October 2023 arXiv papers — page 53

J. C. Souza, M. V. Ale Crivillero, H. Dawczak-Dębicki, Andrzej Ptok

Half-Heusler systems host a plethora of different ground states, especially with non-trivial topology. However, there is still a lack of spectroscopic insight into the corresponding band inversion in this family. In this work, we locally explore the half-Heuslers Y$T$Bi ($T =$ Pt and Pd) by means of scanning tunneling microscopy/spectroscopy. From our analys

Kaidi Wang, Zhiguo Ding, George K. Karagiannidis

This letter investigates the coexistence between near-field (NF) and far-field (FF) communications, where multiple FF users are clustered to be served on the beams of legacy NF users, via non-orthogonal multiple access (NOMA). Three different successive interference cancellation (SIC) decoding strategies are proposed and a sum rate maximization problem is fo

Imanol Echeverria, Maialen Murua, Roberto Santana

In scheduling problems common in the industry and various real-world scenarios, responding in real-time to disruptive events is essential. Recent methods propose the use of deep reinforcement learning (DRL) to learn policies capable of generating solutions under this constraint. The objective of this paper is to introduce a new DRL method for solving the fle

Hitesh Gudwani

We consider a system of multiple sources, a single communication channel, and a single monitoring station. Each source measures a time-varying quantity with varying levels of accuracy and one of them sends its update to the monitoring station via the channel. The probability of success of each attempted communication is a function of the source scheduled for

Owen A. Johnson, Vishal Gajjar, Evan F. Keane, David J. McKenna

The Search for Extraterrestrial Intelligence aims to find evidence of technosignatures, which can point toward the possible existence of technologically advanced extraterrestrial life. Radio signals similar to those engineered on Earth may be transmitted by other civilizations, motivating technosignature searches across the entire radio spectrum. In this end

Carlos Galindo, Fernando Hernando, Carlos Munuera, Diego Ruano

Locally recoverable codes (LRCs) are classical error-correcting codes widely used in large-scale distributed and cloud storage systems. Quantum locally recoverable codes of locality $(r,δ)$ (quantum $(r,δ)$-LRCs) are the quantum counterpart of classical $(r,δ)$-LRCs. They allow us to correct erasures at several positions using a trace-preserving quantum oper

Tomas Goldsack, Zhihao Zhang, Chen Tang, Carolina Scarton

Previous approaches for automatic lay summarisation are exclusively reliant on the source article that, given it is written for a technical audience (e.g., researchers), is unlikely to explicitly define all technical concepts or state all of the background information that is relevant for a lay audience. We address this issue by augmenting eLife, an existing

Michaël Liefsoens, Timothy Földes, Maria Barbi

Involved in mitotic condensation, interaction of transcriptional regulatory elements or isolation of structural domains, understanding loop formation is becoming a paradigm in the deciphering of chromatin architecture and its functional role. Despite the emergence of increasingly powerful genome visualization techniques, the high variability in cell populati

Yasemin Yildirim, M. Firat Arikan

For more than two decades it has been known that any compact Stein surface (of real dimension four) admits a compatible Lefschetz fibration over a two-disk. More recently, Giroux and Pardon have generalized this result by giving a complex geometric proof for the existence of compatible Lefschetz fibrations on Stein domains of any even dimension. As a prepara

Zheng Zhang, Dengyu Zhang, Qingrui Zhang, Wei Pan

Integrating rule-based policies into reinforcement learning promises to improve data efficiency and generalization in cooperative pursuit problems. However, most implementations do not properly distinguish the influence of neighboring robots in observation embedding or inter-robot interaction rules, leading to information loss and inefficient cooperation. Th

Christian Bick, Tobias Böhle, Oleh E. Omel'chenko

Synchronization is an essential collective phenomenon in networks of interacting oscillators. Twisted states are rotating wave solutions in ring networks where the oscillator phases wrap around the circle in a linear fashion. Here, we analyze Hopf bifurcations of twisted states in ring networks of phase oscillators with nonpairwise higher-order interactions.

