April 2023 arXiv papers — page 17

Seyyed Sadegh Gholami, Yousef Zamani

Let $V$ be an $n$-dimensional inner product space. Assume $G$ is a subgroup of the symmetric group of degree $m$, and $\lambda$ is an irreducible character of $G$. Consider the \emph{Cartesian symmetrizer} $C_{\lambda}$ on the Cartesian space $\times^{m}V$ defined by \[ C_{\lambda} = \frac{\lambda(1)}{|G|}\sum_{\tau\in G} \lambda(\tau) Q(\tau). \] The vector

Kia Kirstein Hansen, Rob van der Goot

The Wall Street Journal section of the Penn Treebank has been the de-facto standard for evaluating POS taggers for a long time, and accuracies over 97\% have been reported. However, less is known about out-of-domain tagger performance, especially with fine-grained label sets. Using data from Elder Scrolls Fandom, a wiki about the \textit{Elder Scrolls} video

Yusuke Nagata, Brian Kenji Iwana, Seiichi Uchida

In documents and graphics, contours are a popular format to describe specific shapes. For example, in the True Type Font (TTF) file format, contours describe vector outlines of typeface shapes. Each contour is often defined as a sequence of points. In this paper, we tackle the contour completion task. In this task, the input is a contour sequence with missin

Taiwo Adetiloye, Anjali Awasthi

The logistics of urban areas are becoming more sophisticated due to the fast city population growth. The stakeholders are faced with the challenges of the dynamic complexity of city logistics(CL) systems characterized by the uncertainty effect together with the freight vehicle emissions causing pollution. In this conceptual paper, we present a research metho

Jiechong Song, Chong Mou, Shiqi Wang, Siwei Ma

By integrating certain optimization solvers with deep neural networks, deep unfolding network (DUN) with good interpretability and high performance has attracted growing attention in compressive sensing (CS). However, existing DUNs often improve the visual quality at the price of a large number of parameters and have the problem of feature information loss d

Khaled Alanezi, Nuha Albadi, Omar Hammad, Maram Kurdi

Online reviews have become essential for users to make informed decisions in everyday tasks ranging from planning summer vacations to purchasing groceries and making financial investments. A key problem in using online reviews is the overabundance of online that overwhelms the users. As a result, recommendation systems for providing helpfulness of reviews ar

Ziyi Xu, Xue Cheng

In an extended Kyle's model, the interactions between a large informed trader and a high-frequency trader (HFT) who can anticipate the former's incoming order are studied. We find that, in equilibrium, HFT may play the role of Small-IT or Round-Tripper: both of them trade in the same direction as IT in advance, but when IT's order arrives, Small-IT continues

Ilan Doron-Arad, Ariel Kulik, Hadas Shachnai

We study the budgeted laminar matroid independent set problem. The input is a ground set, where each element has a cost and a non-negative profit, along with a laminar matroid over the elements and a budget. The goal is to select a maximum profit independent set of the matroid whose total cost is bounded by the budget. Several well known special cases, where

P. Mohanty, N. Sharma, D. Singh, Y. Breard

Geometrically frustrated structures combined with competing exchange interactions that have different magnitudes are known ingredients for achieving exotic properties. Herein, we studied detailed structural, magnetic, thermal (specific heat), magneto-dielectric, and magnetic exchange bias properties of a mixed 3d - 4d spinel oxide with composition CoFeRhO$_4

K. Suchorab, M. Gaweda, L. Kurpaska

This work describes Raman imaging and its data evaluation methods by using the softwares original features: built-in fitting function and K-means cluster analysis KMC followed by fitting in an external environment. For the first time, these methods were compared in terms of their principles, limitations, versatility, and process duration. The performed analy

Tatsuya Hosoi, Hidetaka Sakai

The sixth Painlev\'e equation is a basic equation among the non-linear differential equations with three fixed singularities, corresponding to Gauss's hypergeometric differential equation among the linear differential equations. It is known that 2nd order Fuchsian differential equations with three singular points are reduced to the hypergeometric differentia

Binbin Xiang, Yuanwen Yue, Torben Peters, Konrad Schindler

3D point cloud panoptic segmentation is the combined task to (i) assign each point to a semantic class and (ii) separate the points in each class into object instances. Recently there has been an increased interest in such comprehensive 3D scene understanding, building on the rapid advances of semantic segmentation due to the advent of deep 3D neural network

Zhen Feng, Yuchao Feng, Yanning Guo, Yuxiang Sun

Segmentation of drivable roads and negative obstacles is critical to the safe driving of autonomous vehicles. Currently, many multi-modal fusion methods have been proposed to improve segmentation accuracy, such as fusing RGB and depth images. However, we find that when fusing two modals of data with untrustworthy features, the performance of multi-modal netw

