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1,802.1026
High-entropy ceramic thin films; A case study on transition metal diborides
High-entropy materials often outperform their lower-entropy relatives in various aspects, such as thermal stability and fracture toughness. While there are extensive research activities in the field of high-entropy alloys, comparably little is performed for high-entropy ceramics, and especially for high-entropy diborides. Here we show, that not only the hardness of ZrB2 layers can be improved from 43.2 to 45.8 to 47.2 GPa through the formation of solid solution ternary diborides (Zr0.61Ti0.39B2) and high-entropy diborides (Zr0.23Ti0.20Hf0.19V0.14Ta0.24B2), respectively, but especially their thermal stability against structural rearrangements and decomposition towards the constituting binary diborides.
cond-mat.mtrl-sci
highentropy materials often outperform their lowerentropy relatives in various aspects such as thermal stability and fracture toughness while there are extensive research activities in the field of highentropy alloys comparably little is performed for highentropy ceramics and especially for highentropy diborides here we show that not only the hardness of zrb2 layers can be improved from 432 to 458 to 472 gpa through the formation of solid solution ternary diborides zr061ti039b2 and highentropy diborides zr023ti020hf019v014ta024b2 respectively but especially their thermal stability against structural rearrangements and decomposition towards the constituting binary diborides
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1,802.10261
A cut-free proof system for a predicate extension of the logic of provability
In this paper, we introduce a proof system $\mathsf{NQGL}$ for a Kripke complete predicate extension of the logic $\mathbf{GL}$, that is, the logic of provability, which is defned by $\mathbf{K}$ and the L\"{o}b formula $\Box(\Box p\supset p)\supset\Box p$. $\mathsf{NQGL}$ is a modal extension of Gentzen's sequent calculus $\mathsf{LK}$. Although the propositional fragment of $\mathsf{NQGL}$ axiomatizes $\mathbf{GL}$, it does not have the L\"{o}b formula as its axiom. Instead, it has a non-compact rule, that is, a derivation rule with countably many premises. We show that $\mathsf{NQGL}$ enjoys cut admissibility and is complete with respect to the class of Kripke frames such that for each world, the supremum of the length of the paths from the world is finite.
math.LO
in this paper we introduce a proof system mathsfnqgl for a kripke complete predicate extension of the logic mathbfgl that is the logic of provability which is defned by mathbfk and the lob formula boxbox psupset psupsetbox p mathsfnqgl is a modal extension of gentzens sequent calculus mathsflk although the propositional fragment of mathsfnqgl axiomatizes mathbfgl it does not have the lob formula as its axiom instead it has a noncompact rule that is a derivation rule with countably many premises we show that mathsfnqgl enjoys cut admissibility and is complete with respect to the class of kripke frames such that for each world the supremum of the length of the paths from the world is finite
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1,802.10262
Effective versions of two theorems of Rado
Let $M$ be a representable matroid on $n$ elements. We give bounds, in terms of $n$, on the least positive characteristic and smallest field over which $M$ is representable.
math.CO
let m be a representable matroid on n elements we give bounds in terms of n on the least positive characteristic and smallest field over which m is representable
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1,802.10263
Spectra of Eigenstates in Fermionic Tensor Quantum Mechanics
We study the $O(N_1)\times O(N_2)\times O(N_3)$ symmetric quantum mechanics of 3-index Majorana fermions. When the ranks $N_i$ are all equal, this model has a large $N$ limit which is dominated by the melonic Feynman diagrams. We derive an integral formula which computes the number of $SO(N_1)\times SO(N_2)\times SO(N_3)$ invariant states for any set of $N_i$. For equal ranks the number of singlets is non-vanishing only when $N$ is even, and it exhibits rapid growth: it jumps from $36$ in the $O(4)^3$ model to $595354780$ in the $O(6)^3$ model. We derive bounds on the values of energy, which show that they scale at most as $N^3$ in the large $N$ limit, in agreement with expectations. We also show that the splitting between the lowest singlet and non-singlet states is of order $1/N$. For $N_3=1$ the tensor model reduces to $O(N_1)\times O(N_2)$ fermionic matrix quantum mechanics, and we find a simple expression for the Hamiltonian in terms of the quadratic Casimir operators of the symmetry group. A similar expression is derived for the complex matrix model with $SU(N_1)\times SU(N_2)\times U(1)$ symmetry. Finally, we study the $N_3=2$ case of the tensor model, which gives a more intricate complex matrix model whose symmetry is only $O(N_1)\times O(N_2)\times U(1)$. All energies are again integers in appropriate units, and we derive a concise formula for the spectrum. The fermionic matrix models we studied possess standard 't Hooft large $N$ limits where the ground state energies are of order $N^2$, while the energy gaps are of order $1$.
hep-th cond-mat.str-el
we study the on_1times on_2times on_3 symmetric quantum mechanics of 3index majorana fermions when the ranks n_i are all equal this model has a large n limit which is dominated by the melonic feynman diagrams we derive an integral formula which computes the number of son_1times son_2times son_3 invariant states for any set of n_i for equal ranks the number of singlets is nonvanishing only when n is even and it exhibits rapid growth it jumps from 36 in the o43 model to 595354780 in the o63 model we derive bounds on the values of energy which show that they scale at most as n3 in the large n limit in agreement with expectations we also show that the splitting between the lowest singlet and nonsinglet states is of order 1n for n_31 the tensor model reduces to on_1times on_2 fermionic matrix quantum mechanics and we find a simple expression for the hamiltonian in terms of the quadratic casimir operators of the symmetry group a similar expression is derived for the complex matrix model with sun_1times sun_2times u1 symmetry finally we study the n_32 case of the tensor model which gives a more intricate complex matrix model whose symmetry is only on_1times on_2times u1 all energies are again integers in appropriate units and we derive a concise formula for the spectrum the fermionic matrix models we studied possess standard t hooft large n limits where the ground state energies are of order n2 while the energy gaps are of order 1
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1,802.10264
Deep Reinforcement Learning for Vision-Based Robotic Grasping: A Simulated Comparative Evaluation of Off-Policy Methods
In this paper, we explore deep reinforcement learning algorithms for vision-based robotic grasping. Model-free deep reinforcement learning (RL) has been successfully applied to a range of challenging environments, but the proliferation of algorithms makes it difficult to discern which particular approach would be best suited for a rich, diverse task like grasping. To answer this question, we propose a simulated benchmark for robotic grasping that emphasizes off-policy learning and generalization to unseen objects. Off-policy learning enables utilization of grasping data over a wide variety of objects, and diversity is important to enable the method to generalize to new objects that were not seen during training. We evaluate the benchmark tasks against a variety of Q-function estimation methods, a method previously proposed for robotic grasping with deep neural network models, and a novel approach based on a combination of Monte Carlo return estimation and an off-policy correction. Our results indicate that several simple methods provide a surprisingly strong competitor to popular algorithms such as double Q-learning, and our analysis of stability sheds light on the relative tradeoffs between the algorithms.
cs.RO cs.LG stat.ML
in this paper we explore deep reinforcement learning algorithms for visionbased robotic grasping modelfree deep reinforcement learning rl has been successfully applied to a range of challenging environments but the proliferation of algorithms makes it difficult to discern which particular approach would be best suited for a rich diverse task like grasping to answer this question we propose a simulated benchmark for robotic grasping that emphasizes offpolicy learning and generalization to unseen objects offpolicy learning enables utilization of grasping data over a wide variety of objects and diversity is important to enable the method to generalize to new objects that were not seen during training we evaluate the benchmark tasks against a variety of qfunction estimation methods a method previously proposed for robotic grasping with deep neural network models and a novel approach based on a combination of monte carlo return estimation and an offpolicy correction our results indicate that several simple methods provide a surprisingly strong competitor to popular algorithms such as double qlearning and our analysis of stability sheds light on the relative tradeoffs between the algorithms
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1,802.10265
A Study of Environmental Effects on Galaxy Spin Using MaNGA Data
We investigate environmental effects on galaxy spin using the recent public data of MaNGA integral field spectroscopic survey containing ~2800 galaxies. We measure the spin parameter of 1830 galaxies through the analysis of two-dimensional stellar kinematic maps within the effective radii, and obtain their large- (background mass density from 20 nearby galaxies) and small-scale (distance to and morphology of the nearest neighbour galaxy) environmental parameters for 1529 and 1767 galaxies, respectively. We first examine the mass dependence of galaxy spin, and find that the spin parameter of early-type galaxies decreases with stellar mass at log (M$_*/$M$_{\odot}$) $\gtrsim$ 10, consistent with the results from previous studies. We then divide the galaxies into three subsamples using their stellar masses to minimize the mass effects on galaxy spin. The spin parameters of galaxies in each subsample do not change with background mass density, but do change with distance to and morphology of the nearest neighbour. In particular, the spin parameter of late-type galaxies decreases as early-type neighbours approach within the virial radius. These results suggest that the large-scale environments hardly affect the galaxy spin, but the small-scale environments such as hydrodynamic galaxy-galaxy interactions can play a substantial role in determining galaxy spin.
astro-ph.GA
we investigate environmental effects on galaxy spin using the recent public data of manga integral field spectroscopic survey containing 2800 galaxies we measure the spin parameter of 1830 galaxies through the analysis of twodimensional stellar kinematic maps within the effective radii and obtain their large background mass density from 20 nearby galaxies and smallscale distance to and morphology of the nearest neighbour galaxy environmental parameters for 1529 and 1767 galaxies respectively we first examine the mass dependence of galaxy spin and find that the spin parameter of earlytype galaxies decreases with stellar mass at log m_m_odot gtrsim 10 consistent with the results from previous studies we then divide the galaxies into three subsamples using their stellar masses to minimize the mass effects on galaxy spin the spin parameters of galaxies in each subsample do not change with background mass density but do change with distance to and morphology of the nearest neighbour in particular the spin parameter of latetype galaxies decreases as earlytype neighbours approach within the virial radius these results suggest that the largescale environments hardly affect the galaxy spin but the smallscale environments such as hydrodynamic galaxygalaxy interactions can play a substantial role in determining galaxy spin
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1,802.10266
The Conformal Bootstrap at Finite Temperature
We initiate an approach to constraining conformal field theory (CFT) data at finite temperature using methods inspired by the conformal bootstrap for vacuum correlation functions. We focus on thermal one- and two-point functions of local operators on the plane. The KMS condition for thermal two-point functions is cast as a crossing equation. By studying the analyticity properties of thermal two-point functions, we derive a "thermal inversion formula" whose output is the set of thermal one-point functions for all operators appearing in a given OPE. This involves identifying a kinematic regime which is the analog of the Regge regime for four-point functions. We demonstrate the effectiveness of the inversion formula by recovering the spectrum and thermal one-point functions in mean field theory, and computing thermal one-point functions for all higher-spin currents in the critical $O(N)$ model at leading order in $1/N$. Furthermore, we develop a systematic perturbation theory for thermal data in the large spin, low-twist spectrum of any CFT. We explain how the inversion formula and KMS condition may be combined to algorithmically constrain CFTs at finite temperature. Throughout, we draw analogies to the bootstrap for vacuum four-point functions. Finally, we discuss future directions for the thermal conformal bootstrap program, emphasizing applications to various types of CFTs, including those with holographic duals.
hep-th cond-mat.stat-mech cond-mat.str-el
we initiate an approach to constraining conformal field theory cft data at finite temperature using methods inspired by the conformal bootstrap for vacuum correlation functions we focus on thermal one and twopoint functions of local operators on the plane the kms condition for thermal twopoint functions is cast as a crossing equation by studying the analyticity properties of thermal twopoint functions we derive a thermal inversion formula whose output is the set of thermal onepoint functions for all operators appearing in a given ope this involves identifying a kinematic regime which is the analog of the regge regime for fourpoint functions we demonstrate the effectiveness of the inversion formula by recovering the spectrum and thermal onepoint functions in mean field theory and computing thermal onepoint functions for all higherspin currents in the critical on model at leading order in 1n furthermore we develop a systematic perturbation theory for thermal data in the large spin lowtwist spectrum of any cft we explain how the inversion formula and kms condition may be combined to algorithmically constrain cfts at finite temperature throughout we draw analogies to the bootstrap for vacuum fourpoint functions finally we discuss future directions for the thermal conformal bootstrap program emphasizing applications to various types of cfts including those with holographic duals
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1,802.10267
Next Generation New Radio Small Cell Enhancement: Architectural Options, Functionality and Performance Aspects
The 3rd generation partnership project (3GPP) has been engaged in further advancing the evolved universal mobile telecommunications system (UMTS) terrestrial radio access network (E-UTRAN) and UTRAN based radio access network technologies. New radio (NR) is the 3rd generation partnership project (3GPP) endeavor for outlining and standardization of the 5th generation (5G) advanced radio access technology. 3GPP has released the first set of 5G NR standards, i.e., the non-standalone 5G radio specifications. As long-term evolution (LTE) technology is massively deployed and broadly accepted, the transition from LTE to 5G is very critical, and it is of maximal importance that the backward compatibility of 5G with LTE is considered. 3GPP has identified several architecture options for 5G. This article gives an overview of the NR architecture options, their deployment scenarios, and the key migration paths. The LTE-NR dual connectivity (DC) is presented. This DC scenario is unique in the sense that DC is being endowed for two different generations of 3GPP radio access technologies. We, further, present the integration of multipath transmission control protocol (MPTCP) with LTE-NR DC and DC-like aggregation, i.e., 3GPP-non-3GPP interworking to bring in the advantages of MPTCP in terms of link robustness, reliability and dynamic mapping between the traffic flows and the available paths. Finally, we discuss the future research and standardization directions of the next-generation networks.
cs.IT math.IT
the 3rd generation partnership project 3gpp has been engaged in further advancing the evolved universal mobile telecommunications system umts terrestrial radio access network eutran and utran based radio access network technologies new radio nr is the 3rd generation partnership project 3gpp endeavor for outlining and standardization of the 5th generation 5g advanced radio access technology 3gpp has released the first set of 5g nr standards ie the nonstandalone 5g radio specifications as longterm evolution lte technology is massively deployed and broadly accepted the transition from lte to 5g is very critical and it is of maximal importance that the backward compatibility of 5g with lte is considered 3gpp has identified several architecture options for 5g this article gives an overview of the nr architecture options their deployment scenarios and the key migration paths the ltenr dual connectivity dc is presented this dc scenario is unique in the sense that dc is being endowed for two different generations of 3gpp radio access technologies we further present the integration of multipath transmission control protocol mptcp with ltenr dc and dclike aggregation ie 3gppnon3gpp interworking to bring in the advantages of mptcp in terms of link robustness reliability and dynamic mapping between the traffic flows and the available paths finally we discuss the future research and standardization directions of the nextgeneration networks
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1,802.10268
Microscopic theory of a superconducting gap in the quasi-one-dimensional organic conductor (TMTSF)$_2$ClO$_4$: Model derivation and two-particle self-consistent analysis
We present a first-principles band calculation for the quasi-one-dimensional (Q1D) organic superconductor (TMTSF)$_2$ClO$_4$. An effective tight-binding model with the TMTSF molecule to be regarded as the site is derived from a calculation based on maximally localized Wannier orbitals. We apply a two-particle self-consistent (TPSC) analysis by using a four-site Hubbard model, which is composed of the tight-binding model and an on-site (intramolecular) repulsive interaction, which serves as a variable parameter. We assume that the pairing mechanism is mediated by the spin fluctuation, and the sign of the superconducting gap changes between the inner and outer Fermi surfaces, which correspond to a d-wave gap function in a simplified Q1D model. With the parameters we adopt, the critical temperature for superconductivity estimated by the TPSC approach is approximately 1K which is consistent with experiment.
cond-mat.supr-con
we present a firstprinciples band calculation for the quasionedimensional q1d organic superconductor tmtsf_2clo_4 an effective tightbinding model with the tmtsf molecule to be regarded as the site is derived from a calculation based on maximally localized wannier orbitals we apply a twoparticle selfconsistent tpsc analysis by using a foursite hubbard model which is composed of the tightbinding model and an onsite intramolecular repulsive interaction which serves as a variable parameter we assume that the pairing mechanism is mediated by the spin fluctuation and the sign of the superconducting gap changes between the inner and outer fermi surfaces which correspond to a dwave gap function in a simplified q1d model with the parameters we adopt the critical temperature for superconductivity estimated by the tpsc approach is approximately 1k which is consistent with experiment
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1,802.10269
Selective Experience Replay for Lifelong Learning
Deep reinforcement learning has emerged as a powerful tool for a variety of learning tasks, however deep nets typically exhibit forgetting when learning multiple tasks in sequence. To mitigate forgetting, we propose an experience replay process that augments the standard FIFO buffer and selectively stores experiences in a long-term memory. We explore four strategies for selecting which experiences will be stored: favoring surprise, favoring reward, matching the global training distribution, and maximizing coverage of the state space. We show that distribution matching successfully prevents catastrophic forgetting, and is consistently the best approach on all domains tested. While distribution matching has better and more consistent performance, we identify one case in which coverage maximization is beneficial - when tasks that receive less trained are more important. Overall, our results show that selective experience replay, when suitable selection algorithms are employed, can prevent catastrophic forgetting.
cs.AI
deep reinforcement learning has emerged as a powerful tool for a variety of learning tasks however deep nets typically exhibit forgetting when learning multiple tasks in sequence to mitigate forgetting we propose an experience replay process that augments the standard fifo buffer and selectively stores experiences in a longterm memory we explore four strategies for selecting which experiences will be stored favoring surprise favoring reward matching the global training distribution and maximizing coverage of the state space we show that distribution matching successfully prevents catastrophic forgetting and is consistently the best approach on all domains tested while distribution matching has better and more consistent performance we identify one case in which coverage maximization is beneficial when tasks that receive less trained are more important overall our results show that selective experience replay when suitable selection algorithms are employed can prevent catastrophic forgetting
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1,802.1027
Stationary probability vectors of higher-order two-dimensional transition probability tensors
In this paper we investigate stationary probability vectors of higher-order two-dimensional symmetric transition probability tensors. We show that there are two special symmetric transition probability tensors of order $m$ dimension 2, which have and only have two stationary probability vectors; and any other symmetric transition probability tensor of order $m$ dimension 2 has a unique stationary probability vector. As a byproduct, we obtain that any symmetric transition probability tensor of order $m$ dimension 2 has a unique positive stationary probability vector; and that any symmetric irreducible transition probability tensor of order $m$ dimension 2 has a unique stationary probability vector.
