIP) problem, where file placement, user association and power control are jointly considered. To model the tradeoff relationship between energy consumption and end-to-end file delivery delay, a utility function linearly combining these two metrics is used as an objective function of the optimization problem. Then, we solve the problem in two stages, i.e. caching stage and delivery stage, based on the observation that caching is performed during off-peak time. At the caching stage, a local popular file placement policy is proposed by estimating user preference at each SBS. At the delivery stage, with given caching status at SBSs, the MIP problem is further decomposed by Benders' decomposition method. An efficient algorithm is proposed to approach the optimal association and power solution by iteratively shrinking the gap of the upper and lower bounds. Finally, extension simulations are performed to validate our analytical and algorithmic work. The results demonstrate that the proposed algorithms can achieve the optimal tradeoff between energy consumption and end-to-end file delivery delay.
cs.NI
caching popular files in small base stations sbss has been proved to be an effective way to reduce bandwidth pressure on the backhaul links of dense small cell networks dscns many existing studies on cacheenabled dscns attempt to improve user experience by optimizing endtoend file delivery delay however under practical scenarios where files eg video files have diverse quality of service requirements energy consumption at sbss should also be concerned from the network perspective in this paperwe attempt to optimize these two critical metrics in cacheenabled dscns firstly we formulate the energydelay optimization problem as a mixed integer programming mip problem where file placement user association and power control are jointly considered to model the tradeoff relationship between energy consumption and endtoend file delivery delay a utility function linearly combining these two metrics is used as an objective function of the optimization problem then we solve the problem in two stages ie caching stage and delivery stage based on the observation that caching is performed during offpeak time at the caching stage a local popular file placement policy is proposed by estimating user preference at each sbs at the delivery stage with given caching status at sbss the mip problem is further decomposed by benders decomposition method an efficient algorithm is proposed to approach the optimal association and power solution by iteratively shrinking the gap of the upper and lower bounds finally extension simulations are performed to validate our analytical and algorithmic work the results demonstrate that the proposed algorithms can achieve the optimal tradeoff between energy consumption and endtoend file delivery delay
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1,803.03781
The lamppost model: effects of photon trapping, the bottom lamp and disc truncation
We study the lamppost model, in which the primary X-ray sources in accreting black-hole systems are located symmetrically on the rotation axis on both sides of the black hole surrounded by an accretion disc. We show the importance of the emission of the source on the opposite side to the observer. Due to gravitational light bending, its emission can increase the direct (i.e., not re-emitted by the disc) flux by as much as an order of magnitude. This happens for near to face-on observers when the disc is even moderately truncated. For truncated discs, we also consider effects of emission of the top source gravitationally bent around the black hole. We also present results for the attenuation of the observed radiation with respect to that emitted by the lamppost as functions of the lamppost height, black-hole spin and the degree of disc truncation. This attenuation, which is due to the time dilation, gravitational redshift and the loss of photons crossing the black-hole horizon, can be as severe as by several orders of magnitude for low lamppost heights. We also consider the contribution to the observed flux due to re-emission by optically-thick matter within the innermost stable circular orbit.
astro-ph.HE
we study the lamppost model in which the primary xray sources in accreting blackhole systems are located symmetrically on the rotation axis on both sides of the black hole surrounded by an accretion disc we show the importance of the emission of the source on the opposite side to the observer due to gravitational light bending its emission can increase the direct ie not reemitted by the disc flux by as much as an order of magnitude this happens for near to faceon observers when the disc is even moderately truncated for truncated discs we also consider effects of emission of the top source gravitationally bent around the black hole we also present results for the attenuation of the observed radiation with respect to that emitted by the lamppost as functions of the lamppost height blackhole spin and the degree of disc truncation this attenuation which is due to the time dilation gravitational redshift and the loss of photons crossing the blackhole horizon can be as severe as by several orders of magnitude for low lamppost heights we also consider the contribution to the observed flux due to reemission by opticallythick matter within the innermost stable circular orbit
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1,803.03782
Electrodynamics of ferroelectric films with negative capacitance
We construct a comprehensive theory of the electrodynamic response of ferroelectric ultra-thin films containing periodic domain textures (PDT) with 180{\deg} polarization-oriented domains. The focal point of the theory is the negative-capacitance phenomenon which naturally arises from the depolarization field induced by PDT. We derive frequency-dependent dielectric permittivity related to the PDT dynamics across the entire frequency range. We find the resonance mode of domain oscillations in the THz spectral band and the singular points in the phase of the reflected THz beam that are intimately related to the negative capacitance. Our findings provide a platform for the THz negative capacitance-based optics of ferroelectric films and for engineering the epsilon-near-zero plasmonic THz metamaterials.
cond-mat.mes-hall
we construct a comprehensive theory of the electrodynamic response of ferroelectric ultrathin films containing periodic domain textures pdt with 180deg polarizationoriented domains the focal point of the theory is the negativecapacitance phenomenon which naturally arises from the depolarization field induced by pdt we derive frequencydependent dielectric permittivity related to the pdt dynamics across the entire frequency range we find the resonance mode of domain oscillations in the thz spectral band and the singular points in the phase of the reflected thz beam that are intimately related to the negative capacitance our findings provide a platform for the thz negative capacitancebased optics of ferroelectric films and for engineering the epsilonnearzero plasmonic thz metamaterials
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1,803.03783
Linearized stability analysis of Caputo-Katugampola fractional-order nonlinear systems
In this paper, a linearized asymptotic stability result for a Caputo-Katugampola fractional-order systems is described. An application is given to demonstrate the validity of the proposed results.
math.DS
in this paper a linearized asymptotic stability result for a caputokatugampola fractionalorder systems is described an application is given to demonstrate the validity of the proposed results
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1,803.03784
Combining Method of Alternating Projections and Augmented Lagrangian for Task Constrained Trajectory Optimization
Motion planning for manipulators under task space constraints is difficult as it constrains the joint configurations to always lie on an implicitly defined manifold. It is possible to view task constrained motion planning as an optimization problem with non-linear equality constraints which can be solved by general non-linear optimization techniques. In this paper, we present a novel custom optimizer which exploits the underlying structure present in many task constraints. At the core of our approach are some simple reformulations, which when coupled with the \emph{method of alternating projection}, leads to an efficient convex optimization based routine for computing a feasible solution to the task constraints. We subsequently build on this result and use the concept of Augmented Lagrangian to guide the feasible solutions towards those which also minimize the user defined cost function. We show that the proposed optimizer is fully distributive and thus, can be easily parallelized. We validate our formulation on some common robotic benchmark problems. In particular, we show that the proposed optimizer achieves cyclic motion in the joint space corresponding to a similar nature trajectory in the task space. Furthermore, as a baseline, we compare the proposed optimizer with an off-the-shelf non-linear solver provide in open source package SciPy. We show that for similar task constraint residuals and smoothness cost, it can be upto more than three times faster than the SciPy alternative.
cs.RO
motion planning for manipulators under task space constraints is difficult as it constrains the joint configurations to always lie on an implicitly defined manifold it is possible to view task constrained motion planning as an optimization problem with nonlinear equality constraints which can be solved by general nonlinear optimization techniques in this paper we present a novel custom optimizer which exploits the underlying structure present in many task constraints at the core of our approach are some simple reformulations which when coupled with the emphmethod of alternating projection leads to an efficient convex optimization based routine for computing a feasible solution to the task constraints we subsequently build on this result and use the concept of augmented lagrangian to guide the feasible solutions towards those which also minimize the user defined cost function we show that the proposed optimizer is fully distributive and thus can be easily parallelized we validate our formulation on some common robotic benchmark problems in particular we show that the proposed optimizer achieves cyclic motion in the joint space corresponding to a similar nature trajectory in the task space furthermore as a baseline we compare the proposed optimizer with an offtheshelf nonlinear solver provide in open source package scipy we show that for similar task constraint residuals and smoothness cost it can be upto more than three times faster than the scipy alternative
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1,803.03785
Statistical mechanics of high-density bond percolation
High-density (HD) percolation describes the percolation over specific $\kappa$ -clusters, which are the compact sets of sites each connected to $\kappa$ nearest filled sites at least. It takes place in the classical patterns of independently distributed sites or bonds in which the ordinary percolation transition also exsists. Hence, the study of series of $\kappa$ -type percolations amounts to the description of structure of classical clusters for which $\kappa$ -clusters constitute $\kappa$ -cores nested one into another. Such data are needed for description of a number of physical, biological information and other properties of complex systems on random lattices, graphs and networks. They range from magnetic properties of semiconductor alloys to anomalies in supercooled water and clustering in biological and social networks. Here we present the statistical mechanics approach to study HD bond percolation on arbitrary graph. It is shown that generating function for $\kappa$ -clusters' size distribution can be obtained from partition function of specific $q$-state Potts-Ising model in $q \to 1$ limit. Using this approach we find exact $\kappa$ -clusters' size distribution for Bethe lattice and Erdos Renyi graph. The application of the method to Euclidean lattices is also discussed.
cond-mat.stat-mech cond-mat.dis-nn
highdensity hd percolation describes the percolation over specific kappa clusters which are the compact sets of sites each connected to kappa nearest filled sites at least it takes place in the classical patterns of independently distributed sites or bonds in which the ordinary percolation transition also exsists hence the study of series of kappa type percolations amounts to the description of structure of classical clusters for which kappa clusters constitute kappa cores nested one into another such data are needed for description of a number of physical biological information and other properties of complex systems on random lattices graphs and networks they range from magnetic properties of semiconductor alloys to anomalies in supercooled water and clustering in biological and social networks here we present the statistical mechanics approach to study hd bond percolation on arbitrary graph it is shown that generating function for kappa clusters size distribution can be obtained from partition function of specific qstate pottsising model in q to 1 limit using this approach we find exact kappa clusters size distribution for bethe lattice and erdos renyi graph the application of the method to euclidean lattices is also discussed
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1,803.03786
We Built a Fake News & Click-bait Filter: What Happened Next Will Blow Your Mind!
It is completely amazing! Fake news and click-baits have totally invaded the cyber space. Let us face it: everybody hates them for three simple reasons. Reason #2 will absolutely amaze you. What these can achieve at the time of election will completely blow your mind! Now, we all agree, this cannot go on, you know, somebody has to stop it. So, we did this research on fake news/click-bait detection and trust us, it is totally great research, it really is! Make no mistake. This is the best research ever! Seriously, come have a look, we have it all: neural networks, attention mechanism, sentiment lexicons, author profiling, you name it. Lexical features, semantic features, we absolutely have it all. And we have totally tested it, trust us! We have results, and numbers, really big numbers. The best numbers ever! Oh, and analysis, absolutely top notch analysis. Interested? Come read the shocking truth about fake news and click-bait in the Bulgarian cyber space. You won't believe what we have found!
cs.CL
it is completely amazing fake news and clickbaits have totally invaded the cyber space let us face it everybody hates them for three simple reasons reason 2 will absolutely amaze you what these can achieve at the time of election will completely blow your mind now we all agree this cannot go on you know somebody has to stop it so we did this research on fake newsclickbait detection and trust us it is totally great research it really is make no mistake this is the best research ever seriously come have a look we have it all neural networks attention mechanism sentiment lexicons author profiling you name it lexical features semantic features we absolutely have it all and we have totally tested it trust us we have results and numbers really big numbers the best numbers ever oh and analysis absolutely top notch analysis interested come read the shocking truth about fake news and clickbait in the bulgarian cyber space you wont believe what we have found
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1,803.03787
Interplay of structural design and interaction processes in tunnel-injection semiconductor lasers
Tunnel-injection lasers promise various advantages in comparison to conventional laser designs. In this paper, we present a theoretical analysis for the physics of the tunnel-injection process in quantum-dot based laser devices. We describe the carrier dynamics in terms of scattering between states of the coupled system consisting of injector quantum-well, tunnel-barrier, and quantum-dots. Our analysis demonstrates how current quantum-dot based lasers can benefit from the tunnel-injection design. We find that the often assumed LO-phonon resonance condition for the level alignment only weakly influences the injection rate of carriers into the quantum-dot states. On the other hand, our investigations show that the energetic alignment of quantum-dot and quantum-well states modifies the injection efficiency, as it controls the hybridization strength. Our description of tunneling includes the phonon-mediated and the Coulomb scattering contributions and is based on material realistic electronic structure calculations.
physics.app-ph cond-mat.mes-hall
tunnelinjection lasers promise various advantages in comparison to conventional laser designs in this paper we present a theoretical analysis for the physics of the tunnelinjection process in quantumdot based laser devices we describe the carrier dynamics in terms of scattering between states of the coupled system consisting of injector quantumwell tunnelbarrier and quantumdots our analysis demonstrates how current quantumdot based lasers can benefit from the tunnelinjection design we find that the often assumed lophonon resonance condition for the level alignment only weakly influences the injection rate of carriers into the quantumdot states on the other hand our investigations show that the energetic alignment of quantumdot and quantumwell states modifies the injection efficiency as it controls the hybridization strength our description of tunneling includes the phononmediated and the coulomb scattering contributions and is based on material realistic electronic structure calculations
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1,803.03788
Dimension of the repeller for a piecewise expanding affine map
In this paper, we study the dimension theory of a class of piecewise affine systems in euclidean spaces suggested by Michael Barnsley, with some applications to the fractal image compression. It is a more general version of the class considered in the work of Keane, Simon and Solomyak [The dimension of graph directed attractors with overlaps on the line, with an application to a problem in fractal image recognition. {\it Fund. Math.}, {\bf 180}(3):279-292, 2003] and can be considered as the continuation of the works [On the dimension of self-affine sets and measures with overlaps. {\it Proc. Amer. Math. Soc.}, {\bf 144}(10):4427-4440, 2016], [On the dimension of triangular self-affine sets. {\it Erg. Th. \& Dynam. Sys.}, to appear.] by the authors. We also present some applications of our results for the generalized Takagi functions and fractal interpolation functions.
math.DS
in this paper we study the dimension theory of a class of piecewise affine systems in euclidean spaces suggested by michael barnsley with some applications to the fractal image compression it is a more general version of the class considered in the work of keane simon and solomyak the dimension of graph directed attractors with overlaps on the line with an application to a problem in fractal image recognition it fund math bf 1803279292 2003 and can be considered as the continuation of the works on the dimension of selfaffine sets and measures with overlaps it proc amer math soc bf 1441044274440 2016 on the dimension of triangular selfaffine sets it erg th dynam sys to appear by the authors we also present some applications of our results for the generalized takagi functions and fractal interpolation functions
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1,803.03789
Lyman-alpha emitters gone missing: the different evolution of the bright and faint populations
We model the transmission of the Lyman-alpha line through the circum- and intergalactic media around dark matter haloes expected to host Lyman-alpha emitters (LAEs) at z > 5.7, using the high-dynamic-range Sherwood simulations. We find very different CGM environments around more massive haloes (~10^11 M_sun) compared to less massive haloes (~10^9 M_sun) at these redshifts, which can contribute to a different evolution of the Lyman-alpha transmission from LAEs within these haloes. Additionally we confirm that part of the differential evolution could result from bright LAEs being more likely to reside in larger ionized regions. We conclude that a combination of the CGM environment and the IGM ionization structure is likely to be responsible for the differential evolution of the bright and faint ends of the LAE luminosity function at z > 6. More generally, we confirm the suggestion that the self-shielded neutral gas in the outskirts of the host halo can strongly attenuate the Lyman-alpha emission from high redshift galaxies. We find that this has a stronger effect on the more massive haloes hosting brighter LAEs. The faint-end of the LAE luminosity function is thus a more reliable probe of the average ionization state of the IGM. Comparing our model for LAEs with a range of observational data we find that the favoured reionization histories are our previously advocated `Late' and `Very Late' reionization histories, in which reionization finishes rather rapidly at around z ~ 6.
astro-ph.GA astro-ph.CO
we model the transmission of the lymanalpha line through the circum and intergalactic media around dark matter haloes expected to host lymanalpha emitters laes at z 57 using the highdynamicrange sherwood simulations we find very different cgm environments around more massive haloes 1011 m_sun compared to less massive haloes 109 m_sun at these redshifts which can contribute to a different evolution of the lymanalpha transmission from laes within these haloes additionally we confirm that part of the differential evolution could result from bright laes being more likely to reside in larger ionized regions we conclude that a combination of the cgm environment and the igm ionization structure is likely to be responsible for the differential evolution of the bright and faint ends of the lae luminosity function at z 6 more generally we confirm the suggestion that the selfshielded neutral gas in the outskirts of the host halo can strongly attenuate the lymanalpha emission from high redshift galaxies we find that this has a stronger effect on the more massive haloes hosting brighter laes the faintend of the lae luminosity function is thus a more reliable probe of the average ionization state of the igm comparing our model for laes with a range of observational data we find that the favoured reionization histories are our previously advocated late and very late reionization histories in which reionization finishes rather rapidly at around z 6
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1,803.0379
Towards a Multi-array Architecture for Accelerating Large-scale Matrix Multiplication on FPGAs
Large-scale floating-point matrix multiplication is a fundamental kernel in many scientific and engineering applications. Most existing work only focus on accelerating matrix multiplication on FPGA by adopting a linear systolic array. This paper towards the extension of this architecture by proposing a scalable and highly configurable multi-array architecture. In addition, we propose a work-stealing scheme to ensure the equality in the workload partition among multiple linear arrays. Furthermore, an analytical model is developed to determine the optimal design parameters. Experiments on a real-life convolutional neural network (CNN) show that we can obtain the optimal extension of the linear array architecture.