Vladan Djukić, Mihailo Čubrović

We study the holographic interpretation of the bulk instability, i.e. the bulk Lyapunov exponent in the motion of open classical bosonic strings in AdS black hole/brane/string backgrounds. In the vicinity of homogeneous and isotropic horizons the bulk Lyapunov exponent saturates the MSS chaos bound but in fact has nothing to do with chaos as our string confi

E. A. Tereshina-Chitrova, L. V. Pourovskii, S. Khmelevskyi, L. Horak

Frustrated antiferromagnets offer a captivating platform to study the intricate relationship of magnetic interactions, geometric constraints, and emergent phenomena. By controlling spin orientations, these materials can be tailored for applications in spintronics and quantum information processing. The research focuses on the interplay of magnetic and exchan

Joseph Cho, Masaya Hara, Denis Polly, Tomohiro Tada

We consider Lie minimal surfaces, the critical points of the simplest Lie sphere invariant energy, in Riemannian space forms. These surfaces can be characterized via their Euler-Lagrange equations, which take the form of differential equations of the principal curvatures. Surfaces with constant mean curvature that satisfy these equations turn out to be rotat

Han Zhang, Lin Gui, Yuanzhao Zhai, Hui Wang

The technique of Reinforcement Learning from Human Feedback (RLHF) is a commonly employed method to improve pre-trained Language Models (LM), enhancing their ability to conform to human preferences. Nevertheless, the current RLHF-based LMs necessitate full retraining each time novel queries or feedback are introduced, which becomes a challenging task because

Nazmus Sakib, G. M. Shahariar, Md. Mohsinul Kabir, Md. Kamrul Hasan

Sharing cooking recipes is a great way to exchange culinary ideas and provide instructions for food preparation. However, categorizing raw recipes found online into appropriate food genres can be challenging due to a lack of adequate labeled data. In this study, we present a dataset named the ``Assorted, Archetypal, and Annotated Two Million Extended (3A2M+)

Jan Strohbeck, Sebastian Maschke, Max Mertens, Michael Buchholz

For automated driving, predicting the future trajectories of other road users in complex traffic situations is a hard problem. Modern neural networks use the past trajectories of traffic participants as well as map data to gather hints about the possible driver intention and likely maneuvers. With increasing connectivity between cars and other traffic actors

Ming-Yuan Chang

For high power $k$, the $L^2$-estimates for the Dirac-Dolbeault operator with coefficient $L^k\otimes E$ can be obtained from the Bochner-Kodaira-Nakano identity if $L$ has positive curvature. In this article, we generalize the classical method to obtain $L^2$-estimates for mixed curvature case, and give a bound to the extra error term. Modifying the $L^2$-e

Amir Noorizadegan, D. L. Young, Y. C. Hon, C. S. Chen

In this study, we investigate how the updating of weights during forward operation and the computation of gradients during backpropagation impact the optimization process, training procedure, and overall performance of the neural network, particularly the multi-layer perceptrons (MLPs). This paper introduces a novel neural network structure called the Power-

Silvia Casola, Alberto Lavelli, Horacio Saggion

Patents are legal documents that aim at protecting inventions on the one hand and at making technical knowledge circulate on the other. Their complex style -- a mix of legal, technical, and extremely vague language -- makes their content hard to access for humans and machines and poses substantial challenges to the information retrieval community. This paper

Fu-Ya Luo, Shu-Lin Liu, Yi-Jun Cao, Kai-Fu Yang

Stable imaging in adverse environments (e.g., total darkness) makes thermal infrared (TIR) cameras a prevalent option for night scene perception. However, the low contrast and lack of chromaticity of TIR images are detrimental to human interpretation and subsequent deployment of RGB-based vision algorithms. Therefore, it makes sense to colorize the nighttime

Alkis Blanz, Beatriz Gaitan

In this paper, we compare different mitigation policies when housing investments are irreversible. We use a general equilibrium model with non-homothetic preferences and an elaborate setup of the residential housing and energy production sector. In the first-best transition, the energy demand plays only a secondary role. However, this changes when optimal ca

Łukasz Mikulski, Wojciech Jamroga, Damian Kurpiewski

Model checking of strategic abilities is a notoriously hard problem, even more so in the realistic case of agents with imperfect information. Assume-guarantee reasoning can be of great help here, providing a way to decompose the complex problem into a small set of exponentially easier subproblems. In this paper, we propose two schemes for assume-guarantee ve

Manjunath Bestha, Amirul Hasan, Devika Divakar, Arun Surya

Highly multiplexed spectroscopic surveys have changed the astronomy landscape in recent years. However, these surveys are limited to low and medium spectral resolution. High spectral resolution spectroscopy is often photon starved and will benefit from a large telescope aperture. Multiplexed high-resolution surveys require a wide field of view and a large ap

Chen Tang, Shun Wang, Tomas Goldsack, Chenghua Lin

Abstracts derived from biomedical literature possess distinct domain-specific characteristics, including specialised writing styles and biomedical terminologies, which necessitate a deep understanding of the related literature. As a result, existing language models struggle to generate technical summaries that are on par with those produced by biomedical exp

Veniamin Veselovsky, Manoel Horta Ribeiro, Philip Cozzolino, Andrew Gordon

We show that the use of large language models (LLMs) is prevalent among crowd workers, and that targeted mitigation strategies can significantly reduce, but not eliminate, LLM use. On a text summarization task where workers were not directed in any way regarding their LLM use, the estimated prevalence of LLM use was around 30%, but was reduced by about half

