July 2023 arXiv papers — page 26

Yi-Ting Chuang, Liang-Yan Hsu

The rotating-wave approximation to light-matter interactions is widely used in the quantum electrodynamics Hamiltonian; however, its validity has long been a matter of debate. In this article, we explore the impact of the rotating-wave approximation on the quantum dynamics of multiple molecules in complex dielectric environments within the framework of macro

Meiyun Han, Tianhao Wei, Ying Xia, Austin Morris

Based on the design requirements proposed by the Beijing On-Line Isotope Separation project (BISOL), four Sn$^{22+}$-based,81.25MHz continuous wave (CW) drift tube linac (DTL) cavities have been designed. These DTLs are capable of accelerating Sn$^{22+}$ of 0.1 pmA from 0.5 MeV/u to 1.8 MeV/u over a length of 7 m, with an output longitudinal normalized RMS e

Haitao Nie, Shengbo Zhang, Bin Xie

How to accurately measure the relevance and redundancy of features is an age-old challenge in the field of feature selection. However, existing filter-based feature selection methods cannot directly measure redundancy for continuous data. In addition, most methods rely on manually specifying the number of features, which may introduce errors in the absence o

Kyurae Kim, Yian Ma, Jacob R. Gardner

We prove that black-box variational inference (BBVI) with control variates, particularly the sticking-the-landing (STL) estimator, converges at a geometric (traditionally called "linear") rate under perfect variational family specification. In particular, we prove a quadratic bound on the gradient variance of the STL estimator, one which encompasses misspeci

Guillaume F. Nataf, Hicham Ait Laasri, Damien Brault, Tatiana Chartier

Bismuth vanadate - bismuth molybdate solid-solution was prepared to elaborate ceramics with different amounts of cation vacancies. Dense ceramics with similar microstructures were obtained and the evolution of their melting point, specific heat, thermal diffusivity, and conductivity as a function of the amount of vacancy was evaluated. At room temperature, t

Mi-Ra Hwang, Eylee Jung, Museong Kim, DaeKil Park

We develop the Euclidean time method of the variational quantum eigensolver for solving the generalized eigenvalue equation $A \ket{\phi_n} = \lambda_n B \ket{\phi_n}$, where $A$ and $B$ are hermitian operators, and $\ket{\phi_n}$ and $\lambda_n$ are called the eigenvector and the corresponding eigenvalue of this equation respectively. For the purpose we mod

Shun Shimomura

For the first Painlev\'e transcendents Kitaev established an asymptotic representation in terms of the Weierstrass pe-function in cheese-like strips near the point at infinity. We present an explicit error bound of this asymptotic expression, which leads to the order estimate of exponent $-1$.

Yingbo Zhou, Zhihao Yue, Yutong Ye, Pengyu Zhang

Due to the absence of fine structure and texture information, existing fusion-based few-shot image generation methods suffer from unsatisfactory generation quality and diversity. To address this problem, we propose a novel feature Equalization fusion Generative Adversarial Network (EqGAN) for few-shot image generation. Unlike existing fusion strategies that

Zhifeng Wang, Kaihao Zhang, Wenhan Luo, Ramesh Sankaranarayana

Facial expression is related to facial muscle contractions and different muscle movements correspond to different emotional states. For micro-expression recognition, the muscle movements are usually subtle, which has a negative impact on the performance of current facial emotion recognition algorithms. Most existing methods use self-attention mechanisms to c

D. Basilico, G. Bellini, J. Benziger, R. Biondi

We report the first measurement of CNO solar neutrinos by Borexino that uses the Correlated Integrated Directionality (CID) method, exploiting the sub-dominant Cherenkov light in the liquid scintillator detector. The directional information of the solar origin of the neutrinos is preserved by the fast Cherenkov photons from the neutrino scattered electrons,

Tomoki Ozawa, Tomoya Hayata

We introduce a two-dimensional non-Hermitian lattice model with an imaginary magnetic field and elucidate various unique features which are absent in Hermitian lattice models with real magnetic fields. To describe the imaginary magnetic field, we consider both the Landau gauge and the symmetric gauge, which are related by a generalized gauge transformation,

Razi Mahmood, Diego Machado Reyes, Ge Wang, Mannudeep Kalra

With advances in generative artificial intelligence (AI), it is now possible to produce realistic-looking automated reports for preliminary reads of radiology images. This can expedite clinical workflows, improve accuracy and reduce overall costs. However, it is also well-known that such models often hallucinate, leading to false findings in the generated re