Mastane Achab, Reda Alami, Yasser Abdelaziz Dahou Djilali, Kirill Fedyanin

Reinforcement learning (RL) allows an agent interacting sequentially with an environment to maximize its long-term expected return. In the distributional RL (DistrRL) paradigm, the agent goes beyond the limit of the expected value, to capture the underlying probability distribution of the return across all time steps. The set of DistrRL algorithms has led to

Masato Kobayashi

Ramanujan (1916) expressed quotients of certain q-series as polynomials of Eisenstein series of degree 2, 4, 6 and derived the famous Ramanujan's differential equations. We continue this research with the variants of Eisenstein-type series which Hahn (2007) recently introduced. We also prove new formulas of convolution sums for divisor sum functions as subse

Xiao Jiang, Lei Kang, Jianfeng Wang, Bing Huang

Realization of giant and continuously tunable second-order photocurrent is desired for many nonlinear optical (NLO) and optoelectronic applications, which remains to be a great challenge. Here, based on a simple two-band model, we propose a concept of bulk electro-photovoltaic effect, that is, an out-of-plane external electric-field ($E_{ext}$) can continuou

Rui Dai, Yonggang Zhang, Zhen Fang, Bo Han

Domain generalization (DG) aims to tackle the distribution shift between training domains and unknown target domains. Generating new domains is one of the most effective approaches, yet its performance gain depends on the distribution discrepancy between the generated and target domains. Distributionally robust optimization is promising to tackle distributio

Di Wu, Xi Zhang

In this paper, we investigate the noncompact prescribed Chern scalar curvature problem which reduces to solve a Kazdan-Warner type equation on noncompact non-K\"{a}hler manifolds. By introducing an analytic condition on noncompact manifolds, we establish related existence results. As its another application, we further give a new proof of a classical multipl

Hao Feng, Yuting Xu, Yuping Zhao

In reconfigurable intelligent surface (RIS)-assisted wireless communication systems, adjusting the phase shift of RIS unit cells is crucial for improving communication performance. Due to massive RIS unit cells, the number of phase shift parameters fed back from the base station (BS) to the RIS is enormous, which occupies a large number of frequency resource

Mingzhe Hu, Yuheng Li, Xiaofeng Yang

Skin cancer is a prevalent and potentially fatal disease that requires accurate and efficient diagnosis and treatment. Although manual tracing is the current standard in clinics, automated tools are desired to reduce human labor and improve accuracy. However, developing such tools is challenging due to the highly variable appearance of skin cancers and compl

Haochuan Li, Alexander Rakhlin, Ali Jadbabaie

In this paper, we provide a rigorous proof of convergence of the Adaptive Moment Estimate (Adam) algorithm for a wide class of optimization objectives. Despite the popularity and efficiency of the Adam algorithm in training deep neural networks, its theoretical properties are not yet fully understood, and existing convergence proofs require unrealistically s

Cody J. Balos

Multi-physics simulation often involve multiple different scales. The ARKODE ODE solver package in the SUNDIALS library addresses multi-scale problems with a multi-rate time-integrator that can work with a right-hand side that has fast scale and slow scale components. In this report, we use dynamic mode decomposition and time delay embedding to extract the f

Hironori Yamaguchi, Hiroki Takahashi, Takashi Kawakami, Kiyomi Okamoto

We present an organic compound exhibiting a spin-Peierls (SP) transition to an effective spin-1 antiferromagnetic uniform chain, that is, the Haldane chain. The clear disappearance of magnetization, accompanied by a structural phase transition, is well explained by the deformation to an effective spin-1 Haldane chain. The flexibility of the molecular orbital

Krishanu Das Baksi, Vatsala Pokhrel, Kuntal Kumar Bhusan, Sharmila Mande

The community of different types of microbes present in a biological niche plays a very important role in functioning of the system. The crosstalk or interactions among the different microbes contributes to the building blocks of such microbial community structures. Evidence reported in biomedical text serves as a reliable source for predicting such interact

Jie Lu, Guo-Liang Yu, Zhi-Gang Wang

In this work, the strong coupling constants of the vertices $DDJ/\psi$, $DD^{*}J/\psi$, $D^{*}D^{*}J/\psi$, $DD^{*}\eta_{c}$ and $D^{*}D^{*}\eta_{c}$ are calculated within the framework of the QCD sum rules. For each vertex, we analyze the momentum dependence of the coupling constants by considering all possible off-shell cases. In these analyses, we conside

