July 2023 arXiv papers — page 106

Pedro Freitas, James B. Kennedy

Inspired by a recent result of Funano's, we provide a sharp quantitative comparison result between the first nontrivial eigenvalues of the Neumann Laplacian on bounded convex domains $\Omega_{1} \subset \Omega_{2}$ in any dimension $d$ greater than or equal to two, recovering domain monotonicity up to an explicit multiplicative factor. We provide upper and l

Jonathan David Evans, Yanki Lekili

We compute the wrapped Fukaya category $\mathcal{W}(T^*S^1, D)$ of a cylinder relative to a divisor $D= \{p_1,\ldots, p_n\}$ of $n$ points, proving a mirror equivalence with the category of perfect complexes on a crepant resolution (over $k[t_0,\ldots, t_n]$) of the singularity $uv=t_0t_1\ldots t_n$. Upon making the base-change $t_i= f_i(x,y)$, we obtain the

Tengren Zhang, Gye-Seon Lee

We show that if a cusped Borel Anosov representation from a lattice $\Gamma \subset \mathsf{PGL}_2(\mathbb{R})$ to $\mathsf{PGL}_d(\mathbb{R})$ contains a unipotent element with a single Jordan block in its image, then it is necessarily a (cusped) Hitchin representation. We also show that the amalgamation of a Hitchin representation with a cusped Borel Anoso

Hang Du, Shuyang Gong, Rundong Huang

We study the graph alignment problem over two independent Erd\H{o}s-R\'enyi graphs on $n$ vertices, with edge density $p$ falling into two regimes separated by the critical window around $p_c=\sqrt{\log n/n}$. Our result reveals an algorithmic phase transition for this random optimization problem: polynomial-time approximation schemes exist in the sparse reg

Soumya Sasidharan, Naveen Surendran

A class of integrable models, such as the one-dimensional transverse-field Ising model, respond nonmonotonically to a periodic drive with respect to the driving parameters and freezes almost absolutely for certain combinations of the latter. In this paper, we go beyond the two-band structure of the Ising-like models studied previously and ask whether such un

S. F. Lukomskii, A. M. Vodolazov

We discuss the problem on approximation by tight step wavelet frames on the field $\mathbb{Q}_p$ of $p$-adic numbers. Let $G_n=\{x=\sum_{k=n}^\infty x_k p^k\}$, $X$ be a set of characters. We define a step function $\lambda({\chi})$ that is constant on cosets ${G}_n^\bot\setminus{G}_{n-1}^\bot$ by equalities $\lambda ({G}_n^\bot\setminus{G}_{n-1}^\bot)=\lamb

Yi Peng, Huaqiao Wang

In this paper, we focus on the three-dimensional hyper viscous and resistive Hall-MHD equations on the torus, where the viscous and resistive exponent $\alpha\in [\rho, 5/4)$ with a fixed constant $\rho\in (1,5/4)$. We prove the non-uniqueness of a class of weak solutions to the Hall-MHD equations, which have bounded kinetic energy and are smooth in time out

Masaki Yamada, Kazuya Yonekura

We point out that SO($2N$) pure Yang-Mills theory provides a candidate for dark matter (DM) without the explicit need to impose any additional symmetry. The DM candidate is a particular type of glueball, which we refer to as a baryonic glueball, that is naturally stable and produced by a novel production mechanism for a moderately large $N$. In this case, th

Jiahui Huang, Hua Feng, Wei-Min Gu, Wen-Biao Wu

We construct an analytical black hole accretion disk model that incorporates both magnetic pressure and disk wind, which are found to be important from numerical simulations. A saturated magnetic pressure that relates the Alfven velocity with local Keplerian velocity and gas sound speed is assumed in addition to radiation and gas pressures. The mass accretio

A. Caranti, C. M. Scoppola, Gunnar Traustason

We investigate the occurrence of elements of order $p$ in the upper central series of a finite $p$-group.