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

Using a data sample of $(10087\pm44)\times 10^6$ $J/\psi$ events collected by the BESIII detector in 2009, 2012, 2018 and 2019, the electromagnetic Dalitz process $J/\psi \to e^+ e^- \eta(1405)$ is observed via the decay $\eta(1405) \to \pi^0 f_0(980)$, $f_0(980) \to \pi^+ \pi^-$, with a significance of about $9.6\sigma$. The branching fraction of this decay

Subha Vadlamannati, Gözde Gül Şahin

In-context learning (ICL) for large language models has proven to be a powerful approach for many natural language processing tasks. However, determining the best method to select examples for ICL is nontrivial as the results can vary greatly depending on the quality, quantity, and order of examples used. In this paper, we conduct a case study on text simpli

Shengjin Huo, Michel Zinsmeister

A Denjoy domain is a plane domain whose complement is a closed subset $E$ of the extended real line $\bar{R}$ containing $\infty$ : such a domain is called Carleson-homogeneous if there exists $C>0$ such that for all $z\in E$ and $r>0$, one has $\vert E\cap [z-r,z+r]\vert\geq Cr$, where $\vert\cdot\vert$ is the Lebesgue measure on the line. We prove that if

Huajian Huang, Yinzhe Xu, Yingshu Chen, Sai-Kit Yeung

360{\deg} images can provide an omnidirectional field of view which is important for stable and long-term scene perception. In this paper, we explore 360{\deg} images for visual object tracking and perceive new challenges caused by large distortion, stitching artifacts, and other unique attributes of 360{\deg} images. To alleviate these problems, we take adv

Lele Liu, Bo Ning

Let $F$ be a graph and $\SPEX (n, F)$ be the class of $n$-vertex graphs which attain the maximum spectral radius and contain no $F$ as a subgraph. Let $\EX (n, F)$ be the family of $n$-vertex graphs which contain maximum number of edges and no $F$ as a subgraph. It is a fundamental problem in spectral extremal graph theory to characterize all graphs $F$ such

Heng Zhang, Danilo Vasconcellos Vargas

Reservoir computing (RC), first applied to temporal signal processing, is a recurrent neural network in which neurons are randomly connected. Once initialized, the connection strengths remain unchanged. Such a simple structure turns RC into a non-linear dynamical system that maps low-dimensional inputs into a high-dimensional space. The model's rich dynamics

Srivas Chennu, Andrew Maher, Christian Pangerl, Subash Prabanantham

AB testing aids business operators with their decision making, and is considered the gold standard method for learning from data to improve digital user experiences. However, there is usually a gap between the requirements of practitioners, and the constraints imposed by the statistical hypothesis testing methodologies commonly used for analysis of AB tests.

Mujahid Rafiq, Ibrar Hussain, Muhammad Arif, Kinza Sardar

Parkinson's is a Neurologic disorder that not only affects the human body but also their social and personal life. Especially children having the Parkinson's disease come up with infinite difficulties in different areas of life mostly in social interaction, communication, connectedness, and other skills such as thinking, reasoning, learning, remembering. Thi

Donggyu Kim, Eun-Gook Moon

Preparation of a target quantum many-body state on quantum simulators is one of the significant steps in quantum science and technology. With a small number of qubits, a few quantum states, such as the Greenberger-Horne-Zeilinger state, have been prepared, but fundamental difficulties in systems with many qubits remain, including the Lieb-Robinson bounds for

Ze Yu Zhao, Yueling Che, Sheng Luo, Kaishun Wu

This paper proposes a new on-demand wireless energy transfer (WET) scheme of multiple unmanned aerial vehicles (UAVs). Unlike the existing studies that simply pursuing the total or the minimum harvested energy maximization at the Internet of Things (IoT) devices, where the IoT devices' own energy requirements are barely considered, we propose a new metric ca

Yun Soo Myung

Stability of Schwarzschild-AdS (SAdS) black hole is investigated in Einstein-Weyl-scalar (EWS) theory with a negative cosmological constant. Here, we introduce a quadratic scalar coupling to the Weyl term, instead of the Gauss-Bonnet term. The linearized EWS theory admits the Lichnerowicz equation for Einstein tensor as well as scalar equation. The linearize

Chengrui Wei, Meng Yang, Lei He, Nanning Zheng

It has long been an ill-posed problem to predict absolute depth maps from single images in real (unseen) indoor scenes. We observe that it is essentially due to not only the scale-ambiguous problem but also the focal-ambiguous problem that decreases the generalization ability of monocular depth estimation. That is, images may be captured by cameras of differ