Arindam Ghosh, Sarit Maitra

This paper is aimed to study the KP-BBM equation, which was proposed by Abdul Majid Wazwaz in 2005. To check its integrability Painleve test has been performed. Lie Symmetry analysis has been done and point symmetry generators are obtained. The invariants of the Lie algebra are found and the one-dimensional optimal system for subalgebras of the obtained Lie

A. Kh. Bikulov, A. P. Zubarev

Logarithmic oscillations superimposed on a power-law trend appear in the behavior of various complex hierarchical systems. In this paper, we study the logarithmic oscillations of relaxation curves in p-adic diffusion models that are used to describe the conformational dynamics of protein. We consider the case of a purely p-adic diffusion, as well as the case

Zijun Gao, Kai Liao, Lilan Yang, Zong-Hong Zhu

The joint detection of GW signals by a network of instruments will increase the detecting ability of faint and far GW signals with higher signal-to-noise ratios (SNRs), which could improve the ability of detecting the lensed GWs as well, especially for the 3rd generation detectors, e.g. Einstein Telescope (ET) and Cosmic Explorer (CE). However, identifying S

Min Cai, Changpin Li, Yu Wang

In this article, two kinds of numerical algorithms are derived for the ultra-slow (or superslow) diffusion equation in one and two space dimensions, where the ultra-slow diffusion is characterized by the Caputo-Hadamard fractional derivative of order $\alpha \in (0,1)$. To describe the spatial interaction, the Riesz fractional derivative and the fractional L

Matthew McDougall, Hezam Albaqami, Ghulam Mubashar Hassan, Amitava Datta

Epilepsy is a highly prevalent brain condition with many serious complications arising from it. The majority of patients which present to a clinic and undergo electroencephalogram (EEG) monitoring would be unlikely to experience seizures during the examination period, thus the presence of interictal epileptiform discharges (IEDs) become effective markers for

Yao Liu, Ming Zhu, Haiyang Yu, Mei Ai

We report the discovery of a 100 kpc HI tail in the merging galaxy pair NGC 4490/85 detected by the Five-Hundred-meter Aperture Spherical radio Telescope (FAST). The tidal tails extended in both the south and north directions, and they are much longer than that reported previously based on the VLA interferometric maps. The NGC 4490/85 is surrounded by a larg

Yu Gong, Xiaoqiao Wang, Chichun Zhou

Visual-based defect detection is a crucial but challenging task in industrial quality control. Most mainstream methods rely on large amounts of existing or related domain data as auxiliary information. However, in actual industrial production, there are often multi-batch, low-volume manufacturing scenarios with rapidly changing task demands, making it diffic

German G. Blesio, Leonid V. Pourovskii, Markus Aichhorn, Monica Pozzo

Knowing the transport properties of iron under realistic conditions present in the Earth's core is essential for the geophysical modeling of Earth's magnetic field generation. Besides by extreme pressures and temperatures, transport may be influenced importantly also by the presence of light elements. Using a combination of molecular dynamics, density functi

Marko Šterk, Uroš Barać, Andraž Stožer, Marko Gosak

Pancreatic beta cells are coupled excitable oscillators that synchronize their activity via different communication pathways. Their oscillatory activity manifests itself on multiple timescales and consists of bursting electrical activity, subsequent oscillations in the intracellular Ca2+, as well as oscillations in metabolism and exocytosis. The coordination

Frederik Kunstner, Jacques Chen, Jonathan Wilder Lavington, Mark Schmidt

The success of the Adam optimizer on a wide array of architectures has made it the default in settings where stochastic gradient descent (SGD) performs poorly. However, our theoretical understanding of this discrepancy is lagging, preventing the development of significant improvements on either algorithm. Recent work advances the hypothesis that Adam and oth

Wilson Yanez, Yu-Sheng Huang, Supriya Ghosh, Saurav Islam

We report the synthesis and characterization of thin films of the Weyl semimetal NbAs grown on GaAs (100) and GaAs (111)B substrates. By choosing the appropriate substrate, we can stabilize the growth of NbAs in the (001) and (100) directions. We combine x-ray characterization with high-angle annular dark field scanning transmission electron microscopy to un

Atharva Kulkarni, Raya Das, Ravi S. Srivastava, Tanmoy Chakraborty

Poverty is a multifaceted phenomenon linked to the lack of capabilities of households to earn a sustainable livelihood, increasingly being assessed using multidimensional indicators. Its spatial pattern depends on social, economic, political, and regional variables. Artificial intelligence has shown immense scope in analyzing the complexities and nuances of