Jonte R. Hance, Ming Ji, Holger F. Hofmann

We analyse the quantum Cheshire cat using contextuality theory, to see if this can tell us anything about how best to interpret this paradox. We show that this scenario can be analysed using the relation between three different measurements, which seem to result in a logical contradiction. We discuss how this contextual behaviour links to weak values, and co

Dahae Roh, Kwang-Il Goh

A family of models of growing hypergraphs with preferential rules of new linking is introduced and studied. The model hypergraphs evolve via the hyperedge-based growth as well as the node-based one, thus generalizing the preferential-attachment models of scale-free networks. We obtain the degree distribution and hyperedge size distribution for various combin

Hangbin Lee, IL DO HA, Youngjo Lee

For prediction of clustered time-to-event data, we propose a new deep neural network based gamma frailty model (DNN-FM). An advantage of the proposed model is that the joint maximization of the new h-likelihood provides maximum likelihood estimators for fixed parameters and best unbiased predictors for random frailties. Thus, the proposed DNN-FM is trained b

Bo Peng, Yuan Su, Daniel Claudino, Karol Kowalski

A broad spectrum of physical systems in condensed-matter and high-energy physics, vibrational spectroscopy, and circuit and cavity QED necessitates the incorporation of bosonic degrees of freedom, such as phonons, photons, and gluons, into optimized fermion algorithms for near-future quantum simulations. In particular, when a quantum system is surrounded by

Abhishek Dhawan

In this paper, we consider algorithms for edge-coloring multigraphs $G$ of bounded maximum degree, i.e., $\Delta(G) = O(1)$. Shannon's theorem states that any multigraph of maximum degree $\Delta$ can be properly edge-colored with $\lfloor3\Delta/2\rfloor$ colors. Our main results include algorithms for computing such colorings. We design deterministic and r

Pedro C. Rijo, Francisco J. Galindo-Rosales

This work provides a complete rheological characterization of 2D-inks in electric fields with different intensities and orientations to the imposed flow field. 2D nanomaterials used in this study are graphene nanoplatelets, hexagonal boron-nitride, and molybdenum disulfide. These materials with different electric properties are dispersed in a non-polar solve

MD Wahiduzzaman Khan, Hongwei Sheng, Hu Zhang, Heming Du

Retinal vessel segmentation is generally grounded in image-based datasets collected with bench-top devices. The static images naturally lose the dynamic characteristics of retina fluctuation, resulting in diminished dataset richness, and the usage of bench-top devices further restricts dataset scalability due to its limited accessibility. Considering these l

Taisei Nogami, Tachio Terauchi

A rewb is a regular expression extended with a feature called backreference. It is broadly known that backreference is a practical extension of regular expressions, and is supported by most modern regular expression engines, such as those in the standard libraries of Java, Python, and more. Meanwhile, indexed languages are the languages generated by indexed

Zewen Jiang, Wei Wang, Guo Chen, Fei Yan

Transit spectroscopy is the most frequently used technique to reveal the atmospheric properties of exoplanets, while that at high resolution has the advantage to resolve the small Doppler shift of spectral lines, and the trace signal of the exoplanet atmosphere can be separately extracted. We obtain the transmission spectra of the extrasolar planet WASP-85Ab

Boming Yang, Dairui Liu, Toyotaro Suzumura, Ruihai Dong

Precisely recommending candidate news articles to users has always been a core challenge for personalized news recommendation systems. Most recent works primarily focus on using advanced natural language processing techniques to extract semantic information from rich textual data, employing content-based methods derived from local historical news. However, t

Guangwen Li, Xiao Yu

In the search for highly efficient decoders for short LDPC codes approaching maximum likelihood performance, a relayed decoding strategy, specifically activating the ordered statistics decoding process upon failure of a neural min-sum decoder, is enhanced by instilling three innovations. Firstly, soft information gathered at each step of the neural min-sum d

Yizao Wang, Jacek Wesolowski, Zongrui Yang

We introduce a family of multi-dimensional Askey-Wilson signed measures. We offer an explicit description of the stationary measure of the open asymmetric simple exclusion process (ASEP) in the full phase diagram, in terms of integrations with respect to these Askey-Wilson signed measures. Using our description, we provide a rigorous derivation of the densit

Zhigang Pu, Chang Liu, Kun Xu

Most plasmas are only partially ionized. To better understand the dynamics of these plasmas, the behaviors of a mixture of neutral species and plasma in ideal magnetohydrodynamic states are investigated. The current approach is about the construction of coupled kinetic models for the neutral gas, electron, and proton, and the development of the corresponding

Kentaro Nagamine

Feedback effects generated by supernovae (SNe) and active galactic nuclei (AGNs) are pivotal in shaping the evolution of galaxies and their present-day structures. However, our understanding of the specific mechanisms operating at galactic scales, as well as their impact on circum-galactic medium (CGM) and intergalactic medium (IGM), remains incomplete. Gala

Avijeet Prasad, Sanjay Kumar, Alphonse C. Sterling, Ronald L. Moore

Erupting magnetic flux ropes (MFRs) play a crucial role in producing solar flares. However, the formation of erupting MFRs in complex coronal magnetic configurations and their subsequent evolution in the flaring events are not fully understood. We performed an MHD simulation of active region NOAA 12241 to understand the formation of a rising MFR during the o