Archita Gupta, M Hassain

We decompose the tensor product of two irreducible representations of $\mathrm{GL}_2(\mathbb{F}_q)$ for odd $q$ and classify the pairs such that their tensor product is multiplicity free. We also classify the pairs such that their tensor product has unique decomposition property. We additionally characterize the self-dual irreducible representations of $\mat

Shintaro Nakamura, Masashi Sugiyama

We study the real-valued combinatorial pure exploration of the multi-armed bandit in the fixed-budget setting. We first introduce the Combinatorial Successive Asign (CSA) algorithm, which is the first algorithm that can identify the best action even when the size of the action class is exponentially large with respect to the number of arms. We show that the

Siddhartha Solanki, Manohar Lal, Rishabh Sharma, Vineet Kumar Agotiya

We extended the recent work Phys. Rev. D 97(9), 094033 (2018) to investigate quarkonium dissociation in presence of baryonic chemical potential (mu_b) and anisotropy ({\xi}) using quasi-particle approach in hot quantum chromodynamics (QCD) medium. We have determined binding energy and thermal width of S-states of charmonia and bottomonia for n=1 and n=2 (rad

Lorenzo Gigli, Davide Tisi, Federico Grasselli, Michele Ceriotti

Lithium ortho-thiophosphate (Li$_3$PS$_4$) has emerged as a promising candidate for solid-state-electrolyte batteries, thanks to its highly conductive phases, cheap components, and large electrochemical stability range. Nonetheless, the microscopic mechanisms of Li-ion transport in Li$_3$PS$_4$ are far to be fully understood, the role of PS$_4$ dynamics in c

Dominic Jones, Thomas MacDonald, Timothy W. Schmidt, Dane R. McCamey

Singlet fission, which has applications in areas ranging form solar energy to quantum information, relies critically on transitions within a multi-spin manifold. These transitions are driven by fluctuations in the spin-spin exchange interaction, which have been linked to changes in nuclear geometry or exciton migration. Whilst simple calculations have suppor

Luke Robinson, Matthew Gadd, Paul Newman, Daniele De Martini

We present a system which grows and manages a network of remote viewpoints during the natural installation cycle for a newly installed camera network or a newly deployed robot fleet. No explicit notion of camera position or orientation is required, neither global - i.e. relative to a building plan - nor local - i.e. relative to an interesting point in a room

S. Haddadi, M. A. Yurischev, M. Y. Abd-Rabbou, M. Azizi

The merging of quantum information science with the relativity theory presents novel opportunities for understanding the enigmas surrounding the transmission of information in relation to black holes. For this purpose, we study the quantumness near a Schwarzschild black hole in a practical model under decoherence. The scenario we consider in this paper is th

Habib Bukhari, Dipam Chakraborty, Philipp Eller, Takuya Ito

During the public Kaggle competition "IceCube -- Neutrinos in Deep Ice", thousands of reconstruction algorithms were created and submitted, aiming to estimate the direction of neutrino events recorded by the IceCube detector. Here we describe in detail the three ultimate best, award-winning solutions. The data handling, architecture, and training process of

Francesco Sylos Labini, Giordano De Marzo, Matteo Straccamore, Sébastien Comerón

We show that the rotation curves of 16 nearby disc galaxies in the THINGS sample and the Milky Way can be described by the NFW halo model and by the Bosma effect at approximately the same level of accuracy. The latter effect suggests that the behavior of the rotation curve at large radii is determined by the rescaled gas component and thus that dark matter a

Robert Flynn, Anton Ragni

For the task of speech recognition, the use of more than 30 seconds of acoustic context during training is uncommon and under-investigated in literature. In this work, we conduct an empirical study on the effect of scaling the sequence length used to train/evaluate (dense-attention-based) acoustic models on speech recognition performance. For these experimen

Aleksandra S. Avdeeva, Dana A. Kovaleva, Oleg Yu. Malkov, Gang Zhao

Gaia Data Release 3 (DR3) provides extensive information on the astrophysical properties of stars, such as effective temperature, surface gravity, metallicity, and luminosity, for over 470 million objects. However, as Gaia's stellar parameters in GSP-Phot module are derived through model-dependent methods and indirect measurements, it can lead to additional

Linyan Huang, Zhiqi Li, Chonghao Sima, Wenhai Wang

Current research is primarily dedicated to advancing the accuracy of camera-only 3D object detectors (apprentice) through the knowledge transferred from LiDAR- or multi-modal-based counterparts (expert). However, the presence of the domain gap between LiDAR and camera features, coupled with the inherent incompatibility in temporal fusion, significantly hinde