cs.AR
largescale floatingpoint matrix multiplication is a fundamental kernel in many scientific and engineering applications most existing work only focus on accelerating matrix multiplication on fpga by adopting a linear systolic array this paper towards the extension of this architecture by proposing a scalable and highly configurable multiarray architecture in addition we propose a workstealing scheme to ensure the equality in the workload partition among multiple linear arrays furthermore an analytical model is developed to determine the optimal design parameters experiments on a reallife convolutional neural network cnn show that we can obtain the optimal extension of the linear array architecture
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1,803.03791
Shtukas for reductive groups and Langlands correspondence for function fields
We discuss recent developments in the Langlands program for function fields, and in the geometric Langlands program. In particular we explain a canonical decomposition of the space of cuspidal automorphic forms for any reductive group G over a function field, indexed by global Langlands parameters. The proof uses the cohomology of G-shtukas with multiple modifications and the geometric Satake equivalence.
math.AG math.RT
we discuss recent developments in the langlands program for function fields and in the geometric langlands program in particular we explain a canonical decomposition of the space of cuspidal automorphic forms for any reductive group g over a function field indexed by global langlands parameters the proof uses the cohomology of gshtukas with multiple modifications and the geometric satake equivalence
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1,803.03792
Hypoxia-inducible factor 1a protects peripheral sensory neurons from diabetic peripheral neuropathy by suppressing accumulation of reactive oxygen species
Diabetic peripheral neuropathy (DPN) is one of the most common diabetic complications. Mechanisms underlying nerve damage and sensory loss following metabolic dysfunction remain large unclear. Recently, hyperglycemia-induced mitochondrial dysfunction and the generation of ROS have gained attention as possible mechanisms of organ damage in diabetes. Hypoxia-inducible factor 1(HIF1a) is a key transcription factor activated by hypoxia, hyperglycemia, nitric oxide as well as ROS, suggesting a fundamental role in DPN susceptibility. Genetically-modified mutant mice, which conditionally lack HIF1a in peripheral sensory neurons (SNS-HIF1a-/-), were analyzed longitudinally up to 6 months in the streptozotocin (STZ) model of type1 diabetes. Behavioral measurements of sensitivity to thermal and mechanical stimuli, quantitative morphological analyses of intraepidermal nerve fiber density and measurements of reactive oxygen species (ROS) in sensory neurons in vivo were undertaken over several months post-STZ injections to delineate the role of HIF1a in DPN. Longitudinal behavioral and morphological analyses at 5, 13 and 24 wks post-STZ treatment revealed that SNS-HIF1a-/- developed stronger hyperglycemia-evoked losses of peripheral nociceptive sensory axons associated with stronger losses of mechano- and heat sensation with a faster onset than HIF1afl/fl mice. Mechanistically, these histomorphologic and behavioral differences were associated with significantly higher level of STZ-induced production of ROS in sensory neurons of SNS-HIF1a-/- mice as compared with HIF1afl/fl. Our results indicate that HIF1a is as an upstream modulator of ROS in peripheral sensory neurons and exerts a protective function in suppressing hyperglycemia-induced nerve damage by limiting ROS levels. HIF1a stabilization may be thus a new strategy target for limiting sensory loss, a debilitating late complication of diabetes.
q-bio.CB
diabetic peripheral neuropathy dpn is one of the most common diabetic complications mechanisms underlying nerve damage and sensory loss following metabolic dysfunction remain large unclear recently hyperglycemiainduced mitochondrial dysfunction and the generation of ros have gained attention as possible mechanisms of organ damage in diabetes hypoxiainducible factor 1hif1a is a key transcription factor activated by hypoxia hyperglycemia nitric oxide as well as ros suggesting a fundamental role in dpn susceptibility geneticallymodified mutant mice which conditionally lack hif1a in peripheral sensory neurons snshif1a were analyzed longitudinally up to 6 months in the streptozotocin stz model of type1 diabetes behavioral measurements of sensitivity to thermal and mechanical stimuli quantitative morphological analyses of intraepidermal nerve fiber density and measurements of reactive oxygen species ros in sensory neurons in vivo were undertaken over several months poststz injections to delineate the role of hif1a in dpn longitudinal behavioral and morphological analyses at 5 13 and 24 wks poststz treatment revealed that snshif1a developed stronger hyperglycemiaevoked losses of peripheral nociceptive sensory axons associated with stronger losses of mechano and heat sensation with a faster onset than hif1aflfl mice mechanistically these histomorphologic and behavioral differences were associated with significantly higher level of stzinduced production of ros in sensory neurons of snshif1a mice as compared with hif1aflfl our results indicate that hif1a is as an upstream modulator of ros in peripheral sensory neurons and exerts a protective function in suppressing hyperglycemiainduced nerve damage by limiting ros levels hif1a stabilization may be thus a new strategy target for limiting sensory loss a debilitating late complication of diabetes
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1,803.03793
The Maker-Breaker Rado game on a random set of integers
Given an integer-valued matrix $A$ of dimension $\ell \times k$ and an integer-valued vector $b$ of dimension $\ell$, the Maker-Breaker $(A,b)$-game on a set of integers $X$ is the game where Maker and Breaker take turns claiming previously unclaimed integers from $X$, and Maker's aim is to obtain a solution to the system $Ax=b$, whereas Breaker's aim is to prevent this. When $X$ is a random subset of $\{1,\dots,n\}$ where each number is included with probability $p$ independently of all others, we determine the threshold probability $p_0$ for when the game is Maker or Breaker's win, for a large class of matrices and vectors. This class includes but is not limited to all pairs $(A,b)$ for which $Ax=b$ corresponds to a single linear equation. The Maker's win statement also extends to a much wider class of matrices which include those which satisfy Rado's partition theorem.
math.CO
given an integervalued matrix a of dimension ell times k and an integervalued vector b of dimension ell the makerbreaker abgame on a set of integers x is the game where maker and breaker take turns claiming previously unclaimed integers from x and makers aim is to obtain a solution to the system axb whereas breakers aim is to prevent this when x is a random subset of 1dotsn where each number is included with probability p independently of all others we determine the threshold probability p_0 for when the game is maker or breakers win for a large class of matrices and vectors this class includes but is not limited to all pairs ab for which axb corresponds to a single linear equation the makers win statement also extends to a much wider class of matrices which include those which satisfy rados partition theorem
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1,803.03794
Approximation schemes for mixed optimal stopping and control problems with nonlinear expectations and jumps
We propose a class of numerical schemes for mixed optimal stopping and control of processes with infinite activity jumps and where the objective is evaluated by a nonlinear expectation. Exploiting an approximation by switching systems, piecewise constant policy timestepping reduces the problem to nonlocal semi-linear equations with different control parameters, uncoupled over individual time steps, which we solve by fully implicit monotone approximations to the controlled diffusion and the nonlocal term, and specifically the Lax-Friedrichs scheme for the nonlinearity in the gradient. We establish a comparison principle for the switching system and demonstrate the convergence of the schemes, which subsequently gives a constructive proof for the existence of a solution to the switching system. Numerical experiments are presented for a recursive utility maximization problem to demonstrate the effectiveness of the new schemes.
math.NA math.OC
we propose a class of numerical schemes for mixed optimal stopping and control of processes with infinite activity jumps and where the objective is evaluated by a nonlinear expectation exploiting an approximation by switching systems piecewise constant policy timestepping reduces the problem to nonlocal semilinear equations with different control parameters uncoupled over individual time steps which we solve by fully implicit monotone approximations to the controlled diffusion and the nonlocal term and specifically the laxfriedrichs scheme for the nonlinearity in the gradient we establish a comparison principle for the switching system and demonstrate the convergence of the schemes which subsequently gives a constructive proof for the existence of a solution to the switching system numerical experiments are presented for a recursive utility maximization problem to demonstrate the effectiveness of the new schemes
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1,803.03795
Classifying torsion classes for algebras with radical square zero via sign decomposition
To study the set of torsion classes of a finite dimensional basic algebra, we use a decomposition, called sign-decomposition, parametrized by elements of $\{\pm1\}^n$ where $n$ is the number of simple modules. If $A$ is an algebra with radical square zero, then for each $\epsilon \in \{\pm1\}^n$ there is a hereditary algebra $A_{\epsilon}^!$ with radical square zero and a bijection between the set of torsion classes of $A$ associated to $\epsilon$ and the set of faithful torsion classes of $A_{\epsilon}^!$. Furthermore, this bijection preserves the property of being functorially finite. As an application in $\tau$-tilting theory, we prove that the number of support $\tau$-tilting modules over Brauer line algebras (resp. Brauer odd-cycle algebras) having $n$ edges is $\binom{2n}{n}$ (resp. $2^{2n-1}$).
math.RT
to study the set of torsion classes of a finite dimensional basic algebra we use a decomposition called signdecomposition parametrized by elements of pm1n where n is the number of simple modules if a is an algebra with radical square zero then for each epsilon in pm1n there is a hereditary algebra a_epsilon with radical square zero and a bijection between the set of torsion classes of a associated to epsilon and the set of faithful torsion classes of a_epsilon furthermore this bijection preserves the property of being functorially finite as an application in tautilting theory we prove that the number of support tautilting modules over brauer line algebras resp brauer oddcycle algebras having n edges is binom2nn resp 22n1
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1,803.03796
Optical control of competing exchange interactions and coherent spin-charge coupling in two-orbital Mott insulators
In order to have a better understanding of ultrafast electrical control of exchange interactions in multi-orbital systems, we study a two-orbital Hubbard model at half filling under the action of a time-periodic electric field. Using suitable projection operators and a generalized time-dependent canonical transformation, we derive an effective Hamiltonian which describes two different regimes. First, for a wide range of non-resonant frequencies, we find a change of the bilinear Heisenberg exchange $J_{\textrm{ex}}$ that is analogous to the single-orbital case. Moreover we demonstrate that also the additional biquadratic exchange interaction $B_{\textrm{ex}}$ can be enhanced, reduced and even change sign depending on the electric field. Second, for special driving frequencies, we demonstrate a novel spin-charge coupling phenomenon enabling coherent transfer between spin and charge degrees of freedom of doubly ionized states. These results are confirmed by an exact time-evolution of the full two-orbital Mott-Hubbard Hamiltonian.
cond-mat.str-el
in order to have a better understanding of ultrafast electrical control of exchange interactions in multiorbital systems we study a twoorbital hubbard model at half filling under the action of a timeperiodic electric field using suitable projection operators and a generalized timedependent canonical transformation we derive an effective hamiltonian which describes two different regimes first for a wide range of nonresonant frequencies we find a change of the bilinear heisenberg exchange j_textrmex that is analogous to the singleorbital case moreover we demonstrate that also the additional biquadratic exchange interaction b_textrmex can be enhanced reduced and even change sign depending on the electric field second for special driving frequencies we demonstrate a novel spincharge coupling phenomenon enabling coherent transfer between spin and charge degrees of freedom of doubly ionized states these results are confirmed by an exact timeevolution of the full twoorbital motthubbard hamiltonian
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1,803.03797
Efficient FPGA Implementation of Conjugate Gradient Methods for Laplacian System using HLS
In this paper, we study FPGA based pipelined and superscalar design of two variants of conjugate gradient methods for solving Laplacian equation on a discrete grid; the first version corresponds to the original conjugate gradient algorithm, and the second version corresponds to a slightly modified version of the same. In conjugate gradient method to solve partial differential equations, matrix vector operations are required in each iteration; these operations can be implemented as 5 point stencil operations on the grid without explicitely constructing the matrix. We show that a pipelined and superscalar design using high level synthesis written in C language leads to a significant reduction in latencies for both methods. When comparing these two, we show that the later has roughly two times lower latency than the former given the same degree of superscalarity. These reductions in latencies for the newer variant of CG is due to parallel implementations of stencil operation on subdomains of the grid, and dut to overlap of these stencil operations with dot product operations. In a superscalar design, domain needs to be partitioned, and boundary data needs to be copied, which requires padding. In 1D partition, the padding latency increases as the number of partitions increase. For a streaming data flow model, we propose a novel traversal of the grid for 2D domain decomposition that leads to 2 times reduction in latency cost involved with padding compared to 1D partitions. Our implementation is roughly 10 times faster than software implementation for linear system of dimension $10000 \times 10000.$
cs.DC
in this paper we study fpga based pipelined and superscalar design of two variants of conjugate gradient methods for solving laplacian equation on a discrete grid the first version corresponds to the original conjugate gradient algorithm and the second version corresponds to a slightly modified version of the same in conjugate gradient method to solve partial differential equations matrix vector operations are required in each iteration these operations can be implemented as 5 point stencil operations on the grid without explicitely constructing the matrix we show that a pipelined and superscalar design using high level synthesis written in c language leads to a significant reduction in latencies for both methods when comparing these two we show that the later has roughly two times lower latency than the former given the same degree of superscalarity these reductions in latencies for the newer variant of cg is due to parallel implementations of stencil operation on subdomains of the grid and dut to overlap of these stencil operations with dot product operations in a superscalar design domain needs to be partitioned and boundary data needs to be copied which requires padding in 1d partition the padding latency increases as the number of partitions increase for a streaming data flow model we propose a novel traversal of the grid for 2d domain decomposition that leads to 2 times reduction in latency cost involved with padding compared to 1d partitions our implementation is roughly 10 times faster than software implementation for linear system of dimension 10000 times 10000
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1,803.03798
Vacuum birefringence and the X-ray polarization from black-hole accretion disks
In the next decade, x-ray polarimetry will open a new window on the high-energy Universe, as several missions that include an x-ray polarimeter are currently under development. Observations of the polarization of x-rays coming from the accretion disks of stellar-mass and supermassive black holes are among the new polarimeters' major objectives. In this paper, we show that these observations can be affected by the quantum electrodynamic (QED) effect of vacuum birefringence: after an x-ray photon is emitted from the accretion disk, its polarization changes as the photon travels through the accretion disk's magnetosphere, as a result of the vacuum becoming birefringent in presence of a magnetic field. We show that this effect can be important for black holes in the energy band of the upcoming polarimeters, and has to be taken into account in a complete model of the x-ray polarization that we expect to detect from black-hole accretion disks, both for stellar mass and for supermassive black holes. We find that, for a chaotic magnetic field in the disk, QED can significantly decrease the linear polarization fraction of edge-on photons, depending on the spin of the hole and on the strength of the magnetic field. This effect can provide, for the first time, a direct way to probe the magnetic field strength close to the innermost stable orbit of black-hole accretion disks and to study the role of magnetic fields in astrophysical accretion in general.
astro-ph.HE
in the next decade xray polarimetry will open a new window on the highenergy universe as several missions that include an xray polarimeter are currently under development observations of the polarization of xrays coming from the accretion disks of stellarmass and supermassive black holes are among the new polarimeters major objectives in this paper we show that these observations can be affected by the quantum electrodynamic qed effect of vacuum birefringence after an xray photon is emitted from the accretion disk its polarization changes as the photon travels through the accretion disks magnetosphere as a result of the vacuum becoming birefringent in presence of a magnetic field we show that this effect can be important for black holes in the energy band of the upcoming polarimeters and has to be taken into account in a complete model of the xray polarization that we expect to detect from blackhole accretion disks both for stellar mass and for supermassive black holes we find that for a chaotic magnetic field in the disk qed can significantly decrease the linear polarization fraction of edgeon photons depending on the spin of the hole and on the strength of the magnetic field this effect can provide for the first time a direct way to probe the magnetic field strength close to the innermost stable orbit of blackhole accretion disks and to study the role of magnetic fields in astrophysical accretion in general
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1,803.03799
Atomic-scale structure and chemistry of YIG/GGG Interface
Y3Fe5O12 (YIG) is a promising candidate for spin wave devices. In the thin film devices, the interface between YIG and substrate may play important roles in determining the device properties. Here, we use spherical aberration-corrected scanning electron microscopy and spectroscopy to study the atomic arrangement, chemistry and electronic structure of the YIG/Gd3Ga5O12 (GGG) interface. We find that the chemical bonding of the interface is FeO-GdGaO and the interface remains sharp in both atomic and electronic structures. These results provide necessary information for understanding the properties of interface and also for atomistic calculation.