Emma Fraxanet, Max Pellert, Simon Schweighofer, Vicenç Gómez

Political conflict is an essential element of democratic systems, but can also threaten their existence if it becomes too intense. This happens particularly when most political issues become aligned along the same major fault line, splitting society into two antagonistic camps. In the 20th century, major fault lines were formed by structural conflicts, like

Lan Bo, Rongzhi Zhao, Chenglong Hu, Xichao Zhang

Skyrmion bags are composed of an outer skyrmion and arbitrary inner skyrmions, which have recently been observed in bulk chiral magnets, but still remain elusive in magnetic films. Here, we propose a method of creating skyrmion bags in a thin-film nanodisk, which includes three steps. Firstly, the size of outer skyrmion is enlarged by a vertical magnetic fie

Silvia Giuliatti Winter, Jadilene Xavier, Antônio Bertachini Prado, Andre Amarante

In this work, we present the results of a set of numerical simulations carried out to obtain long-duration orbits for a probe around Titania, Uranus' largest satellite. We also propose orbital maneuvers to extend the lifetime of some orbits. Titania's $J_2$ and $C_{22}$ gravitational coefficients and Uranus' gravitational perturbation are considered. The ana

Yi Cheng, Ziwei Xu, Fen Fang, Dongyun Lin

In this technical report, we present our findings from a study conducted on the EPIC-KITCHENS-100 Unsupervised Domain Adaptation task for Action Recognition. Our research focuses on the innovative application of a differentiable logic loss in the training to leverage the co-occurrence relations between verb and noun, as well as the pre-trained Large Language

Matt Alexander

In this paper we introduce a particular lattice of subgroups called a "cyclic-diamond" and show that every finite non-cyclic group contains a cyclic-diamond as a sublattice of its lattice of subgroups. Turning to the infinite case, we show that an infinite abelian group does not contain a cyclic-diamond in its subgroup lattice if and only if all of its finit

Guoan Li, Xiaofan Shi, Ting Lin, Guang Yang

With the development of quantum technology, hybrid devices that combine superconductors (S) and semiconductors (Sm) have attracted great attention due to the possibility of engineering structures that benefit from the integration of the properties of both materials. However, until now, none of the experiments have reported good control of band alignment at t

Zhan Shi, Xin Ding, Peng Ding, Chun Yang

Ship orientation angle prediction (SOAP) with optical remote sensing images is an important image processing task, which often relies on deep convolutional neural networks (CNNs) to make accurate predictions. This paper proposes a novel framework to reduce the model sizes and computational costs of SOAP models without harming prediction accuracy. First, a ne

Lianke Qin, Zhao Song, Yuanyuan Yang

Deep learning has been widely used in many fields, but the model training process usually consumes massive computational resources and time. Therefore, designing an efficient neural network training method with a provable convergence guarantee is a fundamental and important research question. In this paper, we present a static half-space report data structur

Mahmoud Shoush, Marlon Dumas

Prescriptive process monitoring methods seek to optimize the performance of business processes by triggering interventions at runtime, thereby increasing the probability of positive case outcomes. These interventions are triggered according to an intervention policy. Reinforcement learning has been put forward as an approach to learning intervention policies

Ryan Bowler, Chris Speed, Geoffrey Goodell

Money is more than just a numeric value. It embodies trust and moral gravity, and it offers flexible ways to transact. However, the emergence of Central Bank Digital Currency (CBDC) is set to bring about a drastic change in the future of money. This paper invites designers to reflect on their role in shaping material and immaterial monetary change. In this r

Ryoji Tanabe

Normalization of objectives plays a crucial role in evolutionary multi-objective optimization (EMO) to handle objective functions with different scales, which can be found in real-world problems. Although the effect of normalization methods on the performance of EMO algorithms has been investigated in the literature, that of preference-based EMO (PBEMO) algo

Naoki Shibahara, Michihiro Koibuchi, Hiroki Matsutani

Federated learning is a distributed machine learning approach where local weight parameters trained by clients locally are aggregated as global parameters by a server. The global parameters can be trained without uploading privacy-sensitive raw data owned by clients to the server. The aggregation on the server is simply done by averaging the local weight par

M. Niikura, T. Y. Saito, T. Matsuzaki, K. Ishida

Background: The energy distribution of excited states populated by the nuclear muon capture reaction can facilitate an understanding of the reaction mechanism; however, experimental data are fairly sparse. Purpose: We developed a new methodology, called the in-beam activation method, to measure the production probability of residual nuclei by muon capture. F

