December 2024 arXiv papers — page 207

Hamed Haggi, James M. Fenton

The decreasing costs of photovoltaic (PV) systems and battery storage, alongside the rapid rise of electric vehicles (EVs), present a unique opportunity to revolutionize energy use in apartment complexes. Generating electricity via PV and batteries is currently cheaper and greener than relying on grid power, which is often expensive. Yet, residents in multi-

Hamed Haggi, James M. Fenton

Recent advancements, net-zero emission policies, along with declining costs of renewable energy, battery storage, and electric vehicles (EVs), are accelerating the transition toward cleaner, more resilient energy systems. This paper conducts a comprehensive techno-economic analysis of Net-Zero Energy Buildings (NZEBs) within Florida's energy transition by 20

Hamed Haggi, Wei Sun

As the adoption of distributed energy resources grows, power systems are becoming increasingly complex and vulnerable to disruptions, such as natural disasters and cyber-physical threats. Peer-to-peer (P2P) energy markets offer a practical solution to enhance reliability and resilience during power outages while providing monetary and technical benefits to p

Gairola Shashank, Smitha Subramanian, Sreedevi M., Shyam H Menon

Molecular clouds fragment under the action of supersonic turbulence & gravity which results in a scale-free hierarchical distribution of star formation (SF) within galaxies. Recent studies suggest that the hierarchical distribution of SF in nearby galaxies shows a dependence on host galaxy properties. In this context, we study the nature of hierarchical SF f

Junyi Han

Studying hyper-nuclei yields and their collectivity can shed light on their production mechanism as well as the hyperon-nucleon interactions. Heavy-ion collisions from the RHIC beam energy scan phase II (BES-II) provide an unique opportunity to understand these at high baryon densities. In these proceedings, we present a systematic study on energy dependence

Lele Cong, Kaitao Meng, Deshi Li, Hao Jiang

Low-latency and high-precision vehicle localization plays a significant role in enhancing traffic safety and improving traffic management for intelligent transportation. However, in complex road environments, the low latency and high precision requirements could not always be fulfilled due to the high complexity of localization computation. To tackle this is

Thilini Wijesiriwardene, Ruwan Wickramarachchi, Sreeram Vennam, Vinija Jain

Making analogies is fundamental to cognition. Proportional analogies, which consist of four terms, are often used to assess linguistic and cognitive abilities. For instance, completing analogies like "Oxygen is to Gas as <blank> is to <blank>" requires identifying the semantic relationship (e.g., "type of") between the first pair of terms ("Oxygen" and "Gas"

Paulius Rauba, Qiyao Wei, Mihaela van der Schaar

We consider the problem of quantifying how an input perturbation impacts the outputs of large language models (LLMs), a fundamental task for model reliability and post-hoc interpretability. A key obstacle in this domain is disentangling the meaningful changes in model responses from the intrinsic stochasticity of LLM outputs. To overcome this, we introduce D

Aleksandr Rusakov, Pavel Abolmasov, Omer Bromberg

A weakly magnetized neutron star (NS) undergoing disk accretion should release about a half of its power in a compact region known as the accretion boundary layer. Latitudinal spread of the accreted matter and efficient radiative cooling justify the approach to this flow as a two-dimensional spreading layer (SL) on the surface of the star. Numerical simulati

Mehdi Sadeghi

In this paper, we examine Einstein-Hilbert gravity featuring a cosmological constant and a non-abelian nonlinear electromagnetic field that is minimally coupled to gravity. We first present the black brane solution for this model and subsequently calculate the color non-abelian DC conductivity for this solution using AdS/CFT duality. Our results retrieve the

Dahmane Dechicha

This paper is devoted to the study of a kinetic Fokker-Planck equation with general heavy-tailed equilibrium without an explicit formula, such as $C_\beta \langle v \rangle^{-\beta}$, in particular non-symmetric and non-centred. This work extends the results obtained in [Dechicha and Puel, 2023] and [Dechicha and Puel, Asymptot. Anal., 2024]. We prove that i

Kyriakos Flouris, Anna Volokitin, Gustav Bredell, Ender Konukoglu

The autoencoder model typically uses an encoder to map data to a lower dimensional latent space and a decoder to reconstruct it. However, relying on an encoder for inversion can lead to suboptimal representations, particularly limiting in physical sciences where precision is key. We introduce a decoder-only method using gradient flow to directly encode data

Arijit Samal, Haroon R Lone

Non-invasive temperature monitoring of individuals plays a crucial role in identifying and isolating symptomatic individuals. Temperature monitoring becomes particularly vital in settings characterized by close human proximity, often referred to as dense settings. However, existing research on non-invasive temperature estimation using thermal cameras has pre

