November 2022 arXiv papers — page 162

Thomas Vigouroux, Cristian Ene, David Monniaux, Laurent Mounier

Max#SAT is an important problem with multiple applications in security and program synthesis that is proven hard to solve. It is defined as: given a parameterized quantifier-free propositional formula compute parameters such that the number of models of the formula is maximal. As an extension, the formula can include an existential prefix. We propose a CEGAR

Piotr Morawiecki, Philippe H. Trinh

The objective of this three-part work is to formulate and rigorously analyse a number of reduced mathematical models that are nevertheless capable of describing the hydrology at the scale of a river basin (i.e. catchment). Coupled surface and subsurface flows are considered. In this third part, we focus on the development of analytical solutions and scaling

Rao Ma, Xiaobo Wu, Jin Qiu, Yanan Qin

ASR model deployment environment is ever-changing, and the incoming speech can be switched across different domains during a session. This brings a challenge for effective domain adaptation when only target domain text data is available, and our objective is to obtain obviously improved performance on the target domain while the performance on the general do

Wei Song, Yanghao Yue, Ya-jie Zhang, Zhengchen Zhang

Disentanglement of a speaker's timbre and style is very important for style transfer in multi-speaker multi-style text-to-speech (TTS) scenarios. With the disentanglement of timbres and styles, TTS systems could synthesize expressive speech for a given speaker with any style which has been seen in the training corpus. However, there are still some shortc

Yoshikazu Suzumura, Masao Ogata

The Seebeck coefficient, which is proportional to a ratio of the thermoelectric conductivity to electrical conductivity has been examined for Dirac electrons in the organic conductor $\alpha$-(BEDT-TTF)$_2$I$_3$ [BEDT-TTF denotes a molecule given by bis(ethylenedithio)tetrathiafulvalene] under a uniaxial pressure using a two-dimensional tight-binding model w

Patrick Gérard, Alexander Pushnitski, Sergei Treil

We consider an inverse spectral problem for a class of non-compact Hankel operators $H$ such that the modulus of $H$ (restricted onto the orthogonal complement to its kernel) has simple spectrum. Similarly to the case of compact operators, we prove a uniqueness result, i.e. we prove that a Hankel operator from our class is uniquely determined by the spectral

Piotr Morawiecki, Philippe H. Trinh

The objective of this three-part work is to formulate and rigorously analyse a number of reduced mathematical models that are nevertheless capable of describing the hydrology at the scale of a river basin (i.e. catchment). Coupled surface and subsurface flows are considered. In this first part, we identify and analyse the key physical parameters that appear

Xiangqing Kong, Zhiqiang Zhang, Liu Zhao

The thermodynamics of charged spherically symmetric AdS black holes in conformal gravity is revisited using the recently proposed restricted phase space (RPS) formalism. This formalism avoids all the bizarreness that arose in the extended phase space formalism for this model. It is found that the charged AdS black holes in this model may belong to a new univ

Masahito Hayashi

We propose a new concept, oblivious quantum computation, which requires performing oblivious transfer with respect to the computation outcome of the quantum computation, where the secrecy of the input qubits and the program to identify the quantum gates are required. Exploiting quantum teleportation, we propose a two-server protocol for this task, which real

G. Cacciapaglia, A. Deandrea, A. M. Iyer, A. Pinto

New Physics models with either an elementary or composite origin are often associated with a similar imprint in a direct search at colliders, case in point being the production of a light pseudoscalar in association with a monochromatic photon from the decay of a Z boson at future $e+e-$ colliders. We exploit the correlation between the discovery of a signal

Marcin Sroka

We provide the sharp $C^0$ estimate for the quaternionic Monge-Ampere equation on any hyperhermitian manifold. This improves previously known results concerning this estimate in two directions. Namely, it turns out that the estimate depends only on $L^p$ norm of the right hand side for any $p>2$ (as suggested by the local case studied in [Sr20a]). Moreover,

Yuto Watanabe, Hiroto Arima, Hidetomo Usui, Yoshikazu Mizuguchi

We investigated the structural, electronic, and superconducting properties of Co1-xNixZr2, in which c-axis thermal expansion is systematically controlled. At x (smaller than) 0.3, c-axis negative thermal expansion (NTE) was observed, and the thermal expansion constant {\alpha}c approached zero with increasing x. At x = 0.4-0.6, zero thermal expansion was obs