Hideto Asashiba

Let $G$ be a finitely generated right $A$-module for a finite-dimensional algebra $A$ over a filed $\Bbbk$, and $\mathcal{I}$ the additive closure of $G$. We will define a $\mathcal{I}$-relative Koszul coresolution $\mathcal{K}^{\bullet}(V)$ of an indecomposable direct summand $V$ of $G$, and show that for a finitely generated $A$-module $M$, the $\mathcal{I

Junwen Yang, Yifan Feng

We study a ranking and selection problem of learning from choice-based feedback with dynamic assortments. In this problem, a company sequentially displays a set of items to a population of customers and collects their choices as feedback. The only information available about the underlying choice model is that the choice probabilities are consistent with som

Tian Lan, Deng Cai, Yan Wang, Heyan Huang

The dominant text generation models compose the output by sequentially selecting words from a fixed vocabulary. In this paper, we formulate text generation as progressively copying text segments (e.g., words or phrases) from an existing text collection. We compute the contextualized representations of meaningful text segments and index them using efficient v

Diego Paiva Pires, Eduardo R. deAzevedo, Diogo O. Soares-Pinto, Frederico Brito

We studied geometric quantum speed limits (QSL) of a qubit subject to decoherence in an ensemble of chloroform molecules in a Nuclear Magnetic Resonance experiment. The QSL is a fundamental lower bound on the evolution time for quantum systems undergoing general physical processes. To do so, we controlled the system-reservoir interaction and the spin relaxat

Beomdu Lim, Jongsuk Hong, Jinhee Lee, Hyeong-Sik Yun

The star-forming region W5 is a major part of the Cassiopeia OB6 association. Its internal structure and kinematics may provide hints of the star formation process in this region. Here, we present a kinematic study of young stars in W5 using the Gaia data and our radial velocity data. A total 490 out of 2,000 young stars are confirmed as members. Their spati

Shivam Singh, Sajana S, Poornima, Gajje Sreelekha

Detection of Volatile Organic Compounds (VOCs) from the breath is becoming a viable route for the early detection of diseases non-invasively. This paper presents a sensor array with three metal oxide electrodes that can use machine learning methods to identify four distinct VOCs in a mixture. The metal oxide sensor array was subjected to various VOC concentr

Hyungsoo Kang, Isaac Kaminer, Venanzio Cichella, Naira Hovakimyan

In this article, a novel time-coordination algorithm based on event-triggered communications is proposed to achieve coordinated path-following of UAVs. To be specific, in the approach adopted a UAV transmits its progression information over a time-varying network to its neighbors only when a decentralized trigger condition is satisfied, thereby significantly

Rabimba Karanjai, Sangwon Shin, and Wujie Xiong, Xinxin Fan

Cryptographic schemes like Fully Homomorphic Encryption (FHE) and Zero-Knowledge Proofs (ZKPs), while offering powerful privacy-preserving capabilities, are often hindered by their computational complexity. Polynomial multiplication, a core operation in these schemes, is a major performance bottleneck. While algorithmic advancements and specialized hardware

Hyungsoo Kang, Isaac Kaminer, Venanzio Cichella, Naira Hovakimyan

This paper presents a new connectivity condition on the information flow between UAVs to achieve coordinated path following. The information flow is directional, so that the underlying communication network topology is represented by a time-varying digraph. We assume that this digraph is connected in an integral sense. This is a much more general assumption

Carlo Peruzzo, Luciano Simoni, Bernhard Schrefler

Comments to K.M. Pervaiz Fathima, Ren\'e de Borst, Implications of single or multiple pressure degrees of freedom at fracture in fluid saturated porous media, Engineering Fracture Mechanics, 213 (2019), 1-20.

Ante Bing, Donna Spiegelman, Daniel Nevo, Judith J. Lok

It is well known that changing the intervention package while a trial is ongoing does not lead to valid inference using standard statistical methods. However, it is often necessary to adapt, tailor, or tweak a complex intervention package in public health implementation trials, especially when the intervention package does not have the desired effect. This a

Leilani Battle, Alvitta Ottley

Insights are often considered the ideal outcome of visual analysis sessions. However, there is no single definition of what an insight is. Some scholars define insights as correlations, while others define them as hypotheses or aha moments. This lack of a clear definition can make it difficult to build visualization tools that effectively support insight dis