Songjie Xie, Hengtao He, Shenghui Song, Jun Zhang

Task-oriented communication presents a promising approach to improve the communication efficiency of edge inference systems by optimizing learning-based modules to extract and transmit relevant task information. However, real-time applications face practical challenges, such as incomplete coverage and potential malfunctions of edge servers. This situation ne

Robert M. Corless, Nicolas Fillion

The classical WKB method (also known as the WKBJ method, the LG method, or the phase integral method) for solving singularly perturbed linear differential equations has never, as far as we know, been looked at from the structured backward error (BEA) point of view. This is somewhat surprising, because a simple computation shows that for some important proble

Jack Belham, Aryan Bhosale, Samrat Mukherjee, Biplab Banerjee

The aim of this paper is to formalise the task of continual semi-supervised anomaly detection (CSAD), with the aim of highlighting the importance of such a problem formulation which assumes as close to real-world conditions as possible. After an overview of the relevant definitions of continual semi-supervised learning, its components, anomaly detection exte

Wei-Jian Li, Da-Fei Sun, Sheng Ju, Ai-Lei He

The interplay between topology and magnetism often triggers the exotic quantum phases. Here, we report an accessible scheme to engineer the robust $\mathbb{Z}_{2}$ topology by intrinsic magnetism, originating from the zigzag segment connecting two armchair segments with different width, in one-dimensional graphene nanoribbon heterojunctions. Our first-princi

Gianluca Ceruti, Jonas Kusch, Christian Lubich, Dominik Sulz

Computing the numerical solution to high-dimensional tensor differential equations can lead to prohibitive computational costs and memory requirements. To reduce the memory and computational footprint, dynamical low-rank approximation (DLRA) has proven to be a promising approach. DLRA represents the solution as a low-rank tensor factorization and evolves the

Bohai Gu, Hao Luo, Song Guo, Peiran Dong

The text-guided video inpainting technique has significantly improved the performance of content generation applications. A recent family for these improvements uses diffusion models, which have become essential for achieving high-quality video inpainting results, yet they still face performance bottlenecks in temporal consistency and computational efficienc

Kyuwon Kim, Yige Chen, Eunkyul Leah Jo, KyungTae Lim

Critique has surfaced concerning the existing linguistic annotation framework for Korean Universal Dependencies (UDs), particularly in relation to syntactic relationships. In this paper, our primary objective is to refine the definition of syntactic dependency of UDs within the context of analyzing the Korean language. Our aim is not only to achieve a consen

A. B. Lucy, J. L. Sokoloski, G. J. M. Luna, K. Mukai

Symbiotic stars are binaries in which a cool and evolved star of luminosity class I-III accretes onto a smaller companion. However, direct accretion signatures like disc flickering and boundary layer X-rays are typically outshone or suppressed by the luminous giant, shell burning on the accreting white dwarf, and the illuminated wind nebula. We present a new

Shelley Hebert, Slawomir Klimek, Matt McBride

We discuss C$^*$-algebras associated with several different natural shifts on the Hilbert space of the $s$-adic tree, that is, the tree of balls in the space of $s$-adic integers.

Bruno Sicardy, Maryame El Moutamid, Stefan Renner, Rafael Sfair

Until about a decade ago, ring systems were only known to exist around giant planets. Each one of the four giant planets harbours its own distinctive and unique system of rings and inner satellites. The past decade has been marked by the unexpected discoveries of dense rings around small objects of the outer solar system: the Centaur object Chariklo (and pos

Yichao Fu, Keun-Young Kim

We investigate holographic complexities in the context of wedge holography, focusing specifically on black string geometry in AdS$_3$. The wedge spacetime is bounded by two end-of-the-world (EOW) branes with intrinsic Dvali-Gabadadze-Porrati (DGP) gravity. In line with this codimension-two holography, there are three equivalent perspectives: bulk perspective

Weihang Li, Weirong Chen, Shenhan Qian, Jiajie Chen

Recent advances in 3D Gaussian Splatting have shown promising results. Existing methods typically assume static scenes and/or multiple images with prior poses. Dynamics, sparse views, and unknown poses significantly increase the problem complexity due to insufficient geometric constraints. To overcome this challenge, we propose a method that can use only two

Eunhee Ko, Myungshin Im, Seong-Kook Lee, Clotilde Laigle

It is yet to be understood how large-scale environments influence star formation activity in galaxy clusters. One recently proposed mechanism is that galaxy clusters can remain star-forming when fed by infalling groups and star-forming galaxies from large-scale structures surrounding them (the \textit{``web-feeding model"}). Using the COSMOS2020 catalog that