math.SP
in this paper we investigate stationary probability vectors of higherorder twodimensional symmetric transition probability tensors we show that there are two special symmetric transition probability tensors of order m dimension 2 which have and only have two stationary probability vectors and any other symmetric transition probability tensor of order m dimension 2 has a unique stationary probability vector as a byproduct we obtain that any symmetric transition probability tensor of order m dimension 2 has a unique positive stationary probability vector and that any symmetric irreducible transition probability tensor of order m dimension 2 has a unique stationary probability vector
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1,802.10271
Multimodal Sensor-Based Semantic 3D Mapping for a Large-Scale Environment
Semantic 3D mapping is one of the most important fields in robotics, and has been used in many applications, such as robot navigation, surveillance, and virtual reality. In general, semantic 3D mapping is mainly composed of 3D reconstruction and semantic segmentation. As these technologies evolve, there has been great progress in semantic 3D mapping in recent years. Furthermore, the number of robotic applications requiring semantic information in 3D mapping to perform high-level tasks has increased, and many studies on semantic 3D mapping have been published. Existing methods use a camera for both 3D reconstruction and semantic segmentation. However, this is not suitable for large-scale environments and has the disadvantage of high computational complexity. To address this problem, we propose a multimodal sensor-based semantic 3D mapping system using a 3D Lidar combined with a camera. In this study, we build a 3D map by estimating odometry based on a global positioning system (GPS) and an inertial measurement unit (IMU), and use the latest 2D convolutional neural network (CNN) for semantic segmentation. To build a semantic 3D map, we integrate the 3D map with semantic information by using coordinate transformation and Bayes' update scheme. In order to improve the semantic 3D map, we propose a 3D refinement process to correct wrongly segmented voxels and remove traces of moving vehicles in the 3D map. Through experiments on challenging sequences, we demonstrate that our method outperforms state-of-the-art methods in terms of accuracy and intersection over union (IoU). Thus, our method can be used for various applications that require semantic information in 3D map.
cs.RO
semantic 3d mapping is one of the most important fields in robotics and has been used in many applications such as robot navigation surveillance and virtual reality in general semantic 3d mapping is mainly composed of 3d reconstruction and semantic segmentation as these technologies evolve there has been great progress in semantic 3d mapping in recent years furthermore the number of robotic applications requiring semantic information in 3d mapping to perform highlevel tasks has increased and many studies on semantic 3d mapping have been published existing methods use a camera for both 3d reconstruction and semantic segmentation however this is not suitable for largescale environments and has the disadvantage of high computational complexity to address this problem we propose a multimodal sensorbased semantic 3d mapping system using a 3d lidar combined with a camera in this study we build a 3d map by estimating odometry based on a global positioning system gps and an inertial measurement unit imu and use the latest 2d convolutional neural network cnn for semantic segmentation to build a semantic 3d map we integrate the 3d map with semantic information by using coordinate transformation and bayes update scheme in order to improve the semantic 3d map we propose a 3d refinement process to correct wrongly segmented voxels and remove traces of moving vehicles in the 3d map through experiments on challenging sequences we demonstrate that our method outperforms stateoftheart methods in terms of accuracy and intersection over union iou thus our method can be used for various applications that require semantic information in 3d map
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1,802.10272
Large-time asymptotics of a fractional drift-diffusion-Poisson system via the entropy method
The self-similar asymptotics for solutions to the drift-diffusion equation with fractional dissipation, coupled to the Poisson equation, is analyzed in the whole space. It is shown that in the subcritical and supercritical cases, the solutions converge to the fractional heat kernel with algebraic rate. The proof is based on the entropy method and leads to a decay rate in the $L^1(\mathbb{R}^d)$ norm. The technique is applied to other semilinear equations with fractional dissipation.
math.AP
the selfsimilar asymptotics for solutions to the driftdiffusion equation with fractional dissipation coupled to the poisson equation is analyzed in the whole space it is shown that in the subcritical and supercritical cases the solutions converge to the fractional heat kernel with algebraic rate the proof is based on the entropy method and leads to a decay rate in the l1mathbbrd norm the technique is applied to other semilinear equations with fractional dissipation
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1,802.10273
Nonexistence of global solutions of wave equations with weak time-dependent damping and combined nonlinearity
In our previous two works, we studied the blow-up and lifespan estimates for damped wave equations with a power nonlinearity of the solution or its derivative, with scattering damping independently. In this work, we are devoted to establishing a similar result for a combined nonlinearity. Comparing to the result of wave equation without damping, one can say that the scattering damping has no influence.
math.AP
in our previous two works we studied the blowup and lifespan estimates for damped wave equations with a power nonlinearity of the solution or its derivative with scattering damping independently in this work we are devoted to establishing a similar result for a combined nonlinearity comparing to the result of wave equation without damping one can say that the scattering damping has no influence
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1,802.10274
Exponential time decay of solutions to reaction-cross-diffusion systems of Maxwell-Stefan type
The large-time asymptotics of weak solutions to Maxwell--Stefan diffusion systems for chemically reacting fluids with different molar masses and reversible reactions are investigated. The diffusion matrix of the system is generally neither symmetric nor positive definite, but the equations admit a formal gradient-flow structure which provides entropy (free energy) estimates. The main result is the exponential decay to the unique equilibrium with a rate that is constructive up to a finite-dimensional inequality. The key elements of the proof are the existence of a unique detailed-balanced equilibrium and the derivation of an inequality relating the entropy and the entropy production. The main difficulty comes from the fact that the reactions are represented by molar fractions while the conservation laws hold for the concentrations. The idea is to enlarge the space of $n$ partial concentrations by adding the total concentration, viewed as an independent variable, thus working with $n+1$ variables. Further results concern the existence of global bounded weak solutions to the parabolic system and an extension of the results to complex-balanced systems.
math.AP
the largetime asymptotics of weak solutions to maxwellstefan diffusion systems for chemically reacting fluids with different molar masses and reversible reactions are investigated the diffusion matrix of the system is generally neither symmetric nor positive definite but the equations admit a formal gradientflow structure which provides entropy free energy estimates the main result is the exponential decay to the unique equilibrium with a rate that is constructive up to a finitedimensional inequality the key elements of the proof are the existence of a unique detailedbalanced equilibrium and the derivation of an inequality relating the entropy and the entropy production the main difficulty comes from the fact that the reactions are represented by molar fractions while the conservation laws hold for the concentrations the idea is to enlarge the space of n partial concentrations by adding the total concentration viewed as an independent variable thus working with n1 variables further results concern the existence of global bounded weak solutions to the parabolic system and an extension of the results to complexbalanced systems
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1,802.10275
Solving for high dimensional committor functions using artificial neural networks
In this note we propose a method based on artificial neural network to study the transition between states governed by stochastic processes. In particular, we aim for numerical schemes for the committor function, the central object of transition path theory, which satisfies a high-dimensional Fokker-Planck equation. By working with the variational formulation of such partial differential equation and parameterizing the committor function in terms of a neural network, approximations can be obtained via optimizing the neural network weights using stochastic algorithms. The numerical examples show that moderate accuracy can be achieved for high-dimensional problems.
cs.LG cs.NA stat.ML
in this note we propose a method based on artificial neural network to study the transition between states governed by stochastic processes in particular we aim for numerical schemes for the committor function the central object of transition path theory which satisfies a highdimensional fokkerplanck equation by working with the variational formulation of such partial differential equation and parameterizing the committor function in terms of a neural network approximations can be obtained via optimizing the neural network weights using stochastic algorithms the numerical examples show that moderate accuracy can be achieved for highdimensional problems
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1,802.10276
Graph Optimization Approach to Range-based Localization
In this paper, we propose a general graph optimization based framework for localization, which can accommodate different types of measurements with varying measurement time intervals. Special emphasis will be on range-based localization. Range and trajectory smoothness constraints are constructed in a position graph, then the robot trajectory over a sliding window is estimated by a graph based optimization algorithm. Moreover, convergence analysis of the algorithm is provided, and the effects of the number of iterations and window size in the optimization on the localization accuracy are analyzed. Extensive experiments on quadcopter under a variety of scenarios verify the effectiveness of the proposed algorithm and demonstrate a much higher localization accuracy than the existing range-based localization methods, especially in the altitude direction.
cs.RO
in this paper we propose a general graph optimization based framework for localization which can accommodate different types of measurements with varying measurement time intervals special emphasis will be on rangebased localization range and trajectory smoothness constraints are constructed in a position graph then the robot trajectory over a sliding window is estimated by a graph based optimization algorithm moreover convergence analysis of the algorithm is provided and the effects of the number of iterations and window size in the optimization on the localization accuracy are analyzed extensive experiments on quadcopter under a variety of scenarios verify the effectiveness of the proposed algorithm and demonstrate a much higher localization accuracy than the existing rangebased localization methods especially in the altitude direction
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1,802.10277
Degenerations over $(A_\infty)$-singularities and construction of degenerations over commutative rings
We give a necessary condition of degeneration via matrix representations, and consider degenerations of indecomposable Cohen-Macaulay modules over hypersurface singularities of type ($A_\infty$). We also provide a method to construct degenerations of finitely generated modules over commutative rings.
math.AC math.RT
we give a necessary condition of degeneration via matrix representations and consider degenerations of indecomposable cohenmacaulay modules over hypersurface singularities of type a_infty we also provide a method to construct degenerations of finitely generated modules over commutative rings
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1,802.10278
Sign changes of Kloosterman sums and exceptional characters
We prove that the existence of exceptional real zeroes of Dirichlet $L$-functions would lead to cancellations in the sum $\sum_{p\leq x} \Kl(1, p)$ of Kloosterman sums over primes, and also to sign changes of $\Kl(1, n)$, where $n$ runs over integers with exactly two prime factors. Our arguments involve a variant of Bombieri's sieve, bounds for twisted sums of Kloosterman sums, and work of Fouvry and Michel on sums of $\left| \Kl(1, n)\right|$.
math.NT
we prove that the existence of exceptional real zeroes of dirichlet lfunctions would lead to cancellations in the sum sum_pleq x kl1 p of kloosterman sums over primes and also to sign changes of kl1 n where n runs over integers with exactly two prime factors our arguments involve a variant of bombieris sieve bounds for twisted sums of kloosterman sums and work of fouvry and michel on sums of left kl1 nright
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1,802.10279
Medical Exam Question Answering with Large-scale Reading Comprehension
Reading and understanding text is one important component in computer aided diagnosis in clinical medicine, also being a major research problem in the field of NLP. In this work, we introduce a question-answering task called MedQA to study answering questions in clinical medicine using knowledge in a large-scale document collection. The aim of MedQA is to answer real-world questions with large-scale reading comprehension. We propose our solution SeaReader--a modular end-to-end reading comprehension model based on LSTM networks and dual-path attention architecture. The novel dual-path attention models information flow from two perspectives and has the ability to simultaneously read individual documents and integrate information across multiple documents. In experiments our SeaReader achieved a large increase in accuracy on MedQA over competing models. Additionally, we develop a series of novel techniques to demonstrate the interpretation of the question answering process in SeaReader.
cs.CL
reading and understanding text is one important component in computer aided diagnosis in clinical medicine also being a major research problem in the field of nlp in this work we introduce a questionanswering task called medqa to study answering questions in clinical medicine using knowledge in a largescale document collection the aim of medqa is to answer realworld questions with largescale reading comprehension we propose our solution seareadera modular endtoend reading comprehension model based on lstm networks and dualpath attention architecture the novel dualpath attention models information flow from two perspectives and has the ability to simultaneously read individual documents and integrate information across multiple documents in experiments our seareader achieved a large increase in accuracy on medqa over competing models additionally we develop a series of novel techniques to demonstrate the interpretation of the question answering process in seareader
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1,802.1028
Escoin: Efficient Sparse Convolutional Neural Network Inference on GPUs
Deep neural networks have achieved remarkable accuracy in many artificial intelligence applications, e.g. computer vision, at the cost of a large number of parameters and high computational complexity. Weight pruning can compress DNN models by removing redundant parameters in the networks, but it brings sparsity in the weight matrix, and therefore makes the computation inefficient on GPUs. Although pruning can remove more than 80% of the weights, it actually hurts inference performance (speed) when running models on GPUs. Two major problems cause this unsatisfactory performance on GPUs. First, lowering convolution onto matrix multiplication reduces data reuse opportunities and wastes memory bandwidth. Second, the sparsity brought by pruning makes the computation irregular, which leads to inefficiency when running on massively parallel GPUs. To overcome these two limitations, we propose Escort, an efficient sparse convolutional neural networks on GPUs. Instead of using the lowering method, we choose to compute the sparse convolutions directly. We then orchestrate the parallelism and locality for the direct sparse convolution kernel, and apply customized optimization techniques to further improve performance. Evaluation on NVIDIA GPUs show that Escort can improve sparse convolution speed by 2.63x and 3.07x, and inference speed by 1.43x and 1.69x, compared to CUBLAS and CUSPARSE respectively.
cs.DC cs.CV cs.LG
deep neural networks have achieved remarkable accuracy in many artificial intelligence applications eg computer vision at the cost of a large number of parameters and high computational complexity weight pruning can compress dnn models by removing redundant parameters in the networks but it brings sparsity in the weight matrix and therefore makes the computation inefficient on gpus although pruning can remove more than 80 of the weights it actually hurts inference performance speed when running models on gpus two major problems cause this unsatisfactory performance on gpus first lowering convolution onto matrix multiplication reduces data reuse opportunities and wastes memory bandwidth second the sparsity brought by pruning makes the computation irregular which leads to inefficiency when running on massively parallel gpus to overcome these two limitations we propose escort an efficient sparse convolutional neural networks on gpus instead of using the lowering method we choose to compute the sparse convolutions directly we then orchestrate the parallelism and locality for the direct sparse convolution kernel and apply customized optimization techniques to further improve performance evaluation on nvidia gpus show that escort can improve sparse convolution speed by 263x and 307x and inference speed by 143x and 169x compared to cublas and cusparse respectively
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1,802.10281
Spin-one bilinear-biquadratic model on a star lattice
We study the ground-state phase diagram of the $S=1$ bilinear-biquadratic model\,(BLBQ) on the star lattice with the state-of-art tensor network algorithms. The system has five phases: the ferromagnetic, anti-ferromagnetic, ferroquadrupolar, and spin-liquid phases. The phases and their phase boundaries are determined by examining various local observables, correlation functions and transfer matrices exhaustively. The spin liquid phase, which is the first quantum disordered phase found in two-dimensional BLBQ model, is gapped and devoid of any conventional long-range order. It is also characterized by fixed-parity virtual bonds in the tensor network formalism, analogous to the Haldane phase, while the parity varies depending on the location of the bond.
cond-mat.str-el
we study the groundstate phase diagram of the s1 bilinearbiquadratic modelblbq on the star lattice with the stateofart tensor network algorithms the system has five phases the ferromagnetic antiferromagnetic ferroquadrupolar and spinliquid phases the phases and their phase boundaries are determined by examining various local observables correlation functions and transfer matrices exhaustively the spin liquid phase which is the first quantum disordered phase found in twodimensional blbq model is gapped and devoid of any conventional longrange order it is also characterized by fixedparity virtual bonds in the tensor network formalism analogous to the haldane phase while the parity varies depending on the location of the bond
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1,802.10282
Weak Lensing Study in VOICE Survey I: Shear Measurement
The VST Optical Imaging of the CDFS and ES1 Fields (VOICE) Survey is a Guaranteed Time program carried out with the ESO/VST telescope to provide deep optical imaging over two 4 deg$^2$ patches of the sky centred on the CDFS and ES1 pointings. We present the cosmic shear measurement over the 4 deg$^2$ covering the CDFS region in the $r$-band using LensFit. Each of the four tiles of 1 deg$^2$ has more than one hundred exposures, of which more than 50 exposures passed a series of image quality selection criteria for weak lensing study. The $5\sigma$ limiting magnitude in $r$- band is 26.1 for point sources, which is $\sim$1 mag deeper than other weak lensing survey in the literature (e.g. the Kilo Degree Survey, KiDS, at VST). The photometric redshifts are estimated using the VOICE $u,g,r,i$ together with near-infrared VIDEO data $Y,J,H,K_s$. The mean redshift of the shear catalogue is 0.87, considering the shear weight. The effective galaxy number density is 16.35 gal/arcmin$^2$, which is nearly twice the one of KiDS. The performance of LensFit on such a deep dataset was calibrated using VOICE-like mock image simulations. Furthermore, we have analyzed the reliability of the shear catalogue by calculating the star-galaxy cross-correlations, the tomographic shear correlations of two redshift bins and the contaminations of the blended galaxies. As a further sanity check, we have constrained cosmological parameters by exploring the parameter space with Population Monte Carlo sampling. For a flat $\Lambda$CDM model we have obtained $\Sigma_8$ = $\sigma_8(\Omega_m/0.3)^{0.5}$ = $0.68^{+0.11}_{-0.15}$.
astro-ph.CO
the vst optical imaging of the cdfs and es1 fields voice survey is a guaranteed time program carried out with the esovst telescope to provide deep optical imaging over two 4 deg2 patches of the sky centred on the cdfs and es1 pointings we present the cosmic shear measurement over the 4 deg2 covering the cdfs region in the rband using lensfit each of the four tiles of 1 deg2 has more than one hundred exposures of which more than 50 exposures passed a series of image quality selection criteria for weak lensing study the 5sigma limiting magnitude in r band is 261 for point sources which is sim1 mag deeper than other weak lensing survey in the literature eg the kilo degree survey kids at vst the photometric redshifts are estimated using the voice ugri together with nearinfrared video data yjhk_s the mean redshift of the shear catalogue is 087 considering the shear weight the effective galaxy number density is 1635 galarcmin2 which is nearly twice the one of kids the performance of lensfit on such a deep dataset was calibrated using voicelike mock image simulations furthermore we have analyzed the reliability of the shear catalogue by calculating the stargalaxy crosscorrelations the tomographic shear correlations of two redshift bins and the contaminations of the blended galaxies as a further sanity check we have constrained cosmological parameters by exploring the parameter space with population monte carlo sampling for a flat lambdacdm model we have obtained sigma_8 sigma_8omega_m0305 068011_015
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1,802.10283
Weak Lensing Study in VOICE Survey II: Shear Bias Calibrations
The VST Optical Imaging of the CDFS and ES1 Fields (VOICE) Survey is proposed to obtain deep optical $ugri$ imaging of the CDFS and ES1 fields using the VLT Survey Telescope (VST). At present, the observations for the CDFS field have been completed, and comprise in total about 4.9 deg$^2$ down to $r_\mathrm{AB}$$\sim$26 mag. In the companion paper by Fu et al. (2018), we present the weak lensing shear measurements for $r$-band images with seeing $\le$ 0.9 arcsec. In this paper, we perform image simulations to calibrate possible biases of the measured shear signals. Statistically, the properties of the simulated point spread function (PSF) and galaxies show good agreements with those of observations. The multiplicative bias is calibrated to reach an accuracy of $\sim$3.0%. We study the bias sensitivities to the undetected faint galaxies and to the neighboring galaxies. We find that undetected galaxies contribute to the multiplicative bias at the level of $\sim$0.3%. Further analysis shows that galaxies with lower signal-to-noise ratio (SNR) are impacted more significantly because the undetected galaxies skew the background noise distribution. For the neighboring galaxies, we find that although most have been rejected in the shape measurement procedure, about one third of them still remain in the final shear sample. They show a larger ellipticity dispersion and contribute to $\sim$0.2% of the multiplicative bias. Such a bias can be removed by further eliminating these neighboring galaxies. But the effective number density of the galaxies can be reduced considerably. Therefore efficient methods should be developed for future weak lensing deep surveys.