Guitao Lyu, Yuki Minami, Na Young Kim, Tim Byrnes

The phase distribution in a Bose-Einstein condensate can realize various topological states classified by distinct winding numbers. While states with different winding numbers are topologically protected in the linear Schr\"odinger equation, when nonlinearities are introduced, violations of the topological protection can occur, leading to unwinding. Exciton-

Pablo Oliveira, Corinne Arrouvel, Fernando Stavale

The formation and stability of a sulfur-rich surface of the zinc blende ZnS (001) single crystal have been examined by x-ray photoemission spectroscopy (XPS), low-energy electron diffraction (LEED), and density-functional theory (DFT) calculations. LEED patterns obtained from ZnS (001) surface prepared in ultrahigh vacuum conditions are compatible to the for

Jialiang Sun, Wen Yao, Tingsong Jiang, Xiaoqian Chen

Deep neural networks have proven to be vulnerable to adversarial attacks in the form of adding specific perturbations on images to make wrong outputs. Designing stronger adversarial attack methods can help more reliably evaluate the robustness of DNN models. To release the harbor burden and improve the attack performance, auto machine learning (AutoML) has r

Michael James Horry, Subrata Chakraborty, Biswajeet Pradhan, Manoranjan Paul

Lung cancer is the leading cause of cancer death and early diagnosis is associated with a positive prognosis. Chest X-ray (CXR) provides an inexpensive imaging mode for lung cancer diagnosis. Suspicious nodules are difficult to distinguish from vascular and bone structures using CXR. Computer vision has previously been proposed to assist human radiologists i

H. Yao, P. K. Yeung, T. A. Zaki, C. Meneveau

We study fluctuations of the local energy cascade rate $\Phi_\ell$ in turbulent flows at scales ($\ell$) in the inertial range. According to the Kolmogorov refined similarity hypothesis (KRSH), relevant statistical properties of $\Phi_\ell$ should depend on $\epsilon_\ell$, the viscous dissipation rate locally averaged over a sphere of size $\ell$, rather th

Lu Lu, Jize Dai, Sophie Leanza, John W. Hutchinson

Curved-sided hexagrams with multiple equilibrium states have great potential in engineering applications such as foldable architectures, deployable aerospace structures, and shape-morphing soft robots. In Part I, the classical stability criterion based on energy variation was used to study the elastic stability of the curved-sided hexagram and identify the n

Peijun Li, Ying Liang

This paper is concerned with the stability estimates for inverse source problems of the stochastic Helmholtz equation driven by white noise. The well-posedness is established for the direct source problems, which ensures the existence and uniqueness of solutions. The stability estimates are deduced for the inverse source problems, which aim to determine the

Lu Lu, Jize Dai, Sophie Leanza, Ruike Renee Zhao

The stability of the multiple equilibrium states of a hexagram ring with six curved sides is investigated. Each of the six segments is a rod having the same length and uniform natural curvature. These rods are bent uniformly in the plane of the hexagram into equal arcs of 120deg or 240deg and joined at a cusp where their ends meet to form a 1-loop planar rin

Sourabh Zanwar

Algorithms have been becoming increasingly relevant for various decision-making processes in the forms of Decision Support Systems or Decision-making systems in areas such as Criminal-Justice systems, Job Application Filtering, Medicine, and Healthcare to name a few. It is crucial for these algorithms to be fair and for the users to have confidence in these

Luyao Zhang, Yutong Sun, Yutong Quan, Jiaxun Cao

As CryptoPunks pioneers the innovation of non-fungible tokens (NFTs) in AI and art, the valuation mechanics of NFTs has become a trending topic. Earlier research identifies the impact of ethics and society on the price prediction of CryptoPunks. Since the booming year of the NFT market in 2021, the discussion of CryptoPunks has propagated on social media. St

Phillip Kerger, Ryoji Miyazaki

We investigate a framework for binary image denoising via restricted Boltzmann machines (RBMs) that introduces a denoising objective in quadratic unconstrained binary optimization (QUBO) form and is well-suited for quantum annealing. The denoising objective is attained by balancing the distribution learned by a trained RBM with a penalty term for derivations

Yiqing Xu, Finale Doshi-Velez, David Hsu

Inverse reinforcement learning (IRL) algorithms often rely on (forward) reinforcement learning or planning, over a given time horizon, to compute an approximately optimal policy for a hypothesized reward function; they then match this policy with expert demonstrations. The time horizon plays a critical role in determining both the accuracy of reward estimate

Yufei Xie, Rodolfo C. Raga

This study addressed the complex task of sentiment analysis on a dataset of 119,988 original tweets from Weibo using a Convolutional Neural Network (CNN), offering a new approach to Natural Language Processing (NLP). The data, sourced from Baidu's PaddlePaddle AI platform, were meticulously preprocessed, tokenized, and categorized based on sentiment labels.