cond-mat.mtrl-sci
y3fe5o12 yig is a promising candidate for spin wave devices in the thin film devices the interface between yig and substrate may play important roles in determining the device properties here we use spherical aberrationcorrected scanning electron microscopy and spectroscopy to study the atomic arrangement chemistry and electronic structure of the yiggd3ga5o12 ggg interface we find that the chemical bonding of the interface is feogdgao and the interface remains sharp in both atomic and electronic structures these results provide necessary information for understanding the properties of interface and also for atomistic calculation
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1,803.038
ARMDN: Associative and Recurrent Mixture Density Networks for eRetail Demand Forecasting
Accurate demand forecasts can help on-line retail organizations better plan their supply-chain processes. The challenge, however, is the large number of associative factors that result in large, non-stationary shifts in demand, which traditional time series and regression approaches fail to model. In this paper, we propose a Neural Network architecture called AR-MDN, that simultaneously models associative factors, time-series trends and the variance in the demand. We first identify several causal features and use a combination of feature embeddings, MLP and LSTM to represent them. We then model the output density as a learned mixture of Gaussian distributions. The AR-MDN can be trained end-to-end without the need for additional supervision. We experiment on a dataset of an year's worth of data over tens-of-thousands of products from Flipkart. The proposed architecture yields a significant improvement in forecasting accuracy when compared with existing alternatives.
cs.LG cs.AI stat.ML
accurate demand forecasts can help online retail organizations better plan their supplychain processes the challenge however is the large number of associative factors that result in large nonstationary shifts in demand which traditional time series and regression approaches fail to model in this paper we propose a neural network architecture called armdn that simultaneously models associative factors timeseries trends and the variance in the demand we first identify several causal features and use a combination of feature embeddings mlp and lstm to represent them we then model the output density as a learned mixture of gaussian distributions the armdn can be trained endtoend without the need for additional supervision we experiment on a dataset of an years worth of data over tensofthousands of products from flipkart the proposed architecture yields a significant improvement in forecasting accuracy when compared with existing alternatives
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1,803.03801
Properties of the coordinate ring of a convex polyomino
We classify all convex polyomino whose coordinate rings are Gorenstein. We also compute the Castelnuovo-Mumford regularity of the coordinate ring of any stack polyomino in terms of the smallest interval which contains its vertices. We give a recursive formula for computing the multiplicity of a stack polyomino.
math.AC
we classify all convex polyomino whose coordinate rings are gorenstein we also compute the castelnuovomumford regularity of the coordinate ring of any stack polyomino in terms of the smallest interval which contains its vertices we give a recursive formula for computing the multiplicity of a stack polyomino
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1,803.03802
Measurement of the Integrated Luminosities of Cross-section Scan Data Samples Around the $\psi(3770)$ Mass Region
To investigate the nature of the $\psi(3770)$ resonance and to measure the cross section for $e^+e^- \to D\bar{D}$, a cross-section scan data sample, distributed among 41 center-of-mass energy points from 3.73 to 3.89~GeV, was taken with the BESIII detector operated at the BEPCII collider in the year 2010. By analyzing the large angle Bhabha scattering events, we measure the integrated luminosity of the data sample at each center-of-mass energy point. The total integrated luminosity of the data sample is $76.16\pm0.04\pm0.61$~pb$^{-1}$, where the first uncertainty is statistical and the second systematic.
hep-ex
to investigate the nature of the psi3770 resonance and to measure the cross section for ee to dbard a crosssection scan data sample distributed among 41 centerofmass energy points from 373 to 389gev was taken with the besiii detector operated at the bepcii collider in the year 2010 by analyzing the large angle bhabha scattering events we measure the integrated luminosity of the data sample at each centerofmass energy point the total integrated luminosity of the data sample is 7616pm004pm061pb1 where the first uncertainty is statistical and the second systematic
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1,803.03803
Estimating fast mean-reverting jumps in electricity market models
Based on empirical evidence of fast mean-reverting spikes, we model electricity price processes $X+Z^\beta$ as the sum of a continuous It\^o semimartingale $X$ and a a mean-reverting compound Poisson process $Z_t^\beta = \int_0^t \int_{\mathbb{R}} xe^{-\beta(t-s)}\underline{p}(ds,dt)$ where $\underline{p}(ds,dt)$ is Poisson random measure with intensity $\lambda ds\otimes dt$. In a first part, we investigate the estimation of $(\lambda,\beta)$ from discrete observations and establish asymptotic efficiency in various asymptotic settings. In a second part, we discuss the use of our inference results for correcting the value of forward contracts on electricity markets in presence of spikes. We implement our method on real data in the French, Greman and Australian market over 2015 and 2016 and show in particular the effect of spike modelling on the valuation of certain strip options. In particular, we show that some out-of-the-money options have a significant value if we incorporate spikes in our modelling, while having a value close to $0$ otherwise.
math.ST stat.TH
based on empirical evidence of fast meanreverting spikes we model electricity price processes xzbeta as the sum of a continuous ito semimartingale x and a a meanreverting compound poisson process z_tbeta int_0t int_mathbbr xebetatsunderlinepdsdt where underlinepdsdt is poisson random measure with intensity lambda dsotimes dt in a first part we investigate the estimation of lambdabeta from discrete observations and establish asymptotic efficiency in various asymptotic settings in a second part we discuss the use of our inference results for correcting the value of forward contracts on electricity markets in presence of spikes we implement our method on real data in the french greman and australian market over 2015 and 2016 and show in particular the effect of spike modelling on the valuation of certain strip options in particular we show that some outofthemoney options have a significant value if we incorporate spikes in our modelling while having a value close to 0 otherwise
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1,803.03804
Analog of Anderson theorem for the polar phase of liquid 3He in nematic aerogel
It is shown that if impurities in superfluid 3He have form of infinitely long non-magnetic strands, which are straight, parallel to each other and reflect quasi-particles specularly, the temperature of transition of liquid 3He from the normal into the polar phase coincides with that for the bulk liquid without impurities. Magnetic scattering lowers transition temperature for the polar phase in analogy with the conventional superconductors. These results are discussed in connection with the recent experimental findings.
cond-mat.dis-nn cond-mat.supr-con
it is shown that if impurities in superfluid 3he have form of infinitely long nonmagnetic strands which are straight parallel to each other and reflect quasiparticles specularly the temperature of transition of liquid 3he from the normal into the polar phase coincides with that for the bulk liquid without impurities magnetic scattering lowers transition temperature for the polar phase in analogy with the conventional superconductors these results are discussed in connection with the recent experimental findings
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1,803.03805
Two comments on balls in vertex transitive graphs
We observe that a ball of radius $1$ in the grandfather graph can not be realized as a ball of radius $1$ in a finite vertex transitive graph. We remark on when a ball in a finite vertex transitive graph appears as a ball in an infinite vertex transitive graph.
math.CO math.GR
we observe that a ball of radius 1 in the grandfather graph can not be realized as a ball of radius 1 in a finite vertex transitive graph we remark on when a ball in a finite vertex transitive graph appears as a ball in an infinite vertex transitive graph
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1,803.03806
Learning Quick Fixes from Code Repositories
Code analyzers such as Error Prone and FindBugs detect code patterns symptomatic of bugs, performance issues, or bad style. These tools express patterns as quick fixes that detect and rewrite unwanted code. However, it is difficult to come up with new quick fixes and decide which ones are useful and frequently appear in real code. We propose to rely on the collective wisdom of programmers and learn quick fixes from revision histories in software repositories. We present REVISAR, a tool for discovering common Java edit patterns in code repositories. Given code repositories and their revision histories, REVISAR (i) identifies code edits from revisions and (ii) clusters edits into sets that can be described using an edit pattern. The designers of code analyzers can then inspect the patterns and add the corresponding quick fixes to their tools. We ran REVISAR on nine popular GitHub projects, and it discovered 89 useful edit patterns that appeared in 3 or more projects. Moreover, 64% of the discovered patterns did not appear in existing tools. We then conducted a survey with 164 programmers from 124 projects and found that programmers significantly preferred eight out of the nine of the discovered patterns. Finally, we submitted 16 pull requests applying our patterns to 9 projects and, at the time of the writing, programmers accepted 6 (60%) of them. The results of this work aid toolsmiths in discovering quick fixes and making informed decisions about which quick fixes to prioritize based on patterns programmers actually apply in practice.
cs.SE
code analyzers such as error prone and findbugs detect code patterns symptomatic of bugs performance issues or bad style these tools express patterns as quick fixes that detect and rewrite unwanted code however it is difficult to come up with new quick fixes and decide which ones are useful and frequently appear in real code we propose to rely on the collective wisdom of programmers and learn quick fixes from revision histories in software repositories we present revisar a tool for discovering common java edit patterns in code repositories given code repositories and their revision histories revisar i identifies code edits from revisions and ii clusters edits into sets that can be described using an edit pattern the designers of code analyzers can then inspect the patterns and add the corresponding quick fixes to their tools we ran revisar on nine popular github projects and it discovered 89 useful edit patterns that appeared in 3 or more projects moreover 64 of the discovered patterns did not appear in existing tools we then conducted a survey with 164 programmers from 124 projects and found that programmers significantly preferred eight out of the nine of the discovered patterns finally we submitted 16 pull requests applying our patterns to 9 projects and at the time of the writing programmers accepted 6 60 of them the results of this work aid toolsmiths in discovering quick fixes and making informed decisions about which quick fixes to prioritize based on patterns programmers actually apply in practice
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1,803.03807
CIoTA: Collaborative IoT Anomaly Detection via Blockchain
Due to their rapid growth and deployment, Internet of things (IoT) devices have become a central aspect of our daily lives. However, they tend to have many vulnerabilities which can be exploited by an attacker. Unsupervised techniques, such as anomaly detection, can help us secure the IoT devices. However, an anomaly detection model must be trained for a long time in order to capture all benign behaviors. This approach is vulnerable to adversarial attacks since all observations are assumed to be benign while training the anomaly detection model. In this paper, we propose CIoTA, a lightweight framework that utilizes the blockchain concept to perform distributed and collaborative anomaly detection for devices with limited resources. CIoTA uses blockchain to incrementally update a trusted anomaly detection model via self-attestation and consensus among IoT devices. We evaluate CIoTA on our own distributed IoT simulation platform, which consists of 48 Raspberry Pis, to demonstrate CIoTA's ability to enhance the security of each device and the security of the network as a whole.
cs.CY cs.CR cs.DC cs.LG
due to their rapid growth and deployment internet of things iot devices have become a central aspect of our daily lives however they tend to have many vulnerabilities which can be exploited by an attacker unsupervised techniques such as anomaly detection can help us secure the iot devices however an anomaly detection model must be trained for a long time in order to capture all benign behaviors this approach is vulnerable to adversarial attacks since all observations are assumed to be benign while training the anomaly detection model in this paper we propose ciota a lightweight framework that utilizes the blockchain concept to perform distributed and collaborative anomaly detection for devices with limited resources ciota uses blockchain to incrementally update a trusted anomaly detection model via selfattestation and consensus among iot devices we evaluate ciota on our own distributed iot simulation platform which consists of 48 raspberry pis to demonstrate ciotas ability to enhance the security of each device and the security of the network as a whole
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1,803.03808
Distinct collective states due to the trade-off between attractive and repulsive couplings
We investigate the effect of repulsive coupling together with an attractive coupling in a network of nonlocally coupled oscillators. To understand the complex interaction between these two couplings we introduce a control parameter in the repulsive coupling which plays a crucial role in inducing distinct complex collective patterns. In particular, we show the emergence of various cluster chimera death states through a dynamically distinct transition route, namely the oscillatory cluster state and coherent oscillation death state as a function of the repulsive coupling in the presence of the attractive coupling. In the oscillatory cluster state, the oscillators in the network are grouped into two distinct dynamical states of homogeneous and inhomogeneous oscillatory states. Further, the network of coupled oscillators follows the same transition route in the entire coupling range. Depending upon distinct coupling ranges the system displays a different number of clusters in the death state and oscillatory state. We also observe that the number of coherent domains in the oscillatory cluster state exponentially decreases with increase in coupling range and obeys a power law decay. Additionally, we show analytical stability for observed solitary state, synchronized state, and incoherent oscillation death state.
nlin.AO
we investigate the effect of repulsive coupling together with an attractive coupling in a network of nonlocally coupled oscillators to understand the complex interaction between these two couplings we introduce a control parameter in the repulsive coupling which plays a crucial role in inducing distinct complex collective patterns in particular we show the emergence of various cluster chimera death states through a dynamically distinct transition route namely the oscillatory cluster state and coherent oscillation death state as a function of the repulsive coupling in the presence of the attractive coupling in the oscillatory cluster state the oscillators in the network are grouped into two distinct dynamical states of homogeneous and inhomogeneous oscillatory states further the network of coupled oscillators follows the same transition route in the entire coupling range depending upon distinct coupling ranges the system displays a different number of clusters in the death state and oscillatory state we also observe that the number of coherent domains in the oscillatory cluster state exponentially decreases with increase in coupling range and obeys a power law decay additionally we show analytical stability for observed solitary state synchronized state and incoherent oscillation death state
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1,803.03809
Effect of population density on epidemics
Investigations of a possible connection between population density and the propagation and magnitude of epidemics have so far led to mixed and unconvincing results. There are three reasons for that. (i) Previous studies did not focus on the appropriate density interval. (ii) For the density to be a meaningful variable the population must be distributed as uniformly as possible. If an area has towns and cities where a majority of the population is concentrated its average density is meaningless. (iii) In the propagation of an epidemic the initial proportion of susceptibles (that is to say persons who have not developed an immunity) is an essential, yet usually unknown, factor. The assumption that most of the population is susceptible holds only for new strain of diseases. It will be shown that when these requirements are taken care of, the size of epidemics is indeed closely connected with the population density. This empirical observation comes as a welcome confirmation of the classical KMK (Kermack-McKendrick 1927) model. Indeed, one of its key predictions is that the size of the epidemic increases strongly (and in a non linear way) with the initial density of susceptibles. An interesting consequence is that, contrary to common beliefs, in sparsely populated territories, like Alaska, Australia or the west coast of the United states the size of epidemics among native populations must have been limited by the low density even for diseases for which the natives had no immunity (i.e., were susceptibles).
physics.soc-ph physics.bio-ph q-bio.PE
investigations of a possible connection between population density and the propagation and magnitude of epidemics have so far led to mixed and unconvincing results there are three reasons for that i previous studies did not focus on the appropriate density interval ii for the density to be a meaningful variable the population must be distributed as uniformly as possible if an area has towns and cities where a majority of the population is concentrated its average density is meaningless iii in the propagation of an epidemic the initial proportion of susceptibles that is to say persons who have not developed an immunity is an essential yet usually unknown factor the assumption that most of the population is susceptible holds only for new strain of diseases it will be shown that when these requirements are taken care of the size of epidemics is indeed closely connected with the population density this empirical observation comes as a welcome confirmation of the classical kmk kermackmckendrick 1927 model indeed one of its key predictions is that the size of the epidemic increases strongly and in a non linear way with the initial density of susceptibles an interesting consequence is that contrary to common beliefs in sparsely populated territories like alaska australia or the west coast of the united states the size of epidemics among native populations must have been limited by the low density even for diseases for which the natives had no immunity ie were susceptibles
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1,803.0381
Minimal sets and orbit space for group actions on local dendrites
We consider a group $G$ acting on a local dendrite $X$ (in particular on a graph). We give a full characterization of minimal sets of $G$ by showing that any minimal set $M$ of $G$ (whenever $X$ is different from a dendrite) is either a finite orbit, or a Cantor set, or a circle. If $X$ is a graph different from a circle, such a minimal $M$ is a finite orbit. These results extend those of the authors for group actions on dendrites. On the other hand, we show that, for any group $G$ acting on a local dendrite $X$ different from a circle, the following properties are equivalent: (1) ($G, X$) is pointwise almost periodic. (2) The orbit closure relation $R = \{(x, y)\in X\times X: y\in \overline{G(x)}\}$ is closed. (3) Every non-endpoint of $X$ is periodic. In addition, if $G$ is countable and $X$ is a local dendrite, then ($G, X$) is pointwise periodic if and only if the orbit space $X/G$ is Hausdorff.