Goshi Aoki

The advancement of generative AI, particularly large language models (LLMs), has a significant impact on politics and democracy, offering potential across various domains, including policymaking, political communication, analysis, and governance. This paper surveys the recent and potential applications of LLMs in politics, examining both their promises and t

Melanie Gauthier, Svenja Huntemann

Snort is a two-player game played on a simple graph in which the players take turns colouring vertices in their own colour, with the restriction that two adjacent vertices cannot have opposite colours. We will show that on triangular grids with one or two rows of triangles, and many of their variants, the first player will win when playing optimally.

Wojciech Broniowski, Enrique Ruiz Arriola

We present general features of the transverse densities of the stress-energy-momentum tensor $\Theta^{\mu\nu}$ in the pion. We show positivity of the transverse density of $\Theta^{++}$ (analogous to the positivity of the transverse density of the electromagnetic current $J^+$) and discuss its consequences in conjunction with analyticity and quark-hadron dua

Matthias Georg Mayer

Structural independence is the (conditional) independence that arises from the structure rather than the precise numerical values of a distribution. We develop this concept and relate it to $d$-separation and structural causal models. Formally, let $U = (U_i)_{i \in I}$ be an independent family of random elements on a probability space $(\Omega, \mathcal{A},

Avinash Anand, Raj Jaiswal, Abhishek Dharmadhikari, Atharva Marathe

This paper presents GPSM4K, a comprehensive geometry multimodal dataset tailored to augment the problem-solving capabilities of Large Vision Language Models (LVLMs). GPSM4K encompasses 2157 multimodal question-answer pairs manually extracted from mathematics textbooks spanning grades 7-12 and is further augmented to 5340 problems, consisting of both numerica

Ronghan Chen, Yang Cong, Jiayue Liu

This paper presents a Surface-Aligned Gaussian representation for creating animatable human avatars from monocular videos,aiming at improving the novel view and pose synthesis performance while ensuring fast training and real-time rendering. Recently,3DGS has emerged as a more efficient and expressive alternative to NeRF, and has been used for creating dynam

Ghazala Yasmin, Aditi Sharma

The "2-variable general-$\lambda$-matrix polynomials (2VG$\lambda$MP)" is a new family of matrix polynomials, introduced and studied in this article. These matrix polynomials are constructed using umbral and symbolic methods. We delve into the generating function, explicit series representation, differential equation, quasi-monomiality, summation formula, de

Jianzhe Luo, Wenyun Lu, Pengcheng Jiao, Daeik Jang

Despite significant advancements in wireless smart implants over the last two decades, current implantable devices still operate passively and require additional electronic modules for wireless transmission of the stored biological data. To address these challenges, we propose an innovative wireless force sensing paradigm for implantable systems through the

Edyta Bartnicka

Let $\Gamma_k(V)$ be the Grassmann graph whose vertex set is formed by all $k$-dimensional subspaces of an $n$-dimensional vector space $V$ over the finite field $F_q$ consisting of $q$ elements. We discuss its subgraph $\Pi(n,k)_q$ formed by projective codes. We show that there are precisely two types of maximal cliques in $\Pi(n,k)_q$: stars and tops. We g

Yiyu Li, Liangang Peng

Let $\mathcal{A}$ be an arbitrary hereditary abelian category. Lu and Peng defined the semi-derived Ringel-Hall algebra $SH(\mathcal{A})$ of $\mathcal{A}$ and proved that $SH(\mathcal{A})$ has a natural basis and is isomorphic to the Drinfeld double Ringel-Hall algebra of $\mathcal{A}$. In this paper, we introduce a coproduct formula on $SH(\mathcal{A})$ wit

Dengqiang Jia, Xinnian Yang, Xiaosong Xiong, Shijie Huang

Vessel dynamics simulation is vital in studying the relationship between geometry and vascular disease progression. Reliable dynamics simulation relies on high-quality vascular meshes. Most of the existing mesh generation methods highly depend on manual annotation, which is time-consuming and laborious, usually facing challenges such as branch merging and ve

Morimichi Kawasaki, Mitsuaki Kimura, Hiroki Kodama, Yoshifumi Matsuda

Many transformation groups on manifolds are simple, but their universal coverings are not. In the present paper, we study the concept of relatively simple group, that is, a group with the maximum proper normal subgroup. We show that many examples of universal coverings of transformation groups are relatively simple, including the universal covering $\widetil