Lei Cao, Xiao Chen

In this note we research the Abelian Higgs model subject to the Born-Infeld theory of electrodynamics for which the BPS equations can be reduced into a quasi-linear differential equation. We show that the equation exists a unique solution under two interesting boundary conditions which realize the corresponding phase transition. We construct the solution thr

Ainesh Bakshi, Allen Liu, Ankur Moitra, Morris Yau

Recently Chen and Poor initiated the study of learning mixtures of linear dynamical systems. While linear dynamical systems already have wide-ranging applications in modeling time-series data, using mixture models can lead to a better fit or even a richer understanding of underlying subpopulations represented in the data. In this work we give a new approach

Huai-Yu Wang

In the author's previous works, it is derived from the Dirac equation that particles can have negative kinetic energy (NKE) solutions, and they should be treated on an equal footing as the positive kinetic energy (PKE) solutions. More than one NKE particles can make up a stable system by means of interactions between them and such a system has necessarily ne

Mickaël D. Chekroun, Honghu Liu, James C. McWilliams

A general, variational approach to derive low-order reduced systems is presented. The approach is based on the concept of optimal parameterizing manifold (OPM) that substitutes the more classical notions of invariant or slow manifold when breakdown of "slaving" occurs, i.e. when the unresolved variables cannot be expressed as an exact functional of the resol

Peiyu Zhang, Kaijian Chen, Chuanhou Zhang, Jiafang Liang

We employed caustic theory to analyze the propagation dynamics of partially coherent self-accelerating beams such as self-healing of partially coherent Airy beams. Our findings revealed that as the spatial coherence decreases, the self-healing ability of beams increases. This result have been demonstrated both in simulation and experiment. This is an innovat

François Le Gall

Duan, Wu and Zhou (FOCS 2023) recently obtained the improved upper bound on the exponent of square matrix multiplication $\omega<2.3719$ by introducing a new approach to quantify and compensate the ``combination loss" in prior analyses of powers of the Coppersmith-Winograd tensor. In this paper we show how to use this new approach to improve the exponent of

Jaemin Yoo, Yue Zhao, Lingxiao Zhao, Leman Akoglu

Self-supervised learning (SSL) has proven effective in solving various problems by generating internal supervisory signals. Unsupervised anomaly detection, which faces the high cost of obtaining true labels, is an area that can greatly benefit from SSL. However, recent literature suggests that tuning the hyperparameters (HP) of data augmentation functions is

Huafeng Li, Yanmei Mao, Yafei Zhang, Guanqiu Qi

Existing person re-identification (re-ID) research mainly focuses on pedestrian identity matching across cameras in adjacent areas. However, in reality, it is inevitable to face the problem of pedestrian identity matching across long-distance scenes. The cross-camera pedestrian samples collected from long-distance scenes often have no positive samples. It is

D. Y. Park, Y. H. Shin, Yongmin Kim

Methylammonium-lead-halide compounds have emerged as promising bandgap engineering materials due to their ability to fine-tune the energy gap through halogen element mixing. We present a comprehensive investigation of the temperature-dependent photoluminescence (PL) transition characteristics exhibited by single crystals of chlorine and bromine-based methyla

Arthur J. Parzygnat, Tadashi Takayanagi, Yusuke Taki, Zixia Wei

In this paper, we introduce a new quantity called SVD entanglement entropy. This is a generalization of entanglement entropy in that it depends on two different states, as in pre- and post-selection processes. This SVD entanglement entropy takes non-negative real values and is bounded by the logarithm of the Hilbert space dimensions. The SVD entanglement ent

Zeping Min, Jinbo Wang

This paper explores the integration of Large Language Models (LLMs) into Automatic Speech Recognition (ASR) systems to improve transcription accuracy. The increasing sophistication of LLMs, with their in-context learning capabilities and instruction-following behavior, has drawn significant attention in the field of Natural Language Processing (NLP). Our pri

Guanglian Li

We present the Wavelet-based Edge Multiscale Parareal (WEMP) Algorithm, recently proposed in [Li and Hu, {\it J. Comput. Phys.}, 2021], for efficiently solving subdiffusion equations with heterogeneous coefficients in long time. This algorithm combines the benefits of multiscale methods, which can handle heterogeneity in the spatial domain, and the strength