Sheikh Md Shakeel Hassan, Arthur Feeney, Akash Dhruv, Jihoon Kim

In the field of phase change phenomena, the lack of accessible and diverse datasets suitable for machine learning (ML) training poses a significant challenge. Existing experimental datasets are often restricted, with limited availability and sparse ground truth data, impeding our understanding of this complex multiphysics phenomena. To bridge this gap, we pr

Mario Eudave-Muñoz, Joan Carlos Segura Aguilar

The transient number of a knot K, denoted tr(K), is the minimal number of simple arcs that have to be attached to K, in order that K can be homotoped to a trivial knot in a regular neighborhood of the union of K and the arcs. We give a lower bound for tr(K) in terms of the rank of the first homology group of the double branched cover of K. In particular, if

Yu Chen, Chang-Zhi Lu, Juan Li, Siqi Liu

The study of massive neutrinos and their interactions is a critical aspect of contemporary cosmology. Recent advances in parallel computation and high-performance computing provide new opportunities for accurately constraining Large-Scale Structures (LSS). In this paper, we introduce the TianNu cosmological N-body simulation during the co-evolution of massiv

Chenfeng Xu, Bichen Wu, Ji Hou, Sam Tsai

We present NeRF-Det, a novel method for indoor 3D detection with posed RGB images as input. Unlike existing indoor 3D detection methods that struggle to model scene geometry, our method makes novel use of NeRF in an end-to-end manner to explicitly estimate 3D geometry, thereby improving 3D detection performance. Specifically, to avoid the significant extra l

Adam Block, Ali Jadbabaie, Daniel Pfrommer, Max Simchowitz

We propose a theoretical framework for studying behavior cloning of complex expert demonstrations using generative modeling. Our framework invokes low-level controllers - either learned or implicit in position-command control - to stabilize imitation around expert demonstrations. We show that with (a) a suitable low-level stability guarantee and (b) a powerf

Stefano Borghini, Mattia Fogagnolo

Substatic Riemannian manifolds with minimal boundary arise naturally in General Relativity as spatial slices of static spacetimes satisfying the Null Energy Condition. Moreover, they constitute a vast generalization of nonnegative Ricci curvature. In this paper we will prove various geometric results in this class, culminating in a sharp, weighted Isoperimet

Min Ren, Yunlong Wang, Yuhao Zhu, Kunbo Zhang

Occlusion is a common problem with biometric recognition in the wild. The generalization ability of CNNs greatly decreases due to the adverse effects of various occlusions. To this end, we propose a novel unified framework integrating the merits of both CNNs and graph models to overcome occlusion problems in biometric recognition, called multiscale dynamic g

Changkai Chen, Jiliang Jing

We present a novel method that solves Teukolsky equations with the source to calculate radiation fluxes at infinity and event horizon for any perturbation fields of type-D black holes. For the first time, we use the confluent Heun function to obtain the exact solutions of ingoing and outgoing waves for the Teukolsky equation. This benefits from our derivatio

Sai Wang, Yi Gong

Nonlinear convex problems arise in various areas of applied mathematics and engineering. Classical techniques such as the relaxed proximal point algorithm (PPA) and the prediction correction (PC) method were proposed for linearly constrained convex problems. However, these methods have not been investigated for nonlinear constraints. In this paper, we custom

Nick Brettell

Mayhew and Royle (2008) showed that there are 564 excluded minors for the class of GF(5)-representable matroids having at most 9 elements. We enumerate the excluded minors for GF(5)-representable matroids having 10 elements: there are precisely 2128 such excluded minors. In the process we find, for each $i \in \{2,3,4\}$, the excluded minors for the class of

Yixian Ma, Kun Zhan

Augmentation techniques and sampling strategies are crucial in contrastive learning, but in most existing works, augmentation techniques require careful design, and their sampling strategies can only capture a small amount of intrinsic supervision information. Additionally, the existing methods require complex designs to obtain two different representations

Shuyang Wang, Diego Klabjan

We propose an ensemble method to improve the generalization performance of trading strategies trained by deep reinforcement learning algorithms in a highly stochastic environment of intraday cryptocurrency portfolio trading. We adopt a model selection method that evaluates on multiple validation periods, and propose a novel mixture distribution policy to eff

Jing Wu, Naira Hovakimyan, Jennifer Hobbs

Classifying and segmenting patterns from a limited number of examples is a significant challenge in remote sensing and earth observation due to the difficulty in acquiring accurately labeled data in large quantities. Previous studies have shown that meta-learning, which involves episodic training on query and support sets, is a promising approach. However, t

Moon Ye-Bin, Jisoo Kim, Hongyeob Kim, Kilho Son

We propose TextManiA, a text-driven manifold augmentation method that semantically enriches visual feature spaces, regardless of class distribution. TextManiA augments visual data with intra-class semantic perturbation by exploiting easy-to-understand visually mimetic words, i.e., attributes. This work is built on an interesting hypothesis that general langu

Isaac Pesenson

We consider a disjoint cover (partition) of an undirected weighted finite graph $G$ by $|J|$ connected subgraphs (clusters) $\{S_{j}\}_{j\in J}$ and select a function $\zeta_{j}\geq 0$ on each of the clusters. For a given signal $f$ on $G$ the set of its weighted average values samples is defined via inner products $\{\langle \zeta_{j}, f\rangle\}_{j\in J}$.