Syomantak Chaudhuri, Thomas A. Courtade

Differential Privacy (DP) is a well-established framework to quantify privacy loss incurred by any algorithm. Traditional DP formulations impose a uniform privacy requirement for all users, which is often inconsistent with real-world scenarios in which users dictate their privacy preferences individually. This work considers the problem of mean estimation un

Charles Jin, Zhang-Wei Hong, Farid Arthaud, Idan Orzech

This work studies the problem of ad hoc teamwork in teams composed of agents with differing computational capabilities. We consider cooperative multi-player games in which each agent's policy is constrained by a private capability parameter, and agents with higher capabilities are able to simulate the behavior of agents with lower capabilities (but not vice-

Monowar Hasan, Sibin Mohan

Cyber-physical systems (CPS) are vulnerable to attacks targeting outgoing actuation commands that modify their physical behaviors. The limited resources in such systems, coupled with their stringent timing constraints, often prevents the checking of every outgoing command. We present a "selective checking" mechanism that uses game-theoretic modeling to ident

Zhoutao Lei, Ching Hua Lee, Linhu Li

Parity-time ($\mathcal{PT}$) symmetry is a cornerstone of non-Hermitian physics as it ensures real energies for stable experimental realization of non-Hermitian phenomena. In this work, we propose $\mathcal{PT}$ symmetry as a paradigm for designing rich families of higher-dimensional non-Hermitian states with unique bulk, surface, hinge or corner dynamics. T

Shoto Aoki, Hidenori Fukaya, Naoto Kan, Mikito Koshino

The Witten effect predicts that a magnetic monopole acquires a fractional electric charge inside topological insulators. In this work, we give a microscopic description of this phenomenon, as well as an analogous two-dimensional system with a vortex. We solve the Dirac equation of electron field both analytically in continuum and numerically on a lattice, by

Ming Liu

Robust image watermarking that can resist camera shooting has become an active research topic in recent years due to the increasing demand for preventing sensitive information displayed on computer screens from being captured. However, many mainstream schemes require human assistance during the watermark detection process and cannot adapt to scenarios that r

Mingxuan Zhu, Dan Hao, Junjie Chen

Widely used compilers like GCC and LLVM usually have hundreds of optimizations controlled by optimization flags, which are enabled or disabled during compilation to improve runtime performance (e.g., small execution time) of the compiler program. Due to the large number of optimization flags and their combination, it is difficult for compiler users to manual

Jianshen Zhu, Naveed Ahmed Azam, Kazuya Haraguchi, Liang Zhao

A novel framework for designing the molecular structure of chemical compounds with a desired chemical property has recently been proposed. The framework infers a desired chemical graph by solving a mixed integer linear program (MILP) that simulates the computation process of a feature function defined by a two-layered model on chemical graphs and a predictio

Yanfang Li, Guohuan Zhao

This study focuses on approximating solutions to SDEs driven by L\'evy processes with H\"older continuous drifts using the Euler-Maruyama scheme. We derive the $L^p$-error for a broad range of driven noises, including all nondegenerate $\alpha$-stable processes ($0<\alpha<2$).

Zexi Niu, Haibo Yuan, Jifeng Liu

Stellar chemical abundances are crucial and fundamental in astrophysics. However, they could suffer from substantial systematic errors according to several investigations but still lack calibrations in bulk. By using Gaia wide binaries, we find the temperature-dependent bias between the two binary components for [Fe/H] and [alpha/Fe] measurements from the LA

Abhishek Roy, Prasant Mohapatra

Fairness-aware machine learning has garnered significant attention in recent years because of extensive use of machine learning in sensitive applications like judiciary systems. Various heuristics, and optimization frameworks have been proposed to enforce fairness in classification \cite{del2020review} where the later approaches either provides empirical res

Zhiyuan Yan, Yong Zhang, Yanbo Fan, Baoyuan Wu

Deepfake detection remains a challenging task due to the difficulty of generalizing to new types of forgeries. This problem primarily stems from the overfitting of existing detection methods to forgery-irrelevant features and method-specific patterns. The latter has been rarely studied and not well addressed by previous works. This paper presents a novel app

Shiqing Li, Kosmas L. Tsakmakidis, Tao Jiang, Qian Shen

Metasurfaces, composed of subwavelength electromagnetic microstructures, known as meta-atoms, are capable of reshaping the wavefronts of incident beams in desired manners, making them great candidates for revolutionizing conventional optics. However, the requirement for external light excitation and the resonant nature of meta-atoms make it difficult to full