astro-ph.CO
the vst optical imaging of the cdfs and es1 fields voice survey is proposed to obtain deep optical ugri imaging of the cdfs and es1 fields using the vlt survey telescope vst at present the observations for the cdfs field have been completed and comprise in total about 49 deg2 down to r_mathrmabsim26 mag in the companion paper by fu et al 2018 we present the weak lensing shear measurements for rband images with seeing le 09 arcsec in this paper we perform image simulations to calibrate possible biases of the measured shear signals statistically the properties of the simulated point spread function psf and galaxies show good agreements with those of observations the multiplicative bias is calibrated to reach an accuracy of sim30 we study the bias sensitivities to the undetected faint galaxies and to the neighboring galaxies we find that undetected galaxies contribute to the multiplicative bias at the level of sim03 further analysis shows that galaxies with lower signaltonoise ratio snr are impacted more significantly because the undetected galaxies skew the background noise distribution for the neighboring galaxies we find that although most have been rejected in the shape measurement procedure about one third of them still remain in the final shear sample they show a larger ellipticity dispersion and contribute to sim02 of the multiplicative bias such a bias can be removed by further eliminating these neighboring galaxies but the effective number density of the galaxies can be reduced considerably therefore efficient methods should be developed for future weak lensing deep surveys
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1,802.10284
When fast and slow interfaces grow together: connection to the half-space problem of the Kardar-Parisi-Zhang class
We study height fluctuations of interfaces in the $(1+1)$-dimensional Kardar-Parisi-Zhang (KPZ) class, growing at different speeds in the left half and the right half of space. Carrying out simulations of the discrete polynuclear growth model with two different growth rates, combined with the standard setting for the droplet, flat, and stationary geometries, we find that the fluctuation properties at and near the boundary are described by the KPZ half-space problem developed in the theoretical literature. In particular, in the droplet case, the distribution at the boundary is given by the largest-eigenvalue distribution of random matrices in the Gaussian symplectic ensemble, often called the GSE Tracy-Widom distribution. We also characterize crossover from the full-space statistics to the half-space one, which arises when the difference between the two growth speeds is small.
cond-mat.stat-mech math-ph math.MP math.PR
we study height fluctuations of interfaces in the 11dimensional kardarparisizhang kpz class growing at different speeds in the left half and the right half of space carrying out simulations of the discrete polynuclear growth model with two different growth rates combined with the standard setting for the droplet flat and stationary geometries we find that the fluctuation properties at and near the boundary are described by the kpz halfspace problem developed in the theoretical literature in particular in the droplet case the distribution at the boundary is given by the largesteigenvalue distribution of random matrices in the gaussian symplectic ensemble often called the gse tracywidom distribution we also characterize crossover from the fullspace statistics to the halfspace one which arises when the difference between the two growth speeds is small
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1,802.10285
Plasmonic absorption characteristics based on dumbbell-shaped graphene metamaterial arrays
In this paper, we proposed a theoretical model in the far-infrared and terahertz (THz) bands, which is a dumbbell-shaped graphene metamaterial arrays with a combination of graphene nanorod and two semisphere-suspended heads. We report a detailed theoretical investigation on how to enhance localized electric field and the absorption in the dumbbell-shaped graphene metamaterial arrays. The simulation results show that by changing the geometrical parameters of the structure and the Fermi level of graphene, we can change the absorption characteristics. Furthermore, we have discovered that the resonant wavelength is insensitive to TM polarization. In addition, we also find that the double-layer graphene arrays have better absorption characteristics than single-layer graphene arrays. This work allows us to achieve tunable terahertz absorber, and may also provide potential applications in optical filter and biochemical sensing.
physics.optics
in this paper we proposed a theoretical model in the farinfrared and terahertz thz bands which is a dumbbellshaped graphene metamaterial arrays with a combination of graphene nanorod and two semispheresuspended heads we report a detailed theoretical investigation on how to enhance localized electric field and the absorption in the dumbbellshaped graphene metamaterial arrays the simulation results show that by changing the geometrical parameters of the structure and the fermi level of graphene we can change the absorption characteristics furthermore we have discovered that the resonant wavelength is insensitive to tm polarization in addition we also find that the doublelayer graphene arrays have better absorption characteristics than singlelayer graphene arrays this work allows us to achieve tunable terahertz absorber and may also provide potential applications in optical filter and biochemical sensing
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1,802.10286
Formulation of the normal forms of Turing-Hopf bifurcation in reaction-diffusion systems with time delay
The normal forms up to the third order for a Hopf-steady state bifurcation of a general system of partial functional differential equations (PFDEs) is derived based on the center manifold and normal form theory of PFDEs. This is a codimension-two degenerate bifurcation with the characteristic equation having a pair of simple purely imaginary roots and a simple zero root, and the corresponding eigenfunctions may be spatially inhomogeneous. The PFDEs are reduced to a three-dimensional system of ordinary differential equations and precise dynamics near bifurcation point can be revealed by two unfolding parameters. The normal forms are explicitly written as functions of the Fr\'echet derivatives up to the third orders and characteristic functions of the original PFDEs, and they are presented in a concise matrix notation, which greatly eases the applications to the original PFDEs and is convenient for computer implementation. This provides a user-friendly approach of showing the existence and stability of patterned stationary and time-periodic solutions with spatial heterogeneity when the parameters are near a Turing-Hopf bifurcation point, and it can also be applied to reaction-diffusion systems without delay and the retarded functional differential equations without diffusion.
math.DS
the normal forms up to the third order for a hopfsteady state bifurcation of a general system of partial functional differential equations pfdes is derived based on the center manifold and normal form theory of pfdes this is a codimensiontwo degenerate bifurcation with the characteristic equation having a pair of simple purely imaginary roots and a simple zero root and the corresponding eigenfunctions may be spatially inhomogeneous the pfdes are reduced to a threedimensional system of ordinary differential equations and precise dynamics near bifurcation point can be revealed by two unfolding parameters the normal forms are explicitly written as functions of the frechet derivatives up to the third orders and characteristic functions of the original pfdes and they are presented in a concise matrix notation which greatly eases the applications to the original pfdes and is convenient for computer implementation this provides a userfriendly approach of showing the existence and stability of patterned stationary and timeperiodic solutions with spatial heterogeneity when the parameters are near a turinghopf bifurcation point and it can also be applied to reactiondiffusion systems without delay and the retarded functional differential equations without diffusion
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1,802.10287
Particle Number Dependence of The $N$-Body Simulations of Moon Formation
The formation of the Moon from the circumterrestrial disk has been investigated by using $N$-body simulations with the number $N$ of particles limited from $10^4$ to $10^5$. We develop an $N$-body simulation code on multiple Pezy-SC processors and deploy FDPS (Framework for Developing Particle Simulators) to deal with large number of particles. We execute several high- and extra-high-resolution $N$-body simulations of lunar accretion from a circumterrestrial disk of debris generated by a giant impact on Earth. The number of particles is up to $10^7$, in which 1 particle corresponds to a 10 km-size satellitesimal. We find that the spiral structures inside the Roche limit radius differ between low-resolution simulations ($N \leq10^5$) and high-resolution simulations ($N \geq10^6$). According to this difference, angular momentum fluxes, which determine the accretion timescale of the Moon also depend on the numerical resolution.
astro-ph.EP astro-ph.IM
the formation of the moon from the circumterrestrial disk has been investigated by using nbody simulations with the number n of particles limited from 104 to 105 we develop an nbody simulation code on multiple pezysc processors and deploy fdps framework for developing particle simulators to deal with large number of particles we execute several high and extrahighresolution nbody simulations of lunar accretion from a circumterrestrial disk of debris generated by a giant impact on earth the number of particles is up to 107 in which 1 particle corresponds to a 10 kmsize satellitesimal we find that the spiral structures inside the roche limit radius differ between lowresolution simulations n leq105 and highresolution simulations n geq106 according to this difference angular momentum fluxes which determine the accretion timescale of the moon also depend on the numerical resolution
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1,802.10288
Beating the classical precision limit with spin-1 Dicke state of more than 10000 atoms
Interferometry is a paradigm for most precision measurements. Using $N$ uncorrelated particles, the achievable precision for a two-mode (two-path) interferometer is bounded by the standard quantum limit (SQL), $1/\sqrt{N}$, due to the discrete (quanta) nature of individual measurements. Despite being a challenging benchmark, the two-mode SQL has been approached in a number of systems, including the LIGO and today's best atomic clocks. Employing multi-mode interferometry, the SQL becomes $1/[(M-1)\sqrt{N}]$ using M modes. Higher precision can also be achieved using entangled particles such that quantum noises from individual particles cancel out. In this work, we demonstrate an interferometric precision of $2.42^{+1.76}_{-1.29}\,$dB beyond the three-mode SQL, using balanced spin-1 (three-mode) Dicke states containing thousands of entangled atoms. The input quantum states are deterministically generated by controlled quantum phase transition and exhibit close to ideal quality. Our work shines light on the pursuit of quantum metrology beyond SQL.
cond-mat.quant-gas quant-ph
interferometry is a paradigm for most precision measurements using n uncorrelated particles the achievable precision for a twomode twopath interferometer is bounded by the standard quantum limit sql 1sqrtn due to the discrete quanta nature of individual measurements despite being a challenging benchmark the twomode sql has been approached in a number of systems including the ligo and todays best atomic clocks employing multimode interferometry the sql becomes 1m1sqrtn using m modes higher precision can also be achieved using entangled particles such that quantum noises from individual particles cancel out in this work we demonstrate an interferometric precision of 242176_129db beyond the threemode sql using balanced spin1 threemode dicke states containing thousands of entangled atoms the input quantum states are deterministically generated by controlled quantum phase transition and exhibit close to ideal quality our work shines light on the pursuit of quantum metrology beyond sql
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1,802.10289
Poincar\'{e} parameters and principal component analysis of Heart rate variability of subjects with health disorder
Heart rate variability,important marker for modulation of autonomic nervous system is studied for diabetic,hypertensive and control group of subjects.Lagged Poincar\'{e} plot of heart rate(HR),method of principal component analysis and auto-correlation of HR fluctuation are used to analyze HR obtained from ECG signal recorded over short time duration.The parameters $(SD1)$,$(SD2)$ and their ratio $(SD12)$,characterizing the Poincar\'{e} plot reveal a significant reduction of their values for diabetic and hypertensive subjects compared to the corresponding results of control one.The slope and the curvature of the plot of these parameters with lagged number exhibit similar trend.In particular,the curvature of $(SD12)$ for the control group differs widely from that of other groups.The principal component analysis is used for analysing multi-dimensional data set resulting from the Poincar\'{e} plot for all subjects.The correlation matrix points out significant correlation between slope and curvature.The analysis demonstrates that three groups are well separated in the domain of two significant principal components.The auto-correlation of HR fluctuation exhibits highly correlated pattern for subjects with health disorder compared to that of control subject.
physics.med-ph
heart rate variabilityimportant marker for modulation of autonomic nervous system is studied for diabetichypertensive and control group of subjectslagged poincare plot of heart ratehrmethod of principal component analysis and autocorrelation of hr fluctuation are used to analyze hr obtained from ecg signal recorded over short time durationthe parameters sd1sd2 and their ratio sd12characterizing the poincare plot reveal a significant reduction of their values for diabetic and hypertensive subjects compared to the corresponding results of control onethe slope and the curvature of the plot of these parameters with lagged number exhibit similar trendin particularthe curvature of sd12 for the control group differs widely from that of other groupsthe principal component analysis is used for analysing multidimensional data set resulting from the poincare plot for all subjectsthe correlation matrix points out significant correlation between slope and curvaturethe analysis demonstrates that three groups are well separated in the domain of two significant principal componentsthe autocorrelation of hr fluctuation exhibits highly correlated pattern for subjects with health disorder compared to that of control subject
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1,802.1029
A large sample of shear selected clusters from the Hyper Suprime-Cam Subaru Strategic Program S16A wide field mass maps
We present the result of searching for clusters of galaxies based on weak gravitational lensing analysis of the $\sim 160$~deg$^2$ area surveyed by Hyper Suprime-Cam (HSC) as a Subaru Strategic Program. HSC is a new prime focus optical imager with a 1.5 diameter field of view on the 8.2-meter Subaru telescope. The superb median seeing on the HSC $i$-band images of $0.56$ arcsec allows the reconstruction of high angular resolution mass maps via weak lensing, which is crucial for the weak lensing cluster search. We identify 65 mass map peaks with signal-to-noise (SN) ratio larger than 4.7, and carefully examine their properties by cross-matching the clusters with optical and X-ray cluster catalogs. We find that all the 39 peaks with SN$>5.1$ have counterparts in the optical cluster catalogs, and only 2 out of the 65 peaks are probably false positives. The upper limits of X-ray luminosities from ROSAT All Sky Survey (RASS) imply the existence of an X-ray under-luminous cluster population. We show that the X-rays from the shear selected clusters can be statistically detected by stacking the RASS images. The inferred average X-ray luminosity is about half that of the X-ray selected clusters of the same mass. The radial profile of the dark matter distribution derived from the stacking analysis is well modeled by the Navarro-Frenk-White profile with a small concentration parameter value of $c_{500}\sim 2.5$, which suggests that the selection bias on the orientation or the internal structure for our shear selected cluster sample is not strong.
astro-ph.CO
we present the result of searching for clusters of galaxies based on weak gravitational lensing analysis of the sim 160deg2 area surveyed by hyper suprimecam hsc as a subaru strategic program hsc is a new prime focus optical imager with a 15 diameter field of view on the 82meter subaru telescope the superb median seeing on the hsc iband images of 056 arcsec allows the reconstruction of high angular resolution mass maps via weak lensing which is crucial for the weak lensing cluster search we identify 65 mass map peaks with signaltonoise sn ratio larger than 47 and carefully examine their properties by crossmatching the clusters with optical and xray cluster catalogs we find that all the 39 peaks with sn51 have counterparts in the optical cluster catalogs and only 2 out of the 65 peaks are probably false positives the upper limits of xray luminosities from rosat all sky survey rass imply the existence of an xray underluminous cluster population we show that the xrays from the shear selected clusters can be statistically detected by stacking the rass images the inferred average xray luminosity is about half that of the xray selected clusters of the same mass the radial profile of the dark matter distribution derived from the stacking analysis is well modeled by the navarrofrenkwhite profile with a small concentration parameter value of c_500sim 25 which suggests that the selection bias on the orientation or the internal structure for our shear selected cluster sample is not strong
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1,802.10291
FFT Multichannel Interpolation and Application to Image Super-resolution
This paper presents an innovative set of tools to support a methodology for the multichannel interpolation (MCI) of a discrete signal. It is shown that a bandlimited signal $f$ can be exactly reconstructed from finite samples of $g_k$ ($1\leq k\leq M$) which are the responses of $M$ linear systems with input $f$. The proposed interpolation can also be applied to approximate non-bandlimited signals. Quantitative error is analyzed to ensure its effectiveness in approximating non-bandlimited signals and its Hilbert transform. Based on the FFT technique, a fast algorithm which brings high computational efficiency and reliability for MCI is presented. The standout performance of MCI is illustrated by several simulations. Additionally, the proposed interpolation is applied to the single image super-resolution (SISR). Its superior performance in accuracy and speed of SISR is demonstrated by the experimental studies. Our results are compared qualitatively and quantitatively with the state-of-the-art methods in image upsampling and reconstruction by using the standard measurement criteria.
cs.IT math.IT math.NA
this paper presents an innovative set of tools to support a methodology for the multichannel interpolation mci of a discrete signal it is shown that a bandlimited signal f can be exactly reconstructed from finite samples of g_k 1leq kleq m which are the responses of m linear systems with input f the proposed interpolation can also be applied to approximate nonbandlimited signals quantitative error is analyzed to ensure its effectiveness in approximating nonbandlimited signals and its hilbert transform based on the fft technique a fast algorithm which brings high computational efficiency and reliability for mci is presented the standout performance of mci is illustrated by several simulations additionally the proposed interpolation is applied to the single image superresolution sisr its superior performance in accuracy and speed of sisr is demonstrated by the experimental studies our results are compared qualitatively and quantitatively with the stateoftheart methods in image upsampling and reconstruction by using the standard measurement criteria
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1,802.10292
Cahen-Gutt moment map, closed Fedosov star product and structure of the automorphism group
We show that if a compact Kaehler manifold $M$ of non-negative Ricci curvature admits closed Fedosov star product then the reduced Lie algebra of holomorphic vector fields on $M$ is reductive. This comes in pair with the obstruction previously found by La Fuente-Gravy. More generally we consider the squared norm of Cahen-Gutt moment map as in the same spirit of Calabi functional for the scalar curvature in cscK problem, and prove a Cahen-Gutt version of Calabi's theorem on the structure of the Lie algebra of holomorphic vector fields for extremal Kaehler manifolds. The proof uses a Hessian formula for the squared norm of Cahen-Gutt moment map.
math.DG
we show that if a compact kaehler manifold m of nonnegative ricci curvature admits closed fedosov star product then the reduced lie algebra of holomorphic vector fields on m is reductive this comes in pair with the obstruction previously found by la fuentegravy more generally we consider the squared norm of cahengutt moment map as in the same spirit of calabi functional for the scalar curvature in csck problem and prove a cahengutt version of calabis theorem on the structure of the lie algebra of holomorphic vector fields for extremal kaehler manifolds the proof uses a hessian formula for the squared norm of cahengutt moment map
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1,802.10293
Higher derivative quartic vertex of $f(R)$ gravity in light-cone gauge
In the recent studies of four-dimensional Einstein-Hilbert action, quite a few interesting results such as the Kawai-Lewellen-Tye (KLT) relations, MHV-Lagrangian and quadratic forms have been reported. These results naturally raise an important question: Whether these results are valid for the modified theories of gravity in 4-dimensions? In this work, we consider $R+\alpha\,R^2$ gravity and derive the complete quartic interaction vertex in light-cone gauge. We then discuss the implications of the results for KLT relations, and computing MHV amplitudes.
hep-th gr-qc
in the recent studies of fourdimensional einsteinhilbert action quite a few interesting results such as the kawailewellentye klt relations mhvlagrangian and quadratic forms have been reported these results naturally raise an important question whether these results are valid for the modified theories of gravity in 4dimensions in this work we consider ralphar2 gravity and derive the complete quartic interaction vertex in lightcone gauge we then discuss the implications of the results for klt relations and computing mhv amplitudes
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1,802.10294
Nuclear dynamics and particle production near threshold energies in heavy-ion collisions
Recent progress of the quantum molecular dynamics model for describing the dynamics of heavy-ion collisions is viewed, in particular the nuclear fragmentation, isospin physics, particle production and in-medium effect, hadron-induced nuclear reactions, hypernucleus etc. The neck fragmentation in Fermi-energy heavy-ion collisions is investigated for extracting the symmetry energy at subsaturation densities. The isospin effects, in-medium properties and the behavior of high-density symmetry energy in medium and high energy heavy-ion collisions are thoroughly discussed. The hypernuclide dynamics formed in heavy-ion collisions and in hadron induced reactions is analyzed and addressed in the future experiments at the High-Intensity heavy-ion Accelerator Facility (HIAF).
nucl-th
recent progress of the quantum molecular dynamics model for describing the dynamics of heavyion collisions is viewed in particular the nuclear fragmentation isospin physics particle production and inmedium effect hadroninduced nuclear reactions hypernucleus etc the neck fragmentation in fermienergy heavyion collisions is investigated for extracting the symmetry energy at subsaturation densities the isospin effects inmedium properties and the behavior of highdensity symmetry energy in medium and high energy heavyion collisions are thoroughly discussed the hypernuclide dynamics formed in heavyion collisions and in hadron induced reactions is analyzed and addressed in the future experiments at the highintensity heavyion accelerator facility hiaf
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1,802.10295
Beliaev Damping in Spin-$\frac{1}{2}$ Interacting Bosons with Spin-Orbit Coupling
Beliaev damping provides one of the most important mechanisms for dissipation of quasiparticles through beyond-mean-field effects at zero temperature. Here we present the first analytical result of Beliaev damping in low-energy excitations of spin-$\frac{1}{2}$ interacting bosons with equal Rashba and Dresslhaus spin-orbit couplings. We identify novel features of Beliaev decay rate due to spin-orbit coupling, in particular, it shows explicit dependence on the spin-density interaction and diverges at the interaction-modified phase boundary between the zero-momentum and plane-wave phases. This represents a manifestation of the effect of spin-orbit coupling in the beyond-mean-field regime, which by breaking Galilean invariance couples excitations in the density- and spin-channels. By describing the Beliaev damping in terms of the observable dynamic structure factors, our results allow direct experimental access within current facilities.