Dimitrios Bralios, Efthymios Tzinis, Paris Smaragdis

Recent approaches in source separation leverage semantic information about their input mixtures and constituent sources that when used in conditional separation models can achieve impressive performance. Most approaches along these lines have focused on simple descriptions, which are not always useful for varying types of input mixtures. In this work, we pre

Liu Cao, Zhaoyu Liu, Lyutianyang Zhang

5G New Radio (NR) Sidelink (SL) Mode 2 has enabled decentralized, infrastructure-less direct communications which is evolving to serve reliability-critical services in 6G SL. Particularly, the channel access in NR SL Mode 2 relies on the Sensing-based Semi-Persistent Scheduling (SPS) whose key features significantly influence the packet reception ratio (PRR)

Dong Liu, Yufeng Pei, Limeng Xia, Kaiming Zhao

In this paper, we present a determinant formula for the contravariant form on Verma modules over the N=1 Bondi-Metzner-Sachs (BMS) superalgebra. This formula establishes a necessary and sufficient condition for the irreducibility of the Verma modules. We then introduce and characterize a class of simple smooth modules that generalize both Verma and Whittaker

Takahiro Ohgoe, Hokuto Iwakiri, Masaya Kohda, Kazuhide Ichikawa

Understanding and predicting the properties of solid-state materials from first-principles has been a great challenge for decades. Owing to the recent advances in quantum technologies, quantum computations offer a promising way to achieve this goal. Here, we demonstrate the first-principles calculation of a quasiparticle band structure on actual quantum comp

Mingchen Liu, Lijian Zhang, Haixing Miao

The precision of phase estimation with interferometers can be greatly enhanced using non-classical quantum states, and the SU(11) interferometer is an elegant scheme, which generates two-mode squeezed state internally and also amplifies the signal. It has been shown in [Phys. Rev. A {\bf 95}, 063843 (2017)] that the photon-number measurement can achieve the

Tuo Feng, Wenguan Wang, Xiaohan Wang, Yi Yang

Point cloud analysis (such as 3D segmentation and detection) is a challenging task, because of not only the irregular geometries of many millions of unordered points, but also the great variations caused by depth, viewpoint, occlusion, etc. Current studies put much focus on the adaption of neural networks to the complex geometries of point clouds, but are bl

Arghajit Jana, Hsiang-Kuang Chang

We studied the polarization properties of Cygnus X-1 in both hard and soft spectral states with Imaging X-ray Polarimetry Explorer (IXPE) observations. The polarization degree is $\sim4$%, and $\sim 2.6-2.8$% in the hard and soft states, respectively. The polarization angle is observed along the jet axis and remains the same in both states. Energy-dependent

Bingxue Wang, Liwen Zou, Jun Chen, Yingying Cao

The presence of tertiary lymphoid structures (TLSs) on pancreatic pathological images is an important prognostic indicator of pancreatic tumors. Therefore, TLSs detection on pancreatic pathological images plays a crucial role in diagnosis and treatment for patients with pancreatic tumors. However, fully supervised detection algorithms based on deep learning

Kohki Kawabata, Tatsuma Nishioka, Takuya Okuda

We construct fermionic conformal field theories (CFTs) whose spectra are characterized by quantum stabilizer codes. We exploit our construction to search for fermionic CFTs with supersymmetry by focusing on quantum stabilizer codes of the Calderbank-Shor-Steane type, and derive simple criteria for the theories to be supersymmetric. We provide several example

Md Hasanujjaman

We have used the relativistic second-order causal viscous hydrodynamics equipped with an equation of state which includes the QCD critical point to study the propagation of linear and nonlinear perturbations in quark gluon plasma created in a relativistic heavy-ion collision. We have also studied the behaviour of dynamic structure factor, which is calculated

Sohom Bhattacharya, Nabarun Deb, Sumit Mukherjee

In this paper, we study a class of multilinear Gibbs measures with Hamiltonian given by a generalized $\mathrm{U}$-statistic and with a general base measure. Expressing the asymptotic free energy as an optimization problem over a space of functions, we obtain sufficient conditions for replica-symmetry, and provide examples to show why these conditions are al