Hridyesh Tewani, Megan Hinaus, Mayukh Talukdar, Hiroki Sone

Polymer syntactic foams are transforming materials that will shape the future of next-generation aerospace and marine structures. When manufactured using traditional processes, like compression molding, syntactic foams consist of a solid continuous polymer matrix reinforced with stiff hollow particles. However, polymer matrix segregation can be achieved duri

Kan Jiang

In this paper, we prove some new thickness theorems with partial derivatives. We give some applications. First, we give a simple criterion that can judge whether two scaled Cantor sets have non-empty intersection. Second, we prove under some checkable conditions that the continuous image of arbitrary self-similar sets with positive similarity ratios is a clo

Erin Carson, Jörg Liesen, Zdeněk Strakoš

When the CG method for solving linear algebraic systems was formulated about 70 years ago by Lanczos, Hestenes, and Stiefel, it was considered an iterative process possessing a mathematical finite termination property. CG was placed into a rich mathematical context, including links with Gauss quadrature and continued fractions. The optimality property of CG

Sonali Pradhan, Pratik P. Deshmukh, Rahul C. Kambale, Tulshidas C. Darvade

The existence of magnetostriction in bulk BiFeO3 is still a matter of investigation and it is also an issue to investigate the magnetostriction effect in nano BiFeO3. Present work demonstrates the existence of magnetostrictive strain in superparamagnetic BiFeO3 nanoparticles at room temperature and the magnetoelectric coupling properties in composite form wi

Yusuke Nakayama

In this paper, we study arithmetically Cohen--Macaulay (ACM) bundles on homogeneous varieties $G/P$. Indeed we characterize the homogeneous ACM bundles on $G/P$ of Picard rank one in terms of highest weights. This is a generalization of the result on $G/P$ of classical types presented by Costa and Miró-Roig for type $A$, and Du, Fang, and Ren for types $B,C$

Ruochen Xiao, Qiaochu Feng, Ruxin Deng

Models trained under assumptions in the complete market usually don't take effect in the incomplete market. This paper solves the hedging problem in incomplete market with three sources of incompleteness: risk factor, illiquidity, and discrete transaction dates. A new jump-diffusion model is proposed to describe stochastic asset prices. Three neutral network

Evgenii Ievlev, Michael R. R. Good

Classical radiation from a single relativistically accelerating electron is investigated where the temperature characterizing the system highlights the dependence on acceleration. In the context of the dynamic Casimir effect with Planck-distributed photons and thermal black hole evaporation, we demonstrate analytic consistency between the ideas of constant a

Xinkuang Wang, Wenjing Li, Zhongcheng Wu

Automatic car damage detection has attracted significant attention in the car insurance business. However, due to the lack of high-quality and publicly available datasets, we can hardly learn a feasible model for car damage detection. To this end, we contribute with Car Damage Detection (CarDD), the first public large-scale dataset designed for vision-based

Alec Wright, Vesa Välimäki, Lauri Juvela

We propose an audio effects processing framework that learns to emulate a target electric guitar tone from a recording. We train a deep neural network using an adversarial approach, with the goal of transforming the timbre of a guitar, into the timbre of another guitar after audio effects processing has been applied, for example, by a guitar amplifier. The m

Surajit Kalita, Amanda Weltman

Since the unexpected discovery of fast radio bursts (FRBs), researchers have proposed varied theories and models to explain these phenomena. One such model that has recently been developed incorporates the so-called Gertsenshtein-Zel'dovich (GZ) effect, which states that when gravitational waves traverse a pulsar magnetosphere, a portion of the gravitational

A. M. Ondieki, Z. Birech, K. A. Kaduki, P. W. Mwangi

This research describes the use of surface-enhanced Raman spectroscopy (SERS) substrates based on colloidal silver nanoparticles (AgNPs) produced by laser ablation of silver granules in pure water that are inexpensive, easy to make, and chemically stable. Here, the effects of the laser power, pulse repetition frequency, and ablation duration on the Surface P

Erik J. Amézquita, Farzana Nasrin, Kathleen M. Storey, Masato Yoshizawa

Mapper, a topological algorithm, is frequently used as an exploratory tool to build a graphical representation of data. This representation can help to gain a better understanding of the intrinsic shape of high-dimensional genomic data and to retain information that may be lost using standard dimension-reduction algorithms. We propose a novel workflow to pro

Daniela Guericke, Amos Schledorn, Henrik Madsen

District heating is an important component in the EU strategy to reach the set emission goals, since it allows an efficient supply of heat while using the advantages of sector coupling between different energy carriers such as power, heat, gas and biomass. Most district heating systems use several different types of units to produce heat for hundreds or thou