math.DS
we consider a group g acting on a local dendrite x in particular on a graph we give a full characterization of minimal sets of g by showing that any minimal set m of g whenever x is different from a dendrite is either a finite orbit or a cantor set or a circle if x is a graph different from a circle such a minimal m is a finite orbit these results extend those of the authors for group actions on dendrites on the other hand we show that for any group g acting on a local dendrite x different from a circle the following properties are equivalent 1 g x is pointwise almost periodic 2 the orbit closure relation r x yin xtimes x yin overlinegx is closed 3 every nonendpoint of x is periodic in addition if g is countable and x is a local dendrite then g x is pointwise periodic if and only if the orbit space xg is hausdorff
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1,803.03811
Band-offset-induced lateral shift of valley electrons in ferromagnetic MoS$_2$/WS$_2$ planar heterojunctions
Low-energy coherent transport and Goos-H\"{a}nchen (GH) lateral shift of valley electrons in planar heterojunctions composed of normal MoS$_2$ and ferromagnetic WS$_2$ monolayers are theoretically investigated. Two types of heterojunctions in the forms of WS$_2$/MoS$_2$/WS$_2$ (type-A) and MoS$_2$/WS$_2$/MoS$_2$ (type-B) with incident electrons in MoS$_2$ region are considered in which the lateral shift of electrons is induced by band alignments of the two constituent semiconductors. It is shown that the type-A heterojunction can act as an electron waveguide due to electron confinement between the two WS$_2$/MoS$_2$ interfaces which cause the incident electrons with an appropriate incidence angle to propagate along the interfaces. In this case the spin- and valley-dependent GH shifts of totally reflected electrons from the interface lead to separated electrons with distinct spin-valley indexes after traveling a sufficiently long distance. In type-B heterojunction, however, transmission resonances occur for incident electron beams passing through the structure, and large spin- and valley-dependent lateral shift values in propagating states can be achieved. Consequently, the transmitted electrons are spatially well-separated into electrons with distinct spin-valley indexes. Our findings reveal that the planar heterojunctions of transition metal dichalcogenides can be utilized as spin-valley beam filter and/or splitter without external gating.
cond-mat.mes-hall
lowenergy coherent transport and gooshanchen gh lateral shift of valley electrons in planar heterojunctions composed of normal mos_2 and ferromagnetic ws_2 monolayers are theoretically investigated two types of heterojunctions in the forms of ws_2mos_2ws_2 typea and mos_2ws_2mos_2 typeb with incident electrons in mos_2 region are considered in which the lateral shift of electrons is induced by band alignments of the two constituent semiconductors it is shown that the typea heterojunction can act as an electron waveguide due to electron confinement between the two ws_2mos_2 interfaces which cause the incident electrons with an appropriate incidence angle to propagate along the interfaces in this case the spin and valleydependent gh shifts of totally reflected electrons from the interface lead to separated electrons with distinct spinvalley indexes after traveling a sufficiently long distance in typeb heterojunction however transmission resonances occur for incident electron beams passing through the structure and large spin and valleydependent lateral shift values in propagating states can be achieved consequently the transmitted electrons are spatially wellseparated into electrons with distinct spinvalley indexes our findings reveal that the planar heterojunctions of transition metal dichalcogenides can be utilized as spinvalley beam filter andor splitter without external gating
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1,803.03812
Exoplanet Diversity in the Era of Space-based Direct Imaging Missions
This whitepaper discusses the diversity of exoplanets that could be detected by future observations, so that comparative exoplanetology can be performed in the upcoming era of large space-based flagship missions. The primary focus will be on characterizing Earth-like worlds around Sun-like stars. However, we will also be able to characterize companion planets in the system simultaneously. This will not only provide a contextual picture with regards to our Solar system, but also presents a unique opportunity to observe size dependent planetary atmospheres at different orbital distances. We propose a preliminary scheme based on chemical behavior of gases and condensates in a planet's atmosphere that classifies them with respect to planetary radius and incident stellar flux.
astro-ph.EP
this whitepaper discusses the diversity of exoplanets that could be detected by future observations so that comparative exoplanetology can be performed in the upcoming era of large spacebased flagship missions the primary focus will be on characterizing earthlike worlds around sunlike stars however we will also be able to characterize companion planets in the system simultaneously this will not only provide a contextual picture with regards to our solar system but also presents a unique opportunity to observe size dependent planetary atmospheres at different orbital distances we propose a preliminary scheme based on chemical behavior of gases and condensates in a planets atmosphere that classifies them with respect to planetary radius and incident stellar flux
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1,803.03813
Optimal partitions for Robin Laplacian eigenvalues
We prove the existence of an optimal partition for the multiphase shape optimization problem which consists in minimizing the sum of the first Robin Laplacian eigenvalue of $k$ mutually disjoint {\it open} sets which have a $\mathcal H ^ {d-1}$-countably rectifiable boundary and are contained into a given box $D$ in $R^d$
math.AP
we prove the existence of an optimal partition for the multiphase shape optimization problem which consists in minimizing the sum of the first robin laplacian eigenvalue of k mutually disjoint it open sets which have a mathcal h d1countably rectifiable boundary and are contained into a given box d in rd
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1,803.03814
Detecting higher spin fields through statistical anisotropy in the CMB bispectrum
Inflation may provide a suitable collider to probe physics at very high energies. In this paper we investigate the impact on the CMB bispectrum of higher spin fields which are long-lived on super-Hubble scales, e.g. partially massless higher spin fields. We show that distinctive statistical anisotropic signals on the CMB three-point correlator are induced and we investigate their detectability.
astro-ph.CO gr-qc hep-ph hep-th
inflation may provide a suitable collider to probe physics at very high energies in this paper we investigate the impact on the cmb bispectrum of higher spin fields which are longlived on superhubble scales eg partially massless higher spin fields we show that distinctive statistical anisotropic signals on the cmb threepoint correlator are induced and we investigate their detectability
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1,803.03815
Topological Nonlinear Optics with Spin-Orbit coupled Bose-Einstein Condensate in Cavity
We report topological nonlinear optics with spin-orbit coupled Bose-Einstein condensate in a cavity. The cavity is driven by a pump laser and weak probe laser which excite Bose-Einstein condensate to an intermediate storage level, where the standard Raman process engineers spin-orbit coupling. We show that the nonlinear photonic interactions at the transitional pathways of dressed states result in new type of optical transparencies, which get completely inverted with atom induced gain. These nonlinear interactions also implant topological sort of features in probe transmission modes by inducing gapless Dirac-like cones, which become gaped in presence of Raman detuning. The topological features get interestingly enhanced in gain regime where the gapless topological edge-like states emerge among the probe modes, which can cause non-trivial phase transition. We show that spin-orbit coupling and Zeeman field effects also impressively revamp fast and slow probe light. The manipulation of dressed states for quantum nonlinear optics with topological characteristics in our findings could be a crucial step towards topological quantum computation.
physics.optics cond-mat.quant-gas physics.atom-ph quant-ph
we report topological nonlinear optics with spinorbit coupled boseeinstein condensate in a cavity the cavity is driven by a pump laser and weak probe laser which excite boseeinstein condensate to an intermediate storage level where the standard raman process engineers spinorbit coupling we show that the nonlinear photonic interactions at the transitional pathways of dressed states result in new type of optical transparencies which get completely inverted with atom induced gain these nonlinear interactions also implant topological sort of features in probe transmission modes by inducing gapless diraclike cones which become gaped in presence of raman detuning the topological features get interestingly enhanced in gain regime where the gapless topological edgelike states emerge among the probe modes which can cause nontrivial phase transition we show that spinorbit coupling and zeeman field effects also impressively revamp fast and slow probe light the manipulation of dressed states for quantum nonlinear optics with topological characteristics in our findings could be a crucial step towards topological quantum computation
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1,803.03816
ShuffleSeg: Real-time Semantic Segmentation Network
Real-time semantic segmentation is of significant importance for mobile and robotics related applications. We propose a computationally efficient segmentation network which we term as ShuffleSeg. The proposed architecture is based on grouped convolution and channel shuffling in its encoder for improving the performance. An ablation study of different decoding methods is compared including Skip architecture, UNet, and Dilation Frontend. Interesting insights on the speed and accuracy tradeoff is discussed. It is shown that skip architecture in the decoding method provides the best compromise for the goal of real-time performance, while it provides adequate accuracy by utilizing higher resolution feature maps for a more accurate segmentation. ShuffleSeg is evaluated on CityScapes and compared against the state of the art real-time segmentation networks. It achieves 2x GFLOPs reduction, while it provides on par mean intersection over union of 58.3% on CityScapes test set. ShuffleSeg runs at 15.7 frames per second on NVIDIA Jetson TX2, which makes it of great potential for real-time applications.
cs.CV
realtime semantic segmentation is of significant importance for mobile and robotics related applications we propose a computationally efficient segmentation network which we term as shuffleseg the proposed architecture is based on grouped convolution and channel shuffling in its encoder for improving the performance an ablation study of different decoding methods is compared including skip architecture unet and dilation frontend interesting insights on the speed and accuracy tradeoff is discussed it is shown that skip architecture in the decoding method provides the best compromise for the goal of realtime performance while it provides adequate accuracy by utilizing higher resolution feature maps for a more accurate segmentation shuffleseg is evaluated on cityscapes and compared against the state of the art realtime segmentation networks it achieves 2x gflops reduction while it provides on par mean intersection over union of 583 on cityscapes test set shuffleseg runs at 157 frames per second on nvidia jetson tx2 which makes it of great potential for realtime applications
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1,803.03817
Fayet-Iliopoulos terms in supergravity and D-term inflation
We analyse the consequences of a new gauge invariant Fayet-Iliopoulos (FI) term proposed recently to a class of inflation models driven by supersymmetry breaking with the inflaton being the superpartner of the goldstino. We first show that charged matter fields can be consistently added with the new term, as well as the standard FI term in supergravity in a K\"ahler frame where the $U(1)$ is not an R-symmetry. We then show that the slow-roll conditions can be easily satisfied with inflation driven by a D-term depending on the two FI parameters. Inflation starts at initial conditions around the maximum of the potential where the $U(1)$ symmetry is restored and stops when the inflaton rolls down to the minimum describing the present phase of our Universe. The resulting tensor-to-scalar ratio of primordial perturbations can be even at observable values in the presence of higher order terms in the K\"ahler potential.
hep-th astro-ph.CO gr-qc hep-ph
we analyse the consequences of a new gauge invariant fayetiliopoulos fi term proposed recently to a class of inflation models driven by supersymmetry breaking with the inflaton being the superpartner of the goldstino we first show that charged matter fields can be consistently added with the new term as well as the standard fi term in supergravity in a kahler frame where the u1 is not an rsymmetry we then show that the slowroll conditions can be easily satisfied with inflation driven by a dterm depending on the two fi parameters inflation starts at initial conditions around the maximum of the potential where the u1 symmetry is restored and stops when the inflaton rolls down to the minimum describing the present phase of our universe the resulting tensortoscalar ratio of primordial perturbations can be even at observable values in the presence of higher order terms in the kahler potential
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1,803.03818
Nuclear Reactions in the Crusts of Accreting Neutron Stars
X-ray observations of transiently accreting neutron stars during quiescence provide information about the structure of neutron star crusts and the properties of dense matter. Interpretation of the observational data requires an understanding of the nuclear reactions that heat and cool the crust during accretion, and define its nonequilibrium composition. We identify here in detail the typical nuclear reaction sequences down to a depth in the inner crust where the mass density is 2E12 g/cm^3 using a full nuclear reaction network for a range of initial compositions. The reaction sequences differ substantially from previous work. We find a robust reduction of crust impurity at the transition to the inner crust regardless of initial composition, though shell effects can delay the formation of a pure crust somewhat to densities beyond 2E12 g/cm^3. This naturally explains the small inner crust impurity inferred from observations of a broad range of systems. The exception are initial compositions with A >= 102 nuclei, where the inner crust remains impure with an impurity parameter of Qimp~20 due to the N = 82 shell closure. In agreement with previous work we find that nuclear heating is relatively robust and independent of initial composition, while cooling via nuclear Urca cycles in the outer crust depends strongly on initial composition. This work forms a basis for future studies of the sensitivity of crust models to nuclear physics and provides profiles of composition for realistic crust models.
astro-ph.HE astro-ph.SR nucl-th
xray observations of transiently accreting neutron stars during quiescence provide information about the structure of neutron star crusts and the properties of dense matter interpretation of the observational data requires an understanding of the nuclear reactions that heat and cool the crust during accretion and define its nonequilibrium composition we identify here in detail the typical nuclear reaction sequences down to a depth in the inner crust where the mass density is 2e12 gcm3 using a full nuclear reaction network for a range of initial compositions the reaction sequences differ substantially from previous work we find a robust reduction of crust impurity at the transition to the inner crust regardless of initial composition though shell effects can delay the formation of a pure crust somewhat to densities beyond 2e12 gcm3 this naturally explains the small inner crust impurity inferred from observations of a broad range of systems the exception are initial compositions with a 102 nuclei where the inner crust remains impure with an impurity parameter of qimp20 due to the n 82 shell closure in agreement with previous work we find that nuclear heating is relatively robust and independent of initial composition while cooling via nuclear urca cycles in the outer crust depends strongly on initial composition this work forms a basis for future studies of the sensitivity of crust models to nuclear physics and provides profiles of composition for realistic crust models
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1,803.03819
On ruled surfaces with big anti-canonical divisor and numerically trivial divisors on weak log Fano surfaces
We investigate the structure of geometrically ruled surfaces whose anti-canonical class is big. As an application we show that the Picard group of a normal projective surface whose anti-canonical class is nef and big is a free abelian group of finite rank.
math.AG
we investigate the structure of geometrically ruled surfaces whose anticanonical class is big as an application we show that the picard group of a normal projective surface whose anticanonical class is nef and big is a free abelian group of finite rank
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1,803.0382
Continuum Charge Excitations in High-Valence Transition-Metal Oxides Revealed by Resonant Inelastic X-ray Scattering
We present a theoretical investigation of the origin of Raman-like and fluorescencelike (FL) features of resonant inelastic x-ray scattering (RIXS) spectra. Using a combination of local-density approximation + dynamical mean-field theory and a configuration interaction solver for Anderson impurity model, we calculate the $L$-edge RIXS and x-ray absorption spectra of high-valence transition-metal oxides LaCuO$_3$ and NaCuO$_2$. We analyze in detail the behavior of the FL feature and show how it is connected to the details of electronic and crystal structure. On the studied compounds we demonstrate how material details determine whether the electron-hole continuum can be excited in the $L$-edge RIXS process.
cond-mat.str-el
we present a theoretical investigation of the origin of ramanlike and fluorescencelike fl features of resonant inelastic xray scattering rixs spectra using a combination of localdensity approximation dynamical meanfield theory and a configuration interaction solver for anderson impurity model we calculate the ledge rixs and xray absorption spectra of highvalence transitionmetal oxides lacuo_3 and nacuo_2 we analyze in detail the behavior of the fl feature and show how it is connected to the details of electronic and crystal structure on the studied compounds we demonstrate how material details determine whether the electronhole continuum can be excited in the ledge rixs process
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1,803.03821
Theory of differential inclusions and its application in mechanics
The following chapter deals with systems of differential equations with discontinuous right-hand sides. The key question is how to define the solutions of such systems. The most adequate approach is to treat discontinuous systems as systems with multivalued right-hand sides (differential inclusions). In this work three well-known definitions of solution of discontinuous system are considered. We will demonstrate the difference between these definitions and their application to different mechanical problems. Mathematical models of drilling systems with discontinuous friction torque characteristics are considered. Here, opposite to classical Coulomb symmetric friction law, the friction torque characteristic is asymmetrical. Problem of sudden load change is studied. Analytical methods of investigation of systems with such asymmetrical friction based on the use of Lyapunov functions are demonstrated. The Watt governor and Chua system are considered to show different aspects of computer modeling of discontinuous systems.
math.DS nlin.CD
the following chapter deals with systems of differential equations with discontinuous righthand sides the key question is how to define the solutions of such systems the most adequate approach is to treat discontinuous systems as systems with multivalued righthand sides differential inclusions in this work three wellknown definitions of solution of discontinuous system are considered we will demonstrate the difference between these definitions and their application to different mechanical problems mathematical models of drilling systems with discontinuous friction torque characteristics are considered here opposite to classical coulomb symmetric friction law the friction torque characteristic is asymmetrical problem of sudden load change is studied analytical methods of investigation of systems with such asymmetrical friction based on the use of lyapunov functions are demonstrated the watt governor and chua system are considered to show different aspects of computer modeling of discontinuous systems
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1,803.03822
Cut elimination, identity elimination, and interpolation in super-Belnap logics
We develop a Gentzen-style proof theory for super-Belnap logics (extensions of the four-valued Dunn-Belnap logic), expanding on an approach initiated by Pynko. We show that just like substructural logics may be understood proof-theoretically as logics which relax the structural rules of classical logic but keep its logical rules as well as the rules of Identity and Cut, super-Belnap logics may be seen as logics which relax Identity and Cut but keep the logical rules as well as the structural rules of classical logic. A generalization of the cut elimination theorem for classical propositional logic is then proved and used to establish interpolation for various super-Belnap logics. In particular, we obtain an alternative syntactic proof of a refinement of the Craig interpolation theorem for classical propositional logic discovered recently by Milne.