Zhi-Qiang Li, Dmitry E. Pelinovsky, Shou-Fu Tian

The newly discovered exponential and algebraic double-soliton solutions of the massive Thirring model in laboratory coordinates are placed in the context of the inverse scattering transform. We show that the exponential double-solitons correspond to double isolated eigenvalues in the Lax spectrum, whereas the algebraic double-solitons correspond to double em

Jin Lyu, Tianyi Zhu, Yi Gu, Li Lin

Quantitative analysis of animal behavior and biomechanics requires accurate animal pose and shape estimation across species, and is important for animal welfare and biological research. However, the small network capacity of previous methods and limited multi-species dataset leave this problem underexplored. To this end, this paper presents AniMer to estimat

Edward Kembery, Ben Bucknall, Morgan Simpson

The downstream use cases, benefits, and risks of AI systems depend significantly on the access afforded to the system, and to whom. However, the downstream implications of different access styles are not well understood, making it difficult for decision-makers to govern model access responsibly. Consequently, we spotlight Model Access Governance, an emerging

Christian Möller, Niklas Funk, Jan Peters

Object pose estimation from a single view remains a challenging problem. In particular, partial observability, occlusions, and object symmetries eventually result in pose ambiguity. To account for this multimodality, this work proposes training a diffusion-based generative model for 6D object pose estimation. During inference, the trained generative model al

Andrea Pascucci, Alessio Rondelli

This work revisits the well-posedness of non-degenerate McKean-Vlasov stochastic differential equations with H\"older continuous coefficients, recently established by Chaudru de Raynal. We provide a streamlined and direct proof that leverages standard Gaussian estimates for uniformly parabolic PDEs, bypassing the need for derivatives with respect to the meas

Yan Li, Yifei Xing, Xiangyuan Lan, Xin Li

Cross-modal alignment is crucial for multimodal representation fusion due to the inherent heterogeneity between modalities. While Transformer-based methods have shown promising results in modeling inter-modal relationships, their quadratic computational complexity limits their applicability to long-sequence or large-scale data. Although recent Mamba-based ap

Shaoyu Liu, Jianing Li, Guanghui Zhao, Yunjian Zhang

Event cameras record visual information as asynchronous pixel change streams, excelling at scene perception under unsatisfactory lighting or high-dynamic conditions. Existing multimodal large language models (MLLMs) concentrate on natural RGB images, failing in scenarios where event data fits better. In this paper, we introduce EventGPT, the first MLLM for e

Maximilian Rutz, Pia Neuberger, Simon Pick, Torsten Straßer

Augmented reality display performance depends strongly on features of the human visual system. This is especially true for retinal scan glasses, which use laser beam scanning and transparent holographic optical combiners. Human-centered approaches allow us to go beyond conventional optical metrology and evaluate display performance as it is perceived in actu

Eyad Algahtani

We present SPILDL, a Scalable and Parallel Inductive Learner in Description Logic (DL). SPILDL is based on the DL-Learner (the state of the art in DL-based ILP learning). As a DL-based ILP learner, SPILDL targets the $\mathcal{ALCQI}^{\mathcal{(D)}}$ DL language, and can learn DL hypotheses expressed as disjunctions of conjunctions (using the $\sqcup$ operat

Jian Qin, Pengjie Zhang, Yu Yu, Haojie Xu

In \citep{Qin+}, we attempted to reconstruct the weak lensing convergence map $\hat{\kappa}$ from cosmic magnification by linearly weighting the DECaLS galaxy overdensities in different magnitude bins of $grz$ photometry bands. The $\hat{\kappa}$ map is correlated with cosmic shear at 20-$\sigma$ significance. However, the low galaxy number density in the DE

Xin Yin, Chao Ni, Xiaodan Xu, Xiaohu Yang

Software defects heavily affect software's functionalities and may cause huge losses. Recently, many AI-based approaches have been proposed to detect defects, which can be divided into two categories: software defect prediction and automatic unit test generation. While these approaches have made great progress in software defect detection, they still have se

Bo-Chuan Lin, Chun-Wei Kong, Simone Semeraro, Jay W. McMahon

A control framework is presented to solve the rendezvous and proximity operations (RPO) problem of the EP-Gemini mission. In this mission, a CubeSat chaser is controlled to approach and circumnavigate the other uncooperative CubeSat target. Such a problem is challenging because the chaser operates on a single electric propulsion thruster, for which coupling

L. Balkenhol

The compression of multi-frequency cosmic microwave background (CMB) power spectrum measurements into a series of foreground-marginalised CMB-only band powers allows for the construction of faster and more easily interpretable 'lite' likelihoods. However, obtaining the compressed data vector is computationally expensive and yields a covariance matrix with sa

Yan Liu

This paper provides an exploration of parking functions, a classical combinatorial object. We present two viewpoints on their structure and properties: through poset of noncrossing partitions and polytopes.