cond-mat.quant-gas
beliaev damping provides one of the most important mechanisms for dissipation of quasiparticles through beyondmeanfield effects at zero temperature here we present the first analytical result of beliaev damping in lowenergy excitations of spinfrac12 interacting bosons with equal rashba and dresslhaus spinorbit couplings we identify novel features of beliaev decay rate due to spinorbit coupling in particular it shows explicit dependence on the spindensity interaction and diverges at the interactionmodified phase boundary between the zeromomentum and planewave phases this represents a manifestation of the effect of spinorbit coupling in the beyondmeanfield regime which by breaking galilean invariance couples excitations in the density and spinchannels by describing the beliaev damping in terms of the observable dynamic structure factors our results allow direct experimental access within current facilities
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1,802.10296
Images and Spectra of Time Dependent Two Component Advective Flow in Presence of Outflows
Two Component Advective Flow (TCAF) successfully explains the spectral and tem- poral properties of outbursting or persistent sources. Images of static TCAF with Compton cloud or CENtrifugal pressure supported Boundary Layer (CENBOL) due to gravitational bending of photons have been studied before. In this paper, we study time dependent images of advective flows around a Schwarzschild black hole which include cooling effects due to Comptonization of soft photons from a Keplerian disks well as the self-consistently produced jets and outflows. We show the overall image of the disk-jet system after convolving with a typical beamwidth. A long exposure image with time dependent system need not show the black hole horizon conspicuously, un- less one is looking at a soft state with no jet or the system along the jet axis. Assuming these disk-jet configurations are relevant to radio emitting systems also, our results would be useful to look for event horizons in high accretion rate Supermassive Black Holes in Seyfert galaxies, RL Quasars.
astro-ph.HE
two component advective flow tcaf successfully explains the spectral and tem poral properties of outbursting or persistent sources images of static tcaf with compton cloud or centrifugal pressure supported boundary layer cenbol due to gravitational bending of photons have been studied before in this paper we study time dependent images of advective flows around a schwarzschild black hole which include cooling effects due to comptonization of soft photons from a keplerian disks well as the selfconsistently produced jets and outflows we show the overall image of the diskjet system after convolving with a typical beamwidth a long exposure image with time dependent system need not show the black hole horizon conspicuously un less one is looking at a soft state with no jet or the system along the jet axis assuming these diskjet configurations are relevant to radio emitting systems also our results would be useful to look for event horizons in high accretion rate supermassive black holes in seyfert galaxies rl quasars
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1,802.10297
Semi-MapReduce Meets Congested Clique
Graph problems are troublesome when it comes to MapReduce. Typically, to be able to design algorithms that make use of the advantages of MapReduce, assumptions beyond what the model imposes, such as the density of the input graph, are required. In a recent shift, a simple and robust model of MapReduce for graph problems, where the space per machine is set to be O(|V|), has attracted considerable attention. We term this model semi-MapReduce, or in short, semiMPC, and focus on its computational power. We show through a set of simulation methods that semiMPC is, perhaps surprisingly, equivalent to the congested clique model of distributed computing. However, semiMPC, in addition to round complexity, incorporates another practically important dimension to optimize: the number of machines. Furthermore, we show that algorithms in other distributed computing models, such as CONGEST, can be simulated to run in the same number of rounds of semiMPC while also using an optimal number of machines. We later show the implications of these simulation methods by obtaining improved algorithms for these models using the recent algorithms that have been developed.
cs.DC
graph problems are troublesome when it comes to mapreduce typically to be able to design algorithms that make use of the advantages of mapreduce assumptions beyond what the model imposes such as the density of the input graph are required in a recent shift a simple and robust model of mapreduce for graph problems where the space per machine is set to be ov has attracted considerable attention we term this model semimapreduce or in short semimpc and focus on its computational power we show through a set of simulation methods that semimpc is perhaps surprisingly equivalent to the congested clique model of distributed computing however semimpc in addition to round complexity incorporates another practically important dimension to optimize the number of machines furthermore we show that algorithms in other distributed computing models such as congest can be simulated to run in the same number of rounds of semimpc while also using an optimal number of machines we later show the implications of these simulation methods by obtaining improved algorithms for these models using the recent algorithms that have been developed
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1,802.10298
A van der Waals DFT study of chain length dependence of alkanethiol adsorption on Au(111): Physisorption vs.chemisorption
The energetics and structures of physisorbed and chemisorbed alkanethiols on Au(111) have been systematically investigated up to 10 carbon atoms using van der Waals (vdW) corrected density functional theory (DFT) calculations. The role of chain length, tilting angle and coverage on the adsorption characteristics have been examined to elucidate the energetics and plausible transformation mechanisms between lying down and standing up phases. Coverage and size dependent chain-chain electronic interactions counteract with the alkyl chain-gold surface interactions and the surface relaxation of the metal in the formation of standing up monolayer structures. For the striped phases of long chain alkanethiols, however, our calculations on decanethiol indicates alkyl chain-gold surface interactions to be strong enough to force the molecule to be perfectly parallel to the surface by lifting a gold atom up, in agreement with the proposed models for this film in the literature.
physics.chem-ph cond-mat.str-el
the energetics and structures of physisorbed and chemisorbed alkanethiols on au111 have been systematically investigated up to 10 carbon atoms using van der waals vdw corrected density functional theory dft calculations the role of chain length tilting angle and coverage on the adsorption characteristics have been examined to elucidate the energetics and plausible transformation mechanisms between lying down and standing up phases coverage and size dependent chainchain electronic interactions counteract with the alkyl chaingold surface interactions and the surface relaxation of the metal in the formation of standing up monolayer structures for the striped phases of long chain alkanethiols however our calculations on decanethiol indicates alkyl chaingold surface interactions to be strong enough to force the molecule to be perfectly parallel to the surface by lifting a gold atom up in agreement with the proposed models for this film in the literature
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1,802.10299
Limit theory for an AR(1) model with intercept and a possible infinite variance
In this paper, we derive the limit distribution of the least squares estimator for an AR(1) model with a non-zero intercept and a possible infinite variance. It turns out that the estimator has a quite different limit for the cases of $|\rho| < 1$, $|\rho| > 1$, and $\rho = 1 + \frac{c}{n^\alpha}$ for some constant $c \in R$ and $\alpha \in (0, 1]$, and whether or not the variance of the model errors is infinite also has a great impact on both the convergence rate and the limit distribution of the estimator.
math.ST stat.TH
in this paper we derive the limit distribution of the least squares estimator for an ar1 model with a nonzero intercept and a possible infinite variance it turns out that the estimator has a quite different limit for the cases of rho 1 rho 1 and rho 1 fraccnalpha for some constant c in r and alpha in 0 1 and whether or not the variance of the model errors is infinite also has a great impact on both the convergence rate and the limit distribution of the estimator
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1,802.103
Edge Partitions of Optimal $2$-plane and $3$-plane Graphs
A topological graph is a graph drawn in the plane. A topological graph is $k$-plane, $k>0$, if each edge is crossed at most $k$ times. We study the problem of partitioning the edges of a $k$-plane graph such that each partite set forms a graph with a simpler structure. While this problem has been studied for $k=1$, we focus on optimal $2$-plane and $3$-plane graphs, which are $2$-plane and $3$-plane graphs with maximum density. We prove the following results. (i) It is not possible to partition the edges of a simple optimal $2$-plane graph into a $1$-plane graph and a forest, while (ii) an edge partition formed by a $1$-plane graph and two plane forests always exists and can be computed in linear time. (iii) We describe efficient algorithms to partition the edges of a simple optimal $2$-plane graph into a $1$-plane graph and a plane graph with maximum vertex degree $12$, or with maximum vertex degree $8$ if the optimal $2$-plane graph is such that its crossing-free edges form a graph with no separating triangles. (iv) We exhibit an infinite family of simple optimal $2$-plane graphs such that in any edge partition composed of a $1$-plane graph and a plane graph, the plane graph has maximum vertex degree at least $6$ and the $1$-plane graph has maximum vertex degree at least $12$. (v) We show that every optimal $3$-plane graph whose crossing-free edges form a biconnected graph can be decomposed, in linear time, into a $2$-plane graph and two plane forests.
math.CO
a topological graph is a graph drawn in the plane a topological graph is kplane k0 if each edge is crossed at most k times we study the problem of partitioning the edges of a kplane graph such that each partite set forms a graph with a simpler structure while this problem has been studied for k1 we focus on optimal 2plane and 3plane graphs which are 2plane and 3plane graphs with maximum density we prove the following results i it is not possible to partition the edges of a simple optimal 2plane graph into a 1plane graph and a forest while ii an edge partition formed by a 1plane graph and two plane forests always exists and can be computed in linear time iii we describe efficient algorithms to partition the edges of a simple optimal 2plane graph into a 1plane graph and a plane graph with maximum vertex degree 12 or with maximum vertex degree 8 if the optimal 2plane graph is such that its crossingfree edges form a graph with no separating triangles iv we exhibit an infinite family of simple optimal 2plane graphs such that in any edge partition composed of a 1plane graph and a plane graph the plane graph has maximum vertex degree at least 6 and the 1plane graph has maximum vertex degree at least 12 v we show that every optimal 3plane graph whose crossingfree edges form a biconnected graph can be decomposed in linear time into a 2plane graph and two plane forests
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1,802.10301
Avoiding overfitting of multilayer perceptrons by training derivatives
Resistance to overfitting is observed for neural networks trained with extended backpropagation algorithm. In addition to target values, its cost function uses derivatives of those up to the $4^{\mathrm{th}}$ order. For common applications of neural networks, high order derivatives are not readily available, so simpler cases are considered: training network to approximate analytical function inside 2D and 5D domains and solving Poisson equation inside a 2D circle. For function approximation, the cost is a sum of squared differences between output and target as well as their derivatives with respect to the input. Differential equations are usually solved by putting a multilayer perceptron in place of unknown function and training its weights, so that equation holds within some margin of error. Commonly used cost is the equation's residual squared. Added terms are squared derivatives of said residual with respect to the independent variables. To investigate overfitting, the cost is minimized for points of regular grids with various spacing, and its root mean is compared with its value on much denser test set. Fully connected perceptrons with six hidden layers and $2\cdot10^{4}$, $1\cdot10^{6}$ and $5\cdot10^{6}$ weights in total are trained with Rprop until cost changes by less than 10% for last 1000 epochs, or when the $10000^{\mathrm{th}}$ epoch is reached. Training the network with $5\cdot10^{6}$ weights to represent simple 2D function using 10 points with 8 extra derivatives in each produces cost test to train ratio of $1.5$, whereas for classical backpropagation in comparable conditions this ratio is $2\cdot10^{4}$.
cs.NE
resistance to overfitting is observed for neural networks trained with extended backpropagation algorithm in addition to target values its cost function uses derivatives of those up to the 4mathrmth order for common applications of neural networks high order derivatives are not readily available so simpler cases are considered training network to approximate analytical function inside 2d and 5d domains and solving poisson equation inside a 2d circle for function approximation the cost is a sum of squared differences between output and target as well as their derivatives with respect to the input differential equations are usually solved by putting a multilayer perceptron in place of unknown function and training its weights so that equation holds within some margin of error commonly used cost is the equations residual squared added terms are squared derivatives of said residual with respect to the independent variables to investigate overfitting the cost is minimized for points of regular grids with various spacing and its root mean is compared with its value on much denser test set fully connected perceptrons with six hidden layers and 2cdot104 1cdot106 and 5cdot106 weights in total are trained with rprop until cost changes by less than 10 for last 1000 epochs or when the 10000mathrmth epoch is reached training the network with 5cdot106 weights to represent simple 2d function using 10 points with 8 extra derivatives in each produces cost test to train ratio of 15 whereas for classical backpropagation in comparable conditions this ratio is 2cdot104
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1,802.10302
Bahadur representations for the bootstrap median absolute deviation and the application to projection depth weighted mean
Median absolute deviation (hereafter MAD) is known as a robust alternative to the ordinary variance. It has been widely utilized to induce robust statistical inferential procedures. In this paper, we investigate the strong and weak Bahadur representations of its bootstrap counterpart. As a useful application, we utilize the results to derive the weak Bahadur representation of the bootstrap sample projection depth weighted mean---a quite important location estimator depending on MAD.
math.ST stat.TH
median absolute deviation hereafter mad is known as a robust alternative to the ordinary variance it has been widely utilized to induce robust statistical inferential procedures in this paper we investigate the strong and weak bahadur representations of its bootstrap counterpart as a useful application we utilize the results to derive the weak bahadur representation of the bootstrap sample projection depth weighted meana quite important location estimator depending on mad
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1,802.10303
RRR: Rank-Regret Representative
Selecting the best items in a dataset is a common task in data exploration. However, the concept of "best" lies in the eyes of the beholder: different users may consider different attributes more important, and hence arrive at different rankings. Nevertheless, one can remove "dominated" items and create a "representative" subset of the data set, comprising the "best items" in it. A Pareto-optimal representative is guaranteed to contain the best item of each possible ranking, but it can be almost as big as the full data. Representative can be found if we relax the requirement to include the best item for every possible user, and instead just limit the users' "regret". Existing work defines regret as the loss in score by limiting consideration to the representative instead of the full data set, for any chosen ranking function. However, the score is often not a meaningful number and users may not understand its absolute value. Sometimes small ranges in score can include large fractions of the data set. In contrast, users do understand the notion of rank ordering. Therefore, alternatively, we consider the position of the items in the ranked list for defining the regret and propose the {\em rank-regret representative} as the minimal subset of the data containing at least one of the top-$k$ of any possible ranking function. This problem is NP-complete. We use the geometric interpretation of items to bound their ranks on ranges of functions and to utilize combinatorial geometry notions for developing effective and efficient approximation algorithms for the problem. Experiments on real datasets demonstrate that we can efficiently find small subsets with small rank-regrets.
cs.DB
selecting the best items in a dataset is a common task in data exploration however the concept of best lies in the eyes of the beholder different users may consider different attributes more important and hence arrive at different rankings nevertheless one can remove dominated items and create a representative subset of the data set comprising the best items in it a paretooptimal representative is guaranteed to contain the best item of each possible ranking but it can be almost as big as the full data representative can be found if we relax the requirement to include the best item for every possible user and instead just limit the users regret existing work defines regret as the loss in score by limiting consideration to the representative instead of the full data set for any chosen ranking function however the score is often not a meaningful number and users may not understand its absolute value sometimes small ranges in score can include large fractions of the data set in contrast users do understand the notion of rank ordering therefore alternatively we consider the position of the items in the ranked list for defining the regret and propose the em rankregret representative as the minimal subset of the data containing at least one of the topk of any possible ranking function this problem is npcomplete we use the geometric interpretation of items to bound their ranks on ranges of functions and to utilize combinatorial geometry notions for developing effective and efficient approximation algorithms for the problem experiments on real datasets demonstrate that we can efficiently find small subsets with small rankregrets
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1,802.10304
Reality and Myths of AGN Feedback
Feedback from active galactic nuclei (AGN) remains controversial despite its wide acceptance as necessary to regulate massive galaxy growth. A dedicated workshop was held on 16-20 October 2017 at the Lorentz Center in Leiden to distinguish between the reality and myths of AGN feedback from the observational side. Here, we summarize briefly all the sessions and outcome of the stimulating workshop. More details on the outcome of the discussions are provided in a series of articles.
astro-ph.GA
feedback from active galactic nuclei agn remains controversial despite its wide acceptance as necessary to regulate massive galaxy growth a dedicated workshop was held on 1620 october 2017 at the lorentz center in leiden to distinguish between the reality and myths of agn feedback from the observational side here we summarize briefly all the sessions and outcome of the stimulating workshop more details on the outcome of the discussions are provided in a series of articles
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1,802.10305
Observing positive and negative AGN feedback
Galaxy-scale outflows powered by actively accreting supermassive black holes are routinely detected, and they have been associated both with suppression and triggering of star formation. Recent observational evidence and simulations are favouring a delayed mechanism that connects outflows and star formation
astro-ph.GA
galaxyscale outflows powered by actively accreting supermassive black holes are routinely detected and they have been associated both with suppression and triggering of star formation recent observational evidence and simulations are favouring a delayed mechanism that connects outflows and star formation
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1,802.10306
AGN outflows and feedback twenty years on
It is the twentieth anniversary of the publication of the seminal papers by Magorrian et al. and Silk & Rees which, along with other related work, ignited an explosion of publications connecting active galactic nuclei (AGN)-driven outflows to galaxy evolution. With a surge in observations of AGN outflows, studies are attempting to directly test AGN feedback models using the outflow properties. With a focus on outflows traced by optical and CO emission lines, we discuss significant challenges which greatly complicate this task from both an observational and theoretical perspective. We highlight observational uncertainties involved, and the assumptions required, when deriving kinetic coupling efficiencies (i.e., outflow kinetic power as a fraction of AGN luminosity) from typical observations. Based on recent models we demonstrate that extreme caution should taken when comparing observationally-derived kinetic coupling efficiencies to coupling efficiencies from fiducial feedback models.
astro-ph.GA astro-ph.HE
it is the twentieth anniversary of the publication of the seminal papers by magorrian et al and silk rees which along with other related work ignited an explosion of publications connecting active galactic nuclei agndriven outflows to galaxy evolution with a surge in observations of agn outflows studies are attempting to directly test agn feedback models using the outflow properties with a focus on outflows traced by optical and co emission lines we discuss significant challenges which greatly complicate this task from both an observational and theoretical perspective we highlight observational uncertainties involved and the assumptions required when deriving kinetic coupling efficiencies ie outflow kinetic power as a fraction of agn luminosity from typical observations based on recent models we demonstrate that extreme caution should taken when comparing observationallyderived kinetic coupling efficiencies to coupling efficiencies from fiducial feedback models
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1,802.10307
Questions and challenges of what powers galactic outflows in active galactic nuclei
Different mechanisms can drive outflows in active galactic nuclei (AGN), but it is often unclear which mechanism dominates, if any. To quantify the impact of AGN feedback on galaxy evolution, the driving mechanism of outflows must be better understood.
astro-ph.GA
different mechanisms can drive outflows in active galactic nuclei agn but it is often unclear which mechanism dominates if any to quantify the impact of agn feedback on galaxy evolution the driving mechanism of outflows must be better understood
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1,802.10308
The largely unconstrained multiphase nature of outflows in AGN host galaxies
Observations and simulations show that outflows in active galactic nuclei (AGN) contain gas in different phases. To understand their true impact on galaxy evolution, we advocate consistent and unbiased investigation of these multiphase winds in large AGN samples.