math.LO
we develop a gentzenstyle proof theory for superbelnap logics extensions of the fourvalued dunnbelnap logic expanding on an approach initiated by pynko we show that just like substructural logics may be understood prooftheoretically as logics which relax the structural rules of classical logic but keep its logical rules as well as the rules of identity and cut superbelnap logics may be seen as logics which relax identity and cut but keep the logical rules as well as the structural rules of classical logic a generalization of the cut elimination theorem for classical propositional logic is then proved and used to establish interpolation for various superbelnap logics in particular we obtain an alternative syntactic proof of a refinement of the craig interpolation theorem for classical propositional logic discovered recently by milne
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1,803.03823
Examining the Efficiency of Sun Lightening and Shadow Tools in AutoCAD Program
The AutoCAD is one of the most famous Computer Aided Drawing programs with high and accurate specifications in the engineering design. It is highly qualified and contains many of the tools it needs in many engineering departments. A useful tool is the lighting tool because it gives a simulated rendering of reality to a great degree that benefits the architect as well as urban designers. This tool includes simulating sunlight by date during the year, timing of day, and position of the body on the Earth. We tested the sunlight status tools in this program in the limit of our test region to see how accurate it was and it turned out to have a 45% error difference. The sun shadow in AutoCAD rendering is longer than the real by 145%. There is another error in the direction of shadow also. It is essential to note these errors for any designer need to calculate the shadow length and direction from the AutoCAD program.
physics.pop-ph physics.app-ph
the autocad is one of the most famous computer aided drawing programs with high and accurate specifications in the engineering design it is highly qualified and contains many of the tools it needs in many engineering departments a useful tool is the lighting tool because it gives a simulated rendering of reality to a great degree that benefits the architect as well as urban designers this tool includes simulating sunlight by date during the year timing of day and position of the body on the earth we tested the sunlight status tools in this program in the limit of our test region to see how accurate it was and it turned out to have a 45 error difference the sun shadow in autocad rendering is longer than the real by 145 there is another error in the direction of shadow also it is essential to note these errors for any designer need to calculate the shadow length and direction from the autocad program
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1,803.03824
Extraction of Heavy-Flavor Transport Coefficients in QCD Matter
We report on broadly based systematic investigations of the modeling components for open heavy-flavor diffusion and energy loss in strongly interacting matter in their application to heavy-flavor observables in high-energy heavy-ion collisions, conducted within an EMMI Rapid Reaction Task Force framework. Initial spectra including cold-nuclear-matter effects, a wide variety of space-time evolution models, heavy-flavor transport coefficients, and hadronization mechanisms are scrutinized in an effort to quantify pertinent uncertainties in the calculations of nuclear modification factors and elliptic flow of open heavy-flavor particles in nuclear collisions. We develop procedures for error assessments and criteria for common model components to improve quantitative estimates for the (low-momentum) heavy-flavor diffusion coefficient as a long-wavelength characteristic of QCD matter as a function of temperature, and for energy loss coefficients of high-momentum heavy-flavor particles.
nucl-th hep-ph nucl-ex
we report on broadly based systematic investigations of the modeling components for open heavyflavor diffusion and energy loss in strongly interacting matter in their application to heavyflavor observables in highenergy heavyion collisions conducted within an emmi rapid reaction task force framework initial spectra including coldnuclearmatter effects a wide variety of spacetime evolution models heavyflavor transport coefficients and hadronization mechanisms are scrutinized in an effort to quantify pertinent uncertainties in the calculations of nuclear modification factors and elliptic flow of open heavyflavor particles in nuclear collisions we develop procedures for error assessments and criteria for common model components to improve quantitative estimates for the lowmomentum heavyflavor diffusion coefficient as a longwavelength characteristic of qcd matter as a function of temperature and for energy loss coefficients of highmomentum heavyflavor particles
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1,803.03825
Observation of Chiral character deep in the topological insulating regime in Bi$_{1-x}$Sb$_x$
Bi$_{1-x}$Sb$_x$ is a topological insulator (TI) for $x \approx 0.03 $--$0.20$. Close to the Topological phase transition at $x = 0.03$, a magnetic field induced Weyl semi-metal (WSM) state is stabilized due to the splitting of the Dirac cone into two Weyl cones of opposite chirality. A signature of the Weyl state is the observation of a Chiral anomaly [negative longitudnal magnetoresistance (LMR)] and a violation of the Ohm's law (non-linear $I-V$). We report the unexpected discovery of a Chiral anomaly in the whole range ($x = 0.032, 0.072, 0.16$) of the TI state. This points to a field induced WSM state in an extended $x$ range and not just near the topological transition at $x = 0.03$. Surprisingly, the strongest Weyl phase is found at $x = 0.16$ with a non-saturating negative LMR much larger than observed for $x = 0.03$. The negative LMR vanishes rapidly with increasing angle between $B$ and $I$. Additionally, non-linear $I$--$V$ is found for $x = 0.16$ indicating a violation of Ohm's law. This unexpected observation of a strong Weyl state in the whole TI regime in Bi$_{1-x}$Sb$_x$ points to a gap in our understanding of the detailed electronic structure evolution in this alloy system.
cond-mat.mtrl-sci cond-mat.str-el
bi_1xsb_x is a topological insulator ti for x approx 003 020 close to the topological phase transition at x 003 a magnetic field induced weyl semimetal wsm state is stabilized due to the splitting of the dirac cone into two weyl cones of opposite chirality a signature of the weyl state is the observation of a chiral anomaly negative longitudnal magnetoresistance lmr and a violation of the ohms law nonlinear iv we report the unexpected discovery of a chiral anomaly in the whole range x 0032 0072 016 of the ti state this points to a field induced wsm state in an extended x range and not just near the topological transition at x 003 surprisingly the strongest weyl phase is found at x 016 with a nonsaturating negative lmr much larger than observed for x 003 the negative lmr vanishes rapidly with increasing angle between b and i additionally nonlinear iv is found for x 016 indicating a violation of ohms law this unexpected observation of a strong weyl state in the whole ti regime in bi_1xsb_x points to a gap in our understanding of the detailed electronic structure evolution in this alloy system
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1,803.03826
The shift map on Floer trajectory spaces
In this article we give a uniform proof why the shift map on Floer homology trajectory spaces is scale smooth. This proof works for various Floer homologies, periodic, Lagrangian, Hyperk\"ahler, elliptic or parabolic, and uses Hilbert space valued Sobolev theory.
math.SG math.FA
in this article we give a uniform proof why the shift map on floer homology trajectory spaces is scale smooth this proof works for various floer homologies periodic lagrangian hyperkahler elliptic or parabolic and uses hilbert space valued sobolev theory
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1,803.03827
Face2Text: Collecting an Annotated Image Description Corpus for the Generation of Rich Face Descriptions
The past few years have witnessed renewed interest in NLP tasks at the interface between vision and language. One intensively-studied problem is that of automatically generating text from images. In this paper, we extend this problem to the more specific domain of face description. Unlike scene descriptions, face descriptions are more fine-grained and rely on attributes extracted from the image, rather than objects and relations. Given that no data exists for this task, we present an ongoing crowdsourcing study to collect a corpus of descriptions of face images taken `in the wild'. To gain a better understanding of the variation we find in face description and the possible issues that this may raise, we also conducted an annotation study on a subset of the corpus. Primarily, we found descriptions to refer to a mixture of attributes, not only physical, but also emotional and inferential, which is bound to create further challenges for current image-to-text methods.
cs.CL cs.AI cs.CV
the past few years have witnessed renewed interest in nlp tasks at the interface between vision and language one intensivelystudied problem is that of automatically generating text from images in this paper we extend this problem to the more specific domain of face description unlike scene descriptions face descriptions are more finegrained and rely on attributes extracted from the image rather than objects and relations given that no data exists for this task we present an ongoing crowdsourcing study to collect a corpus of descriptions of face images taken in the wild to gain a better understanding of the variation we find in face description and the possible issues that this may raise we also conducted an annotation study on a subset of the corpus primarily we found descriptions to refer to a mixture of attributes not only physical but also emotional and inferential which is bound to create further challenges for current imagetotext methods
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1,803.03828
Fire detection in a still image using colour information
Colour analysis is a crucial step in image-based fire detection algorithms. Many of the proposed fire detection algorithms in a still image are prone to false alarms caused by objects with a colour similar to fire. To design a colour-based system with a better false alarm rate, a new colour-differentiating conversion matrix, efficient on images of high colour complexity, is proposed. The elements of this conversion matrix are obtained by performing K-medoids clustering and Particle Swarm Optimisation procedures on a fire sample image with a background of high fire-colour similarity. The proposed conversion matrix is then used to construct two new fire colour detection frameworks. The first detection method is a two-stage non-linear image transformation framework, while the second is a direct transformation of an image with the proposed conversion matrix. A performance comparison of the proposed methods with alternate methods in the literature was carried out. Experimental results indicate that the linear image transformation method outperforms other methods regarding false alarm rate while the non-linear two-stage image transformation method has the best performance on the F-score metric and provides a better trade-off between missed detection and false alarm rate.
eess.IV cs.CV
colour analysis is a crucial step in imagebased fire detection algorithms many of the proposed fire detection algorithms in a still image are prone to false alarms caused by objects with a colour similar to fire to design a colourbased system with a better false alarm rate a new colourdifferentiating conversion matrix efficient on images of high colour complexity is proposed the elements of this conversion matrix are obtained by performing kmedoids clustering and particle swarm optimisation procedures on a fire sample image with a background of high firecolour similarity the proposed conversion matrix is then used to construct two new fire colour detection frameworks the first detection method is a twostage nonlinear image transformation framework while the second is a direct transformation of an image with the proposed conversion matrix a performance comparison of the proposed methods with alternate methods in the literature was carried out experimental results indicate that the linear image transformation method outperforms other methods regarding false alarm rate while the nonlinear twostage image transformation method has the best performance on the fscore metric and provides a better tradeoff between missed detection and false alarm rate
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1,803.03829
Optically induced phonon blockade in an optomechanical system with second-order nonlinearity
Quantum control of phonons has being become a focus of attention for developing quantum technologies. Here, we propose a proposal to realize phonon blockade in a quadratically coupled optomechanical system, where a strong nonlinear interaction between photons and phonons can be induced by an external field coherently driving the cavity, and the effective coupling strength is tunable by adjusting the amplitude of the driving field. This optically induced nonlinearity is different from standard methods for realization of phonon blockade, where the nonlinearity is achieved by coupling the mechanical system to superconducting qubits. We both analytically and numerically study the phonon statistical properties via the steady-state solution of the second-order correlation function, and find phonon blockade can be efficiently realized for a large cooperativity of the system, which is achievable based on the optically enhanced nonlinear coupling and high quality mechanical system.
quant-ph
quantum control of phonons has being become a focus of attention for developing quantum technologies here we propose a proposal to realize phonon blockade in a quadratically coupled optomechanical system where a strong nonlinear interaction between photons and phonons can be induced by an external field coherently driving the cavity and the effective coupling strength is tunable by adjusting the amplitude of the driving field this optically induced nonlinearity is different from standard methods for realization of phonon blockade where the nonlinearity is achieved by coupling the mechanical system to superconducting qubits we both analytically and numerically study the phonon statistical properties via the steadystate solution of the secondorder correlation function and find phonon blockade can be efficiently realized for a large cooperativity of the system which is achievable based on the optically enhanced nonlinear coupling and high quality mechanical system
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1,803.0383
Evaluation of the Einstein's strength of difference schemes for some chemical reaction-diffusion equations
In this paper we present a difference algebraic technique for the evaluation of the Einstein's strength of a system of partial difference equations and apply this technique to the comparative analysis of difference schemes for chemical reaction-diffusion equations. In particular, we analyze finite-difference schemes for the Murray, Fisher, Burgers and some other reaction-diffusion equations, as well as mass balance PDEs of chromatography from the point of view of their strength.
math.AP physics.chem-ph
in this paper we present a difference algebraic technique for the evaluation of the einsteins strength of a system of partial difference equations and apply this technique to the comparative analysis of difference schemes for chemical reactiondiffusion equations in particular we analyze finitedifference schemes for the murray fisher burgers and some other reactiondiffusion equations as well as mass balance pdes of chromatography from the point of view of their strength
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1,803.03831
Graph-based Clustering under Differential Privacy
In this paper, we present the first differentially private clustering method for arbitrary-shaped node clusters in a graph. This algorithm takes as input only an approximate Minimum Spanning Tree (MST) $\mathcal{T}$ released under weight differential privacy constraints from the graph. Then, the underlying nonconvex clustering partition is successfully recovered from cutting optimal cuts on $\mathcal{T}$. As opposed to existing methods, our algorithm is theoretically well-motivated. Experiments support our theoretical findings.
cs.DS cs.LG
in this paper we present the first differentially private clustering method for arbitraryshaped node clusters in a graph this algorithm takes as input only an approximate minimum spanning tree mst mathcalt released under weight differential privacy constraints from the graph then the underlying nonconvex clustering partition is successfully recovered from cutting optimal cuts on mathcalt as opposed to existing methods our algorithm is theoretically wellmotivated experiments support our theoretical findings
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1,803.03832
Viscosity Solution for Optimal Stopping Problems of Feller Processes
We study an optimal stopping problem when the state process is governed by a general Feller process. In particular, we examine viscosity properties of the associated value function with no a priori assumption on the stochastic differential equation satisfied by the state process. Our approach relies on properties of the Feller semigroup. We present conditions on the state process under which the value function is the unique viscosity solution to an Hamilton-Jacobi-Bellman (HJB) equation associated with a particular operator. More specifically, assuming that the state process is a Feller process, we prove uniqueness of the viscosity solution which was conjectured in [26]. We then apply our results to study viscosity property of optimal stopping problems for some particular Feller processes, namely diffusion processes with piecewise coefficients and semi-Markov processes. Finally, we obtain explicit value functions for optimal stopping of straddle options, when the state process is a reflected Brownian motion, Brownian motion with jump at boundary and regime switching Feller diffusion, respectively (see Section 8).
math.OC
we study an optimal stopping problem when the state process is governed by a general feller process in particular we examine viscosity properties of the associated value function with no a priori assumption on the stochastic differential equation satisfied by the state process our approach relies on properties of the feller semigroup we present conditions on the state process under which the value function is the unique viscosity solution to an hamiltonjacobibellman hjb equation associated with a particular operator more specifically assuming that the state process is a feller process we prove uniqueness of the viscosity solution which was conjectured in 26 we then apply our results to study viscosity property of optimal stopping problems for some particular feller processes namely diffusion processes with piecewise coefficients and semimarkov processes finally we obtain explicit value functions for optimal stopping of straddle options when the state process is a reflected brownian motion brownian motion with jump at boundary and regime switching feller diffusion respectively see section 8
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1,803.03833
Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering
We introduce submodular hypergraphs, a family of hypergraphs that have different submodular weights associated with different cuts of hyperedges. Submodular hypergraphs arise in clustering applications in which higher-order structures carry relevant information. For such hypergraphs, we define the notion of p-Laplacians and derive corresponding nodal domain theorems and k-way Cheeger inequalities. We conclude with the description of algorithms for computing the spectra of 1- and 2-Laplacians that constitute the basis of new spectral hypergraph clustering methods.
cs.LG cs.DM cs.DS cs.SI
we introduce submodular hypergraphs a family of hypergraphs that have different submodular weights associated with different cuts of hyperedges submodular hypergraphs arise in clustering applications in which higherorder structures carry relevant information for such hypergraphs we define the notion of plaplacians and derive corresponding nodal domain theorems and kway cheeger inequalities we conclude with the description of algorithms for computing the spectra of 1 and 2laplacians that constitute the basis of new spectral hypergraph clustering methods
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1,803.03834
Learning and analyzing vector encoding of symbolic representations
We present a formal language with expressions denoting general symbol structures and queries which access information in those structures. A sequence-to-sequence network processing this language learns to encode symbol structures and query them. The learned representation (approximately) shares a simple linearity property with theoretical techniques for performing this task.
cs.AI
we present a formal language with expressions denoting general symbol structures and queries which access information in those structures a sequencetosequence network processing this language learns to encode symbol structures and query them the learned representation approximately shares a simple linearity property with theoretical techniques for performing this task
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1,803.03835
Kickstarting Deep Reinforcement Learning
We present a method for using previously-trained 'teacher' agents to kickstart the training of a new 'student' agent. To this end, we leverage ideas from policy distillation and population based training. Our method places no constraints on the architecture of the teacher or student agents, and it regulates itself to allow the students to surpass their teachers in performance. We show that, on a challenging and computationally-intensive multi-task benchmark (DMLab-30), kickstarted training improves the data efficiency of new agents, making it significantly easier to iterate on their design. We also show that the same kickstarting pipeline can allow a single student agent to leverage multiple 'expert' teachers which specialize on individual tasks. In this setting kickstarting yields surprisingly large gains, with the kickstarted agent matching the performance of an agent trained from scratch in almost 10x fewer steps, and surpassing its final performance by 42 percent. Kickstarting is conceptually simple and can easily be incorporated into reinforcement learning experiments.