Suncheng Xiang, Hao Chen, Wei Ran, Zefang Yu

Person re-identification plays a significant role in realistic scenarios due to its various applications in public security and video surveillance. Recently, leveraging the supervised or semi-unsupervised learning paradigms, which benefits from the large-scale datasets and strong computing performance, has achieved a competitive performance on a specific tar

Hao Ma, Zhiqing Wei, Zening Li, Fan Ning

The increasing complexity of urban environments introduces additional uncertainty to the deployment of the autonomous vehicular network. A novel road infrastructure cooperative detection model using Joint Communication and Sensing (JCS) technology is proposed in this article to simultaneously achieve high-efficient communication and obstacle detection for ur

Omar Mustafa

We explicitly study and report the effects of the gravitational fields on the spectroscopic structure of Klein-Gordon (KG) particles in Som-Raychaudhuri cosmic string spacetime with space-like dislocation and a non-uniform magnetic field. We extend this study to include the effects of the gravitational fields on some position-dependent mass (PDM) KG-particle

J. K. Jang, Sukyoug K. Yi, Yohan Dubois, Jinsu Rhee

Based on the recent advancements in the numerical simulations of galaxy formation, we anticipate the achievement of realistic models of galaxies in the near future. Morphology is the most basic and fundamental property of galaxies, yet observations and simulations still use different methods to determine galaxy morphology, making it difficult to compare them

N. Mowlavi, B. Holl, I. Lecœur-Taïbi, F. Barblan

We present the first Gaia catalogue of eclipsing binary candidates released in Gaia DR3, describe its content, provide tips for its usage, estimate its quality, and show illustrative samples. The catalogue contains 2,184,477 sources with G magnitudes up to 20 mag. Candidate selection is based on the results of variable object classification performed within

Savya Khosla, Chew Kin Whye, Jordan T. Ash, Cyril Zhang

Models that can actively seek out the best quality training data hold the promise of more accurate, adaptable, and efficient machine learning. Active learning techniques often tend to prefer examples that are the most difficult to classify. While this works well on homogeneous datasets, we find that it can lead to catastrophic failures when performed on mult

Olga I. Vinogradova, Elena F. Silkina, Evgeny S. Asmolov

The theory of electrokinetic ion transport in cylindrical channels of a fixed surface charge density is revisited. Attention is focused on impact of the hydrophobic slippage and mobility of adsorbed surface charges. We formulate generalised Onsager relations for a cylinder of an arbitrary radius and then derive exact expressions for the mean electro-osmotic

Meng Chen, Zhi Jiang

For all nonsingular projective $n$-folds $V$ of general type, we prove the existence of Noether type inequalities in the following form: $$\text{vol}(V)\geq a_{n,k}h^0(\Omega_V^k)-b_{n,k}$$ where $0< k\leq n$, $a_{n,k}$ and $b_{n,k}$ are positive constants only depending on $n$ and $k$. As applications, we prove the minimal volume conjecture for $3$-folds of

Neeraj Kumar, Soham Sen, Sunandan Gangopadhyay

In this paper, we have studied the thermodynamics of Gauss-Bonnet black holes in D-dimensional $AdS$ spacetime. Here, the cosmological constant ($\Lambda$), Newton's gravitational constant ($G$) and the Gauss-Bonnet parameter ($\alpha$) are varied in the bulk, and a mixed first law is rewritten considering central charge ($C$) (of dual boundary conformal the

Se Jin Park, Minsu Kim, Joanna Hong, Jeongsoo Choi

The challenge of talking face generation from speech lies in aligning two different modal information, audio and video, such that the mouth region corresponds to input audio. Previous methods either exploit audio-visual representation learning or leverage intermediate structural information such as landmarks and 3D models. However, they struggle to synthesiz

Yassine El Kheir, Shammur Absar Chowdhury, Ahmed Ali, Hamdy Mubarak

The lack of labeled second language (L2) speech data is a major challenge in designing mispronunciation detection models. We introduce SpeechBlender - a fine-grained data augmentation pipeline for generating mispronunciation errors to overcome such data scarcity. The SpeechBlender utilizes varieties of masks to target different regions of phonetic units, and

Tianqi Zhang, Tong Shen, Kai Yuan, Kaiwen Xue

Implementing fully automatic unmanned surface vehicles (USVs) monitoring water quality is challenging since effectively collecting environmental data while keeping the platform stable and environmental-friendly is hard to approach. To address this problem, we construct a USV that can automatically navigate an efficient path to sample water quality parameters