Amritanshu Prasad, Samrith Ram

We express the number of anti-invariant subspaces for a linear operator on a finite vector space in terms of the number of its invariant subspaces. When the operator is diagonalizable with distinct eigenvalues, our formula gives a finite-field interpretation for the entries of the $q$-Hermite Catalan matrix. We also obtain an interesting new proof of Touchar

Michael Herty, Niklas Kolbe, Siegfried Müller

A novel numerical scheme to solve coupled systems of conservation laws is introduced. The scheme is derived based on a relaxation approach and does not require information on the Lax curves of the coupled systems, which simplifies the computation of suitable coupling data. The coupling condition for the underlying relaxation system plays a crucial role as it

Ke Wang, Kun-Peng Chen, Morgan Le Delliou

In principle, the local cosmic void can be simply modeled by the spherically symmetric Lemaitre-Tolman-Bondi (LTB) metric. In practice, the real local cosmic void is probably not spherically symmetric. In this paper, to reconstruct a more realistic profile of the local cosmic void, we divide it into several segments. Each segment with certain solid angle is

Naga VS Raviteja Chappa, Pha Nguyen, Alexander H Nelson, Han-Seok Seo

This paper introduces a novel approach to Social Group Activity Recognition (SoGAR) using Self-supervised Transformers network that can effectively utilize unlabeled video data. To extract spatio-temporal information, we created local and global views with varying frame rates. Our self-supervised objective ensures that features extracted from contrasting vie

Tong Han, David J. Hill, Yue Song

This paper focuses on the N-k security-constrained optimal transmission switching (OTS) problem for variable renewable energy (VRE) penetrated power grids. A new three-stage stochastic and distributionally robust OTS model is proposed. The first stage has the primary purpose to schedule the power generation and network topology based on the forecast of VRE.

Yuan Gao, Kentaro Barhydt, Christopher Niezrecki, Yan Gu

Accurate control of a humanoid robot's global position (i.e., its three-dimensional position in the world) is critical to the reliable execution of high-risk tasks such as avoiding collision with pedestrians in a crowded environment. This paper introduces a time-based nonlinear control method that achieves accurate global-position tracking (GPT) for multi-do

Xiaoqian Liu, Xu Han, Eric C. Chi, Boaz Nadler

In 1-bit matrix completion, the aim is to estimate an underlying low-rank matrix from a partial set of binary observations. We propose a novel method for 1-bit matrix completion called Majorization-Minimization Gauss-Newton (MMGN). Our method is based on the majorization-minimization principle, which converts the original optimization problem into a sequence

Elaine Gorom-Alexander, Xingjie Helen Li

Inspired by the blending method developed by [P. Seleson, S. Beneddine, and S. Prudhome, \emph{A Force-Based Coupling Scheme for Peridynamics and Classical Elasticity}, (2013)] for the nonlocal-to-local coupling, we create a symmetric and consistent blended force-based Atomistic-to-Continuum (a/c) scheme for the atomistic chain in one-dimensional space. The

Haolin Wang, Yafei Ou, Wanxuan Fang, Prasoon Ambalathankandy

Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease that results in progressive articular destruction and severe disability. Joint space narrowing (JSN) progression has been regarded as an important indicator for RA progression and has received sustained attention. In the diagnosis and monitoring of RA, radiology plays a crucial role to mo

Yuntao Du, Jianxun Lian, Jing Yao, Xiting Wang

Collaborative Filtering (CF) is a widely used and effective technique for recommender systems. In recent decades, there have been significant advancements in latent embedding-based CF methods for improved accuracy, such as matrix factorization, neural collaborative filtering, and LightGCN. However, the explainability of these models has not been fully explor

Miao Wu, Xin Li, Di-Feng Yin, Wei Chen

Materials synthesis in a microfluidic environment enables the flexible and controllable production of various types of nanostructures which are of great potential in the fields of chemistry, environmental science, bioengineering, and medicine. Here, we demonstrate on-chip simultaneous continuous-flow synthesis and in-situ spectrum diagnosis of zinc oxide (Zn

Rodrigo Zeidan, Silvio Luiz de Almeida, Inácio Bó, Neil Lewis

This survey article provides insights regarding the future of affirmative action by analyzing the implementation methods and the empirical evidence on the use of placement quotas in the Brazilian higher education system. All federal universities have required income and racial-based quotas in Brazil since 2012. Affirmative action in federal universities is u