Vsevolod Gubarev

We describe all Rota-Baxter operators $R$ of weight zero on the matrix algebra $M_3(F)$ over a quadratically closed field $F$ of characteristic not 2 or 3 such that $R(1)\neq0$. Thus, we get a partial classification of solutions to the associative Yang-Baxter equation on $M_3(F)$. For the solution, the computer algebra system Singular was involved.

Ishwar Kant, Ayushi Awasthi, Arushi Sharma, Shikha Awasthi

In this paper, the inverse potentials for the resonant f states of {\alpha}-3H and {\alpha}-3He are constructed using the phase function method by utilizing an ab-initio approach. A combination of three Morse functions are joined smoothly to prepare the reference potential. While the regular Morse function captures the nuclear and Coulomb interactions at sho

Casey Bradshaw, David M. Blei

In an effort to quantify and combat sexual assault, US colleges and universities are required to disclose the number of reported sexual assaults on their campuses each year. However, many instances of sexual assault are never reported to authorities, and consequently the number of reported assaults does not fully reflect the true total number of assaults tha

Matteo D'Achille

We construct and study the ideal Poisson--Voronoi tessellation of the product of two hyperbolic planes $\mathbb{H}_{2}\times \mathbb{H}_{2}$ endowed with the $L^{1}$ norm. We prove that its law is invariant under all isometries of this space and study some geometric features of its cells. Among other things, we prove that the set of points at equal separatio

Raj Jaiswal, Dhruv Jain, Harsh Parimal Popat, Avinash Anand

Large Language Models (LLMs) demonstrate remarkable capabilities in various reasoning tasks. However, they encounter significant challenges when it comes to scientific reasoning, particularly in physics, which requires not only mathematical reasoning but also factual and conceptual understanding. When addressing complex physics problems, LLMs typically face

Feng Wang, Shengyu Zhang, Huiting Yang, Tony Q. S. Quek

From 5G onwards, Non-Terrestrial Networks (NTNs) have emerged as a key component of future network architectures. Leveraging Low Earth Orbit (LEO) satellite constellations, NTNs are capable of building a space Internet and present a paradigm shift in delivering mobile services to even the most remote regions on Earth. However, the extensive coverage and rapi

V. Torlao, E. A. Fajardo

Determining the stability of chemical compounds is essential for advancing material discovery. In this study, we introduce a novel deep neural network model designed to predict a crystal's formation energy, which identifies its stability property. Our model leverages elemental fractions derived from material composition and incorporates the symmetry classifi

Yuhao Lin, Lingqiao Liu, Javen Shi

Animal re-identification (ReID) has become an indispensable tool in ecological research, playing a critical role in tracking population dynamics, analyzing behavioral patterns, and assessing ecological impacts, all of which are vital for informed conservation strategies. Unlike human ReID, animal ReID faces significant challenges due to the high variability

Hussein Cheikh-Ali, Bruno Premoselli

Let $\Omega$ be a bounded, smooth connected open domain in $\mathbb{R}^n$ with $n\geq 3$. We investigate in this paper compactness properties for the set of sign-changing solutions $v \in H^1_0(\Omega)$ of \begin{equation} \tag{*} -\Delta v+h v =\left|v\right|^{2^*-2}v \hbox{ in } \Omega, \quad v = 0 \hbox{ on } \partial \Omega \end{equation} where $h\in C^1

Hang Su, Ling Gao, Tao Liu, Laurent Kneip

As the ubiquity of smart mobile devices continues to rise, Optical Camera Communication systems have gained more attention as a solution for efficient and private data streaming. This system utilizes optical cameras to receive data from digital screens via visible light. Despite their promise, most of them are hindered by dynamic factors such as screen refre

Yitian Feng, Weiqiang Zhu, Xinzheng Lu

Ground motion prediction (GMP) models are critical for hazard reduction before, during and after destructive earthquakes. In these three stages, intensity forecasting, early warning and interpolation models are corresponding employed to assess the risk. Considering the high cost in numerical methods and the oversimplification in statistical methods, deep-lea