Shujian Zhang, Chengyue Gong, Xingchao Liu

Retriever-reader models achieve competitive performance across many different NLP tasks such as open question answering and dialogue conversations. In this work, we notice these models easily overfit the top-rank retrieval passages and standard training fails to reason over the entire retrieval passages. We introduce a learnable passage mask mechanism which

Yuxiang Liu, Ligong Wang

Let $\rho(G)$ be the spectral radius of a graph $G$ with $m$ edges. Let $S_{m-k+1}^{k}$ be the graph obtained from $K_{1,m-k}$ by adding $k$ disjoint edges within its independent set. Nosal's theorem states that if $\rho(G)>\sqrt{m}$, then $G$ contains a triangle. Zhai and Shu showed that any non-bipartite graph $G$ with $m\geq26$ and $\rho(G)\geq\rho(S_{m}^

Tianjiao Hua, Peng Luo

In this paper, we study the global solvability of multidimensional forward-backward stochastic differential equations (FBSDEs) with diagonally Lipschitz, quadratic or super-quadratic generators. Under a certain "monotonicity" condition, we provide a unified approach which shows that there exists a decoupling field that is uniformly Lipschitz in its spatial v

Huan Qing, Jingli Wang

Modeling and estimating mixed memberships for overlapping unipartite un-weighted networks has been well studied in recent years. However, to our knowledge, there is no model for a more general case, the overlapping bipartite weighted networks. To close this gap, we introduce a novel model, the Bipartite Mixed Membership Distribution-Free (BiMMDF) model. Our

Li-Hang Ren, Yun-Hao Shi, Jin-Jun Chen, Heng Fan

We present the generalized state-dependent entropic uncertainty relations in multiple measurements setting, and the optimal lower bound is obtained by considering different measurement sequences. We then apply this uncertainty relation to witness entanglement, and give the experimentally accessible lower bounds on both bipartite and tripartite entanglements.

Geoffroy Horel, Manuel Krannich, Alexander Kupers

We record two facts on spaces of derived maps between the operads $E_d$ of little $d$-cubes. Firstly, these mapping spaces are equivalent to the mapping spaces between the non-unitary versions of $E_d$. Secondly, all endomorphisms of $E_d$ are automorphisms. We also discuss variants for localisations of $E_d$ and for versions with tangential structures.

Unmesh Ghorai, Ayan Ghosh, Anindya Das, Rajdeep Sensarma

Twisted double bilayer graphene is a compensated semi-metal near the charge neutrality point with the presence of small electron and hole pockets in its band structure. We show that strong Coulomb attraction between the electrons and holes can lead to the formation of indirect excitons. Condensation of these excitons at low temperature creates an excitonic m

Chengyi Li, Bo-Qiang Ma

We show that the space-time foam model from string/D-brane theory predicts a scenario in which neutrinos can possess linearly energy dependent speed variation, together with an asymmetry between neutrinos and antineutrinos, indicating the possibility of Lorentz and CPT symmetry violation for neutrinos. Such scenario is supported by a phenomenological conject

Hao Dang, Yuekai Zhang, Xingqun Qi, Wanting Zhou

In recent years, deep convolution neural networks (DCNNs) have achieved great prospects in coronary artery vessel segmentation. However, it is difficult to deploy complicated models in clinical scenarios since high-performance approaches have excessive parameters and high computation costs. To tackle this problem, we propose \textbf{LightVessel}, a Similarit

Duc Le, Frank Seide, Yuhao Wang, Yang Li

We show how factoring the RNN-T's output distribution can significantly reduce the computation cost and power consumption for on-device ASR inference with no loss in accuracy. With the rise in popularity of neural-transducer type models like the RNN-T for on-device ASR, optimizing RNN-T's runtime efficiency is of great interest. While previous work has prima

Jongho Choi, Kyogu Lee

Piano covers of pop music are enjoyed by many people. However, the task of automatically generating piano covers of pop music is still understudied. This is partly due to the lack of synchronized {Pop, Piano Cover} data pairs, which made it challenging to apply the latest data-intensive deep learning-based methods. To leverage the power of the data-driven ap

Huan Qing

Over the past decade, community detection in overlapping un-weighted networks, where nodes can belong to multiple communities, has been one of the most popular topics in modern network science. However, community detection in overlapping weighted networks, where edge weights can be any real value, remains challenging. In this article, we propose a generative

Haoze He, Parijat Dube

SOTA decentralized SGD algorithms can overcome the bandwidth bottleneck at the parameter server by using communication collectives like Ring All-Reduce for synchronization. While the parameter updates in distributed SGD may happen asynchronously there is still a synchronization barrier to make sure that the local training epoch at every learner is complete b