Changhoon Kang, Jongsoo Woo, James Won-Ki Hong

Bitcoin transactions include unspent transaction outputs (UTXOs) as their inputs and generate one or more newly owned UTXOs at specified addresses. Each UTXO can only be used as an input in a transaction once, and using it in two or more different transactions is referred to as a double-spending attack. Ultimately, due to the characteristics of the Bitcoin p

Thitithep Sitthiyot, Kanyarat Holasut

Given that the existing parametric functional forms for the Lorenz curve do not fit all possible size distributions, a universal parametric functional form is introduced. By using the empirical data from different scientific disciplines and also the hypothetical data, this study shows that, the proposed model fits not only the data whose actual Lorenz plots

Louis Hickman, Jason Kuruzovich, Vincent Ng, Kofi Arhin

Organizations are increasingly adopting machine learning (ML) for personnel assessment. However, concerns exist about fairness in designing and implementing ML assessments. Supervised ML models are trained to model patterns in data, meaning ML models tend to yield predictions that reflect subgroup differences in applicant attributes in the training data, reg

Stephen A. Giles, Hugh Shortt, Peter K. Liaw, Debasis Sengupta

Development of process-structure-property relationships in materials science is an important and challenging frontier which promises improved materials and reduced time and cost in production. Refractory high entropy alloys (RHEAs) are a class of materials that are capable of excellent hightemperature properties. However, due to their multi-component nature,

Zefeng Chen, Wensheng Gan, Jiayi Sun, Jiayang Wu

With the evolution of content on the web and the Internet, there is a need for cyberspace that can be used to work, live, and play in digital worlds regardless of geography. The Metaverse provides the possibility of future Internet and represents a future trend. In the future, the Metaverse will be a space where the real and the virtual are combined. In this

Jonelle Angelo S. Cenita, Zyra R. De Guzman

The objective of this study is to determine Education in the Digital World from the lens of millennial learners. This also identifies the cybergogical implications of the issue with digital education as seen through the lens of the outlier. This study uses a mixed methods sequential explanatory design. A quantitative method was employed during the first phas

Xiaofei Li, Shengqi Lin

This paper considers the two-dimensional narrow escape problem in a domain which is composed of a relatively big head and several thin necks. The narrow escape problem is to compute the mean first passage time(MFPT) of a Brownian particle traveling from inside the head to the end of the necks. The original model for MFPT is to solve a mixed Dirichlet-Neumann

Bowen Wang, Jianchi Zhu, Xiaoming She, Peng Chen

The orthogonal time frequency space (OTFS) modulation as a promising signal representation attracts growingcinterest for integrated sensing and communication (ISAC), yet its merits over orthogonal frequency division multiplexing (OFDM) remain controversial. This paper devotes to a comprehensive comparison of OTFS and OFDM for sensing from the perspective of

Ryo Tamura, Koji Tsuda, Shoichi Matsuda

NIMS-OS (NIMS Orchestration System) is a Python library created to realize a closed loop of robotic experiments and artificial intelligence (AI) without human intervention for automated materials exploration. It uses various combinations of modules to operate autonomously. Each module acts as an AI for materials exploration or a controller for a robotic expe

Renata Kallosh

We study candidate counterterms (CT)'s in maximal supergravities in diverse integer dimensions $d \geq 4 $. We find that UV divergences in these theories occur at the number of loops $L$ below certain critical value $L_{cr}$. At $L\geq L_{cr}$ the CT's have nonlinear local supersymmetry and local $H$ symmetry, but the ones below $L_{cr}$ break these symmetri

Albert Lam, Mihai Anitescu, Anirudh Subramanyam

Measures of power grid vulnerability are often assessed by the amount of damage an adversary can exact on the network. However, the cascading impact of such attacks is often overlooked, even though cascades are one of the primary causes of large-scale blackouts. This paper explores modifications of transmission line protection settings as candidates for adve

Pedro H. C. Sant'Anna, Qi Xu

This paper studies Difference-in-Differences (DiD) setups with repeated cross-sectional data and potential compositional changes across time periods. We begin our analysis by deriving the efficient influence function and the semiparametric efficiency bound for the average treatment effect on the treated (ATT). We introduce nonparametric estimators that attai

Wenxuan Liu, Zhihai Zhang

This paper investigates the data-driven pricing newsvendor problem, which focuses on maximizing expected profit by deciding on inventory and pricing levels based on historical demand and feature data. We first build an approximate model by assigning weights to historical samples. However, due to decision-dependent effects, the resulting approximate model is

Jiahua Rao, Zifei Shan, Longpo Liu, Yao Zhou

With the recent progress in large-scale vision and language representation learning, Vision Language Pre-training (VLP) models have achieved promising improvements on various multi-modal downstream tasks. Albeit powerful, these models have not fully leveraged world knowledge to their advantage. A key challenge of knowledge-augmented VLP is the lack of clear