astro-ph.GA
observations and simulations show that outflows in active galactic nuclei agn contain gas in different phases to understand their true impact on galaxy evolution we advocate consistent and unbiased investigation of these multiphase winds in large agn samples
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1,802.10309
Online Non-preemptive Scheduling on Unrelated Machines with Rejections
When a computer system schedules jobs there is typically a significant cost associated with preempting a job during execution. This cost can be from the expensive task of saving the memory's state and loading data into and out of memory. It is desirable to schedule jobs non-preemptively to avoid the costs of preemption. There is a need for non-preemptive system schedulers on desktops, servers and data centers. Despite this need, there is a gap between theory and practice. Indeed, few non-preemptive \emph{online} schedulers are known to have strong foundational guarantees. This gap is likely due to strong lower bounds on any online algorithm for popular objectives. Indeed, typical worst case analysis approaches, and even resource augmented approaches such as speed augmentation, result in all algorithms having poor performance guarantees. This paper considers on-line non-preemptive scheduling problems in the worst-case rejection model where the algorithm is allowed to reject a small fraction of jobs. By rejecting only a few jobs, this paper shows that the strong lower bounds can be circumvented. This approach can be used to discover algorithmic scheduling policies with desirable worst-case guarantees. Specifically, the paper presents algorithms for the following two objectives: minimizing the total flow-time and minimizing the total weighted flow-time plus energy under the speed-scaling mechanism. The algorithms have a small constant competitive ratio while rejecting only a constant fraction of jobs. Beyond specific results, the paper asserts that alternative models beyond speed augmentation should be explored to aid in the discovery of good schedulers in the face of the requirement of being online and non-preemptive.
cs.DS
when a computer system schedules jobs there is typically a significant cost associated with preempting a job during execution this cost can be from the expensive task of saving the memorys state and loading data into and out of memory it is desirable to schedule jobs nonpreemptively to avoid the costs of preemption there is a need for nonpreemptive system schedulers on desktops servers and data centers despite this need there is a gap between theory and practice indeed few nonpreemptive emphonline schedulers are known to have strong foundational guarantees this gap is likely due to strong lower bounds on any online algorithm for popular objectives indeed typical worst case analysis approaches and even resource augmented approaches such as speed augmentation result in all algorithms having poor performance guarantees this paper considers online nonpreemptive scheduling problems in the worstcase rejection model where the algorithm is allowed to reject a small fraction of jobs by rejecting only a few jobs this paper shows that the strong lower bounds can be circumvented this approach can be used to discover algorithmic scheduling policies with desirable worstcase guarantees specifically the paper presents algorithms for the following two objectives minimizing the total flowtime and minimizing the total weighted flowtime plus energy under the speedscaling mechanism the algorithms have a small constant competitive ratio while rejecting only a constant fraction of jobs beyond specific results the paper asserts that alternative models beyond speed augmentation should be explored to aid in the discovery of good schedulers in the face of the requirement of being online and nonpreemptive
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1,802.1031
Static and Radio-frequency magnetic response of high Tc Superconducting Quantum Interference Filters made by ion irradiation
Superconducting Quantum Interference Filters (SQIF) are promising devices for Radio- Frequency (RF) detection combining low noise, high sensitivity, large dynamic range and wide-band capabilities. Impressive progress have been made recently in the field, with SQIF based antennas and amplifiers showing interesting properties in the GHz range using the well-established Nb/AlOx technology. The possibility to extend these results to High Temperature Superconductors (HTS) is still open, and different techniques to fabricate HTS SQIFs are competing to make RF devices. We report on the DC and RF response of a High Temperature SQIF fabricated by the ion irradiation technique. It is made of 1000 Superconducting QUantum Interference Devices (SQUIDs) in series, with loop areas randomly distributed between 6 micron2 and 60 micron2. The DC transfer factor is around 450 V/T at optimal bias and temperature, and the maximum voltage swing around 2:5 mV . We show that such a SQIF detects RF signals up to 150 MHz. It presents linear characteristics for RF power spanning more than five decades, and non-linearities develop beyond PRF = -35 dBm in our set-up configuration. Second-harmonic generation has been shown to be minimum at the functioning point in the whole range of frequencies. A model has been developed which captures the essential features of the SQIF RF response.
physics.app-ph cond-mat.supr-con
superconducting quantum interference filters sqif are promising devices for radio frequency rf detection combining low noise high sensitivity large dynamic range and wideband capabilities impressive progress have been made recently in the field with sqif based antennas and amplifiers showing interesting properties in the ghz range using the wellestablished nbalox technology the possibility to extend these results to high temperature superconductors hts is still open and different techniques to fabricate hts sqifs are competing to make rf devices we report on the dc and rf response of a high temperature sqif fabricated by the ion irradiation technique it is made of 1000 superconducting quantum interference devices squids in series with loop areas randomly distributed between 6 micron2 and 60 micron2 the dc transfer factor is around 450 vt at optimal bias and temperature and the maximum voltage swing around 25 mv we show that such a sqif detects rf signals up to 150 mhz it presents linear characteristics for rf power spanning more than five decades and nonlinearities develop beyond prf 35 dbm in our setup configuration secondharmonic generation has been shown to be minimum at the functioning point in the whole range of frequencies a model has been developed which captures the essential features of the sqif rf response
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1,802.10311
Fast Maximum Likelihood estimation via Equilibrium Expectation for Large Network Data
A major line of contemporary research on complex networks is based on the development of statistical models that specify the local motifs associated with macro-structural properties observed in actual networks. This statistical approach becomes increasingly problematic as network size increases. In the context of current research on efficient estimation of models for large network data sets, we propose a fast algorithm for maximum likelihood estimation (MLE) that afords a signifcant increase in the size of networks amenable to direct empirical analysis. The algorithm we propose in this paper relies on properties of Markov chains at equilibrium, and for this reason it is called equilibrium expectation (EE). We demonstrate the performance of the EE algorithm in the context of exponential random graphmodels (ERGMs) a family of statistical models commonly used in empirical research based on network data observed at a single period in time. Thus far, the lack of efcient computational strategies has limited the empirical scope of ERGMs to relatively small networks with a few thousand nodes. The approach we propose allows a dramatic increase in the size of networks that may be analyzed using ERGMs. This is illustrated in an analysis of several biological networks and one social network with 104,103 nodes
stat.ME stat.ML
a major line of contemporary research on complex networks is based on the development of statistical models that specify the local motifs associated with macrostructural properties observed in actual networks this statistical approach becomes increasingly problematic as network size increases in the context of current research on efficient estimation of models for large network data sets we propose a fast algorithm for maximum likelihood estimation mle that afords a signifcant increase in the size of networks amenable to direct empirical analysis the algorithm we propose in this paper relies on properties of markov chains at equilibrium and for this reason it is called equilibrium expectation ee we demonstrate the performance of the ee algorithm in the context of exponential random graphmodels ergms a family of statistical models commonly used in empirical research based on network data observed at a single period in time thus far the lack of efcient computational strategies has limited the empirical scope of ergms to relatively small networks with a few thousand nodes the approach we propose allows a dramatic increase in the size of networks that may be analyzed using ergms this is illustrated in an analysis of several biological networks and one social network with 104103 nodes
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1,802.10312
Conditions where RPA becomes exact in the high-density limit
It is shown that in $d$-dimensional systems, the vertex corrections beyond the random phase approximation (RPA) or GW approximation scales with the power $d-\beta-\alpha$ of the Fermi momentum if the relation between Fermi energy and Fermi momentum is $\epsilon_{\rm f}\sim p_{\rm f}^\beta$ and the interacting potential possesses a momentum-power-law of $\sim p^{-\alpha}$. The condition $d-\beta-\alpha<0$ specifies systems where RPA is exact in the high-density limit. The one-dimensional structure factor is found to be the interaction-free one in the high-density limit for contact interaction. A cancellation of RPA and vertex corrections render this result valid up to second-order in contact interaction. For finite-range potentials of cylindrical wires a large-scale cancellation appears and found to be independent of the width parameter of the wire. The proposed high-density expansion agrees with the Quantum Monte Carlo simulations.
cond-mat.str-el cond-mat.mes-hall physics.atm-clus quant-ph
it is shown that in ddimensional systems the vertex corrections beyond the random phase approximation rpa or gw approximation scales with the power dbetaalpha of the fermi momentum if the relation between fermi energy and fermi momentum is epsilon_rm fsim p_rm fbeta and the interacting potential possesses a momentumpowerlaw of sim palpha the condition dbetaalpha0 specifies systems where rpa is exact in the highdensity limit the onedimensional structure factor is found to be the interactionfree one in the highdensity limit for contact interaction a cancellation of rpa and vertex corrections render this result valid up to secondorder in contact interaction for finiterange potentials of cylindrical wires a largescale cancellation appears and found to be independent of the width parameter of the wire the proposed highdensity expansion agrees with the quantum monte carlo simulations
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1,802.10313
Polarization effects due to dark matter interaction between massive standard particles
We propose deeper tests of the existence of DM interactions between heavy particles in $e^+e^-\to t\bar t, ZZ, W^+W^-$ by looking at the effects on final state polarization. We show that indeed $t$, $W$ and $Z$ polarization are particularly sensitive to the structure of these interactions, to their relation with the origin of the masses and to the quantum numbers of the possibly exchanged dark particles.
hep-ph
we propose deeper tests of the existence of dm interactions between heavy particles in eeto tbar t zz ww by looking at the effects on final state polarization we show that indeed t w and z polarization are particularly sensitive to the structure of these interactions to their relation with the origin of the masses and to the quantum numbers of the possibly exchanged dark particles
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1,802.10314
Almost diagonalization of $\tau$-pseudodifferential operators with symbols in Wiener amalgam and modulation spaces
In this paper we focus on the almost-diagonalization properties of $\tau$-pseudodifferential operators using techniques from time-frequency analysis. Our function spaces are modulation spaces and the special class of Wiener amalgam spaces arising by considering the action of the Fourier transform of modulation spaces. A particular example is provided by the Sj\"ostrand class, for which Gr\"ochenig exhibited the almost diagonalization of Weyl operators. We shall show that such result can be extended to any $\tau$-pseudodifferential operator, for $\tau \in [0,1]$, also with symbol in weighted Wiener amalgam spaces. As a consequence, we infer boundedness, algebra and Wiener properties for $\tau$-pseudodifferential operators on Wiener amalgam and modulation spaces.
math.FA
in this paper we focus on the almostdiagonalization properties of taupseudodifferential operators using techniques from timefrequency analysis our function spaces are modulation spaces and the special class of wiener amalgam spaces arising by considering the action of the fourier transform of modulation spaces a particular example is provided by the sjostrand class for which grochenig exhibited the almost diagonalization of weyl operators we shall show that such result can be extended to any taupseudodifferential operator for tau in 01 also with symbol in weighted wiener amalgam spaces as a consequence we infer boundedness algebra and wiener properties for taupseudodifferential operators on wiener amalgam and modulation spaces
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1,802.10315
Configurations of flags in orbits of real forms
In this paper we start the study of configurations of flags in closed orbits of real forms using mainly tools of GIT. As an application, using cross ratio coordinates for generic configurations, we identify boundary unipotent representations of the fundamental group of the figure eight knot complement into real forms of $\mathrm{PGL}(4,\mathbb{C})$.
math.AG math.RT
in this paper we start the study of configurations of flags in closed orbits of real forms using mainly tools of git as an application using cross ratio coordinates for generic configurations we identify boundary unipotent representations of the fundamental group of the figure eight knot complement into real forms of mathrmpgl4mathbbc
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1,802.10316
A Model for Medical Diagnosis Based on Plantar Pressure
The process of determining which disease or condition explains a person's symptoms and signs can be very complicated and may be inaccurate in some cases. The general belief is that diagnosing diseases relies on doctors' keen intuition, rich experience and professional equipment. In this work, we employ ideas from recent advances in plantar pressure research and from the powerful capacity of the convolutional neural network for learning representations. Here, we propose a model using convolutional neural network based on plantar pressure for medical diagnosis. Our model learns a network that maps plantar pressure data to its corresponding medical diagnostic label. We then apply our model to make the medical diagnosis on datasets we collected from cooperative hospital and achieve an accuracy of 98.36%. We demonstrate that the model base on the convolutional neural network is competitive in medical diagnosis.
cs.CV
the process of determining which disease or condition explains a persons symptoms and signs can be very complicated and may be inaccurate in some cases the general belief is that diagnosing diseases relies on doctors keen intuition rich experience and professional equipment in this work we employ ideas from recent advances in plantar pressure research and from the powerful capacity of the convolutional neural network for learning representations here we propose a model using convolutional neural network based on plantar pressure for medical diagnosis our model learns a network that maps plantar pressure data to its corresponding medical diagnostic label we then apply our model to make the medical diagnosis on datasets we collected from cooperative hospital and achieve an accuracy of 9836 we demonstrate that the model base on the convolutional neural network is competitive in medical diagnosis
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1,802.10317
Simulation Studies on Generation, Handling and Transport of laser-accelerated Carbon Ions
To this day the interaction of high-intensity lasers with matter is considered to be a possible candidate for next generation particle accelerators. Within the LIGHT collaboration crucial work for the merging of a high-intensity laser driven ion source with conventional accelerator technology has been done in the past years. The simulation studies we report about are an important step in providing short and intense mid-Z heavy ion beams for future applications.
physics.acc-ph physics.plasm-ph
to this day the interaction of highintensity lasers with matter is considered to be a possible candidate for next generation particle accelerators within the light collaboration crucial work for the merging of a highintensity laser driven ion source with conventional accelerator technology has been done in the past years the simulation studies we report about are an important step in providing short and intense midz heavy ion beams for future applications
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1,802.10318
Resonant magneto-acoustic switching: influence of Rayleigh wave frequency and wavevector
We show on in-plane magnetized thin films that magnetization can be switched efficiently by 180 degrees using large amplitude Rayleigh waves travelling along the hard or easy magnetic axis. Large characteristic filament-like domains are formed in the latter case. Micromagnetic simulations clearly confirm that this multi-domain configuration is compatible with a resonant precessional mechanism. The reversed domains are in both geometries several hundreds of \mu m^2, much larger than has been shown using spin transfer torque- or field-driven precessional switching. We show that surface acoustic waves can travel at least 1mm before addressing a given area, and can interfere to create magnetic stripes that can be positionned with a sub-micronic precision.
cond-mat.mtrl-sci
we show on inplane magnetized thin films that magnetization can be switched efficiently by 180 degrees using large amplitude rayleigh waves travelling along the hard or easy magnetic axis large characteristic filamentlike domains are formed in the latter case micromagnetic simulations clearly confirm that this multidomain configuration is compatible with a resonant precessional mechanism the reversed domains are in both geometries several hundreds of mu m2 much larger than has been shown using spin transfer torque or fielddriven precessional switching we show that surface acoustic waves can travel at least 1mm before addressing a given area and can interfere to create magnetic stripes that can be positionned with a submicronic precision
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1,802.10319
General-relativistic pulsar magnetospheric emission
Most current pulsar emission models assume photon production and emission within the magnetosphere. Low frequency radiation is preferentially produced in the vicinity of the polar caps whereas the high-energy tail is shifted to regions closer but still inside the light-cylinder. We conducted a systematic study of the merit of several popular radiation sites like the polar cap, the outer gap and the slot gap. We computed sky maps emanating from each emission site according to a prescribed distribution function for the emitting particles made of an electron/positron mixture. Calculations are performed using a three dimensional integration of the plasma emissivity in the vacuum electromagnetic field of a rotating centred general-relativistic dipole. We compare Newtonian electromagnetic fields to their general-relativistic counterpart. In the latter case, light bending is also taken into account. As a typical example, light-curves and sky maps are plotted for several power-law indices of the particle distribution function. The detailed pulse profiles strongly depend on the underlying assumption about the fluid motion subject to strong electromagnetic fields. This electromagnetic topology enforces the photon propagation direction directly, or indirectly, from aberration effects. We also discuss the implication of a net stellar electric charge on to the sky maps. Taking into account the electric field strongly affects the light-curves originating close to the light-cylinder where the electric field strength becomes comparable to the magnetic field strength.
astro-ph.HE
most current pulsar emission models assume photon production and emission within the magnetosphere low frequency radiation is preferentially produced in the vicinity of the polar caps whereas the highenergy tail is shifted to regions closer but still inside the lightcylinder we conducted a systematic study of the merit of several popular radiation sites like the polar cap the outer gap and the slot gap we computed sky maps emanating from each emission site according to a prescribed distribution function for the emitting particles made of an electronpositron mixture calculations are performed using a three dimensional integration of the plasma emissivity in the vacuum electromagnetic field of a rotating centred generalrelativistic dipole we compare newtonian electromagnetic fields to their generalrelativistic counterpart in the latter case light bending is also taken into account as a typical example lightcurves and sky maps are plotted for several powerlaw indices of the particle distribution function the detailed pulse profiles strongly depend on the underlying assumption about the fluid motion subject to strong electromagnetic fields this electromagnetic topology enforces the photon propagation direction directly or indirectly from aberration effects we also discuss the implication of a net stellar electric charge on to the sky maps taking into account the electric field strongly affects the lightcurves originating close to the lightcylinder where the electric field strength becomes comparable to the magnetic field strength
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1,802.1032
A Hardware-Efficient Analog Network Structure for Hybrid Precoding in Millimeter Wave Systems
Hybrid precoding has been recently proposed as a cost-effective transceiver solution for millimeter wave (mm-wave) systems. While the number of radio frequency (RF) chains has been effectively reduced in existing works, a large number of high-precision phase shifters are still needed. Practical phase shifters are with coarsely quantized phases, and their number should be reduced to a minimum due to cost and power consideration. In this paper, we propose a novel hardware-efficient implementation for hybrid precoding, called the fixed phase shifter (FPS) implementation. It only requires a small number of phase shifters with quantized and fixed phases. To enhance the spectral efficiency, a switch network is put forward to provide dynamic connections from phase shifters to antennas, which is adaptive to the channel states. An effective alternating minimization (AltMin) algorithm is developed with closed-form solutions in each iteration to determine the hybrid precoder and the states of switches. Moreover, to further reduce the hardware complexity, a group-connected mapping strategy is proposed to reduce the number of switches. Simulation results show that the FPS fully-connected hybrid precoder achieves higher hardware efficiency with much fewer phase shifters than existing proposals. Furthermore, the group-connected mapping achieves a good balance between spectral efficiency and hardware complexity.
cs.IT math.IT
hybrid precoding has been recently proposed as a costeffective transceiver solution for millimeter wave mmwave systems while the number of radio frequency rf chains has been effectively reduced in existing works a large number of highprecision phase shifters are still needed practical phase shifters are with coarsely quantized phases and their number should be reduced to a minimum due to cost and power consideration in this paper we propose a novel hardwareefficient implementation for hybrid precoding called the fixed phase shifter fps implementation it only requires a small number of phase shifters with quantized and fixed phases to enhance the spectral efficiency a switch network is put forward to provide dynamic connections from phase shifters to antennas which is adaptive to the channel states an effective alternating minimization altmin algorithm is developed with closedform solutions in each iteration to determine the hybrid precoder and the states of switches moreover to further reduce the hardware complexity a groupconnected mapping strategy is proposed to reduce the number of switches simulation results show that the fps fullyconnected hybrid precoder achieves higher hardware efficiency with much fewer phase shifters than existing proposals furthermore the groupconnected mapping achieves a good balance between spectral efficiency and hardware complexity
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1,802.10321
High-resolution long-working-distance reference-free holographic microscopy exploiting speckle-correlation scattering matrix
Using conventional refraction-based optical lens, it is challenging to achieve both high-resolution imaging and long-working-distance condition. To increase the numerical aperture of a lens, the working distance should be compensated, and vice versa. Here we propose and demonstrate a new concept in optical microscopy that can achieve both high-resolution imaging and long-working-distance conditions by utilising a scattering layer instead of refractive optics. When light passes through a scattering layer, it creates a unique interference pattern. To retrieve the complex amplitude image from the interference pattern without introducing a reference beam, we utilised a speckle-correlation scattering matrix method. This property enables holographic microscopy without any lens or external reference beam. Importantly, the proposed method allows high-resolution imaging with a long working distance beyond what a conventional objective lens can achieve. As an experimental verification, we imaged various microscopic samples and compared their performance with off-axis digital holographic microscopy.