Yanan Liu, Daoyi Dong, Sen Kuang, Ian R. Petersen

Quantum entanglement plays a fundamental role in quantum computation and quantum communication. Feedback control has been widely used in stochastic quantum systems to generate given entangled states since it has good robustness, where the time required to compute filter states and conduct filter based control usually cannot be ignored in many practical appli

Ruijia Li, Chang Xu

We apply a three-dimensional (3D) approach to investigate the quasi-stationary states of well-deformed $\alpha$-emitters. With a splitting of the anisotropic 3D potential into internal and external parts at a separation surface, the 3D $\alpha$-cluster decay width is determined by the initial wave function of a true bound state of an anisotropic harmonic osc

Yajun Zhao

This article presents a novel solution for reconfigurable intelligent surfaces (RISs) based on cascaded channel decoupling. The proposed mechanism simplifies the RIS regulation matrix, by decomposing the electromagnetic wave regulation process into two sub-processes: virtual receiving response and virtual regular transmission, which leads to the decoupling o

Shuo Yan

We consider coupled slow-fast stochastic processes, where the averaged slow motion is given by a two-dimensional Hamiltonian system with multiple critical points. On a proper time scale, the evolution of the first integral converges to a diffusion process on the corresponding Reeb graph, with certain gluing conditions specified at the interior vertices, as i

Zezhi Shao, Fei Wang, Tao Sun, Chengqing Yu

Traffic forecasting, which aims to predict traffic conditions based on historical observations, has been an enduring research topic and is widely recognized as an essential component of intelligent transportation. Recent proposals on Spatial-Temporal Graph Neural Networks~(STGNNs) have made significant progress by combining sequential models with graph convo

Dong-min Kim, Jeongmin Nam, Bong Jae Lee

We investigated the thermal conductivity of surface plasmon polaritons (SPPs) propagating along thin Au and Ag films on a SiO$_2$ substrate with a Ti adhesive layer. To determine the propagation length and skin depth of SPPs along Au and Ag thin films, we numerically solved the dispersion relation while considering the size effect of the permittivity of meta

Hua-Li Li, Jing Wang, Li-Ping Xin, Jian-Ying Bai

Stellar white-light flares are believed to play an essential role on the physical and chemical properties of the atmosphere of the surrounding exoplanets. Here we report an optical monitoring campaign on the nearby flaring system EI~Cnc carried out by the Ground-based Wide Angle Cameras (GWAC) and its dedicated follow-up telescope. A superflare, coming from

Pu Sun, Honggang Qi, Yuezun Li, Siwei Lyu

Face-swap DeepFake is an emerging AI-based face forgery technique that can replace the original face in a video with a generated face of the target identity while retaining consistent facial attributes such as expression and orientation. Due to the high privacy of faces, the misuse of this technique can raise severe social concerns, drawing tremendous attent

Qi Meng, Ziyang Lu, Chang Xu

Motivated by recent high-energy electron and $\rm ^3H$ and $\rm ^3He$ nuclei scattering experiment in Jefferson Lab (Nature 609, 41 (2022)), the short-range correlations (SRCs) between nucleon pairs for 3-nucleon systems are microscopically studied using realistic $NN$ 2-body interaction and two-Gaussian type $NNN$ 3-body interaction. The wave functions of b

Junchao Huang, Xiaoqi He Yebo Wu, Sheng Zhao

The purpose of multi-object tracking (MOT) is to continuously track and identify objects detected in videos. Currently, most methods for multi-object tracking model the motion information and combine it with appearance information to determine and track objects. In this paper, unfalsified control is employed to address the ID-switch problem in multi-object t

Samuel E. Begg, Matthew J. Davis, Matthew T. Reeves

We consider the far-from-equilibrium quantum transport dynamics in a 1D Josephson junction chain of multi-mode Bose-Einstein condensates. We develop a theoretical model to examine the experiment of R. Labouvie et al. [Phys. Rev. Lett. 115, 050601 (2015)], wherein the phenomenon of negative differential conductivity (NDC) was reported in the refilling dynamic

Markus Dittmer, Alexander Kappes

In the upcoming IceCube-Gen2 extension, the newly developed optical modules will include 4-inch PMTs. For this purpose, the manufacturers Hamamatsu and North Night Vision Technology have developed new PMT models to meet the requirements of the IceCube-Gen2 science case. The specifications include strict requirements on temporal resolution, detection efficien