Yiming Quan, Shian Chen

This study presents a generalised least squares based method for fitting polygons and ellipses to data points. The method is based on a trigonometric fitness function that approximates a unit shape accurately, making it applicable to various geometric shapes with minimal fitting parameters. Furthermore, the proposed method does not require any constraints an

Haoran Wang, Qinghua Cheng, Baosheng Yu, Yibing Zhan

Egocentric action recognition is gaining significant attention in the field of human action recognition. In this paper, we address data scarcity issue in egocentric action recognition from a compositional generalization perspective. To tackle this problem, we propose a free-form composition network (FFCN) that can simultaneously learn disentangled verb, prep

CMS Collaboration

A search for the production of pairs of heavy Majorana neutrinos (N$_\ell$) from the decays of Z' bosons is performed using the CMS detector at the LHC. The data were collected in proton-proton collisions at a center-of-mass energy of $\sqrt{s}$ = 13 TeV, with an integrated luminosity of 138 fb$^{-1}$. The signature for the search is an excess in the invaria

Liangcheng Han, Haifan Yin

Superdirective array may achieve an array gain proportional to the square of the number of antennas $M^2$. In the early studies of superdirectivity, little research has been done from wireless communication point of view. To leverage superdirectivity for enhancing the spectral efficiency, this paper investigates multi-user communication systems with superdir

Shuo Huang, Zongxin Yang, Liangting Li, Yi Yang

Large-scale pre-trained vision-language models allow for the zero-shot text-based generation of 3D avatars. The previous state-of-the-art method utilized CLIP to supervise neural implicit models that reconstructed a human body mesh. However, this approach has two limitations. Firstly, the lack of avatar-specific models can cause facial distortion and unreali

Baojie Jiang, Jiawen Zhang

In this paper, we investigate the rigidity problems for geometric ideals in uniform Roe algebras associated to discrete metric spaces of bounded geometry. These ideals were introduced by Chen and Wang, and can be fully characterised in terms of ideals in the associated coarse structures. Our main result is that if two geometric ideals in uniform Roe algebras

Amogh Mannekote, Bonnie J. Dorr, Kristy Elizabeth Boyer

Automated negotiation support systems aim to help human negotiators reach more favorable outcomes in multi-issue negotiations (e.g., an employer and a candidate negotiating over issues such as salary, hours, and promotions before a job offer). To be successful, these systems must accurately track agreements reached by participants in real-time. Existing appr

Ming Zhang, Xiaoyu Mi, Linfeng Zhang, Chengyin Wu

The spin-dependent Berry force is a genuine effect of Berry curvature in molecular dynamics, which can dramatically result in spatial spin separation and change of reaction pathways. However, the way to probe the effect of Berry force remains challenging, because the time-reversal (TR) symmetry required for opposite Berry forces conflicts with TR symmetry br

Kenneth Ascher, Dori Bejleri, Harold Blum, Kristin DeVleming

We develop the moduli theory of boundary polarized CY pairs, which are slc Calabi-Yau pairs $(X,D)$ such that $D$ is ample. The motivation for studying this moduli problem is to construct a moduli space at the Calabi-Yau wall interpolating between certain K-moduli and KSBA moduli spaces. We prove that the moduli stack of boundary polarized CY pairs is S-comp

Catrin Hasselgren, Tudor I. Oprea

Drug discovery is adapting to novel technologies such as data science, informatics, and artificial intelligence (AI) to accelerate effective treatment development while reducing costs and animal experiments. AI is transforming drug discovery, as indicated by increasing interest from investors, industrial and academic scientists, and legislators. Successful d

Khondokar Fida Hasan, Leonie Simpson, Mir Ali Rezazadeh Baee, Chadni Islam

Quantum computing is emerging as a significant threat to information protected by widely used cryptographic systems. Cryptographic methods, once deemed secure for decades, are now at risk of being compromised, posing a massive threat to the security of sensitive data and communications across enterprises worldwide. As a result, there is an urgent need to mig

Patricio Gaete, J. A. Helayël-Neto

We examine the electromagnetic radiation produced by a moving charge in the QED vacuum that behaves as a dispersive medium characterized by a geometrical structure (discreteness/granularity) that emerges from loop quantum gravity. It is shown that the radiation is driven by the refractive vacuum the charged particle travels through reproducing the profile of

Glen Berman

Machine Learning (ML) systems, particularly when deployed in high-stakes domains, are deeply consequential. They can exacerbate existing inequities, create new modes of discrimination, and reify outdated social constructs. Accordingly, the social context (i.e. organisations, teams, cultures) in which ML systems are developed is a site of active research for