physics.optics
using conventional refractionbased optical lens it is challenging to achieve both highresolution imaging and longworkingdistance condition to increase the numerical aperture of a lens the working distance should be compensated and vice versa here we propose and demonstrate a new concept in optical microscopy that can achieve both highresolution imaging and longworkingdistance conditions by utilising a scattering layer instead of refractive optics when light passes through a scattering layer it creates a unique interference pattern to retrieve the complex amplitude image from the interference pattern without introducing a reference beam we utilised a specklecorrelation scattering matrix method this property enables holographic microscopy without any lens or external reference beam importantly the proposed method allows highresolution imaging with a long working distance beyond what a conventional objective lens can achieve as an experimental verification we imaged various microscopic samples and compared their performance with offaxis digital holographic microscopy
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1,802.10322
Thermal drag in electronic conductors
We study the electronic thermal drag in two different Coulomb-coupled systems, the first one composed of two Coulomb blockaded metallic islands and the second one consisting of two parallel quantum wires. The two conductors of each system are electrically isolated and placed in the two circuits (the drive and the drag) of a four-electrode setup. The systems are biased, either by a temperature $\Delta T$ or a voltage $V$ difference, on the drive circuit, while no biases are present on the drag circuit. In the case of a pair of metallic islands we use a master equation approach to determine the general properties of the dragged heat current $I^{\rm (h)}_{\rm drag}$, accounting also for co-tunneling contributions and the presence of large biases. Analytic results are obtained in the sequential tunneling regime for small biases, finding, in particular, that $I^{\rm (h)}_{\rm drag}$ is quadratic in $\Delta T$ or $V$ and non-monotonous as a function of the inter-island coupling. Finally, by replacing one of the electrodes in the drag circuit with a superconductor, we find that heat can be extracted from the other normal electrode. In the case of the two interacting quantum wires, using the Luttinger liquid theory and the bosonization technique, we derive an analytic expression for the thermal trans-resistivity $\rho^{\rm (h)}_{12}$, in the weak-coupling limit and at low temperatures. $\rho^{\rm (h)}_{12}$ turns out to be proportional to the electric trans-resistivity $\rho^{\rm (c)}_{12}$, in such a way that their ratio (a kind of Wiedemann-Franz law) is proportional to $T^3$. We find that the thermal trans-resistivity is proportional to $T$ for low temperatures and decreases like $1/T$ for intermediate temperatures or like $1/T^3$ for high temperatures. We complete our analyses by performing numerical simulations that confirm the above results and allow to access the strong coupling regime.
cond-mat.mes-hall
we study the electronic thermal drag in two different coulombcoupled systems the first one composed of two coulomb blockaded metallic islands and the second one consisting of two parallel quantum wires the two conductors of each system are electrically isolated and placed in the two circuits the drive and the drag of a fourelectrode setup the systems are biased either by a temperature delta t or a voltage v difference on the drive circuit while no biases are present on the drag circuit in the case of a pair of metallic islands we use a master equation approach to determine the general properties of the dragged heat current irm h_rm drag accounting also for cotunneling contributions and the presence of large biases analytic results are obtained in the sequential tunneling regime for small biases finding in particular that irm h_rm drag is quadratic in delta t or v and nonmonotonous as a function of the interisland coupling finally by replacing one of the electrodes in the drag circuit with a superconductor we find that heat can be extracted from the other normal electrode in the case of the two interacting quantum wires using the luttinger liquid theory and the bosonization technique we derive an analytic expression for the thermal transresistivity rhorm h_12 in the weakcoupling limit and at low temperatures rhorm h_12 turns out to be proportional to the electric transresistivity rhorm c_12 in such a way that their ratio a kind of wiedemannfranz law is proportional to t3 we find that the thermal transresistivity is proportional to t for low temperatures and decreases like 1t for intermediate temperatures or like 1t3 for high temperatures we complete our analyses by performing numerical simulations that confirm the above results and allow to access the strong coupling regime
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1,802.10323
A FFT-based finite-difference solver for massively-parallel direct numerical simulations of turbulent flows
We present an efficient solver for massively-parallel direct numerical simulations of incompressible turbulent flows. The method uses a second-order, finite-volume pressure-correction scheme, where the pressure Poisson equation is solved with the method of eigenfunction expansions. This approach allows for very efficient FFT-based solvers in problems with different combinations of homogeneous pressure boundary conditions. Our algorithm explores all combinations of pressure boundary conditions valid for such a solver, in a single, general framework. The method is implemented in a 2D pencil-like domain decomposition, which enables efficient massively-parallel simulations. The implementation was validated against different canonical flows, and its computational performance was examined. Excellent strong scaling performance up to $10^4$ cores is demonstrated for a domain with $10^9$ spatial degrees of freedom, corresponding to a very small wall-clock time/time step. The resulting tool, CaNS, has been made freely available and open-source.
physics.flu-dyn
we present an efficient solver for massivelyparallel direct numerical simulations of incompressible turbulent flows the method uses a secondorder finitevolume pressurecorrection scheme where the pressure poisson equation is solved with the method of eigenfunction expansions this approach allows for very efficient fftbased solvers in problems with different combinations of homogeneous pressure boundary conditions our algorithm explores all combinations of pressure boundary conditions valid for such a solver in a single general framework the method is implemented in a 2d pencillike domain decomposition which enables efficient massivelyparallel simulations the implementation was validated against different canonical flows and its computational performance was examined excellent strong scaling performance up to 104 cores is demonstrated for a domain with 109 spatial degrees of freedom corresponding to a very small wallclock timetime step the resulting tool cans has been made freely available and opensource
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1,802.10324
High-order splitting integrators for nonlinear Schr\"odinger equations over long times
The long-time behaviour of splitting integrators applied to nonlinear Schr\"odinger equations in a weakly nonlinear setting is studied. It is proven that the energy is nearly conserved on long time intervals. The analysis includes all consistent splitting integrators with real-valued coefficients, in particular splitting integrators of high order. The proof is based on a completely resonant modulated Fourier expansion in time of the numerical solution.
math.NA
the longtime behaviour of splitting integrators applied to nonlinear schrodinger equations in a weakly nonlinear setting is studied it is proven that the energy is nearly conserved on long time intervals the analysis includes all consistent splitting integrators with realvalued coefficients in particular splitting integrators of high order the proof is based on a completely resonant modulated fourier expansion in time of the numerical solution
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1,802.10325
Shifting Maximum Eigenvalue Detection in Low SNR Environment
Maximum eigenvalue detection (MED) is an important application of random matrix theory in spectrum sensing and signal detection. However, in small signal-to-noise ratio environment, the maximum eigenvalue of the representative signal is at the edge of Marchenko-Pastur (M-P) law bulk and meets the Tracy-Widom distribution. Since the distribution of Tracy-Widom has no closed-form expression, it brings great difficulty in processing. In this paper, we propose a shifting maximum eigenvalue (SMED) algorithm, which shifts the maximum eigenvalue out of the M-P law bulk by combining an auxiliary signal associated with the signal to be detected. According to the random matrix theory, the shifted maximum eigenvalue is consistent with Gaussian distribution. The proposed SMED not only simplifies the detection algorithm, but also greatly improve the detection performance. In this paper, the performance of SMED, MED and trace (FMD) algorithm is analyzed and the theoretical performance comparisons are obtained. The algorithm and theoretical results are verified by the simulations in different signal environments.
eess.SP
maximum eigenvalue detection med is an important application of random matrix theory in spectrum sensing and signal detection however in small signaltonoise ratio environment the maximum eigenvalue of the representative signal is at the edge of marchenkopastur mp law bulk and meets the tracywidom distribution since the distribution of tracywidom has no closedform expression it brings great difficulty in processing in this paper we propose a shifting maximum eigenvalue smed algorithm which shifts the maximum eigenvalue out of the mp law bulk by combining an auxiliary signal associated with the signal to be detected according to the random matrix theory the shifted maximum eigenvalue is consistent with gaussian distribution the proposed smed not only simplifies the detection algorithm but also greatly improve the detection performance in this paper the performance of smed med and trace fmd algorithm is analyzed and the theoretical performance comparisons are obtained the algorithm and theoretical results are verified by the simulations in different signal environments
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1,802.10326
An Analysis on Caching Placement for Millimeter/Micro Wave Hybrid Networks
In this paper, we consider a hybrid millimeter wave (mmWave) and micro wave ($\mu$Wave) network from the perspective of \emph{wireless caching} and study the optimal probabilistic content/file caching placement at desirable base stations (BSs) using a stochastic geometric framework. Considering the average success probability (ASP) of file delivery as the performance metric, we derive expressions for the association probability of the typical user to the mmWave and $\mu$Wave networks. Accordingly, we provide an upper bound for the ASP of file delivery and formulate the content caching placement scheme as an optimization problem with respect to caching probabilities, that jointly optimizes the ASP of file delivery considering both content placement and delivery phases. In particular, we consider the caching placement strategy under both noise-limited and interference-limited environments. We numerically evaluate the performance of the proposed caching schemes under essential factors, such as blockages in the mmWave network, cluster radius, BS density, and path loss and compare it with uniform caching placement, caching $M$ most popular contents, and random caching placement. Numerical results demonstrate the superiority of the proposed caching scheme over others, albeit certain trade-offs.
eess.SP
in this paper we consider a hybrid millimeter wave mmwave and micro wave muwave network from the perspective of emphwireless caching and study the optimal probabilistic contentfile caching placement at desirable base stations bss using a stochastic geometric framework considering the average success probability asp of file delivery as the performance metric we derive expressions for the association probability of the typical user to the mmwave and muwave networks accordingly we provide an upper bound for the asp of file delivery and formulate the content caching placement scheme as an optimization problem with respect to caching probabilities that jointly optimizes the asp of file delivery considering both content placement and delivery phases in particular we consider the caching placement strategy under both noiselimited and interferencelimited environments we numerically evaluate the performance of the proposed caching schemes under essential factors such as blockages in the mmwave network cluster radius bs density and path loss and compare it with uniform caching placement caching m most popular contents and random caching placement numerical results demonstrate the superiority of the proposed caching scheme over others albeit certain tradeoffs
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1,802.10327
Short intervals containing a prescribed number of primes
We prove that for every nonnegative integer $m$ there exists an $\varepsilon>0$ such that if $\lambda\in (0,\varepsilon]$ and $x$ is sufficiently large in terms of $m$, then the number of positive integers $n\leq x$ for which the interval $[n,n+\lambda\log n]$ contains exactly $m$ primes is at least a constant times $x/\log x.$ This improves a result of T. Freiberg, when $\lambda$ is small.
math.NT
we prove that for every nonnegative integer m there exists an varepsilon0 such that if lambdain 0varepsilon and x is sufficiently large in terms of m then the number of positive integers nleq x for which the interval nnlambdalog n contains exactly m primes is at least a constant times xlog x this improves a result of t freiberg when lambda is small
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1,802.10328
Neural Inverse Rendering for General Reflectance Photometric Stereo
We present a novel convolutional neural network architecture for photometric stereo (Woodham, 1980), a problem of recovering 3D object surface normals from multiple images observed under varying illuminations. Despite its long history in computer vision, the problem still shows fundamental challenges for surfaces with unknown general reflectance properties (BRDFs). Leveraging deep neural networks to learn complicated reflectance models is promising, but studies in this direction are very limited due to difficulties in acquiring accurate ground truth for training and also in designing networks invariant to permutation of input images. In order to address these challenges, we propose a physics based unsupervised learning framework where surface normals and BRDFs are predicted by the network and fed into the rendering equation to synthesize observed images. The network weights are optimized during testing by minimizing reconstruction loss between observed and synthesized images. Thus, our learning process does not require ground truth normals or even pre-training on external images. Our method is shown to achieve the state-of-the-art performance on a challenging real-world scene benchmark.
cs.CV cs.NE
we present a novel convolutional neural network architecture for photometric stereo woodham 1980 a problem of recovering 3d object surface normals from multiple images observed under varying illuminations despite its long history in computer vision the problem still shows fundamental challenges for surfaces with unknown general reflectance properties brdfs leveraging deep neural networks to learn complicated reflectance models is promising but studies in this direction are very limited due to difficulties in acquiring accurate ground truth for training and also in designing networks invariant to permutation of input images in order to address these challenges we propose a physics based unsupervised learning framework where surface normals and brdfs are predicted by the network and fed into the rendering equation to synthesize observed images the network weights are optimized during testing by minimizing reconstruction loss between observed and synthesized images thus our learning process does not require ground truth normals or even pretraining on external images our method is shown to achieve the stateoftheart performance on a challenging realworld scene benchmark
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1,802.10329
Reconsidering Linear Transmit Signal Processing in 1-Bit Quantized Multi-User MISO Systems
In this contribution, we investigate a coarsely quantized Multi-User (MU)-Multiple Input Single Output (MISO) downlink communication system, where we assume 1-Bit Digital-to-Analog Converters (DACs) at the Base Station (BS) antennas. First, we analyze the achievable sum rate lower-bound using the Bussgang decomposition. In the presence of the non-linear quanization, our analysis indicates the potential merit of reconsidering traditional signal processing techniques in coarsely quantized systems, i.e., reconsidering transmit covariance matrices whose rank is equal to the rank of the channel. Furthermore, in the second part of this paper, we propose a linear precoder design which achieves the predicted increase in performance compared with a state of the art linear precoder design. Moreover, our linear signal processing algorithm allows for higher-order modulation schemes to be employed.
cs.IT math.IT
in this contribution we investigate a coarsely quantized multiuser mumultiple input single output miso downlink communication system where we assume 1bit digitaltoanalog converters dacs at the base station bs antennas first we analyze the achievable sum rate lowerbound using the bussgang decomposition in the presence of the nonlinear quanization our analysis indicates the potential merit of reconsidering traditional signal processing techniques in coarsely quantized systems ie reconsidering transmit covariance matrices whose rank is equal to the rank of the channel furthermore in the second part of this paper we propose a linear precoder design which achieves the predicted increase in performance compared with a state of the art linear precoder design moreover our linear signal processing algorithm allows for higherorder modulation schemes to be employed
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1,802.1033
Extreme-value copulas associated with the expected scaled maximum of independent random variables
It is well-known that the expected scaled maximum of non-negative random variables with unit mean defines a stable tail dependence function associated with some extreme-value copula. In the special case when these random variables are independent and identically distributed, min-stable multivariate exponential random vectors with the associated survival extreme-value copulas are shown to arise as finite-dimensional margins of an infinite exchangeable sequence in the sense of De Finetti's Theorem. The associated latent factor is a stochastic process which is strongly infinitely divisible with respect to time, which induces a bijection from the set of distribution functions F of non-negative random variables with finite mean to the set of L\'evy measures on the positive half-axis. Since the Gumbel and the Galambos copula are the most popular examples of this construction, the investigation of this bijection contributes to a further understanding of their well-known analytical similarities. Furthermore, a simulation algorithm based on the latent factor representation is developed, if the support of F is bounded. Especially in large dimensions, this algorithm is efficient because it makes use of the De Finetti structure.
stat.ME
it is wellknown that the expected scaled maximum of nonnegative random variables with unit mean defines a stable tail dependence function associated with some extremevalue copula in the special case when these random variables are independent and identically distributed minstable multivariate exponential random vectors with the associated survival extremevalue copulas are shown to arise as finitedimensional margins of an infinite exchangeable sequence in the sense of de finettis theorem the associated latent factor is a stochastic process which is strongly infinitely divisible with respect to time which induces a bijection from the set of distribution functions f of nonnegative random variables with finite mean to the set of levy measures on the positive halfaxis since the gumbel and the galambos copula are the most popular examples of this construction the investigation of this bijection contributes to a further understanding of their wellknown analytical similarities furthermore a simulation algorithm based on the latent factor representation is developed if the support of f is bounded especially in large dimensions this algorithm is efficient because it makes use of the de finetti structure
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1,802.10331
Capturing Logarithmic Space and Polynomial Time on Chordal Claw-Free Graphs
We show that the class of chordal claw-free graphs admits LREC$_=$-definable canonization. LREC$_=$ is a logic that extends first-order logic with counting by an operator that allows it to formalize a limited form of recursion. This operator can be evaluated in logarithmic space. It follows that there exists a logarithmic-space canonization algorithm, and therefore a logarithmic-space isomorphism test, for the class of chordal claw-free graphs. As a further consequence, LREC$_=$ captures logarithmic space on this graph class. Since LREC$_=$ is contained in fixed-point logic with counting, we also obtain that fixed-point logic with counting captures polynomial time on the class of chordal claw-free graphs.
cs.LO cs.DM
we show that the class of chordal clawfree graphs admits lrec_definable canonization lrec_ is a logic that extends firstorder logic with counting by an operator that allows it to formalize a limited form of recursion this operator can be evaluated in logarithmic space it follows that there exists a logarithmicspace canonization algorithm and therefore a logarithmicspace isomorphism test for the class of chordal clawfree graphs as a further consequence lrec_ captures logarithmic space on this graph class since lrec_ is contained in fixedpoint logic with counting we also obtain that fixedpoint logic with counting captures polynomial time on the class of chordal clawfree graphs
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1,802.10332
Theoretical basis of the diagonal scan method for determining the laser ablation threshold for femtosecond vortex pulses
In femtosecond laser micromachining, the ablation threshold is a key processing parameter that characterises the energy density required to cause ablation. Current techniques for measuring the ablation threshold such as the diameter regression and diagonal scan methods are based on the assumption of a Gaussian spatial profile, however no techniques currently exist for measuring the ablation threshold using a non-Gaussian beam shape. Here we present a formalism of the diagonal scan method for determining the ablation threshold and pulse superposition for femtosecond vortex pulses. To the authors' knowledge this is the first ablation threshold technique developed for pulses with non-Gaussian spatial profiles. Using this method, the ablation threshold can be calculated using measurement of a single feature (the maximum damage radius $\rho_{max}$), which allows investigations of ablation threshold and incubation effects to be carried out quickly and easily. Extending this method to non-Gaussian beams will allow exploration of new avenues of research, enabling characterisation of the ablation threshold and incubation behaviour for a material when ablated with femtosecond vortex pulses.