cs.LG
we present a method for using previouslytrained teacher agents to kickstart the training of a new student agent to this end we leverage ideas from policy distillation and population based training our method places no constraints on the architecture of the teacher or student agents and it regulates itself to allow the students to surpass their teachers in performance we show that on a challenging and computationallyintensive multitask benchmark dmlab30 kickstarted training improves the data efficiency of new agents making it significantly easier to iterate on their design we also show that the same kickstarting pipeline can allow a single student agent to leverage multiple expert teachers which specialize on individual tasks in this setting kickstarting yields surprisingly large gains with the kickstarted agent matching the performance of an agent trained from scratch in almost 10x fewer steps and surpassing its final performance by 42 percent kickstarting is conceptually simple and can easily be incorporated into reinforcement learning experiments
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1,803.03836
Large values of Dirichlet $L$- functions inside the critical strip
In the present paper, we study large values of Dirichlet $L$- functions inside the critical strip. For every $1/2<\sigma<1$, we show that for $q$ sufficiently large, there exists a non-principal character $\chi$ modulo $q$ and a constant $c(\sigma)>0$ such that $\log \vert L(\sigma,\chi)\vert \gg c(\sigma)(\log q)^{1-\sigma}(\log\log q)^{-\sigma}$. This matches the believed prediction for these values which was previously known only for the Riemann zeta function since Montgomery, or conditionally on GRH for quadratic $L$- functions due to Lamzouri. In a recent work involving the author, a new implementation of the resonance method was presented in order to exhibit large values of the Riemann zeta function on the line $\Re(s)=1$. We show how to adapt the argument to our setting.
math.NT
in the present paper we study large values of dirichlet l functions inside the critical strip for every 12sigma1 we show that for q sufficiently large there exists a nonprincipal character chi modulo q and a constant csigma0 such that log vert lsigmachivert gg csigmalog q1sigmaloglog qsigma this matches the believed prediction for these values which was previously known only for the riemann zeta function since montgomery or conditionally on grh for quadratic l functions due to lamzouri in a recent work involving the author a new implementation of the resonance method was presented in order to exhibit large values of the riemann zeta function on the line res1 we show how to adapt the argument to our setting
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1,803.03837
Sample-Relaxed Two-Dimensional Color Principal Component Analysis for Face Recognition and Image Reconstruction
A sample-relaxed two-dimensional color principal component analysis (SR-2DCPCA) approach is presented for face recognition and image reconstruction based on quaternion models. A relaxation vector is automatically generated according to the variances of training color face images with the same label. A sample-relaxed, low-dimensional covariance matrix is constructed based on all the training samples relaxed by a relaxation vector, and its eigenvectors corresponding to the $r$ largest eigenvalues are defined as the optimal projection. The SR-2DCPCA aims to enlarge the global variance rather than to maximize the variance of the projected training samples. The numerical results based on real face data sets validate that SR-2DCPCA has a higher recognition rate than state-of-the-art methods and is efficient in image reconstruction.
cs.CV
a samplerelaxed twodimensional color principal component analysis sr2dcpca approach is presented for face recognition and image reconstruction based on quaternion models a relaxation vector is automatically generated according to the variances of training color face images with the same label a samplerelaxed lowdimensional covariance matrix is constructed based on all the training samples relaxed by a relaxation vector and its eigenvectors corresponding to the r largest eigenvalues are defined as the optimal projection the sr2dcpca aims to enlarge the global variance rather than to maximize the variance of the projected training samples the numerical results based on real face data sets validate that sr2dcpca has a higher recognition rate than stateoftheart methods and is efficient in image reconstruction
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1,803.03838
Search for a heavy resonance decaying into a Z boson and a vector boson in the $\nu\overline{\nu}\mathrm{q}\overline{\mathrm{q}}$ final state
A search is presented for a heavy resonance decaying into either a pair of Z bosons or a Z boson and a W boson (ZZ or WZ), with a Z boson decaying into a pair of neutrinos and the other boson decaying hadronically into two collimated quarks that are reconstructed as a highly energetic large-cone jet. The search is performed using the data collected with the CMS detector at the CERN LHC during 2016 in proton-proton collisions at a center-of-mass energy of 13 TeV, corresponding to a total integrated luminosity of 35.9 fb$^{-1}$. No excess is observed in data with regard to background expectations. Results are interpreted in scenarios of physics beyond the standard model. Limits at 95% confidence level on production cross sections are set at 0.9 fb (63 fb) for spin-1 W$'$ bosons, included in the heavy vector triplet model, with mass 4.0 TeV (1.0 TeV), and at 0.5 fb (40 fb) for spin-2 bulk gravitons with mass 4.0 TeV (1.0 TeV). Lower limits are set on the masses of W$'$ bosons in the context of two versions of the heavy vector triplet model of 3.1 TeV and 3.4 TeV, respectively.
hep-ex
a search is presented for a heavy resonance decaying into either a pair of z bosons or a z boson and a w boson zz or wz with a z boson decaying into a pair of neutrinos and the other boson decaying hadronically into two collimated quarks that are reconstructed as a highly energetic largecone jet the search is performed using the data collected with the cms detector at the cern lhc during 2016 in protonproton collisions at a centerofmass energy of 13 tev corresponding to a total integrated luminosity of 359 fb1 no excess is observed in data with regard to background expectations results are interpreted in scenarios of physics beyond the standard model limits at 95 confidence level on production cross sections are set at 09 fb 63 fb for spin1 w bosons included in the heavy vector triplet model with mass 40 tev 10 tev and at 05 fb 40 fb for spin2 bulk gravitons with mass 40 tev 10 tev lower limits are set on the masses of w bosons in the context of two versions of the heavy vector triplet model of 31 tev and 34 tev respectively
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1,803.03839
Efficient Enumeration of Bipartite Subgraphs in Graphs
Subgraph enumeration problems ask to output all subgraphs of an input graph that belongs to the specified graph class or satisfy the given constraint. These problems have been widely studied in theoretical computer science. As far, many efficient enumeration algorithms for the fundamental substructures such as spanning trees, cycles, and paths, have been developed. This paper addresses the enumeration problem of bipartite subgraphs. Even though bipartite graphs are quite fundamental and have numerous applications in both theory and application, its enumeration algorithms have not been intensively studied, to the best of our knowledge. We propose the first non-trivial algorithms for enumerating all bipartite subgraphs in a given graph. As the main results, we develop two efficient algorithms: the one enumerates all bipartite induced subgraphs of a graph with degeneracy $k$ in $O(k)$ time per solution. The other enumerates all bipartite subgraphs in $O(1)$ time per solution.
cs.DS
subgraph enumeration problems ask to output all subgraphs of an input graph that belongs to the specified graph class or satisfy the given constraint these problems have been widely studied in theoretical computer science as far many efficient enumeration algorithms for the fundamental substructures such as spanning trees cycles and paths have been developed this paper addresses the enumeration problem of bipartite subgraphs even though bipartite graphs are quite fundamental and have numerous applications in both theory and application its enumeration algorithms have not been intensively studied to the best of our knowledge we propose the first nontrivial algorithms for enumerating all bipartite subgraphs in a given graph as the main results we develop two efficient algorithms the one enumerates all bipartite induced subgraphs of a graph with degeneracy k in ok time per solution the other enumerates all bipartite subgraphs in o1 time per solution
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1,803.0384
Efficient lattice constants and energy band gaps for condensed systems from a meta-GGA level screened range separated hybrid functional
A meta generalized gradient level screened range-separated hybrid functional is developed for solid-state electronic structure theory. Assessment of the present range-separated hybrid functional for solid-state lattice constants and band gaps indicate that the present functional can be used for describing those properties efficiently in meta-GGA level. Specifically, the performance of the present functional for band gap of solids indicates that the present meta-GGA level screened hybrids functional is quite productive beyond the GGA level. The most appealing feature of the present formalism is that a method has been suggested which is based upon an accurate semilocal functional.
cond-mat.mtrl-sci
a meta generalized gradient level screened rangeseparated hybrid functional is developed for solidstate electronic structure theory assessment of the present rangeseparated hybrid functional for solidstate lattice constants and band gaps indicate that the present functional can be used for describing those properties efficiently in metagga level specifically the performance of the present functional for band gap of solids indicates that the present metagga level screened hybrids functional is quite productive beyond the gga level the most appealing feature of the present formalism is that a method has been suggested which is based upon an accurate semilocal functional
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1,803.03841
Spectral statistics in spatially extended chaotic quantum many-body systems
We study spectral statistics in spatially extended chaotic quantum many-body systems, using simple lattice Floquet models without time-reversal symmetry. Computing the spectral form factor $K(t)$ analytically and numerically, we show that it follows random matrix theory (RMT) at times longer than a many-body Thouless time, $t_{\rm Th}$. We obtain a striking dependence of $t_{\rm Th}$ on the spatial dimension $d$ and size of the system. For $d>1$, $t_{\rm Th}$ is finite in the thermodynamic limit and set by the inter-site coupling strength. By contrast, in one dimension $t_{\rm Th}$ diverges with system size, and for large systems there is a wide window in which spectral correlations are not of RMT form.
cond-mat.stat-mech cond-mat.str-el hep-th quant-ph
we study spectral statistics in spatially extended chaotic quantum manybody systems using simple lattice floquet models without timereversal symmetry computing the spectral form factor kt analytically and numerically we show that it follows random matrix theory rmt at times longer than a manybody thouless time t_rm th we obtain a striking dependence of t_rm th on the spatial dimension d and size of the system for d1 t_rm th is finite in the thermodynamic limit and set by the intersite coupling strength by contrast in one dimension t_rm th diverges with system size and for large systems there is a wide window in which spectral correlations are not of rmt form
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1,803.03842
Turbulence in the TW Hya Disk
Turbulence is a fundamental parameter in models of grain growth during the early stages of planet formation. As such, observational constraints on its magnitude are crucial. Here we self-consistently analyze ALMA CO(2-1), SMA CO(3-2), and SMA CO(6-5) observations of the disk around TW Hya and find an upper limit on the turbulent broadening of $<$0.08c$_s$ ($\alpha<$0.007 for $\alpha$ defined only within 2-3 pressure scale heights above the midplane), lower than the tentative detection previously found from an analysis of the CO(2-1) data. We examine in detail the challenges of image plane fitting vs directly fitting the visibilities, while also considering the role of the vertical temperature gradient, systematic uncertainty in the amplitude calibration, and assumptions about the CO abundance, as potential sources of the discrepancy in the turbulence measurements. These tests result in variations of the turbulence limit between $<$0.04c$_s$ and $<$0.13c$_s$, consistently lower than the 0.2-0.4c$_s$ found previously. Having ruled out numerous factors, we restrict the source of the discrepancy to our assumed coupling between temperature and density through hydrostatic equilibrium in the presence of a vertical temperature gradient and/or the confinement of CO to a thin molecular layer above the midplane, although further work is needed to quantify the influence of these prescriptions. Assumptions about hydrostatic equilibrium and the CO distribution are physically motivated, and may have a small influence on measuring the kinematics of the gas, but they become important when constraining small effects such as the strength of the turbulence within a protoplanetary disk.
astro-ph.EP
turbulence is a fundamental parameter in models of grain growth during the early stages of planet formation as such observational constraints on its magnitude are crucial here we selfconsistently analyze alma co21 sma co32 and sma co65 observations of the disk around tw hya and find an upper limit on the turbulent broadening of 008c_s alpha0007 for alpha defined only within 23 pressure scale heights above the midplane lower than the tentative detection previously found from an analysis of the co21 data we examine in detail the challenges of image plane fitting vs directly fitting the visibilities while also considering the role of the vertical temperature gradient systematic uncertainty in the amplitude calibration and assumptions about the co abundance as potential sources of the discrepancy in the turbulence measurements these tests result in variations of the turbulence limit between 004c_s and 013c_s consistently lower than the 0204c_s found previously having ruled out numerous factors we restrict the source of the discrepancy to our assumed coupling between temperature and density through hydrostatic equilibrium in the presence of a vertical temperature gradient andor the confinement of co to a thin molecular layer above the midplane although further work is needed to quantify the influence of these prescriptions assumptions about hydrostatic equilibrium and the co distribution are physically motivated and may have a small influence on measuring the kinematics of the gas but they become important when constraining small effects such as the strength of the turbulence within a protoplanetary disk
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1,803.03843
The intersection of three spheres in a sphere and a new application of the Sato-Levine invariant
Take transverse immersions f from a disjoint unin of the three 4-spheres $S^4_1$, $S^4_2$, and $S^4_3$ into $S^6$ with the following properties: (1) The restriction of $f$ to $S^4_i$ is an embedding, (2) The intersection of $f(S^4_i)$ and $f(S^4_j)$ is not empty and connected, (3)The intersection among $f(S^4_1)$, $f(S^4_2)$, and $f(S^4_3)$ is not empty. Then we obtain three surface-links $L_i=(S^4_i\cap S^4_j, S^4_i\cap S^4_k)$ in $S^4_i$, where $(i,j,k)=(1,2,3), (2,3,1), (3,1,2).$ We prove that, we have the equality $\beta(L_1)+\beta(L_2)+\beta(L_3)=0$, where $\beta(L_i)$ is the Sato-Levine invariant of $L_i$, if all $L_i$ are semi-boundary links.
math.GT
take transverse immersions f from a disjoint unin of the three 4spheres s4_1 s4_2 and s4_3 into s6 with the following properties 1 the restriction of f to s4_i is an embedding 2 the intersection of fs4_i and fs4_j is not empty and connected 3the intersection among fs4_1 fs4_2 and fs4_3 is not empty then we obtain three surfacelinks l_is4_icap s4_j s4_icap s4_k in s4_i where ijk123 231 312 we prove that we have the equality betal_1betal_2betal_30 where betal_i is the satolevine invariant of l_i if all l_i are semiboundary links
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1,803.03844
Exploring the hadron resonance gas phase on the QCD phase diagram
Lattice computations of strongly interacting matter at finite temperature $T$ and baryon chemical potential $\mu_B$ suggest that the QCD thermodynamics deep in the hadronic phase can be adequately modeled by an ideal hadron resonance gas (I-HRG). However, it is not clear where on the $(\mu_B, T)$ plane this description breaks down, making it essential to account for hadronic interactions and change in the nature of the degrees of freedom. We have studied several thermodynamic functions within the I-HRG model and try to identify the region of the QCD phase diagram where it becomes essential to include non-ideal effects into the I-HRG model. We work with only those thermodynamic quantities that show a monotonic rise with $T$ and $\mu_B$ in I-HRG. Their high temperature limiting values where QCD becomes simply a Stefan-Boltzmann (SB) gas of massless quarks and gluons is known. The rise of these quantities in I-HRG beyond the corresponding SB limit values indicate the need to include interactions into I-HRG to study QCD thermodynamics. This works as a guiding principle on the QCD phase diagram where interacting HRG can take over from I-HRG. For $\mu_B/T\leq2$, $\chi^Q_2$ shoots the SB limit at the smallest $T$, while for higher values of $\mu_B/T$,$C_{BS}=-3\chi^{BS}_{11}/\chi^S_2$ takes over. We further comment on the relative positions between the freezeout curve obtained by thermal fits to the measured hadron yields and the obtained line where I-HRG overshoots SB limit.
hep-ph nucl-th
lattice computations of strongly interacting matter at finite temperature t and baryon chemical potential mu_b suggest that the qcd thermodynamics deep in the hadronic phase can be adequately modeled by an ideal hadron resonance gas ihrg however it is not clear where on the mu_b t plane this description breaks down making it essential to account for hadronic interactions and change in the nature of the degrees of freedom we have studied several thermodynamic functions within the ihrg model and try to identify the region of the qcd phase diagram where it becomes essential to include nonideal effects into the ihrg model we work with only those thermodynamic quantities that show a monotonic rise with t and mu_b in ihrg their high temperature limiting values where qcd becomes simply a stefanboltzmann sb gas of massless quarks and gluons is known the rise of these quantities in ihrg beyond the corresponding sb limit values indicate the need to include interactions into ihrg to study qcd thermodynamics this works as a guiding principle on the qcd phase diagram where interacting hrg can take over from ihrg for mu_btleq2 chiq_2 shoots the sb limit at the smallest t while for higher values of mu_btc_bs3chibs_11chis_2 takes over we further comment on the relative positions between the freezeout curve obtained by thermal fits to the measured hadron yields and the obtained line where ihrg overshoots sb limit
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1,803.03845
5G NR Jamming, Spoofing, and Sniffing: Threat Assessment and Mitigation
In December 2017, the Third Generation Partnership Project (3GPP) released the first set of specifications for 5G New Radio (NR), which is currently the most widely accepted 5G cellular standard. 5G NR is expected to replace LTE and previous generations of cellular technology over the next several years, providing higher throughput, lower latency, and a host of new features. Similar to LTE, the 5G NR physical layer consists of several physical channels and signals, most of which are vital to the operation of the network. Unfortunately, like for any wireless technology, disruption through radio jamming is possible. This paper investigates the extent to which 5G NR is vulnerable to jamming and spoofing, by analyzing the physical downlink and uplink control channels and signals. We identify the weakest links in the 5G NR frame, and propose mitigation strategies that should be taken into account during implementation of 5G NR chipsets and base stations.