Carlo Rovelli

The notions of cause and effect are widely employed in science. I discuss why and how they are rooted into thermodynamics. The entropy gradient (i) explains in which sense interventions affect the future rather than the past, and (ii) underpins the time orientation of the subject of knowledge as a physical system. Via these two distinct paths, it is this gra

Jhih-Cing Huang, Yu-Lin Tsai, Chao-Han Huck Yang, Cheng-Fang Su

Recently, quantum classifiers have been found to be vulnerable to adversarial attacks, in which quantum classifiers are deceived by imperceptible noises, leading to misclassification. In this paper, we propose the first theoretical study demonstrating that adding quantum random rotation noise can improve robustness in quantum classifiers against adversarial

Davin Jeong, Allison Gunby-Mann, Sarel Cohen, Maximilian Katzmann

One of the most fundamental graph problems is finding a shortest path from a source to a target node. While in its basic forms the problem has been studied extensively and efficient algorithms are known, it becomes significantly harder as soon as parts of the graph are susceptible to failure. Although one can recompute a shortest replacement path after every

Shun Shimomura

For a general solution of the third Painlev\'e equation of complete type we show the Boutroux ansatz near the point at infinity. It admits an asymptotic representation in terms of the Jacobi sn-function in cheese-like strips along generic directions. The expression is derived by using isomonodromy deformation of a linear system governed by the third Painlev\

Rohun Agrawal, Oscar Leong

Phase retrieval is the nonlinear inverse problem of recovering a true signal from its Fourier magnitude measurements. It arises in many applications such as astronomical imaging, X-Ray crystallography, microscopy, and more. The problem is highly ill-posed due to the phase-induced ambiguities and the large number of possible images that can fit to the given m

Colm P Kelleher, Yash Rana, Daniel J Needleman

During eukaryotic cell division, a microtubule-based structure called the spindle exerts forces on chromosomes, thereby organizing and segregating them Extensive work demonstrates that the forces acting parallel to the spindle axis, including those responsible for separating sister chromatids, are generated by microtubule polymerization and depolymerization,

Chee Wei Tan, Pei-Duo Yu, Siya Chen, H. Vincent Poor

Digital contact tracing aims to curb epidemics by identifying and mitigating public health emergencies through technology. Backward contact tracing, which tracks the sources of infection, proved crucial in places like Japan for identifying COVID-19 infections from superspreading events. This paper presents a novel perspective of digital contact tracing as on

Haris Aziz, Jeremy Lindsay, Angus Ritossa, Mashbat Suzuki

We consider the problem of fair allocation of indivisible chores under additive valuations. We assume that the chores are divided into two types and under this scenario, we present several results. Our first result is a new characterization of Pareto optimal allocations in our setting, and a polynomial-time algorithm to compute an envy-free up to one item (E

Jin Woo Lee, Kyogu Lee

We present a neural network for rendering binaural speech from given monaural audio, position, and orientation of the source. Most of the previous works have focused on synthesizing binaural speeches by conditioning the positions and orientations in the feature space of convolutional neural networks. These synthesis approaches are powerful in estimating the

Yoshiharu Kawamura, Eiji Kodaira, Kentaro Kojima, Toshifumi Yamashita

We study the existence of diagonal representatives in each equivalence class of representation matrices of boundary conditions in $SU(n)$ or $U(n)$ gauge theories compactified on the orbifolds $T^2/{\mathbb Z}_N$ ($N = 2, 3, 4, 6$). We suppose that the theory has a global $G' = U(n)$ symmetry. Using constraints, unitary transformations and gauge transformati

Benjamin Beach, Robert Burlacu, Andreas Bärmann, Lukas Hager

We study mixed-integer programming (MIP) relaxation techniques for the solution of non convex mixed-integer quadratically constrained quadratic programs (MIQCQPs). We present MIP relaxation methods for non convex continuous variable products. In Part I, we consider MIP relaxations based on separable reformulation. The main focus is the introduction of the en

Qing Yao, Shaodong Ma, Jing Liang, Kim Christensen

The Chinese venture capital (VC) market is a young and rapidly expanding financial subsector. Gaining a deeper understanding of the investment behaviours of VC firms is crucial for the development of a more sustainable and healthier market and economy. Contrasting evidence supports that either specialisation or diversification helps to achieve a better inves