Colan F. Biemer, Seth Cooper

Many games feature a progression of levels that doesn't adapt to the player. This can be problematic because some players may get stuck if the progression is too difficult, while others may find it boring if the progression is too slow to get to more challenging levels. This can be addressed by building levels based on the player's performance and preference

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

Using $(1.0087\pm0.0044)\times10^{10}$ $J/\psi$ events collected with the BESIII detector at the BEPCII storage ring, the process $\Xi^{0}n\rightarrow\Xi^{-}p$ is studied, where the $\Xi^0$ baryon is produced in the process $J/\psi\rightarrow\Xi^0\bar{\Xi}^0$ and the neutron is a component of the $^9\rm{Be}$, $^{12}\rm{C}$ and $^{197}\rm{Au}$ nuclei in the b

Dongliang Cao, Paul Roetzer, Florian Bernard

We propose a novel learning-based approach for robust 3D shape matching. Our method builds upon deep functional maps and can be trained in a fully unsupervised manner. Previous deep functional map methods mainly focus on predicting optimised functional maps alone, and then rely on off-the-shelf post-processing to obtain accurate point-wise maps during infere

Ryuji Chiba, Toru Kojo

We study zero temperature equations of state (EOS) in isospin QCD within a quark-meson model which is renormalizable and hence eliminates high density artifacts in models with the ultraviolet cutoff (e.g., NJL models). The model exhibits a crossover transition of pion condensations from the Bose-Einstein-Condensation regime at low density to the Bardeen-Coop

Ramneet Kaur, Yiannis Kantaros, Wenwen Si, James Weimer

Deep neural networks (DNN) have become a common sensing modality in autonomous systems as they allow for semantically perceiving the ambient environment given input images. Nevertheless, DNN models have proven to be vulnerable to adversarial digital and physical attacks. To mitigate this issue, several detection frameworks have been proposed to detect whethe

H M Dipu Kabir, Subrota Kumar Mondal, Sadia Khanam, Abbas Khosravi

Researchers have proposed several approaches for neural network (NN) based uncertainty quantification (UQ). However, most of the approaches are developed considering strong assumptions. Uncertainty quantification algorithms often perform poorly in an input domain and the reason for poor performance remains unknown. Therefore, we present a neural network trai

Madhuvanthi Srivatsav R, Shantanu Chakrabartty, Chetan Singh Thakur

Address-Event-Representation (AER) is a spike-routing protocol that allows the scaling of neuromorphic and spiking neural network (SNN) architectures to a size that is comparable to that of digital neural network architectures. However, in conventional neuromorphic architectures, the AER protocol and, in general, any virtual interconnect plays only a passive

Cuong Q. Nguyen, Dante Pertusi, Kim M. Branson

Image-based profiling techniques have become increasingly popular over the past decade for their applications in target identification, mechanism-of-action inference, and assay development. These techniques have generated large datasets of cellular morphologies, which are typically used to investigate the effects of small molecule perturbagens. In this work,

Qingpeng Zhu, Wenxiu Sun, Yuekun Dai, Chongyi Li

Depth completion from RGB images and sparse Time-of-Flight (ToF) measurements is an important problem in computer vision and robotics. While traditional methods for depth completion have relied on stereo vision or structured light techniques, recent advances in deep learning have enabled more accurate and efficient completion of depth maps from RGB images an

Sabee Grewal, Vishnu Iyer, William Kretschmer, Daniel Liang

We study the complexity of learning quantum states in various models with respect to the stabilizer formalism and obtain the following results: - We prove that $\Omega(n)$ $T$-gates are necessary for any Clifford+$T$ circuit to prepare computationally pseudorandom quantum states, an exponential improvement over the previously known bound. This bound is asymp

J. S. Zhou, R. Z. Xu, X. Q. Yu, F. J. Cheng

There has been a long-standing debate about the mechanism of the unusual superconductivity in alkali-intercalated fulleride superconductors. In this work, using high-resolution angle-resolved photoemission spectroscopy, we systematically investigate the electronic structures of superconducting K3C60 thin films. We observe a dispersive energy band crossing th

Takahiro Murotani

The Grothendieck conjecture for hyperbolic curves over finite fields was solved affirmatively by Tamagawa and Mochizuki. On the other hand, (a ``weak version'' of) the Grothendieck conjecture for some hyperbolic curves over algebraic closures of finite fields is also known by Tamagawa and Sarashina. So, it is natural to consider anabelian geometry over (infi