Liang Xu, Mingxiao Chen, Yi Cheng, Pengfei Shao

The UNet architecture, based on Convolutional Neural Networks (CNN), has demonstrated its remarkable performance in medical image analysis. However, it faces challenges in capturing long-range dependencies due to the limited receptive fields and inherent bias of convolutional operations. Recently, numerous transformer-based techniques have been incorporated

Yuchi Qiu, Guo-Wei Wei

Protein engineering is an emerging field in biotechnology that has the potential to revolutionize various areas, such as antibody design, drug discovery, food security, ecology, and more. However, the mutational space involved is too vast to be handled through experimental means alone. Leveraging accumulative protein databases, machine learning (ML) models,

Chong Wang, Yuangang Xie, Junwei Ma, Guangwei Hu

Stacking bilayer structures is an efficient way to tune the topology of polaritons in in-plane anisotropic films, e.g., by leveraging the twist angle (TA). However, the effect of another geometric parameter, film thickness ratio (TR), on manipulating the plasmon topology in bilayers is elusive. Here, we fabricate bilayer structures of WTe2 films, which natur

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

Using $e^+e^-$ collision data with an integrated luminosity of $7.33~\mathrm{fb}^{-1}$ collected at center-of-mass energies between 4.128 and 4.226 GeV with the BESIII detector operating at the BEPCII collider, the branching fraction of the leptonic decay $D_s^+\to\mu^+\nu_\mu$ is measured to be $(0.5294\pm0.0108_{\rm stat}\pm0.0085_{\rm syst})$\%. Based on

Leyan Nian, Haoying Sun, Zhichao Wang, Duo Xu

Freestanding perovskite oxide membranes have drawn great attention recently since they offer exceptional structural tunability and stacking ability, providing new opportunities in fundamental research and potential device applications in silicon-based semiconductor technology. Among different types of sacrificial layers, the $ \mathrm{(Ca, Sr, Ba)}_{3}\mathr

Yanan Liu, Daoyi Dong, Ian R. Petersen, Hidehiro Yonezaw

Optical Parametric Oscillators (OPOs) have wide applications in quantum optics for generating squeezed states and developing advanced technologies. When the phase or/and the amplitude of the pumping field for an OPO have fluctuations due to fault signals, time-varying uncertainties will be introduced in the dynamic parameters of the system. In this paper, we

John F. Sevic, Nobuhiko P. Kobayashi

A phase field method self-consistently coupled to continuum heat transport and charge conservation is used to simulate conducting filament dynamical evolution and nanostructure of electroformed resistive switching thin films. Our method does not require a pre-defined idealized conducting filament, as previous methods do, instead treating its dynamical evolut

Florian Kowarsch, Lisa Weijler, FLorian Kleber, Matthias Wödlinger

Explainability for Deep Learning Models is especially important for clinical applications, where decisions of automated systems have far-reaching consequences. While various post-hoc explainable methods, such as attention visualization and saliency maps, already exist for common data modalities, including natural language and images, little work has been don

Hanjaya Mandala, Guilherme Christmann

Navigation in the real-world is hard and filled with complex scenarios. The Benchmark Autonomous Robot Navigation (BARN) Challenge is a competition that focuses on highly constrained spaces. Teams compete using a standard platform in a simulation and a real-world stage, with scenarios ranging from easy to challenging. This technical report presents the syste

Hyoung Suk Park, Kiwan Jeon, Jin Keun Seo

This study introduces a novel reconstruction method for dental cone-beam computed tomography (CBCT), focusing on effectively reducing metal-induced artifacts commonly encountered in the presence of prevalent metallic implants. Despite significant progress in metal artifact reduction techniques, challenges persist owing to the intricate physical interactions

Yuxiang Guo, Siyuan Huang, Ram Prabhakar, Chun Pong Lau

Gait recognition holds the promise of robustly identifying subjects based on walking patterns instead of appearance information. While previous approaches have performed well for curated indoor data, they tend to underperform in unconstrained situations, e.g. in outdoor, long distance scenes, etc. We propose a framework, termed GAit DEtection and Recognition

Jiadu Xie, Yang Wang, Hui Kang, Jinsong Cheng

Ultrahigh quality factor (Q) microcavities have been emerging as an appealing compact photonic platform for various applications. The Q factor plays a critical role in determining the nonlinear optical performance of a microcavity. However, a silica microcavity suffers from severe degradation of its Q value over time during storage or use in air due to the a

Sourav Chowdhury, Suparna Roychowdhury, Indranath Chaudhuri

Between the years 2020 to 2022, the world was hit by the pandemic of COVID-19 giving rise to an extremely grave situation. The global economy was badly hurt due to the consequences of various intervention strategies (like social distancing, lockdown) which were applied by different countries to control this pandemic. There are multiple speculations that huma