Jinxiang Lai, Siqian Yang, Wenlong Liu, Yi Zeng

Few-Shot Learning (FSL) alleviates the data shortage challenge via embedding discriminative target-aware features among plenty seen (base) and few unseen (novel) labeled samples. Most feature embedding modules in recent FSL methods are specially designed for corresponding learning tasks (e.g., classification, segmentation, and object detection), which limits

Vianey Palacios Ramirez, Miguel de Carvalho, Luis Gutierrez Inostroza

Heavy tails are often found in practice, and yet they are an Achilles heel of a variety of mainstream random probability measures such as the Dirichlet process (DP). The first contribution of this paper focuses on characterizing the tails of the so-called normalized generalized gamma (NGG) process. We show that the right tail of an NGG process is heavy-taile

Hongyu Zang, Xin Li, Jie Yu, Chen Liu

Offline reinforcement learning (RL) struggles in environments with rich and noisy inputs, where the agent only has access to a fixed dataset without environment interactions. Past works have proposed common workarounds based on the pre-training of state representations, followed by policy training. In this work, we introduce a simple, yet effective approach

Skip Garibaldi

We fill in the details in a procedure outlined by Serre for drawing pictures of compact real Lie groups. In the case of Sp($2n$), the picture generated by the method is connected with abelian varieties over a number field or a finite field. We follow the procedure to produce pictures for the three simply connected simple groups of rank 2. The pictures for tw

Takuya Kurihana, James Franke, Ian Foster, Ziwei Wang

Clouds play a critical role in the Earth&#39;s energy budget and their potential changes are one of the largest uncertainties in future climate projections. However, the use of satellite observations to understand cloud feedbacks in a warming climate has been hampered by the simplicity of existing cloud classification schemes, which are based on single-pixel

Huan Zheng, Zhao Zhang, Jicong Fan, Richang Hong

Low-light stereo image enhancement (LLSIE) is a relatively new task to enhance the quality of visually unpleasant stereo images captured in dark condition. However, current methods achieve inferior performance on detail recovery and illumination adjustment. We find it is because: 1) the insufficient single-scale inter-view interaction makes the cross-view cu

Jingshi Cui, Peibiao Zhao

In the present paper, we first establish and verify a new sharp hyperbolic version of the Michael-Simon inequality for mean curvatures in hyperbolic space $\mathbb{H}^{n+1}$ based on the locally constrained inverse curvature flow introduced by Brendle, Guan and Li, provided that $M$ is $h$-convex and $f$ is a positive smooth function, where $\lambda^{'}(r)=\

Dan Berrebbi, Ronan Collobert, Navdeep Jaitly, Tatiana Likhomanenko

Self-training (ST) and self-supervised learning (SSL) methods have demonstrated strong improvements in automatic speech recognition (ASR). In spite of these advances, to the best of our knowledge, there is no analysis of how the composition of the labelled and unlabelled datasets used in these methods affects the results. In this work we aim to analyse the e

Dianming Hou, Lili Ju, Zhonghua Qiao

In this paper, we propose and analyze a linear second-order numerical method for solving the Allen-Cahn equation with a general mobility. The proposed fully-discrete scheme is carefully constructed based on the combination of first and second-order backward differentiation formulas with nonuniform time steps for temporal approximation and the central finite

Elisabete da Cunha

The Atacama Large Millimetre/Sub-millimetre Array (ALMA) is obtaining the deepest observations of early galaxies ever achieved at (sub-)millimetre wavelengths, and detecting the dust emission of young galaxies in the first billion years of cosmic history, well in the epoch of reionization. Here I review some of the latest results from these observations, wit

Yanxin Long, Jianhua Han, Runhui Huang, Xu Hang

Inspired by the success of vision-language methods (VLMs) in zero-shot classification, recent works attempt to extend this line of work into object detection by leveraging the localization ability of pre-trained VLMs and generating pseudo labels for unseen classes in a self-training manner. However, since the current VLMs are usually pre-trained with alignin

Jianwu Fang, Chen Zhu, Pu Zhang, Hongkai Yu

Heterogeneous trajectory forecasting is critical for intelligent transportation systems, but it is challenging because of the difficulty of modeling the complex interaction relations among the heterogeneous road agents as well as their agent-environment constraints. In this work, we propose a risk and scene graph learning method for trajectory forecasting of

Xudong Wang, Yao Chen

Expanding medium is very common in many different fields, such as biology and cosmology. It brings a nonnegligible influence on particle's diffusion, which is quite different from the effect of an external force field. The dynamic mechanism of particle's motion in expanding medium has only been investigated in the framework of continuous-time random walk. To