Zhaofeng Luo, Zhitong Cui, Shijian Luo, Mengyu Chu

We introduce VR-Doh, an open-source, hands-on 3D modeling system that enables intuitive creation and manipulation of elastoplastic objects in Virtual Reality (VR). By customizing the Material Point Method (MPM) for real-time simulation of hand-induced large deformations and enhancing 3D Gaussian Splatting for seamless rendering, VR-Doh provides an interactiv

Pablo Leon, B. Mishra, Y. Gomez-Leyton, Francisco Tello-Ortiz

Through gravitational decoupling using the extended minimal geometric deformation, a new family of static and rotating ``hairy'' black holes is provided. The background of these models is a generic Schwarzschild metric containing as special cases, the Schwarzschild, Schwarzschild-dS, Reissner-Nordstrom and Reissner-Nordstrom-dS black holes. Assuming the Kerr

Bin Li, Li Li, Zhenwei Zhang, Yuping Duan

Underwater optical images inevitably suffer from various degradation factors such as blurring, low contrast, and color distortion, which hinder the accuracy of object detection tasks. Due to the lack of paired underwater/clean images, most research methods adopt a strategy of first enhancing and then detecting, resulting in a lack of feature communication be

Jiafeng Xia, Dongsheng Li, Hansu Gu, Tun Lu

Sequential recommendation methods can capture dynamic user preferences from user historical interactions to achieve better performance. However, most existing methods only use past information extracted from user historical interactions to train the models, leading to the deviations of user preference modeling. Besides past information, future information is

Peng Guo, Frank X. Lee

The formalism developed in Refs.\cite{Guo:2023ecc,Guo:2024zal} that connects integrated correlation function of a trapped two-particle system to infinite volume scattering phase shift is further extended to coupled-channel systems in the present work. Using a trapped non-relativistic two-channel system as an example, a new relation is derived that retains th

Peijun Bao, Chenqi Kong, Zihao Shao, Boon Poh Ng

Given a natural language query, video moment retrieval aims to localize the described temporal moment in an untrimmed video. A major challenge of this task is its heavy dependence on labor-intensive annotations for training. Unlike existing works that directly train models on manually curated data, we propose a novel paradigm to reduce annotation costs: pret

Yan Yan, Yuanchi Ma

Outline generation aims to reveal the internal structure of a document by identifying underlying chapter relationships and generating corresponding chapter summaries. Although existing deep learning methods and large models perform well on small- and medium-sized texts, they struggle to produce readable outlines for very long texts (such as fictional works),

Vladislav Egorov, Boris Kryzhanovsky

The 1/t Wang-Landau algorithm is analyzed from the viewpoint of execution time and accuracy when it is used in computations of the density of states of a two-dimensional Ising model. We find that the simulation results have a systematic error, the magnitude of which decreases with increasing the lattice size. The relative error has two maxima: the first one

Sergio Yanez-Pagans, Nathan Harkema, Arvinder Sandhu, Coleman Cariker

We study the nonlinear optical response of argon to a four-wave-mixing pulse sequence consisting of an extreme ultraviolet pulse, an overlapping collinear IR and an non-collinear delayed IR pulses. Absorption of an extreme ultraviolet and an IR photon from the collinear beams excites, sequentially, the $3s^{-1}4p$ bright state and the {$3s^{-1}3d/5s$} dark s

Jingyi Zhao, Yuxuan Ou, Austin Tripp, Morteza Rasoulianboroujeni

Ionizable lipids are essential in developing lipid nanoparticles (LNPs) for effective messenger RNA (mRNA) delivery. While traditional methods for designing new ionizable lipids are typically time-consuming, deep generative models have emerged as a powerful solution, significantly accelerating the molecular discovery process. However, a practical challenge a

Philip L. Lederer, Christoph Lehrenfeld, Paul Stocker, Igor Voulis

This paper presents a framework for the analysis of discretization methods based on the decomposition into local and global problems. We apply the framework to provide a comprehensive error analysis for the embedded Trefftz discontinuous Galerkin method, for a wide range of second-order scalar elliptic partial differential equations and a scalar reaction-adv

Motoko Fujiwara, Gonzalo Herrera, Shunsaku Horiuchi

Multi-messenger observations of astrophysical transients provide powerful probes of the underlying physics of the source as well as beyond the Standard Model effects. We explore transients that can occur in the vicinity of supermassive black holes at the center of galaxies, including tidal disruption events (TDEs), certain types of blazars, or even supernova

Junhyuk Choi, Yeseon Hong, Minju Kim, Bugeun Kim

Large Language Models (LLMs) show impressive conversational abilities but sometimes show identity drift problems, where their interaction patterns or styles change over time. As the problem has not been thoroughly examined yet, this study examines identity consistency across nine LLMs. Specifically, we (1) investigate whether LLMs could maintain consistent p