Rongqin Liang, Yuanman Li, Yingxin Yi, Jiantao Zhou

Identifying traffic accidents in driving videos is crucial to ensuring the safety of autonomous driving and driver assistance systems. To address the potential danger caused by the long-tailed distribution of driving events, existing traffic accident detection (TAD) methods mainly rely on unsupervised learning. However, TAD is still challenging due to the ra

Darsh Kachhara, John K. E Markin, Astha Singh

Earnings announcements (EADs) are corporate events that provide investors with fundamentally important information. The prospect of stock price rises may also contribute to EADs increased volatility. Using data on extremely short term options, we study that bimodality in the risk neutral distribution and concavity in the IV smiles are ubiquitous characterist

Justine Fasquel, Shigenori Nakatsuka

We study the representation theory of the subregular W-algebra $\mathcal{W}^k(\mathfrak{so}_{2n+1},f_{sub})$ of type B and the principal W-superalgebra $\mathcal{W}^\ell(\mathfrak{osp}_{2|2n})$, which are related by an orthosymplectic analogue of Feigin-Semikhatov duality in type A. We establish a block-wise equivalence of weight modules over the W-superalge

Naihuan Jing, Yinlong Liu, Jian Zhang

The classical Capelli identity is an important determinantal identity of a matrix with noncommutative entries that determines the center of the enveloping algebra of the general linear Lie algebra, and was used by Weyl as a main tool to study irreducible representations in his famous book on classical groups. In 1996 Okounkov found higher Capelli identities

Yuqi Tang, Zhijie Dong, Nanchao Wang, Angela del Aguila

Photoacoustic computed tomography (PACT) is a proven technology for imaging hemodynamics in deep brain of small animal models. PACT is inherently compatible with ultrasound (US) imaging, providing complementary contrast mechanisms. While PACT can quantify the brain's oxygen saturation of hemoglobin (sO$_2$), US imaging can probe the blood flow based on the D

Akshay Gopalkrishnan, Ross Greer, Maitrayee Keskar, Mohan Trivedi

Vehicle light detection, association, and localization are required for important downstream safe autonomous driving tasks, such as predicting a vehicle's light state to determine if the vehicle is making a lane change or turning. Currently, many vehicle light detectors use single-stage detectors which predict bounding boxes to identify a vehicle light, in a

Sandika Biswas, Kejie Li, Biplab Banerjee, Subhasis Chaudhuri

Holistic 3D human-scene reconstruction is a crucial and emerging research area in robot perception. A key challenge in holistic 3D human-scene reconstruction is to generate a physically plausible 3D scene from a single monocular RGB image. The existing research mainly proposes optimization-based approaches for reconstructing the scene from a sequence of RGB

Aurélien Vattré

Interfaces such as grain boundaries in polycrystalline as well as heterointerfaces in multiphase solids are ubiquitous in materials science and engineering. Far from being featureless dividing surfaces between neighboring crystals, elucidating features of solid-solid interfaces is challenging and requires theoretical and numerical strategies to describe the

Brian Angulo, Gregory Gorbov, Aleksandr Panov, Konstantin Yakovlev

While reinforcement learning algorithms have had great success in the field of autonomous navigation, they cannot be straightforwardly applied to the real autonomous systems without considering the safety constraints. The later are crucial to avoid unsafe behaviors of the autonomous vehicle on the road. To highlight the importance of these constraints, in th

Berit Schlüter, Willem Achtermann, Martin Antonio Unland Elorrieta

Photomultiplier tubes (PMTs) are a central component of neutrino telescopes such as IceCube and KM3NeT, and an accurate understanding and measurement of their properties is indispensable for improvements of these experiments. In this contribution we focus on a detailed investigation of the photocathode and the dynode system and their influence on the perform

Yanan Liu, William J. Munro, Jason Twamley

Self-sustained oscillators (SSOs) is a commonly used method to generate classical clock signals and SSOs using delayed feedback have been developed commercially which possess ultra-low phase noise and drift. Research into the development of quantum self-oscillation, where one can also have a periodic and regular output {\em tick}, that can be used to control

Daniel J. Katz, Miriam E. Ramirez

Various problems in engineering and natural science demand binary sequences that do not resemble translates of themselves, that is, the sequences must have small aperiodic autocorrelation at every nonzero shift. If $f$ is a sequence, then the demerit factor of $f$ is the sum of the squared magnitudes of the autocorrelations at all nonzero shifts for the sequ

Peng Li, Yeye He, Cong Yan, Yue Wang

Relational tables, where each row corresponds to an entity and each column corresponds to an attribute, have been the standard for tables in relational databases. However, such a standard cannot be taken for granted when dealing with tables "in the wild". Our survey of real spreadsheet-tables and web-tables shows that over 30% of such tables do not conform t

Kevin J. McGown, Amanda Tucker

We prove that the number of quartic fields $K$ with discriminant $|\Delta_K|\leq X$ whose Galois closure is $D_4$ equals $CX+O(X^{5/8+\varepsilon})$, improving the error term in a well-known result of Cohen, Diaz y Diaz, and Olivier. We prove an analogous result for counting quartic dihedral extensions over an arbitrary base field.