cs.NI
in december 2017 the third generation partnership project 3gpp released the first set of specifications for 5g new radio nr which is currently the most widely accepted 5g cellular standard 5g nr is expected to replace lte and previous generations of cellular technology over the next several years providing higher throughput lower latency and a host of new features similar to lte the 5g nr physical layer consists of several physical channels and signals most of which are vital to the operation of the network unfortunately like for any wireless technology disruption through radio jamming is possible this paper investigates the extent to which 5g nr is vulnerable to jamming and spoofing by analyzing the physical downlink and uplink control channels and signals we identify the weakest links in the 5g nr frame and propose mitigation strategies that should be taken into account during implementation of 5g nr chipsets and base stations
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1,803.03846
Gradient estimates for SDEs without monotonicity type conditions
We prove gradient estimates for transition Markov semigroups $(P_t)$ associated to SDEs driven by multiplicative Brownian noise having possibly unbounded $C^1$-coefficients, without requiring any monotonicity type condition. In particular, first derivatives of coefficients can grow polynomially and even exponentially. We establish pointwise estimates with weights for $D_x P_t\varphi$ of the form \[ {\sqrt{t}} \, |D_x P_t \varphi (x) | \le c \, (1+ |x|^k) \, \| \varphi\|_{\infty} \] $t \in (0,1]$, $\varphi \in C_b ({\mathbb R}^d)$, $x \in {\mathbb R}^d.$ To prove the result we use two main tools. First, we consider a Feynman--Kac semigroup with potential $V$ related to the growth of the coefficients and of their derivatives for which we can use a Bismut-Elworthy-Li type formula. Second, we introduce a new regular approximation for the coefficients of the SDE. At the end of the paper we provide an example of SDE with additive noise and drift $b$ having sublinear growth together with its derivative such that uniform estimates for $D_x P_t \varphi$ without weights do not hold.
math.PR math.AP
we prove gradient estimates for transition markov semigroups p_t associated to sdes driven by multiplicative brownian noise having possibly unbounded c1coefficients without requiring any monotonicity type condition in particular first derivatives of coefficients can grow polynomially and even exponentially we establish pointwise estimates with weights for d_x p_tvarphi of the form sqrtt d_x p_t varphi x le c 1 xk varphi_infty t in 01 varphi in c_b mathbb rd x in mathbb rd to prove the result we use two main tools first we consider a feynmankac semigroup with potential v related to the growth of the coefficients and of their derivatives for which we can use a bismutelworthyli type formula second we introduce a new regular approximation for the coefficients of the sde at the end of the paper we provide an example of sde with additive noise and drift b having sublinear growth together with its derivative such that uniform estimates for d_x p_t varphi without weights do not hold
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1,803.03847
Structure and Stability of Charged Colloid-Nanoparticle Mixtures
Physical properties of colloidal materials can be modified by addition of nanoparticles. Within a model of like-charged mixtures of particles governed by effective electrostatic interactions, we explore the influence of charged nanoparticles on the structure and thermodynamic phase stability of charge-stabilized colloidal suspensions. Focusing on salt-free mixtures of particles of high size and charge asymmetry, interacting via repulsive Yukawa effective pair potentials, we perform molecular dynamics simulations and compute radial distribution functions and static structure factors. Analysis of these structural properties indicates that increasing the charge and concentration of nanoparticles progressively weakens correlations between charged colloids. We show that addition of charged nanoparticles to a suspension of like-charged colloids can induce a colloidal crystal to melt and can facilitate aggregation of a fluid suspension due to attractive van der Waals interactions. We attribute the destabilizing influence of charged nanoparticles to enhanced screening of electrostatic interactions, which weakens repulsion between charged colloids. This interpretation is consistent with recent predictions of an effective interaction theory of charged colloid-nanoparticle mixtures.
cond-mat.soft
physical properties of colloidal materials can be modified by addition of nanoparticles within a model of likecharged mixtures of particles governed by effective electrostatic interactions we explore the influence of charged nanoparticles on the structure and thermodynamic phase stability of chargestabilized colloidal suspensions focusing on saltfree mixtures of particles of high size and charge asymmetry interacting via repulsive yukawa effective pair potentials we perform molecular dynamics simulations and compute radial distribution functions and static structure factors analysis of these structural properties indicates that increasing the charge and concentration of nanoparticles progressively weakens correlations between charged colloids we show that addition of charged nanoparticles to a suspension of likecharged colloids can induce a colloidal crystal to melt and can facilitate aggregation of a fluid suspension due to attractive van der waals interactions we attribute the destabilizing influence of charged nanoparticles to enhanced screening of electrostatic interactions which weakens repulsion between charged colloids this interpretation is consistent with recent predictions of an effective interaction theory of charged colloidnanoparticle mixtures
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1,803.03848
WDEC - A code for modeling white dwarf structure and pulsations
The White Dwarf Evolution Code (WDEC), written in Fortran, makes models of white dwarf stars. It is fast, versatile, and includes the latest physics. The code evolves hot (~ 100,000 K) input models down to a chosen effective temperature by relaxing the models to be solutions of the equations of stellar structure. The code can also be used to obtain g-mode oscillation modes for the models. WDEC has a long history going back to the late 1960's. Over the years, it has been updated and re-packaged for modern computer architectures, and has specifically been used in computationally intensive asteroseismic fitting. Generations of white dwarf astronomers and dozens of publications have made use of the WDEC, although the last true instrument paper is the original one, published in 1975. This paper discusses the history of the code, necessary to understand why it works the way it does, details the physics and features in the code today, and points the reader to where to find the code and a user guide.
astro-ph.IM astro-ph.SR
the white dwarf evolution code wdec written in fortran makes models of white dwarf stars it is fast versatile and includes the latest physics the code evolves hot 100000 k input models down to a chosen effective temperature by relaxing the models to be solutions of the equations of stellar structure the code can also be used to obtain gmode oscillation modes for the models wdec has a long history going back to the late 1960s over the years it has been updated and repackaged for modern computer architectures and has specifically been used in computationally intensive asteroseismic fitting generations of white dwarf astronomers and dozens of publications have made use of the wdec although the last true instrument paper is the original one published in 1975 this paper discusses the history of the code necessary to understand why it works the way it does details the physics and features in the code today and points the reader to where to find the code and a user guide
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1,803.03849
Learning to Localize Sound Source in Visual Scenes
Visual events are usually accompanied by sounds in our daily lives. We pose the question: Can the machine learn the correspondence between visual scene and the sound, and localize the sound source only by observing sound and visual scene pairs like human? In this paper, we propose a novel unsupervised algorithm to address the problem of localizing the sound source in visual scenes. A two-stream network structure which handles each modality, with attention mechanism is developed for sound source localization. Moreover, although our network is formulated within the unsupervised learning framework, it can be extended to a unified architecture with a simple modification for the supervised and semi-supervised learning settings as well. Meanwhile, a new sound source dataset is developed for performance evaluation. Our empirical evaluation shows that the unsupervised method eventually go through false conclusion in some cases. We show that even with a few supervision, false conclusion is able to be corrected and the source of sound in a visual scene can be localized effectively.
cs.CV cs.AI cs.MM
visual events are usually accompanied by sounds in our daily lives we pose the question can the machine learn the correspondence between visual scene and the sound and localize the sound source only by observing sound and visual scene pairs like human in this paper we propose a novel unsupervised algorithm to address the problem of localizing the sound source in visual scenes a twostream network structure which handles each modality with attention mechanism is developed for sound source localization moreover although our network is formulated within the unsupervised learning framework it can be extended to a unified architecture with a simple modification for the supervised and semisupervised learning settings as well meanwhile a new sound source dataset is developed for performance evaluation our empirical evaluation shows that the unsupervised method eventually go through false conclusion in some cases we show that even with a few supervision false conclusion is able to be corrected and the source of sound in a visual scene can be localized effectively
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1,803.0385
Long-range phase coexistence models: recent progress on the fractional Allen-Cahn equation
In this set of notes, we present some recent developments on the fractional Allen-Cahn equation $$ (-\Delta)^s u = u-u^3,$$ with special attention to $\Gamma$-convergence results, energy and density estimates, convergence of level sets, Hamiltonian estimates, rigidity and symmetry results.
math.AP
in this set of notes we present some recent developments on the fractional allencahn equation deltas u uu3 with special attention to gammaconvergence results energy and density estimates convergence of level sets hamiltonian estimates rigidity and symmetry results
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1,803.03851
Revisiting Decomposable Submodular Function Minimization with Incidence Relations
We introduce a new approach to decomposable submodular function minimization (DSFM) that exploits incidence relations. Incidence relations describe which variables effectively influence the component functions, and when properly utilized, they allow for improving the convergence rates of DSFM solvers. Our main results include the precise parametrization of the DSFM problem based on incidence relations, the development of new scalable alternative projections and parallel coordinate descent methods and an accompanying rigorous analysis of their convergence rates.
cs.LG cs.CV cs.DM
we introduce a new approach to decomposable submodular function minimization dsfm that exploits incidence relations incidence relations describe which variables effectively influence the component functions and when properly utilized they allow for improving the convergence rates of dsfm solvers our main results include the precise parametrization of the dsfm problem based on incidence relations the development of new scalable alternative projections and parallel coordinate descent methods and an accompanying rigorous analysis of their convergence rates
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1,803.03852
A Deep Learning Approach for Pose Estimation from Volumetric OCT Data
Tracking the pose of instruments is a central problem in image-guided surgery. For microscopic scenarios, optical coherence tomography (OCT) is increasingly used as an imaging modality. OCT is suitable for accurate pose estimation due to its micrometer range resolution and volumetric field of view. However, OCT image processing is challenging due to speckle noise and reflection artifacts in addition to the images' 3D nature. We address pose estimation from OCT volume data with a new deep learning-based tracking framework. For this purpose, we design a new 3D convolutional neural network (CNN) architecture to directly predict the 6D pose of a small marker geometry from OCT volumes. We use a hexapod robot to automatically acquire labeled data points which we use to train 3D CNN architectures for multi-output regression. We use this setup to provide an in-depth analysis on deep learning-based pose estimation from volumes. Specifically, we demonstrate that exploiting volume information for pose estimation yields higher accuracy than relying on 2D representations with depth information. Supporting this observation, we provide quantitative and qualitative results that 3D CNNs effectively exploit the depth structure of marker objects. Regarding the deep learning aspect, we present efficient design principles for 3D CNNs, making use of insights from the 2D deep learning community. In particular, we present Inception3D as a new architecture which performs best for our application. We show that our deep learning approach reaches errors at our ground-truth label's resolution. We achieve a mean average error of $\SI{14.89 \pm 9.3}{\micro\metre}$ and $\SI{0.096 \pm 0.072}{\degree}$ for position and orientation learning, respectively.
cs.CV
tracking the pose of instruments is a central problem in imageguided surgery for microscopic scenarios optical coherence tomography oct is increasingly used as an imaging modality oct is suitable for accurate pose estimation due to its micrometer range resolution and volumetric field of view however oct image processing is challenging due to speckle noise and reflection artifacts in addition to the images 3d nature we address pose estimation from oct volume data with a new deep learningbased tracking framework for this purpose we design a new 3d convolutional neural network cnn architecture to directly predict the 6d pose of a small marker geometry from oct volumes we use a hexapod robot to automatically acquire labeled data points which we use to train 3d cnn architectures for multioutput regression we use this setup to provide an indepth analysis on deep learningbased pose estimation from volumes specifically we demonstrate that exploiting volume information for pose estimation yields higher accuracy than relying on 2d representations with depth information supporting this observation we provide quantitative and qualitative results that 3d cnns effectively exploit the depth structure of marker objects regarding the deep learning aspect we present efficient design principles for 3d cnns making use of insights from the 2d deep learning community in particular we present inception3d as a new architecture which performs best for our application we show that our deep learning approach reaches errors at our groundtruth labels resolution we achieve a mean average error of si1489 pm 93micrometre and si0096 pm 0072degree for position and orientation learning respectively
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1,803.03853
Low-altitude ion heating, downflowing ions, and BBELF waves in the return current region
Heavy (O+) ion energization and field-aligned motion in and near the ionosphere are still not well understood. Based on observations from the CASSIOPE Enhanced Polar Outflow Probe (e-POP) at altitudes between 325 km and 730 km over one year, we present a statistical study (24 events) of ion heating and its relation to field-aligned ion bulk flow velocity, low-frequency waves and field-aligned currents (FACs). The ion temperature and field-aligned bulk flow velocity are derived from 2-D ion velocity distribution functions measured by the suprathermal electron imager (SEI) instrument. Consistent ion heating and flow velocity characteristics are observed from both the SEI and the rapid-scanning ion mass spectrometer (IRM) instruments. We find that transverse O+ ion heating in the ionosphere can be intense (up to 4.5 eV), confined to very narrow regions (~ 2 km across B), is more likely to occur in the downward current region, and is associated with broadband extremely low frequency (BBELF) waves. These waves are interpreted as linearly polarized perpendicular to the magnetic field. The amount of ion heating cannot be explained by frictional heating, and the correlation of ion heating with BBELF waves suggest that significant wave-ion heating is occurring and even dominating at altitudes as low as 350 km, a boundary that is lower than previously reported. Surprisingly, the majority of these heating events (17 out 24) are associated with core ion downflows rather than upflows. This may be explained by a downward-pointing electric field in the low-altitude return current region.
physics.space-ph physics.plasm-ph
heavy o ion energization and fieldaligned motion in and near the ionosphere are still not well understood based on observations from the cassiope enhanced polar outflow probe epop at altitudes between 325 km and 730 km over one year we present a statistical study 24 events of ion heating and its relation to fieldaligned ion bulk flow velocity lowfrequency waves and fieldaligned currents facs the ion temperature and fieldaligned bulk flow velocity are derived from 2d ion velocity distribution functions measured by the suprathermal electron imager sei instrument consistent ion heating and flow velocity characteristics are observed from both the sei and the rapidscanning ion mass spectrometer irm instruments we find that transverse o ion heating in the ionosphere can be intense up to 45 ev confined to very narrow regions 2 km across b is more likely to occur in the downward current region and is associated with broadband extremely low frequency bbelf waves these waves are interpreted as linearly polarized perpendicular to the magnetic field the amount of ion heating cannot be explained by frictional heating and the correlation of ion heating with bbelf waves suggest that significant waveion heating is occurring and even dominating at altitudes as low as 350 km a boundary that is lower than previously reported surprisingly the majority of these heating events 17 out 24 are associated with core ion downflows rather than upflows this may be explained by a downwardpointing electric field in the lowaltitude return current region
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1,803.03854
Multiparametric shell eigenvalue problems
The eigenproblem for thin shells of revolution under uncertainty in material parameters is discussed. Here the focus is on the smallest eigenpairs. Shells of revolution have natural eigenclusters due to symmetries, moreover, the eigenpairs depend on a deterministic parameter, the dimensionless thickness. The stochastic subspace iteration algorithms presented here are capable of resolving the smallest eigenclusters. In the case of random material parameters, it is possible that the eigenmodes cross in the stochastic parameter space. This interesting phenomenon is demonstrated via numerical experiments. Finally, the effect of the chosen material model on the asymptotics in relation to the deterministic parameter is shown to be negligible.
math.NA
the eigenproblem for thin shells of revolution under uncertainty in material parameters is discussed here the focus is on the smallest eigenpairs shells of revolution have natural eigenclusters due to symmetries moreover the eigenpairs depend on a deterministic parameter the dimensionless thickness the stochastic subspace iteration algorithms presented here are capable of resolving the smallest eigenclusters in the case of random material parameters it is possible that the eigenmodes cross in the stochastic parameter space this interesting phenomenon is demonstrated via numerical experiments finally the effect of the chosen material model on the asymptotics in relation to the deterministic parameter is shown to be negligible
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1,803.03855
Determination of the 4-genus of a complete graph (with an appendix)
In this paper, the quadrangular genus (4-genus) of the complete graph $K_p$ is shown to be $\gamma_4 (K_p) = \lceil {p(p-5)}/{8} \rceil +1$ for orientable surfaces. This means that $K_p$ is minimally embeddable in the closed orientable surface of genus $\gamma_4 (K_p)$ under the constraint that each face has length at least 4. In the most general setting, the genus of the complete graph was established by Ringel and Youngs and was mainly concerned with triangulations of surfaces. Nonetheless, since then a great deal of interest has also been generated in quadrangulations of surfaces. Hartsfield and Ringel were the first who considered minimal quadrangulations of surfaces. Sections 1--4 of this paper are essentially a reproduction of the original 1998 version as follows: Chen B., Lawrencenko S., Yang H. Determination of the 4-genus of a complete graph, submitted to Discrete Mathematics and withdrawn by S. Lawrencenko, June 1998, URL: https://t.co/cUg6R9Jwyw . More discussion on this 1998 version is held and some copyright issues around the quadrangular genus of complete graphs are clarified in the Appendix to the current version of the paper; the Appendix was written in 2017.