Zhite Yu, Kirtimaan A. Mohan, C. -P. Yuan

Determining the $CP$ property of the Higgs boson is important for a precision test of the Standard Model as well as for the search for new physics. We propose a novel jet substructure observable based on the azimuthal anisotropy in a linearly polarized gluon jet that is produced in association with a Higgs boson at hadron colliders, and demonstrate that it p

Jiayu Lou, Ligong Wang, Ming Yuan

For any real $\alpha \in [0,1]$, Nikiforov defined the $A_\alpha$-matrix of a graph $G$ as $A_\alpha(G)=\alpha D(G)+(1-\alpha)A(G)$, where $A(G)$ and $D(G)$ are the adjacency matrix and the diagonal matrix of vertex degrees of $G$, respectively. The largest eigenvalue of $A_\alpha(G)$ is called the $\alpha$-index or the $A_\alpha$-spectral radius of $G$. A g

Wuhong Zhang, Diefei Xu, Lixiang Chen

Spontaneous parametric down-conversion (SPDC) is a reliable platform for entanglement generation. Routinely, a coherent laser beam is an essential prerequisite for pumping the nonlinear crystal. Here we break this barrier to generate polarization entangled photon pairs by using a commercial light-emitting diode (LED) source to serve as the pump beam. This ef

Matt Visser

In 1898 Charles Jean de la Valle Poussin, as part of his famed proof of the prime number theorem, developed an ineffective bound on the first Chebyshev function of the form: \[ |\theta(x)-x| = \mathcal{O}\left(x \exp(-K \sqrt{\ln x})\right). \] This bound holds for $x$ sufficiently large, $x\geq x_0$, and $K$ some unspecified positive constant. To the best o

Haoze He, Parijat Dube

The convergence of SGD based distributed training algorithms is tied to the data distribution across workers. Standard partitioning techniques try to achieve equal-sized partitions with per-class population distribution in proportion to the total dataset. Partitions having the same overall population size or even the same number of samples per class may stil

Joseph John, Josh Milthorpe, Peter Strazdins

The task-based dataflow programming model has emerged as an alternative to the process-centric programming model for extreme-scale applications. However, load balancing is still a challenge in task-based dataflow runtimes. In this paper, we present extensions to the PaR-SEC runtime to demonstrate that distributed work stealing is an effective load-balancing

Wenhui Chen, Ryo Ikehata

In this paper, we consider the linearized compressible Navier-Stokes equations in the whole space $\mathbb{R}^n$. Concerning initial datum with suitable regularities, we introduce a new threshold $|\mathbb{B}_0|=0$ to distinguish different large-time behaviors. Particularly in the lower-dimensions, optimal growth estimates ($n=1$ polynomial growth, $n=2$ log

Michael Molloy, Erlang Surya, Lutz Warnke

The degree-restricted random process is a natural algorithmic model for generating graphs with degree sequence D_n=(d_1, \ldots, d_n): starting with an empty n-vertex graph, it sequentially adds new random edges so that the degree of each vertex v_i remains at most d_i. Wormald conjectured in 1999 that, for d-regular degree sequences D_n, the final graph of

Fei Wang, Henry Wolkowicz

In this paper, we study the facial structure of the linear image of a cone. We define the singularity degree of a face of a cone to be the minimum number of steps it takes to expose it using exposing vectors from the dual cone. We show that the singularity degree of the linear image of a cone is exactly the number of facial reduction steps to obtain the mini

Yanchao Zhang, Shuang Wang

Based on a quantum thermodynamic protocol for shortcut to isothermality that smoothly modify the system-reservoir interaction can significantly speed up an isothermal process while keeping the overall dissipation constant [Phys. Rev. X. 10, 031015 (2020)], we extend the study of optimization performance of Carnot-like heat engines and refrigerators in a stra

Jian-Zheng Li, Wen-Lei Zhao, Jie Liu

We numerically investigate the quantum transport in a coupled kicked rotors with the $\mathcal{PT}$-symmetric potential. We find that the spontaneous $\mathcal{PT}$-symmetry breaking of wavefunctions emerges when the amplitude of the imaginary part of the complex potential is beyond a threshold value, which can be modulated by the coupling strength effective

Shantanu Mandal, Todd A. Anderson, Javier Turek, Justin Gottschlich

Automatic software generation based on some specification is known as program synthesis. Most existing approaches formulate program synthesis as a search problem with discrete parameters. In this paper, we present a novel formulation of program synthesis as a continuous optimization problem and use a state-of-the-art evolutionary approach, known as Covarianc