physics.optics cond-mat.mtrl-sci
in femtosecond laser micromachining the ablation threshold is a key processing parameter that characterises the energy density required to cause ablation current techniques for measuring the ablation threshold such as the diameter regression and diagonal scan methods are based on the assumption of a gaussian spatial profile however no techniques currently exist for measuring the ablation threshold using a nongaussian beam shape here we present a formalism of the diagonal scan method for determining the ablation threshold and pulse superposition for femtosecond vortex pulses to the authors knowledge this is the first ablation threshold technique developed for pulses with nongaussian spatial profiles using this method the ablation threshold can be calculated using measurement of a single feature the maximum damage radius rho_max which allows investigations of ablation threshold and incubation effects to be carried out quickly and easily extending this method to nongaussian beams will allow exploration of new avenues of research enabling characterisation of the ablation threshold and incubation behaviour for a material when ablated with femtosecond vortex pulses
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1,802.10333
Dispersion Properties of Explicit Finite Element Methods for Wave Propagation Modelling on Tetrahedral Meshes
We analyse the dispersion properties of two types of explicit finite element methods for modelling acoustic and elastic wave propagation on tetrahedral meshes, namely mass-lumped finite element methods and symmetric interior penalty discontinuous Galerkin methods, both combined with a suitable Lax--Wendroff time integration scheme. The dispersion properties are obtained semi-analytically using standard Fourier analysis. Based on the dispersion analysis, we give an indication of which method is the most efficient for a given accuracy, how many elements per wavelength are required for a given accuracy, and how sensitive the accuracy of the method is to poorly shaped elements.
math.NA
we analyse the dispersion properties of two types of explicit finite element methods for modelling acoustic and elastic wave propagation on tetrahedral meshes namely masslumped finite element methods and symmetric interior penalty discontinuous galerkin methods both combined with a suitable laxwendroff time integration scheme the dispersion properties are obtained semianalytically using standard fourier analysis based on the dispersion analysis we give an indication of which method is the most efficient for a given accuracy how many elements per wavelength are required for a given accuracy and how sensitive the accuracy of the method is to poorly shaped elements
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1,802.10334
Screened Coulomb Hybrid Density Functional Investigation of Oxygen Point Defects on ZnO Nanowires
In this study, oxygen vacancies and adatoms have been considered on the surface of both hexagonal and triangular ZnO nanowires. Their effect on the electronic structure and optical spectra of the nanowires have been investigated using the exact exchange hybrid density functional theory calculations. A surface oxygen vacancy gives rise to appearance of a band gap state at almost 0.7 eV above the valence band of the both types of the nanowires while an oxygen adatom show bulk-like electronic properties. A shape dependence is also indicated by the calculated physical quantities of oxygen related point defects on ZnO nanowires.
cond-mat.str-el cond-mat.mes-hall
in this study oxygen vacancies and adatoms have been considered on the surface of both hexagonal and triangular zno nanowires their effect on the electronic structure and optical spectra of the nanowires have been investigated using the exact exchange hybrid density functional theory calculations a surface oxygen vacancy gives rise to appearance of a band gap state at almost 07 ev above the valence band of the both types of the nanowires while an oxygen adatom show bulklike electronic properties a shape dependence is also indicated by the calculated physical quantities of oxygen related point defects on zno nanowires
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1,802.10335
Bright electroluminescence from single graphene nanoribbon junctions
Thanks to their highly tunable band gaps, graphene nanoribbons (GNRs) with atomically precise edges are emerging as mechanically and chemically robust candidates for nanoscale light emitting devices of modulable emission color. While their optical properties have been addressed theoretically in depth, only few experimental studies exist, limited to ensemble measurements and without any attempt to integrate them in an electronic-like circuit. Here we report on the electroluminescence of individual GNRs suspended between the tip of a scanning tunneling microscope (STM) and a Au(111) substrate, constituting thus a realistic opto-electronic circuit. Emission spectra of such GNR junctions reveal a bright and narrow band emission of red light, whose energy can be tuned with the bias voltage applied to the junction, but always lying below the gap of infinite GNRs. Comparison with {\it ab initio} calculations indicate that the emission involves electronic states localized at the GNR termini. Our results shed light on unpredicted optical transitions in GNRs and provide a promising route for the realization of bright, robust and controllable graphene-based light emitting devices.
cond-mat.mes-hall cond-mat.mtrl-sci
thanks to their highly tunable band gaps graphene nanoribbons gnrs with atomically precise edges are emerging as mechanically and chemically robust candidates for nanoscale light emitting devices of modulable emission color while their optical properties have been addressed theoretically in depth only few experimental studies exist limited to ensemble measurements and without any attempt to integrate them in an electroniclike circuit here we report on the electroluminescence of individual gnrs suspended between the tip of a scanning tunneling microscope stm and a au111 substrate constituting thus a realistic optoelectronic circuit emission spectra of such gnr junctions reveal a bright and narrow band emission of red light whose energy can be tuned with the bias voltage applied to the junction but always lying below the gap of infinite gnrs comparison with it ab initio calculations indicate that the emission involves electronic states localized at the gnr termini our results shed light on unpredicted optical transitions in gnrs and provide a promising route for the realization of bright robust and controllable graphenebased light emitting devices
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1,802.10336
The Prasad conjectures for $\mathrm{GSp_4}$ and $\mathrm{PGSp_4}$
In this paper, we use the theta correspondence between $\mathrm{GSp_4}$ and $\mathrm{GO(V)}$ to discuss the $\mathrm{GSp_4}$-distinction problems over a quadratic field extension $E/F.$ With a similar strategy, we study the period for the pair $(\mathrm{GSp_4(E)},\mathrm{GSp_{1,1}(F)}),$ where $\mathrm{GSp_{1,1}}$ is the unique inner form of $\mathrm{GSp_4}.$ Then we verify the Prasad conjecture for $\mathrm{PGSp_4(E)}$.
math.RT
in this paper we use the theta correspondence between mathrmgsp_4 and mathrmgov to discuss the mathrmgsp_4distinction problems over a quadratic field extension ef with a similar strategy we study the period for the pair mathrmgsp_4emathrmgsp_11f where mathrmgsp_11 is the unique inner form of mathrmgsp_4 then we verify the prasad conjecture for mathrmpgsp_4e
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1,802.10337
Noetherianity up to conjugation of locally diagonal inverse limits
We prove that the inverse limit of the sequence dual to a sequence of Lie algebras is Noetherian up to the action of the direct limit of the corresponding sequence of classical algebraic groups when the sequence of groups consists of diagonal embeddings. We also classify all conjugation-stable closed subsets of the space of $\mathbb{N}\times\mathbb{N}$ matrices.
math.AG math.RT
we prove that the inverse limit of the sequence dual to a sequence of lie algebras is noetherian up to the action of the direct limit of the corresponding sequence of classical algebraic groups when the sequence of groups consists of diagonal embeddings we also classify all conjugationstable closed subsets of the space of mathbbntimesmathbbn matrices
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1,802.10338
Fair Adaptive Data Rate Allocation and Power Control in LoRaWAN
In this paper, we present results of a study of the data rate fairness among nodes within a LoRaWAN cell. Since LoRa/LoRaWAN supports various data rates, we firstly derive the fairest ratios of deploying each data rate within a cell for a fair collision probability. LoRa/LoRaWAN, like other frequency modulation based radio interfaces, exhibits the \textit{capture effect} in which only the stronger signal of colliding signals will be extracted. This leads to unfairness, where far nodes or nodes experiencing higher attenuation are less likely to see their packets received correctly. Therefore, we secondly develop a transmission power control algorithm to balance the received signal powers from all nodes regardless of their distances from the gateway for a fair data extraction. Simulations show that our approach achieves higher fairness in data rate than the state-of-art in almost all network configurations.
cs.NI
in this paper we present results of a study of the data rate fairness among nodes within a lorawan cell since loralorawan supports various data rates we firstly derive the fairest ratios of deploying each data rate within a cell for a fair collision probability loralorawan like other frequency modulation based radio interfaces exhibits the textitcapture effect in which only the stronger signal of colliding signals will be extracted this leads to unfairness where far nodes or nodes experiencing higher attenuation are less likely to see their packets received correctly therefore we secondly develop a transmission power control algorithm to balance the received signal powers from all nodes regardless of their distances from the gateway for a fair data extraction simulations show that our approach achieves higher fairness in data rate than the stateofart in almost all network configurations
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1,802.10339
On Exact Polya and Putinar's Representations
We consider the problem of finding exact sums of squares (SOS) decompositions for certain classes of non-negative multivariate polynomials, relying on semidefinite programming (SDP) solvers. We start by providing a hybrid numeric-symbolic algorithm computing exact rational SOS decompositions for polynomials lying in the interior of the SOS cone. It computes an approximate SOS decomposition for a perturbation of the input polynomial with an arbitrary-precision SDP solver. An exact SOS decomposition is obtained thanks to the perturbation terms. We prove that bit complexity estimates on output size and runtime are both polynomial in the degree of the input polynomial and simply exponential in the number of variables. Next, we apply this algorithm to compute exact Polya and Putinar's representations respectively for positive definite forms and positive polynomials over basic compact semi-algebraic sets. We also compare the implementation of our algorithms with existing methods in computer algebra including cylindrical algebraic decomposition and critical point method.
cs.SC
we consider the problem of finding exact sums of squares sos decompositions for certain classes of nonnegative multivariate polynomials relying on semidefinite programming sdp solvers we start by providing a hybrid numericsymbolic algorithm computing exact rational sos decompositions for polynomials lying in the interior of the sos cone it computes an approximate sos decomposition for a perturbation of the input polynomial with an arbitraryprecision sdp solver an exact sos decomposition is obtained thanks to the perturbation terms we prove that bit complexity estimates on output size and runtime are both polynomial in the degree of the input polynomial and simply exponential in the number of variables next we apply this algorithm to compute exact polya and putinars representations respectively for positive definite forms and positive polynomials over basic compact semialgebraic sets we also compare the implementation of our algorithms with existing methods in computer algebra including cylindrical algebraic decomposition and critical point method
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1,802.1034
On a singular limit for stratified compressible fluids
We consider a singular limit problem for the complete compressible Euler system in the low Mach and strong stratification regime. We identify the limit problem - the anelastic Euler system - in the case of well prepared initial data. The result holds in the large class of the dissipative measure-valued solutions of the primitive system. Applications are discussed to the driven shallow water equations.
math.AP
we consider a singular limit problem for the complete compressible euler system in the low mach and strong stratification regime we identify the limit problem the anelastic euler system in the case of well prepared initial data the result holds in the large class of the dissipative measurevalued solutions of the primitive system applications are discussed to the driven shallow water equations
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1,802.10341
Discovery of pulsations from NGC 300 ULX1 and its fast period evolution
The supernova impostor SN 2010da located in the nearby galaxy NGC 300, later identified as a likely supergiant B[e] high-mass X-ray binary, was simultaneously observed by NuSTAR and XMM-Newton between 2016 December 16 and 20, over a total time span of 310 ks. We report the discovery of a strong periodic modulation in the X-ray flux with a pulse period of 31.6 s and a very rapid spin-up, and confirm therefore that the compact object is a neutron star. We find that the spin period is changing from 31.71 s to 31.54 s over that period, with a spin-up rate of -5.56 x 10-7 s s-1, likely the largest ever observed from an accreting neutron star. The spectrum is described by a power-law and a disk black-body model, leading to a 0.3-30 keV unabsorbed luminosity of 4.7 x 10^39 erg s-1. Applying our best-fit model successfully to the spectra of an XMM-Newton observation from 2010, suggests that the lower fluxes of NGC 300 ULX1 reported from observations around that time are caused by a large amount of absorption, while the intrinsic luminosity was similar as seen in 2016. A more constant luminosity level is also consistent with the long-term pulse period evolution approaching an equilibrium value asymptotically. We conclude that the source is another candidate for the new class of ultraluminous X-ray pulsars.
astro-ph.HE
the supernova impostor sn 2010da located in the nearby galaxy ngc 300 later identified as a likely supergiant be highmass xray binary was simultaneously observed by nustar and xmmnewton between 2016 december 16 and 20 over a total time span of 310 ks we report the discovery of a strong periodic modulation in the xray flux with a pulse period of 316 s and a very rapid spinup and confirm therefore that the compact object is a neutron star we find that the spin period is changing from 3171 s to 3154 s over that period with a spinup rate of 556 x 107 s s1 likely the largest ever observed from an accreting neutron star the spectrum is described by a powerlaw and a disk blackbody model leading to a 0330 kev unabsorbed luminosity of 47 x 1039 erg s1 applying our bestfit model successfully to the spectra of an xmmnewton observation from 2010 suggests that the lower fluxes of ngc 300 ulx1 reported from observations around that time are caused by a large amount of absorption while the intrinsic luminosity was similar as seen in 2016 a more constant luminosity level is also consistent with the longterm pulse period evolution approaching an equilibrium value asymptotically we conclude that the source is another candidate for the new class of ultraluminous xray pulsars
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1,802.10342
A study of periodic potentials based on quadratic splines
We discuss a method based on a segmentary approximation of solutions of the Schr\"odinger by quadratic splines, for which the coefficients are determined by a variational method that does not require the resolution of complicated algebraic equations. The idea is the application of the method to one dimensional periodic potentials. We include the determination of the eigenvalues up to a given level, and therefore an approximation to the lowest energy bands. We apply the method to concrete examples with interest in physics and discussed the numerical errors.
quant-ph
we discuss a method based on a segmentary approximation of solutions of the schrodinger by quadratic splines for which the coefficients are determined by a variational method that does not require the resolution of complicated algebraic equations the idea is the application of the method to one dimensional periodic potentials we include the determination of the eigenvalues up to a given level and therefore an approximation to the lowest energy bands we apply the method to concrete examples with interest in physics and discussed the numerical errors
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1,802.10343
Detection of ultracold molecules using an optical cavity
We theoretically study non-destructive detection of ultracold molecules, using a Fabry-Perot cavity. Specifically, we consider vacuum Rabi splitting where we demonstrate the use of collective strong coupling for detection of molecules with many participating energy levels. We also consider electromagnetically induced transparency and transient response of light for the molecules interacting with a Fabry-Perot cavity mode, as a mean for non-destructive detection. We identify the parameters that are required for the detection of molecules in the cavity electromagnetically induced transparency configuration. The theoretical analysis for these processes is parametrized with realistic values of both, the molecule and the cavity. For each process, we quantify the state occupancy of the molecules interacting with the cavity and determine to what extent the population does not change during a detection cycle.
quant-ph physics.atom-ph
we theoretically study nondestructive detection of ultracold molecules using a fabryperot cavity specifically we consider vacuum rabi splitting where we demonstrate the use of collective strong coupling for detection of molecules with many participating energy levels we also consider electromagnetically induced transparency and transient response of light for the molecules interacting with a fabryperot cavity mode as a mean for nondestructive detection we identify the parameters that are required for the detection of molecules in the cavity electromagnetically induced transparency configuration the theoretical analysis for these processes is parametrized with realistic values of both the molecule and the cavity for each process we quantify the state occupancy of the molecules interacting with the cavity and determine to what extent the population does not change during a detection cycle
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1,802.10344
Almost Markovian processes from closed dynamics
It is common, when dealing with quantum processes involving a subsystem of a much larger composite closed system, to treat them as effectively memory-less (Markovian). While open systems theory tells us that non-Markovian processes should be the norm, the ubiquity of Markovian processes is undeniable. Here, without resorting to the Born-Markov assumption of weak coupling or making any approximations, we formally prove that processes are close to Markovian ones, when the subsystem is sufficiently small compared to the remainder of the composite, with a probability that tends to unity exponentially in the size of the latter. We also show that, for a fixed global system size, it may not be possible to neglect non-Markovian effects when the process is allowed to continue for long enough. However, detecting non-Markovianity for such processes would usually require non-trivial entangling resources. Our results have foundational importance, as they give birth to almost Markovian processes from composite closed dynamics, and to obtain them we introduce a new notion of equilibration that is far stronger than the conventional one and show that this stronger equilibration is attained.
quant-ph
it is common when dealing with quantum processes involving a subsystem of a much larger composite closed system to treat them as effectively memoryless markovian while open systems theory tells us that nonmarkovian processes should be the norm the ubiquity of markovian processes is undeniable here without resorting to the bornmarkov assumption of weak coupling or making any approximations we formally prove that processes are close to markovian ones when the subsystem is sufficiently small compared to the remainder of the composite with a probability that tends to unity exponentially in the size of the latter we also show that for a fixed global system size it may not be possible to neglect nonmarkovian effects when the process is allowed to continue for long enough however detecting nonmarkovianity for such processes would usually require nontrivial entangling resources our results have foundational importance as they give birth to almost markovian processes from composite closed dynamics and to obtain them we introduce a new notion of equilibration that is far stronger than the conventional one and show that this stronger equilibration is attained
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1,802.10345
Extreme energy density confined inside a transparent crystal: Solid - plasma - solid transformations, status and perspectives
It was demonstrated during the past decade that ultrashort intense laser pulse tightly focused deep inside a transparent dielectric generates the energy density in excess of several MJ/cm3. Such energy concentration with extremely high heating and quenching rates leads to unusual solid-plasma-solid transformation paths overcoming kinetic barriers to formation of previously unknown high-pressure material phases, which are preserved in the surrounding pristine crystal. These results were obtained with the pulse of Gaussian shape in space and in time. Recently it was shown that the Bessel-shaped pulse could transform much larger amount of a material and allegedly create even higher energy density than that was achieved with the Gaussian (GB) pulses. Here we present a succinct review of previous results and discuss the possible routes for achieving higher energy density employing the Bessel beams (BB) and take advantage of its unique properties.
physics.optics cond-mat.other physics.plasm-ph
it was demonstrated during the past decade that ultrashort intense laser pulse tightly focused deep inside a transparent dielectric generates the energy density in excess of several mjcm3 such energy concentration with extremely high heating and quenching rates leads to unusual solidplasmasolid transformation paths overcoming kinetic barriers to formation of previously unknown highpressure material phases which are preserved in the surrounding pristine crystal these results were obtained with the pulse of gaussian shape in space and in time recently it was shown that the besselshaped pulse could transform much larger amount of a material and allegedly create even higher energy density than that was achieved with the gaussian gb pulses here we present a succinct review of previous results and discuss the possible routes for achieving higher energy density employing the bessel beams bb and take advantage of its unique properties
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1,802.10346
A flexible and computationally tractable discrete distribution derived from a stationary renewal process
A class of discrete distributions can be derived from stationary renewal processes. They have the useful property that the mean is a simple function of the model parameters. Thus regressions of the distribution mean on covariates can be carried out and marginal effects of covariates calculated. Probabilities can be easily computed in closed form for only two such distributions, when the event interarrival times in the renewal process follow either a gamma or an inverse Gaussian distribution. The gamma-based distribution has more attractive properties and is described and fitted to data. The inverse-Gaussian based distribution is also briefly discussed.
stat.ME
a class of discrete distributions can be derived from stationary renewal processes they have the useful property that the mean is a simple function of the model parameters thus regressions of the distribution mean on covariates can be carried out and marginal effects of covariates calculated probabilities can be easily computed in closed form for only two such distributions when the event interarrival times in the renewal process follow either a gamma or an inverse gaussian distribution the gammabased distribution has more attractive properties and is described and fitted to data the inversegaussian based distribution is also briefly discussed
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1,802.10347
Decompressing Lempel-Ziv Compressed Text
We consider the problem of decompressing the Lempel--Ziv 77 representation of a string $S$ of length $n$ using a working space as close as possible to the size $z$ of the input. The folklore solution for the problem runs in $O(n)$ time but requires random access to the whole decompressed text. Another folklore solution is to convert LZ77 into a grammar of size $O(z\log(n/z))$ and then stream $S$ in linear time. In this paper, we show that $O(n)$ time and $O(z)$ working space can be achieved for constant-size alphabets. On general alphabets of size $\sigma$, we describe (i) a trade-off achieving $O(n\log^\delta \sigma)$ time and $O(z\log^{1-\delta}\sigma)$ space for any $0\leq \delta\leq 1$, and (ii) a solution achieving $O(n)$ time and $O(z\log\log (n/z))$ space. The latter solution, in particular, dominates both folklore algorithms for the problem. Our solutions can, more generally, extract any specified subsequence of $S$ with little overheads on top of the linear running time and working space. As an immediate corollary, we show that our techniques yield improved results for pattern matching problems on LZ77-compressed text.