Jia-Qi Gong, Ji-Chong Yang

Recent advancements in quantum computing technology have enabled the study of fermionic systems at finite temperature via quantum simulations. This presents a novel approach to investigating the chiral phase transition in such systems. Among these, the quantum minimally entangled typical thermal states~(QMETTS) algorithm has recently attracted considerable i

Eyad Algahtani

We present High-Throughput Hypothesis Evaluation in Description Logic (HT-HEDL). HT-HEDL is a high-performance hypothesis evaluation engine that accelerates hypothesis evaluation computations for inductive logic programming (ILP) learners using description logic (DL) for their knowledge representation; in particular, HT-HEDL targets accelerating computations

Zhanyu Ma, Matan Lotem, Yigal Meir, Eran Sela

The interacting resonant level model (IRLM) is the simplest quantum impurity model to display strongly correlated effects in mesoscopic systems, which triggered its extensive theoretical study. However, to date, there have not been any realizations of the model with controllable interaction parameter, and thus the detailed predictions could not be confirmed.

Weiche Hsieh, Ziqian Bi, Chuanqi Jiang, Junyu Liu

Explainable Artificial Intelligence (XAI) addresses the growing need for transparency and interpretability in AI systems, enabling trust and accountability in decision-making processes. This book offers a comprehensive guide to XAI, bridging foundational concepts with advanced methodologies. It explores interpretability in traditional models such as Decision

Yuxiang Qin, Andrei Mesinger, David Prelogović, George Becker

The Lyman alpha (Lya) forest in the spectra of z>5 quasars provides a powerful probe of the late stages of the Epoch of Reionization (EoR). With the recent advent of exquisite datasets such as XQR-30, many models have struggled to reproduce the observed large-scale fluctuations in the Lya opacity. Here we introduce a Bayesian analysis framework that forward-

Seockbean Song, Youngsik Yoon, Siwei Wang, Wei Chen

Combinatorial online learning is a fundamental task for selecting the optimal action (or super arm) as a combination of base arms in sequential interactions with systems providing stochastic rewards. It is applicable to diverse domains such as robotics, social advertising, network routing, and recommendation systems. In many real-world scenarios, we often en

Jianhui Li, Bokang Zhang, Junfeng Wu

This paper proposes an online environment poisoning algorithm tailored for reinforcement learning agents operating in a black-box setting, where an adversary deliberately manipulates training data to lead the agent toward a mischievous policy. In contrast to prior studies that primarily investigate white-box settings, we focus on a scenario characterized by

Zhuo Chen, Fei Shi, Qi Zhao

Quantum entanglement and nonlocality are foundational to quantum technologies, driving quantum computation, communication, and cryptography innovations. To benchmark the capabilities of these quantum techniques, efficient detection and accurate quantification methods are indispensable. This paper focuses on the concept of "detection length" -- a metric that

Julia Ingles-Cerrillo, Pablo Ibanez-Romero, Rajveer Fandan, Jorge Pedros

Negative index metamaterials (NIMs) can be achieved with uniaxial hyperbolic metamaterials (HMMs) featuring $\epsilon_{parallel}>0$ and $\epsilon_{perpendicular}<0$. This type of approach has been traditionally realized using stacked doped/undoped semiconductor layers. Only recently surface phonon polaritons (SPhPs) have emerged as a promising low-loss alter

Roman N. Lee

We calculate a subset of two-loop master integrals relevant for the differential cross section of $e^+e^-\to \mu^+\mu^-$ process. We consider only those families for which the account of the electron mass $m$ is necessary. Our results have the form of the Frobenius series in $m$ with coefficients expressed via Goncharov's polylogarithms.

Yaorui Tan, Maolin Bo

This study systematically investigates the electronic structure and bonding properties of two-dimensional bilayer transition metal chalcogenides MX2 (M = Mo, W; X = S, Se, Te) using density functional theory calculations. By analyzing band gaps, deformation bond energies, and non-Hermitian bonding characteristics across various MX2 compounds, we comprehensiv

Ved Prakash, Upadhyayula M. M. A. Sai Gopal, Sanhita Das, Ananth Ramaswamy

Continuum damage mechanics (CDM) is a popular framework for modelling crack propagation in solids. The CDM uses a damage parameter to quantitatively assess what one loosely calls `material degradation'. While this parameter is sometimes given a physical meaning, the mathematical equations for its evolution are generally not consistent with such physical inte