X. Yang, S. -B. Zhang, J. -S. Wang, X. -F. Wu

Fast radio bursts (FRBs) are mysterious astronomical phenomena, and it is still uncertain whether they consist of multiple types. In this study we use two nonlinear dimensionality reduction algorithms - Uniform Manifold Approximation and Projection (UMAP) and t-distributed stochastic neighbour embedding (t-SNE) - to differentiate repeaters from apparently no

Xiangyang Liu, Tianqi Pang, Chenyou Fan

We investigate how to enhance answer precision in frequently asked questions posed by distributed users using cloud-based Large Language Models (LLMs). Our study focuses on a typical situations where users ask similar queries that involve identical mathematical reasoning steps and problem-solving procedures. Due to the unsatisfactory accuracy of LLMs' zero-s

Xiaomeng Chen, Aimin Li, Shaohua Wu

Spinal codes, a family of rateless codes introduced in 2011, have been proved to achieve Shannon capacity over both the additive white Gaussian noise (AWGN) channel and the binary symmetric channel (BSC). In this paper, we derive explicit tight upper bounds on the error probability of Spinal codes under maximum-likelihood (ML) decoding and perfect channel st

Francesco Di Plinio, A. Walton Green, Brett D. Wick

Given a uniform domain $\Omega \subset {\mathbb R}^d$, we resolve each element of a suitably defined class of Calder\`on-Zygmund (CZ) singular integrals on $\Omega$ as the linear combination of Triebel wavelet operators and paraproduct terms. Our resolution formula entails a testing type characterization, loosely in the vein of the David-Journ\'e theorem, of

Xinchen Li, Levent Guvenc, Bilin Aksun-Guvenc

This paper is on decision making of autonomous vehicles for handling roundabouts. The round intersection is introduced first followed by the Markov Decision Processes (MDP), the Partially Observable Markov Decision Processes (POMDP) and the Object Oriented Partially Observable Markov Decision Process (OOPOMDP). The Partially Observable Monte-Carlo Planning a

Xiou Ge, Sarah E. Brown, Pushpendra Rana, Lav R. Varshney

The incorporation of trees on farms can help to improve livelihoods and build resilience among small-holder farmers in developing countries. On-farm trees can help gen- erate additional income from commercial tree harvest as well as contribute significant environmental benefits and ecosystem services to increase resiliency. Long-term benefits from tree-based

Lifu Zhang, Xuri Yang, Qi Huang, Yanxia Gao

We study the nonlinear propagation of truncated Airyprime pulses in optical fibers with both anomalous or normal dispersion. Weobservenonlinear self-accelerating pulses with notable red-shifted spectral notch (double peaks) or blue-shifted spectral peak depending on whether the dispersion is anomalous or normal. SuchprocessisinsharpcontrasttothatofAirypulses

Shushu Shi, Xin Xie, Sai Yan, Jingnan Yang

Chiral light-matter interactions supported by topological edge modes at the interface of valley photonic crystals provide a robust method to implement the unidirectional spin transfer. The valley topological photonic crystals possess a pair of counterpropagating edge modes. The edge modes are robust against the sharp bend of $60^{\circ}$ and $120^{\circ}$, w

Z. Chu, K. F. Tong, K. K. Wong, C. B. Chae

Reconfigurable intelligent surface (RIS) as a smart reflector is revolutionizing research for next-generation wireless communications. Complementing this is a concept of using RIS as an efficient propagation medium for potentially superior path loss characteristics. Motivated by a recent porous surface architecture that facilitates reconfigurable pathways wi

Dingzirui Wang, Longxu Dou, Wanxiang Che

The limited scale of annotated data constraints existing context-dependent text-to-SQL models because of the complexity of labeling. The data augmentation method is a commonly used method to solve this problem. However, the data generated by current augmentation methods often lack diversity. In this paper, we introduce ConDA, which generates interactive ques

Burkhard C. Schipper

Heifetz, Meier, and Schipper (2013) introduced dynamic game with unawareness consisting of a partially ordered set of games in extensive form. Here, we study the normal form of dynamic games with unawareness. The generalized normal form associated with a dynamic game with unawareness consists of a partially ordered set of games in norm form. We use the gener

Elnaz Rezaian, Karthik Duraisamy

Rapid prediction of the aeroacoustic response is a key component in the design of aircraft and turbomachinery. While it is possible to achieve accurate predictions using direct solution of the compressible Navier-Stokes equations, applications of such solvers is not feasible in design optimization due to the high cost of resolving wave phenomena in an Euleri