cs.DS
we consider the problem of decompressing the lempelziv 77 representation of a string s of length n using a working space as close as possible to the size z of the input the folklore solution for the problem runs in on time but requires random access to the whole decompressed text another folklore solution is to convert lz77 into a grammar of size ozlognz and then stream s in linear time in this paper we show that on time and oz working space can be achieved for constantsize alphabets on general alphabets of size sigma we describe i a tradeoff achieving onlogdelta sigma time and ozlog1deltasigma space for any 0leq deltaleq 1 and ii a solution achieving on time and ozloglog nz space the latter solution in particular dominates both folklore algorithms for the problem our solutions can more generally extract any specified subsequence of s with little overheads on top of the linear running time and working space as an immediate corollary we show that our techniques yield improved results for pattern matching problems on lz77compressed text
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1,802.10348
An Approach to Sparse Continuous-time System Identification from Unevenly Sampled Data
In this work, we address the problem of identifying sparse continuous-time dynamical systems when the spacing between successive samples (the sampling period) is not constant over time. The proposed approach combines the leave-one-sample-out cross-validation error trick from machine learning with an iterative subset growth method to select the subset of basis functions that governs the dynamics of the system. The least-squares solution using only the selected subset of basis functions is then used. The approach is illustrated on two examples: a 6-node feedback ring and the Van der Pol oscillator.
cs.SY math.DS
in this work we address the problem of identifying sparse continuoustime dynamical systems when the spacing between successive samples the sampling period is not constant over time the proposed approach combines the leaveonesampleout crossvalidation error trick from machine learning with an iterative subset growth method to select the subset of basis functions that governs the dynamics of the system the leastsquares solution using only the selected subset of basis functions is then used the approach is illustrated on two examples a 6node feedback ring and the van der pol oscillator
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1,802.10349
Learning to Adapt Structured Output Space for Semantic Segmentation
Convolutional neural network-based approaches for semantic segmentation rely on supervision with pixel-level ground truth, but may not generalize well to unseen image domains. As the labeling process is tedious and labor intensive, developing algorithms that can adapt source ground truth labels to the target domain is of great interest. In this paper, we propose an adversarial learning method for domain adaptation in the context of semantic segmentation. Considering semantic segmentations as structured outputs that contain spatial similarities between the source and target domains, we adopt adversarial learning in the output space. To further enhance the adapted model, we construct a multi-level adversarial network to effectively perform output space domain adaptation at different feature levels. Extensive experiments and ablation study are conducted under various domain adaptation settings, including synthetic-to-real and cross-city scenarios. We show that the proposed method performs favorably against the state-of-the-art methods in terms of accuracy and visual quality.
cs.CV
convolutional neural networkbased approaches for semantic segmentation rely on supervision with pixellevel ground truth but may not generalize well to unseen image domains as the labeling process is tedious and labor intensive developing algorithms that can adapt source ground truth labels to the target domain is of great interest in this paper we propose an adversarial learning method for domain adaptation in the context of semantic segmentation considering semantic segmentations as structured outputs that contain spatial similarities between the source and target domains we adopt adversarial learning in the output space to further enhance the adapted model we construct a multilevel adversarial network to effectively perform output space domain adaptation at different feature levels extensive experiments and ablation study are conducted under various domain adaptation settings including synthetictoreal and crosscity scenarios we show that the proposed method performs favorably against the stateoftheart methods in terms of accuracy and visual quality
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1,802.1035
Spin-dependent magneto-thermopower of narrow-gap lead chalcogenide quantum wells
A semi-classical analysis of magneto-thermopower behaviour, namely, the \textit{Seebeck} and \textit{Nernst} effect (NE) in quantum wells of IV-VI lead salts with significant extrinsic Rashba spin-orbit coupling (RSOC) is performed in this report. In addition to the spin-dependent Seebeck effect that has been observed before, we also theoretically predict a similar spin-delineated behaviour for its thermal analog, the spin-dependent NE. The choice of lead salts follows from a two-fold advantage they offer, in part, to their superior thermoelectric properties, especially PbTe, while their low band gaps and high spin-orbit coupling make them ideal candidates to study \textit{RSOC} in nanostructures. The calculations show a larger longitudinal magneto-thermopower for the spin-up electrons while the transverse components are nearly identical. In contrast, for a magnetic field free case, the related power factor calculations reveal a significantly higher contribution from the spin-down ensemble and suffer a reduction with an increase in the electron density. We also discuss qualitatively the limitations of the semi-classical approach for the extreme case of a high magnetic field and allude to the observed thermopower behaviour when the quantum Hall regime is operational. Finally, techniques to modulate the thermopower are briefly outlined.
cond-mat.mes-hall cond-mat.mtrl-sci
a semiclassical analysis of magnetothermopower behaviour namely the textitseebeck and textitnernst effect ne in quantum wells of ivvi lead salts with significant extrinsic rashba spinorbit coupling rsoc is performed in this report in addition to the spindependent seebeck effect that has been observed before we also theoretically predict a similar spindelineated behaviour for its thermal analog the spindependent ne the choice of lead salts follows from a twofold advantage they offer in part to their superior thermoelectric properties especially pbte while their low band gaps and high spinorbit coupling make them ideal candidates to study textitrsoc in nanostructures the calculations show a larger longitudinal magnetothermopower for the spinup electrons while the transverse components are nearly identical in contrast for a magnetic field free case the related power factor calculations reveal a significantly higher contribution from the spindown ensemble and suffer a reduction with an increase in the electron density we also discuss qualitatively the limitations of the semiclassical approach for the extreme case of a high magnetic field and allude to the observed thermopower behaviour when the quantum hall regime is operational finally techniques to modulate the thermopower are briefly outlined
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1,802.10351
Efficient Black-Box Reductions for Separable Cost Sharing
In cost sharing games with delays, a set of agents jointly allocates a finite subset of resources. Each resource has a fixed cost that has to be shared by the players, and each agent has a nonshareable player-specific delay for each resource. A prominent example is uncapacitated facility location (UFL), where facilities need to be opened (at a shareable cost) and clients want to connect to opened facilities. Each client pays a cost share and his non-shareable physical connection cost. Given any profile of subsets allocated by the agents, a separable cost sharing protocol determines cost shares that satisfy budget balance on every resource and separability over the resources. Moreover, a separable protocol guarantees existence of pure Nash equilibria in the induced strategic game for the agents. In this paper, we study separable cost sharing protocols in several general combinatorial domains. We provide black-box reductions to reduce the design of a separable cost-sharing protocol to the design of an approximation algorithm for the underlying cost minimization problem. In this way, we obtain new separable cost-sharing protocols in games based on arbitrary player-specific matroids, single-source connection games without delays, and connection games on $n$-series-parallel graphs with delays. All these reductions are efficiently computable - given an initial allocation profile, we obtain a cheaper profile and separable cost shares turning the profile into a pure Nash equilibrium. Hence, in these domains any approximation algorithm can be used to obtain a separable cost sharing protocol with a price of stability bounded by the approximation factor.
cs.GT cs.DM cs.DS math.OC
in cost sharing games with delays a set of agents jointly allocates a finite subset of resources each resource has a fixed cost that has to be shared by the players and each agent has a nonshareable playerspecific delay for each resource a prominent example is uncapacitated facility location ufl where facilities need to be opened at a shareable cost and clients want to connect to opened facilities each client pays a cost share and his nonshareable physical connection cost given any profile of subsets allocated by the agents a separable cost sharing protocol determines cost shares that satisfy budget balance on every resource and separability over the resources moreover a separable protocol guarantees existence of pure nash equilibria in the induced strategic game for the agents in this paper we study separable cost sharing protocols in several general combinatorial domains we provide blackbox reductions to reduce the design of a separable costsharing protocol to the design of an approximation algorithm for the underlying cost minimization problem in this way we obtain new separable costsharing protocols in games based on arbitrary playerspecific matroids singlesource connection games without delays and connection games on nseriesparallel graphs with delays all these reductions are efficiently computable given an initial allocation profile we obtain a cheaper profile and separable cost shares turning the profile into a pure nash equilibrium hence in these domains any approximation algorithm can be used to obtain a separable cost sharing protocol with a price of stability bounded by the approximation factor
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1,802.10352
Regression Monte Carlo for Microgrid Management
We study an islanded microgrid system designed to supply a small village with the power produced by photovoltaic panels, wind turbines and a diesel generator. A battery storage system device is used to shift power from times of high renewable production to times of high demand. We introduce a methodology to solve microgrid management problem using different variants of Regression Monte Carlo algorithms and use numerical simulations to infer results about the optimal design of the grid.
math.OC
we study an islanded microgrid system designed to supply a small village with the power produced by photovoltaic panels wind turbines and a diesel generator a battery storage system device is used to shift power from times of high renewable production to times of high demand we introduce a methodology to solve microgrid management problem using different variants of regression monte carlo algorithms and use numerical simulations to infer results about the optimal design of the grid
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1,802.10353
Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and their Interactions
Common-sense physical reasoning is an essential ingredient for any intelligent agent operating in the real-world. For example, it can be used to simulate the environment, or to infer the state of parts of the world that are currently unobserved. In order to match real-world conditions this causal knowledge must be learned without access to supervised data. To address this problem we present a novel method that learns to discover objects and model their physical interactions from raw visual images in a purely \emph{unsupervised} fashion. It incorporates prior knowledge about the compositional nature of human perception to factor interactions between object-pairs and learn efficiently. On videos of bouncing balls we show the superior modelling capabilities of our method compared to other unsupervised neural approaches that do not incorporate such prior knowledge. We demonstrate its ability to handle occlusion and show that it can extrapolate learned knowledge to scenes with different numbers of objects.
cs.LG cs.AI cs.NE
commonsense physical reasoning is an essential ingredient for any intelligent agent operating in the realworld for example it can be used to simulate the environment or to infer the state of parts of the world that are currently unobserved in order to match realworld conditions this causal knowledge must be learned without access to supervised data to address this problem we present a novel method that learns to discover objects and model their physical interactions from raw visual images in a purely emphunsupervised fashion it incorporates prior knowledge about the compositional nature of human perception to factor interactions between objectpairs and learn efficiently on videos of bouncing balls we show the superior modelling capabilities of our method compared to other unsupervised neural approaches that do not incorporate such prior knowledge we demonstrate its ability to handle occlusion and show that it can extrapolate learned knowledge to scenes with different numbers of objects
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1,802.10354
Multiscale relevance and informative encoding in neuronal spike trains
Neuronal responses to complex stimuli and tasks can encompass a wide range of time scales. Understanding these responses requires measures that characterize how the information on these response patterns are represented across multiple temporal resolutions. In this paper we propose a metric -- which we call multiscale relevance (MSR) -- to capture the dynamical variability of the activity of single neurons across different time scales. The MSR is a non-parametric, fully featureless indicator in that it uses only the time stamps of the firing activity without resorting to any a priori covariate or invoking any specific structure in the tuning curve for neural activity. When applied to neural data from the mEC and from the ADn and PoS regions of freely-behaving rodents, we found that neurons having low MSR tend to have low mutual information and low firing sparsity across the correlates that are believed to be encoded by the region of the brain where the recordings were made. In addition, neurons with high MSR contain significant information on spatial navigation and allow to decode spatial position or head direction as efficiently as those neurons whose firing activity has high mutual information with the covariate to be decoded and significantly better than the set of neurons with high local variations in their interspike intervals. Given these results, we propose that the MSR can be used as a measure to rank and select neurons for their information content without the need to appeal to any a priori covariate.
q-bio.NC q-bio.QM
neuronal responses to complex stimuli and tasks can encompass a wide range of time scales understanding these responses requires measures that characterize how the information on these response patterns are represented across multiple temporal resolutions in this paper we propose a metric which we call multiscale relevance msr to capture the dynamical variability of the activity of single neurons across different time scales the msr is a nonparametric fully featureless indicator in that it uses only the time stamps of the firing activity without resorting to any a priori covariate or invoking any specific structure in the tuning curve for neural activity when applied to neural data from the mec and from the adn and pos regions of freelybehaving rodents we found that neurons having low msr tend to have low mutual information and low firing sparsity across the correlates that are believed to be encoded by the region of the brain where the recordings were made in addition neurons with high msr contain significant information on spatial navigation and allow to decode spatial position or head direction as efficiently as those neurons whose firing activity has high mutual information with the covariate to be decoded and significantly better than the set of neurons with high local variations in their interspike intervals given these results we propose that the msr can be used as a measure to rank and select neurons for their information content without the need to appeal to any a priori covariate
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1,802.10355
Improved Upper Bounds on all Maximal $\alpha$-gapped Repeats and Palindromes
We show that the number of all maximal $\alpha$-gapped repeats and palindromes of a word of length $n$ is at most $3(\pi^2/6 + 5/2) \alpha n$ and $7 (\pi^2 / 6 + 1/2) \alpha n - 5 n - 1$, respectively.
cs.FL
we show that the number of all maximal alphagapped repeats and palindromes of a word of length n is at most 3pi26 52 alpha n and 7 pi2 6 12 alpha n 5 n 1 respectively
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1,802.10356
Distinctive Picosecond Spin Polarization Dynamics in Bulk Half-Metals
Femtosecond laser excitations in half-metal (HM) compounds are theoretically predicted to induce an exotic picosecond spin dynamics. In particular, conversely to what is observed in conventional metals and semiconductors, the thermalization process in HMs leads to a long living partially thermalized configuration characterized by three Fermi--Dirac distributions for the minority, majority conduction and majority valence electrons respectively. Remarkably, these distributions have the same temperature but different chemical potentials. This unusual thermodynamics state causes a persistent non-equilibrium spin polarization only well above the Fermi energy. Femtosecond spin dynamics experiments performed on Fe$_3$O$_4$ by time-, spin-, and angle-resolved photoelectron spectroscopy confirm our model. Furthermore, the spin polarization response proves to be very robust and it can be adopted to selectively test the bulk HM character in a wide range of compounds.
cond-mat.mtrl-sci
femtosecond laser excitations in halfmetal hm compounds are theoretically predicted to induce an exotic picosecond spin dynamics in particular conversely to what is observed in conventional metals and semiconductors the thermalization process in hms leads to a long living partially thermalized configuration characterized by three fermidirac distributions for the minority majority conduction and majority valence electrons respectively remarkably these distributions have the same temperature but different chemical potentials this unusual thermodynamics state causes a persistent nonequilibrium spin polarization only well above the fermi energy femtosecond spin dynamics experiments performed on fe_3o_4 by time spin and angleresolved photoelectron spectroscopy confirm our model furthermore the spin polarization response proves to be very robust and it can be adopted to selectively test the bulk hm character in a wide range of compounds
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1,802.10357
Axion-electron coupling from the RGB tip of Globular Clusters
We present a preliminary study of the Globular Cluster RGB devoted to improve the available constraint for the axion-electron coupling. By means of multi-band IR photometry of the cluster M3 we obtain g_{ae}/10^{-13} < 2.57 (95\% C.L.).
astro-ph.SR
we present a preliminary study of the globular cluster rgb devoted to improve the available constraint for the axionelectron coupling by means of multiband ir photometry of the cluster m3 we obtain g_ae1013 257 95 cl
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1,802.10358
Charge Transfer in Classical Molecular Dynamics Simulations of Met-enkephalin: Improving Traditional Force Field with Data Driven Models
The charge transfer and polarization effects are important components in the molecular mechanism description of bio-molecules. Classical force field with fixed point charge cannot take into the account of the non-negligible correlation between atomic charge and structure changes. In this work, high throughput ab initio calculations for the pentapeptide Met-enkephalin (MetEnk) reveal that geometric dependent charge transfer among residues is significant among tens of thousands of conformations. And we suggest a data driven model with machine learning algorithms to solve the geometric dependent charge fluctuations problem. This data driven model can directly provide ab initio level atomic charges of any structure for MetEnk, and avoids self-consistent iteration in polarizable force field. Molecular dynamics simulations demonstrated that the data driven model provides a possible choice to describe the explicit charge flux with minor modification of available classical force fields. This work provides us an alternative molecular mechanism model for future dynamics simulation of oligopeptides.
physics.chem-ph physics.bio-ph
the charge transfer and polarization effects are important components in the molecular mechanism description of biomolecules classical force field with fixed point charge cannot take into the account of the nonnegligible correlation between atomic charge and structure changes in this work high throughput ab initio calculations for the pentapeptide metenkephalin metenk reveal that geometric dependent charge transfer among residues is significant among tens of thousands of conformations and we suggest a data driven model with machine learning algorithms to solve the geometric dependent charge fluctuations problem this data driven model can directly provide ab initio level atomic charges of any structure for metenk and avoids selfconsistent iteration in polarizable force field molecular dynamics simulations demonstrated that the data driven model provides a possible choice to describe the explicit charge flux with minor modification of available classical force fields this work provides us an alternative molecular mechanism model for future dynamics simulation of oligopeptides
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1,802.10359
Sivers effect in Inelastic $J/\psi$ Photoproduction in $ep^\uparrow$ Collision in Color Octet Model
The prediction of single-spin asymmetry in inelastic photoproduction of $J/\psi$ in $ep^\uparrow$ collision is presented. At next-to-leading order, the dominating process is photon-gluon fusion, $\gamma+g\rightarrow J/\psi+g$ for the production of $J/\psi$ in $e+p^\uparrow\rightarrow J/\psi+X$, which directly probes the gluon Sivers function. Using the non-relativistic QCD based color octet model, the color octet states $\leftidx{^{3}}{S}{_1}^{(8)}$, $\leftidx{^{1}}{S}{_0}^{(8)}$ and $\leftidx{^{3}}{P}{_{J(0,1,2)}}^{(8)}$ contribution to $J/\psi$ production is calculated. Sizable asymmetry is estimated as a function of transverse momentum $P_T$ and energy fraction $z$ of $J/\psi$ in the range $0<P_T\leq 1$ GeV and $0.3<z\leq 0.9$. The unpolarized differential cross section of inelastic $J/\psi$ photoproduction is found to be in good agreement with H1 and ZEUS data.
hep-ph hep-ex
the prediction of singlespin asymmetry in inelastic photoproduction of jpsi in epuparrow collision is presented at nexttoleading order the dominating process is photongluon fusion gammagrightarrow jpsig for the production of jpsi in epuparrowrightarrow jpsix which directly probes the gluon sivers function using the nonrelativistic qcd based color octet model the color octet states leftidx3s_18 leftidx1s_08 and leftidx3p_j0128 contribution to jpsi production is calculated sizable asymmetry is estimated as a function of transverse momentum p_t and energy fraction z of jpsi in the range 0p_tleq 1 gev and 03zleq 09 the unpolarized differential cross section of inelastic jpsi photoproduction is found to be in good agreement with h1 and zeus data
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