Hedieh Abdollahi, Atefeh Javadi, Jacco Th. van Loon, Iain McDonald

We conducted an extensive study of the spheroidal dwarf satellite galaxies around the Andromeda galaxy to produce an extensive catalog of LPV stars. The optical monitoring project consists of 55 dwarf galaxies and four globular clusters that are members of the Local Group. We have made observations of these galaxies using the WFC mounted on the 2.5 m INT in

Varshita Kolipaka, Akshit Sinha, Debangan Mishra, Sumit Kumar

Graph Neural Networks (GNNs) are increasingly being used for a variety of ML applications on graph data. Because graph data does not follow the independently and identically distributed (i.i.d.) assumption, adversarial manipulations or incorrect data can propagate to other data points through message passing, which deteriorates the model's performance. To al

Rulin Zhou, Yingjie Feng, Guankun Wang, Xiaopin Zhong

Adenoid hypertrophy stands as a common cause of obstructive sleep apnea-hypopnea syndrome in children. It is characterized by snoring, nasal congestion, and growth disorders. Computed Tomography (CT) emerges as a pivotal medical imaging modality, utilizing X-rays and advanced computational techniques to generate detailed cross-sectional images. Within the re

Suirong He, De He, Yufen Li, Li Gao

Dark photon is one of the promising candidates of light dark matter and could be detected by using its interaction with standard model particles via kinetic mixings. Here, we propose a feasible approach to detect the dark photons by nondestructively probing these mixing-induced quantum state transitions of atomic ensembles. Compared with the scheme by probin

Daniel Kelshaw, Luca Magri

In this paper, we introduce the proper latent decomposition (PLD) as a generalization of the proper orthogonal decomposition (POD) on manifolds. PLD is a nonlinear reduced-order modeling technique for compressing high-dimensional data into nonlinear coordinates. First, we compute a reduced set of intrinsic coordinates (latent space) to accurately describe a

Shuhui Yu, Lijun Ji

Let $\mathcal{F}$ be a family of $k$-dimensional subspaces of an $n$-dimensional vector space. Write $\mathcal{D}_{\mathcal{F}}(H;t)=\{F\in \mathcal{F}\colon \dim(F\cap H)\leq t \}$ for a subspace $H$. The family $\mathcal{F}$ is called $s$-almost $t$-intersecting if $|\mathcal{D}_{\mathcal{F}}(F;t)|\leq s$ for each $F\in \mathcal{F}$. In this note, we prove

Tong Jin, Feng Lu, Shuyu Hu, Chun Yuan

Visual place recognition (VPR) aims to determine the general geographical location of a query image by retrieving visually similar images from a large geo-tagged database. To obtain a global representation for each place image, most approaches typically focus on the aggregation of deep features extracted from a backbone through using current prominent archit

Takao Tomono, Kazuya Tsujimura

We aim to use quantum machine learning to detect various anomalies in image inspection by using small size data. Assuming the possibility that the expressive power of the quantum kernel space is superior to that of the classical kernel space, we are studying a quantum machine learning model. Through trials of image inspection processes not only for factory p

Matan Rusanovsky, Shimon Malnick, Amir Jevnisek, Ohad Fried

Diffusion models dominate the space of text-to-image generation, yet they may produce undesirable outputs, including explicit content or private data. To mitigate this, concept ablation techniques have been explored to limit the generation of certain concepts. In this paper, we reveal that the erased concept information persists in the model and that erased

Jean-Philippe Anker, Guendalina Palmirotta, Yannick Sire

We investigate dispersive and Strichartz estimates for the Schr\"odinger equation involving the fractional Laplacian in real hyperbolic spaces and their discrete analogues, homogeneous trees. Due to the Knapp phenomenon, the Strichartz estimates on Euclidean spaces for the fractional Laplacian exhibit loss of derivatives. A similar phenomenon appears on real

Hongjie Dong, Junhee Ryu

We study a class of degenerate parabolic and elliptic equations in divergence form in the upper half space $\{x_d>0\}$. The leading coefficients are of the form $x_d^2a_{ij}$, where $a_{ij}$ are bounded, uniformly elliptic, and measurable in $(t,x_d)$ except $a_{dd}$, which is measurable in $t$ or $x_d$. Additionally, they have small bounded mean oscillation

Renat Gontsov, Irina Goryuchkina

Solutions of nonlinear functional equations are generally not expressed as a finite number of combinations and compositions of elementary and known special functions. One of the approaches to study them is, firstly, to find formal solutions (that is, series whose terms are described and ordered in some way but which do not converge apriori) and, secondly, to