math.CO
in this paper the quadrangular genus 4genus of the complete graph k_p is shown to be gamma_4 k_p lceil pp58 rceil 1 for orientable surfaces this means that k_p is minimally embeddable in the closed orientable surface of genus gamma_4 k_p under the constraint that each face has length at least 4 in the most general setting the genus of the complete graph was established by ringel and youngs and was mainly concerned with triangulations of surfaces nonetheless since then a great deal of interest has also been generated in quadrangulations of surfaces hartsfield and ringel were the first who considered minimal quadrangulations of surfaces sections 14 of this paper are essentially a reproduction of the original 1998 version as follows chen b lawrencenko s yang h determination of the 4genus of a complete graph submitted to discrete mathematics and withdrawn by s lawrencenko june 1998 url httpstcocug6r9jwyw more discussion on this 1998 version is held and some copyright issues around the quadrangular genus of complete graphs are clarified in the appendix to the current version of the paper the appendix was written in 2017
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1,803.03856
Light-cone velocities after a global quench in a non-interacting model
We study the light-cone velocity for global quenches in the non-interacting XY chain starting from a class of initial states that are eigenstates of the local $z$-component of the spin. We point out how translation invariance of the initial state can affect the maximal speed at which correlations spread. As a consequence the light-cone velocity can be state-dependent also for non-interacting systems: a new effect of which we provide clear numerical evidence and analytic predictions. Analogous considerations, based on numerical results, are drawn for the evolution of the entanglement entropy.
cond-mat.str-el cond-mat.stat-mech
we study the lightcone velocity for global quenches in the noninteracting xy chain starting from a class of initial states that are eigenstates of the local zcomponent of the spin we point out how translation invariance of the initial state can affect the maximal speed at which correlations spread as a consequence the lightcone velocity can be statedependent also for noninteracting systems a new effect of which we provide clear numerical evidence and analytic predictions analogous considerations based on numerical results are drawn for the evolution of the entanglement entropy
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1,803.03857
Learning from Noisy Web Data with Category-level Supervision
As tons of photos are being uploaded to public websites (e.g., Flickr, Bing, and Google) every day, learning from web data has become an increasingly popular research direction because of freely available web resources, which is also referred to as webly supervised learning. Nevertheless, the performance gap between webly supervised learning and traditional supervised learning is still very large, owning to the label noise of web data. To be exact, the labels of images crawled from public websites are very noisy and often inaccurate. Some existing works tend to facilitate learning from web data with the aid of extra information, such as augmenting or purifying web data by virtue of instance-level supervision, which is usually in demand of heavy manual annotation. Instead, we propose to tackle the label noise by leveraging more accessible category-level supervision. In particular, we build our method upon variational autoencoder (VAE), in which the classification network is attached on the hidden layer of VAE in a way that the classification network and VAE can jointly leverage the category-level hybrid semantic information. The effectiveness of our proposed method is clearly demonstrated by extensive experiments on three benchmark datasets.
cs.CV
as tons of photos are being uploaded to public websites eg flickr bing and google every day learning from web data has become an increasingly popular research direction because of freely available web resources which is also referred to as webly supervised learning nevertheless the performance gap between webly supervised learning and traditional supervised learning is still very large owning to the label noise of web data to be exact the labels of images crawled from public websites are very noisy and often inaccurate some existing works tend to facilitate learning from web data with the aid of extra information such as augmenting or purifying web data by virtue of instancelevel supervision which is usually in demand of heavy manual annotation instead we propose to tackle the label noise by leveraging more accessible categorylevel supervision in particular we build our method upon variational autoencoder vae in which the classification network is attached on the hidden layer of vae in a way that the classification network and vae can jointly leverage the categorylevel hybrid semantic information the effectiveness of our proposed method is clearly demonstrated by extensive experiments on three benchmark datasets
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1,803.03858
Testing One Hypothesis Multiple Times: The Multidimensional Case
The identification of new rare signals in data, the detection of a sudden change in a trend, and the selection of competing models, are among the most challenging problems in statistical practice. These challenges can be tackled using a test of hypothesis where a nuisance parameter is present only under the alternative, and a computationally efficient solution can be obtained by the "Testing One Hypothesis Multiple times" (TOHM) method. In the one-dimensional setting, a fine discretization of the space of the non-identifiable parameter is specified, and a global p-value is obtained by approximating the distribution of the supremum of the resulting stochastic process. In this paper, we propose a computationally efficient inferential tool to perform TOHM in the multidimensional setting. Here, the approximations of interest typically involve the expected Euler Characteristics (EC) of the excursion set of the underlying random field. We introduce a simple algorithm to compute the EC in multiple dimensions and for arbitrary large significance levels. This leads to an highly generalizable computational tool to perform inference under non-standard regularity conditions.
stat.ME astro-ph.IM physics.data-an stat.AP stat.CO
the identification of new rare signals in data the detection of a sudden change in a trend and the selection of competing models are among the most challenging problems in statistical practice these challenges can be tackled using a test of hypothesis where a nuisance parameter is present only under the alternative and a computationally efficient solution can be obtained by the testing one hypothesis multiple times tohm method in the onedimensional setting a fine discretization of the space of the nonidentifiable parameter is specified and a global pvalue is obtained by approximating the distribution of the supremum of the resulting stochastic process in this paper we propose a computationally efficient inferential tool to perform tohm in the multidimensional setting here the approximations of interest typically involve the expected euler characteristics ec of the excursion set of the underlying random field we introduce a simple algorithm to compute the ec in multiple dimensions and for arbitrary large significance levels this leads to an highly generalizable computational tool to perform inference under nonstandard regularity conditions
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1,803.03859
Language Identification of Bengali-English Code-Mixed data using Character & Phonetic based LSTM Models
Language identification of social media text still remains a challenging task due to properties like code-mixing and inconsistent phonetic transliterations. In this paper, we present a supervised learning approach for language identification at the word level of low resource Bengali-English code-mixed data taken from social media. We employ two methods of word encoding, namely character based and root phone based to train our deep LSTM models. Utilizing these two models we created two ensemble models using stacking and threshold technique which gave 91.78% and 92.35% accuracies respectively on our testing data.
cs.CL
language identification of social media text still remains a challenging task due to properties like codemixing and inconsistent phonetic transliterations in this paper we present a supervised learning approach for language identification at the word level of low resource bengalienglish codemixed data taken from social media we employ two methods of word encoding namely character based and root phone based to train our deep lstm models utilizing these two models we created two ensemble models using stacking and threshold technique which gave 9178 and 9235 accuracies respectively on our testing data
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1,803.0386
Jet Launching Radius in Low-Power Radio-Loud AGNs in Advection-Dominated Accretion Flows
Using our theory for the production of relativistic outflows, we estimate the jet launching radius and the inferred mass accretion rate for 52 low-power radio-loud AGNs based on the observed jet powers. Our analysis indicates that (1) a significant fraction of the accreted energy is required to convert the accreted mass to relativistic energy particles for the production of the jets near the event horizon, (2) the jets launching radius moves radially toward the horizon as the mass accretion rate or jets power increases, and (3) no jet/outflow formation is possible beyond 44 gravitational radii.
astro-ph.HE
using our theory for the production of relativistic outflows we estimate the jet launching radius and the inferred mass accretion rate for 52 lowpower radioloud agns based on the observed jet powers our analysis indicates that 1 a significant fraction of the accreted energy is required to convert the accreted mass to relativistic energy particles for the production of the jets near the event horizon 2 the jets launching radius moves radially toward the horizon as the mass accretion rate or jets power increases and 3 no jetoutflow formation is possible beyond 44 gravitational radii
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1,803.03861
Reality-check for Econophysics: Likelihood-based fitting of physics-inspired market models to empirical data
The statistical description and modeling of volatility plays a prominent role in econometrics, risk management and finance. GARCH and stochastic volatility models have been extensively studied and are routinely fitted to market data, albeit providing a phenomenological description only. In contrast, the field of econophysics starts from the premise that modern economies consist of a vast number of individual actors with heterogeneous expectations and incentives. In turn explaining observed market statistics as emerging from the collective dynamics of many actors following heterogeneous, yet simple, rather mechanistic rules. While such models generate volatility dynamics qualitatively matching several stylized facts and thus illustrate the possible role of different mechanisms, such as chartist trading, herding behavior etc., rigorous and quantitative statistical fits are still mostly lacking. Here, we show how Stan, a modern probabilistic programming language for Bayesian modeling, can be used to fit several models from econophysics. In contrast to the method of moment matching, which is currently popular, our fits are purely likelihood based with many advantages, including systematic model comparison and principled generation of model predictions conditional on the observed price history. In particular, we investigate models by Vikram & Sinha and Franke & Westerhoff, and provide a quantitative comparison with standard econometric models.
cs.CE q-fin.GN
the statistical description and modeling of volatility plays a prominent role in econometrics risk management and finance garch and stochastic volatility models have been extensively studied and are routinely fitted to market data albeit providing a phenomenological description only in contrast the field of econophysics starts from the premise that modern economies consist of a vast number of individual actors with heterogeneous expectations and incentives in turn explaining observed market statistics as emerging from the collective dynamics of many actors following heterogeneous yet simple rather mechanistic rules while such models generate volatility dynamics qualitatively matching several stylized facts and thus illustrate the possible role of different mechanisms such as chartist trading herding behavior etc rigorous and quantitative statistical fits are still mostly lacking here we show how stan a modern probabilistic programming language for bayesian modeling can be used to fit several models from econophysics in contrast to the method of moment matching which is currently popular our fits are purely likelihood based with many advantages including systematic model comparison and principled generation of model predictions conditional on the observed price history in particular we investigate models by vikram sinha and franke westerhoff and provide a quantitative comparison with standard econometric models
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1,803.03862
The Rudin-Kisler ordering of P-points under $\mathfrak{b} = \mathfrak{c}$
M. E. Rudin proved under CH that for each P-point there exists another P-point strictly RK-greater (M. E. Rudin, Partial orders on the types of $\beta \mathbb{N}$ , Trans. Amer. Math. Soc., 155 (1971), 353-362). Assuming $\mathfrak{p}=\mathfrak{c}$ A. Blass showed the same, and proved that each RK-increasing $\omega$-sequence of P-points is upper bounded by a P-point, and that there is an order embedding of the real line into the class of P-points with respect to the RK-(pre)ordering (A. Blass, Rudin - Keisler ordering on P-points, Trans. Amer. Math. Soc., 179 (1973), 145-166). In the present paper the results cited above are proved under a (weaker) assumption $\mathfrak{b}=\mathfrak{c}$. A. Blass also asked in (A. Blass, Rudin - Keisler ordering on P-points, Trans. Amer. Math. Soc., 179 (1973), 145-166) what ordinals can be embedded in the set of P-points and pointed out, that such an ordinal may not be greater then $\mathfrak{c}^+$. In the present paper the question is answered showing (under $\mathfrak{b} = \mathfrak{c}$) that there is an order embedding of $\mathfrak{c}^+$ into P-points.
math.LO
m e rudin proved under ch that for each ppoint there exists another ppoint strictly rkgreater m e rudin partial orders on the types of beta mathbbn trans amer math soc 155 1971 353362 assuming mathfrakpmathfrakc a blass showed the same and proved that each rkincreasing omegasequence of ppoints is upper bounded by a ppoint and that there is an order embedding of the real line into the class of ppoints with respect to the rkpreordering a blass rudin keisler ordering on ppoints trans amer math soc 179 1973 145166 in the present paper the results cited above are proved under a weaker assumption mathfrakbmathfrakc a blass also asked in a blass rudin keisler ordering on ppoints trans amer math soc 179 1973 145166 what ordinals can be embedded in the set of ppoints and pointed out that such an ordinal may not be greater then mathfrakc in the present paper the question is answered showing under mathfrakb mathfrakc that there is an order embedding of mathfrakc into ppoints
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1,803.03863
Smartphone apps usage patterns as a predictor of perceived stress levels at workplace
Explosion of number of smartphone apps and their diversity has created a fertile ground to study behaviour of smartphone users. Patterns of app usage, specifically types of apps and their duration are influenced by the state of the user and this information can be correlated with the self-reported state of the users. The work in this paper is along the line of understanding patterns of app usage and investigating relationship of these patterns with the perceived stress level within the workplace context. Our results show that using a subject-centric behaviour model we can predict stress levels based on smartphone app usage. The results we have achieved, of average accuracy of 75% and precision of 85.7%, can be used as an indicator of overall stress levels in work environments and in turn inform stress reduction organisational policies, especially when considering interrelation between stress and productivity of workers.
cs.CY
explosion of number of smartphone apps and their diversity has created a fertile ground to study behaviour of smartphone users patterns of app usage specifically types of apps and their duration are influenced by the state of the user and this information can be correlated with the selfreported state of the users the work in this paper is along the line of understanding patterns of app usage and investigating relationship of these patterns with the perceived stress level within the workplace context our results show that using a subjectcentric behaviour model we can predict stress levels based on smartphone app usage the results we have achieved of average accuracy of 75 and precision of 857 can be used as an indicator of overall stress levels in work environments and in turn inform stress reduction organisational policies especially when considering interrelation between stress and productivity of workers
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1,803.03864
Probabilistic Analysis of Block Wiedemann for Leading Invariant Factors
We determine the probability, structure dependent, that the block Wiedemann algorithm correctly computes leading invariant factors. This leads to a tight lower bound for the probability, structure independent. We show, using block size slightly larger than $r$, that the leading $r$ invariant factors are computed correctly with high probability over any field. Moreover, an algorithm is provided to compute the probability bound for a given matrix size and thus to select the block size needed to obtain the desired probability. The worst case probability bound is improved, post hoc, by incorporating the partial information about the invariant factors.
cs.SC
we determine the probability structure dependent that the block wiedemann algorithm correctly computes leading invariant factors this leads to a tight lower bound for the probability structure independent we show using block size slightly larger than r that the leading r invariant factors are computed correctly with high probability over any field moreover an algorithm is provided to compute the probability bound for a given matrix size and thus to select the block size needed to obtain the desired probability the worst case probability bound is improved post hoc by incorporating the partial information about the invariant factors
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1,803.03865
Charge sensitivity enhancement via mechanical oscillation in suspended carbon nanotube devices
Single electron transistors (SETs) fabricated from single-walled carbon nanotubes (SWNTs) can be operated as highly sensitive charge detectors reaching sensitivity levels comparable to metallic radio frequency SETs (rf-SETs). Here we demonstrate how the charge sensitivity of the device can be improved by using the mechanical oscillations of a single-walled carbon nanotube quantum dot. To optimize the charge sensitivity $\delta Q$, we drive the mechanical resonator far into the nonlinear regime and bias it to an operating point where the mechanical third order nonlinearity is cancelled out. This way we enhance $\delta Q$, from 6 $\mu e/\sqrt{\textrm{Hz}}$ for the static case, to 0.97 $\mu e/\sqrt{\textrm{Hz}}$, at a probe frequency of $\sim$ 1.3 kHz.
cond-mat.mes-hall
single electron transistors sets fabricated from singlewalled carbon nanotubes swnts can be operated as highly sensitive charge detectors reaching sensitivity levels comparable to metallic radio frequency sets rfsets here we demonstrate how the charge sensitivity of the device can be improved by using the mechanical oscillations of a singlewalled carbon nanotube quantum dot to optimize the charge sensitivity delta q we drive the mechanical resonator far into the nonlinear regime and bias it to an operating point where the mechanical third order nonlinearity is cancelled out this way we enhance delta q from 6 mu esqrttextrmhz for the static case to 097 mu esqrttextrmhz at a probe frequency of sim 13 khz
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1,803.03866
Time-Staging Enhancement of Hybrid System Falsification
Optimization-based falsification employs stochastic optimization algorithms to search for error input of hybrid systems. In this paper we introduce a simple idea to enhance falsification, namely time staging, that allows the time-causal structure of time-dependent signals to be exploited by the optimizers. Time staging consists of running a falsification solver multiple times, from one interval to another, incrementally constructing an input signal candidate. Our experiments show that time staging can dramatically increase performance in some realistic examples. We also present theoretical results that suggest the kinds of models and specifications for which time staging is likely to be effective.
cs.SY eess.SY
optimizationbased falsification employs stochastic optimization algorithms to search for error input of hybrid systems in this paper we introduce a simple idea to enhance falsification namely time staging that allows the timecausal structure of timedependent signals to be exploited by the optimizers time staging consists of running a falsification solver multiple times from one interval to another incrementally constructing an input signal candidate our experiments show that time staging can dramatically increase performance in some realistic examples we also present theoretical results that suggest the kinds of models and specifications for which time staging is likely to be effective
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