K. Ueda, S. Fujiyama, R. Kato

We found a plateau in the magnitude of the isolated magnetic moments as a function of the anisotropy of the transfer integral (t'/t) in the gapless quantum spin liquid (QSL) phase of an S=1/2 triangular lattice molecular solid X[Pd(dmit)2]2 (dmit = 1,3-dithiole-2-thione-4,5-dithiolate), accomplished by a fine-tuning of t'/t through the mixing of cations, X.

Jongwon Park, Massimo Ricotti, Kazuyuki Sugimura

Outward migration of massive binary stars or black holes in their circumbinary disc is often observed in simulations and it is key to the formation of wide black hole binaries. Using numerical simulations of Population III (Pop III) star formation, we study the angular momentum of Pop III binaries and the torques between stars and gas discs to understand the

Huijie Qiao

This work concerns about multiscale multivalued McKean-Vlasov stochastic systems. First of all, we use a contractive mapping principle to establish the well-posedness for fully coupled multivalued McKean-Vlasov stochastic systems under non-Lipschitz conditions. Then for multiscale multivalued McKean-Vlasov stochastic systems with small noises, we prove a lar

Carlos Daniel Tamayo Castro, Juan Bory Reyes

We use a high-dimensional version of the Marcinkiewicz exponent, a metric characteristic for non-rectifiable plane curves, to present a direct application to the solution of some kind of Riemann boundary value problems on fractal domains of Euclidean space $\mathbb{R}^{n+1}, n\geq2$ for Clifford algebra-valued polymonogenic functions with boundary data in cl

William Luszczak

Past results from the IceCube Collaboration have suggested that the blazar TXS 0506+056 is a potential source of astrophysical neutrinos. However, in the years since there have been numerous updates to event processing and reconstruction, as well as improvements to the statistical methods used to search for astrophysical neutrino sources. These improvements

Peixin Tian

This paper reveal the selective rotation in the CNNs' forward processing. It elucidates the activation function as a discerning mechanism that unifies and quantizes the rotational aspects of the input data. Experiments show how this defined methodology reflects the progress network distinguish inputs based on statistical indicators, which can be comprehended

Stephan Bröker, Michael te Vrugt, Julian Jeggle, Joakim Stenhammar

The pair-distribution function, which provides information about correlations in a system of interacting particles, is one of the key objects of theoretical soft matter physics. In particular, it allows for microscopic insights into the phase behavior of active particles. While this function is by now well studied for two-dimensional active matter systems, t

Mengyuan Li, Haoran Geng, Michael Niemier, Xiaobo Sharon Hu

Lattice-based cryptographic algorithms built on ring learning with error theory are gaining importance due to their potential for providing post-quantum security. However, these algorithms involve complex polynomial operations, such as polynomial modular multiplication (PMM), which is the most time-consuming part of these algorithms. Accelerating PMM is cruc

Martin Sablotny, Bjørn Sand Jensen, Jeremy Singer

Generation-based fuzz testing can uncover various bugs and security vulnerabilities. However, compared to mutation-based fuzz testing, it takes much longer to develop a well-balanced generator that produces good test cases and decides where to break the underlying structure to exercise new code paths. We propose a novel approach to combine a trained test cas

Jai-chan Hwang, Hyerim Noh

In curved spacetime, Maxwell's equations can be expressed in forms valid in Minkowski background, with the effect of the metric (gravity) appearing as effective polarizations and magnetizations. The electric and magnetic (EM) fields depend on the observer's frame four-vector. We derive Maxwell's equations valid in general curved spacetime using the fields de

Sarath Raman Nair, Shilu Tian, Gavin K. Brennen, Sougato Bose

Macroscopic quantum superpositions of massive objects are deeply interesting as they have a number of potential applications ranging from the exploration of the interaction of gravity with quantum mechanics to quantum sensing, quantum simulation, and computation. In this letter, we propose two related schemes to prepare a spatial superposition of massive qua