Jonah Blasiak, Mark Haiman, Jennifer Morse, Anna Pun

We give an explicit raising operator formula for the modified Macdonald polynomials $\tilde{H}_{\mu }(X;q,t)$, which follows from our recent formula for $\nabla$ on an LLT polynomial and the Haglund-Haiman-Loehr formula expressing modified Macdonald polynomials as sums of LLT polynomials. Our method just as easily yields a formula for a family of symmetric f

Koki Eto, Yoshihiko Okamoto, Naoyuki Katayama, Hajime Ishikawa

NaPrTe2, NaNdTe2, and NaTbTe2 are found to be triangular lattice magnets with the alpha-NaFeO2 structure, where lanthanoid atoms with 4f electrons form a triangular lattice, based on the structural analysis and physical property measurements of synthesized polycrystalline samples. The alpha-NaFeO2 structure is a new polymorph of NaPrTe2, which has been repor

Sihang Li, Kuangzheng Li, Haibing Lu

Many companies and organizations have started to use some form of AIenabled auto mated tools to assist in their hiring process, e.g. screening resumes, interviewing candi dates, performance evaluation. While those AI tools have greatly improved human re source operations efficiency and provided conveniences to job seekers as well, there are increasing concer

Jiu-Long Wang, Yi-Feng Zhao, Wen Xu, Jun-Ding Zheng

Low-dimensional ferroelectric tunnel junctions are appealing for the realization of nanoscale nonvolatile memory devices due to their inherent advantage of device miniaturization. Those based on current mechanisms still have restrictions including low tunneling electroresistance (TER) effects and complex heterostructures. Here, we introduce an entirely new T

Daniil Klyuev

Let $\mathcal{A}$ be a quantized ($K$-theoretic) BFN Coulomb branch with $G=\mathbb{C}^*$ and any $N$, that is, $\mathcal{A}$ is a generalized Weyl or $q$-Weyl algebra. Let $M$ be an $\mathcal{A}$-$\overline{\mathcal{A}}$ bimodule. Choosing an automorphism $\rho$ of $\mathcal{A}$ we can define the notion of an invariant Hermitian form: $(au,v)=(u,v\rho(a))$

Qiuyi, Zhang, Michael S. Lee, Sherol Chen

Beliefs and values are increasingly being incorporated into our AI systems through alignment processes, such as carefully curating data collection principles or regularizing the loss function used for training. However, the meta-alignment problem is that these human beliefs are diverse and not aligned across populations; furthermore, the implicit strength of

Noriaki Kawaguchi

We study a special type of shadowing (DSP) of chain transitive continuous self-maps of compact Hausdorff spaces. We prove some basic properties of DSP. As application of DSP, we obtain sufficient conditions for a statistical variant of $\omega$-chaos and prove the topological genericity of it. We also consider topological distribution of irregular points und

Zihao Song

We are concerned with the global solution of the compressible Euler-Korteweg equations in $\mathbb{R}^{3}$. In the case of zero sound speed $P'(\rho^{\ast})=0$, it is found that the perturbation problem of irrotational fluids could be reformulated into a quasi-linear Schr$\ddot{o}$dinger equation. Based on techniques of dispersive estimates and methods of no

Xuda Ye, Zhennan Zhou

The quantum thermal average plays a central role in describing the thermodynamic properties of a quantum system. Path integral molecular dynamics (PIMD) is a prevailing approach for computing quantum thermal averages by approximating the quantum partition function as a classical isomorphism on an augmented space, enabling efficient classical sampling, but th

Benjamin Fields, Sohom Gupta, McCullen Sandora

We propose the mathematical notion of information gain as a way of quantitatively assessing the value of biosignature missions. This makes it simple to determine how mission value depends on design parameters, prior knowledge, and input assumptions. We demonstrate the utility of this framework by applying it to a plethora of case examples: the minimal number

Eliza M. -R. Kempton, Madeline Lessard, Matej Malik, Leslie A. Rogers

It remains to be ascertained whether sub-Neptune exoplanets primarily possess hydrogen-rich atmospheres or whether a population of H$_2$O-rich "water worlds" lurks in their midst. Addressing this question requires improved modeling of water-rich exoplanetary atmospheres, both to predict and interpret spectroscopic observations and to serve as upper boundary

Romain Hardy, Joe Klepich, Ryan Mitchell, Steve Hall

Integrating deep learning with clinical expertise holds great potential for addressing healthcare challenges and empowering medical professionals with improved diagnostic tools. However, the need for annotated medical images is often an obstacle to leveraging the full power of machine learning models. Our research demonstrates that by combining synthetic ima