Yan Yin, Qihua Gong, Min Yi, Wanlin Guo

The discovery of two-dimensional (2D) layered MoSi$_2$N$_4$ and WSi$_2$N$_4$ without knowing their 3D parents by chemical vapor deposition in 2020 has stimulated extensive studies of 2D MA$_2$Z$_4$ system due to its structural complexity and diversity as well as versatile and intriguing properties. Here, a comprehensive overview on the state-of-the-art progr

Li Xiang, He Miao, Luo Haibo, Yang Huiyuan

Among current anchor-based detectors, a positive anchor box will be intuitively assigned to the object that overlaps it the most. The assigned label to each anchor will directly determine the optimization direction of the corresponding prediction box, including the direction of box regression and category prediction. In our practice of crowded object detecti

Xing Chen, Jie Wang, Xiao-Lei Zhang, Wei-Qiang Zhang

Although the security of automatic speaker verification (ASV) is seriously threatened by recently emerged adversarial attacks, there have been some countermeasures to alleviate the threat. However, many defense approaches not only require the prior knowledge of the attackers but also possess weak interpretability. To address this issue, in this paper, we pro

Shijie Bao, Qi'an Guan, Zheng Yuan

In this article, we present characterizations of the concavity property of minimal $L^2$ integrals degenerating to linearity in the case of fibrations over products of open Riemann surfaces. As applications, we obtain characterizations of the holding of equality in optimal jets $L^2$ extension problem from fibers over products of analytic subsets to fibratio

Min Yi, Wenxuan Wang, Ming Xue, Qihua Gong

Sintering, as a thermal process at elevated temperature below the melting point, is widely used to bond contacting particles into engineering products such as ceramics, metals, polymers, and cemented carbides. Modelling and simulation as important complement to experiments are essential for understanding the sintering mechanisms and for the optimization and

Sergio González, Wan-Ting Hsieh, Davide Burba, Trista Pei-Chun Chen

Survival modeling in healthcare relies on explainable statistical models; yet, their underlying assumptions are often simplistic and, thus, unrealistic. Machine learning models can estimate more complex relationships and lead to more accurate predictions, but are non-interpretable. This study shows it is possible to estimate hospitalization for congestive he

Qi'an Guan, Zheng Yuan

In this article, we present characterizations of the concavity property of minimal $L^2$ integrals degenerating to linearity in the case of products of analytic subsets on products of open Riemann surfaces. As applications, we obtain characterizations of the holding of equality in optimal jets $L^2$ extension problem from products of analytic subsets to prod

Qi'an Guan, Zheng Yuan

In this article, we present a characterization of the concavity property of minimal $L^2$ integrals degenerating to linearity in the case of finite points on open Riemann surfaces. As an application, we give a characterization of the holding of equality in optimal jets $L^2$ extension problem from analytic subsets to open Riemann surfaces, which is a weighte

Mingdai Yang, Zhiwei Liu, Liangwei Yang, Xiaolong Liu

Due to the proliferation of social media, a growing number of users search for and join group activities in their daily life. This develops a need for the study on the ranking-based group identification (RGI) task, i.e., recommending groups to users. The major challenge in this task is how to effectively and efficiently leverage both the item interaction and

Yihong Dong, Xue Jiang, Yuchen Liu, Ge Li

In the process of code generation, it is essential to guarantee the generated code satisfies grammar constraints of programming language (PL). However, neglecting grammar constraints is a fatal drawback of commonly used sequence-based code generation. In this paper, we devise a pushdown automaton (PDA)-based methodology to address this problem, exploiting th

N. A. Lemos, D. Müller, M. J. Reboucas

In general relativity, cosmology and quantum field theory, spacetime is assumed to be an orientable manifold endowed with a Lorentz metric that makes it spatially and temporally orientable. The question as to whether the laws of physics require these orientability assumptions is ultimately of observational or experimental nature, or the answer might come fro

Zhengyang Chen, Bing Han, Xu Xiang, Houjun Huang

Many speaker recognition challenges have been held to assess the speaker verification system in the wild and probe the performance limit. Voxceleb Speaker Recognition Challenge (VoxSRC), based on the voxceleb, is the most popular. Besides, another challenge called CN-Celeb Speaker Recognition Challenge (CNSRC) is also held this year, which is based on the Ch

Yang Liu, Songtai Lv, Yang Yang, Haiyuan Zou

Concepts of the complex partition functions and the Fisher zeros provide intrinsic statistical mechanisms for finite temperature and real time dynamical phase transitions. We extend the utility of these complexifications to quantum phase transitions. We exactly identify different Fisher zeros on lines or closed curves and elucidate their correspondence with