Miranda Boutilier, Konstantin Brenner, Victorita Dolean

For the Poisson equation posed in a domain containing a large number of polygonal perforations, we propose a low-dimensional coarse approximation space based on a coarse polygonal partitioning of the domain. Similarly to other multiscale numerical methods, this coarse space is spanned by locally discrete harmonic basis functions. Along the subdomain boundari

Geon Lee, Seokbum Yoon, Jihoon Ko, Hyunju Kim

Hypergraphs naturally represent group interactions, which are omnipresent in many domains: collaborations of researchers, co-purchases of items, and joint interactions of proteins, to name a few. In this work, we propose tools for answering the following questions: (Q1) what are the structural design principles of real-world hypergraphs? (Q2) how can we comp

D. Algethami, A. Mudrov, V. Stukopin

We list solutions of the graded reflection equation associated with the fundamental vector representation of the quantum supergroup of GL-type.

Akimitsu Kirikoshi, Satoru Hayami

A ferroaxial ordering, which appears without mirror symmetry parallel to an electric axial moment, is described by a ferroic alignment of the electric toroidal (ET) dipole rather than the conventional electric and magnetic dipoles. Although its emergence requires neither spatial inversion nor time-reversal symmetry breakings, unconventional transverse respon

Dietmar Gallistl, Shudan Tian

For the pure biharmonic equation and a biharmonic singular perturbation problem, a residual-based error estimator is introduced which applies to many existing nonconforming finite elements. The error estimator involves the local best-approximation error of the finite element function by piecewise polynomial functions of the degree determining the expected ap

Jing Xiong, Chengming Li, Min Yang, Xiping Hu

Math Word Problems (MWP) aims to automatically solve mathematical questions given in texts. Previous studies tend to design complex models to capture additional information in the original text so as to enable the model to gain more comprehensive features. In this paper, we turn our attention in the opposite direction, and work on how to discard redundant fe

Mateo Cámara, José Luis Blanco

In this research, we present an interface based on Variational Autoencoders trained with a wide range of natural sounds for the innovative creation of Foley effects. The model can transfer new sound features to prerecorded audio or microphone-captured speech in real time. In addition, it allows interactive modification of latent variables, facilitating preci

Linxiao Yang, Rui Ren, Xinyue Gu, Liang Sun

Electric load forecasting is an indispensable component of electric power system planning and management. Inaccurate load forecasting may lead to the threat of outages or a waste of energy. Accurate electric load forecasting is challenging when there is limited data or even no data, such as load forecasting in holiday, or under extreme weather conditions. As

Yuanshao Zhu, Yongchao Ye, Xiangyu Zhao, James J. Q. Yu

Modeling future traffic conditions often relies heavily on complex spatial-temporal neural networks to capture spatial and temporal correlations, which can overlook the inherent noise in the data. This noise, often manifesting as unexpected short-term peaks or drops in traffic observation, is typically caused by traffic accidents or inherent sensor vibration

J. Podgorný, F. Marin, M. Dovčiak

We present a broad analysis of X-ray polarimetric observational prospects for radio-quiet active galactic nuclei (AGN), focusing on the role of parsec-scale components. We provide a revision of self-consistent type-1 and type-2 generic AGN radiative transfer models that were obtained with a Monte Carlo code STOKES, evaluating the effects of absorption and sc

Filip Alamaa, Frédéric Daigne, Robert Mochkovitch

The early steep decay, a rapid decrease in X-ray flux as a function of time following the prompt emission, is a robust feature seen in almost all gamma-ray bursts with early enough X-ray observations. This peculiar phenomenon has often been explained as emission from high latitudes of the last flashing shell. However, in photospheric models of gamma-ray burs

Xiaoyang Xie

In high-dimensional linear models the problem of constructing adaptive confidence sets for the full parameter is known to be generally impossible. We propose re-weighted loss functions under which constructing fully adaptive confidence sets for the parameter is shown to be possible. We give necessary and sufficient conditions on the weights for adaptive conf

Shuoran Jiang, Qingcai Chen, Yang Xiang, Youcheng Pan

The excellent generalization, contextual learning, and emergence abilities in the pre-trained large models (PLMs) handle specific tasks without direct training data, making them the better foundation models in the adversarial domain adaptation (ADA) methods to transfer knowledge learned from the source domain to target domains. However, existing ADA methods

Junjie Kang, Jinsong Wu, Shiqi Jiang

Image style transfer is a challenging task in computational vision. Existing algorithms transfer the color and texture of style images by controlling the neural network's feature layers. However, they fail to control the strength of textures in different regions of the content image. To address this issue, we propose a training method that uses a loss functi

Zhe Liu, Chunyang Chen, Junjie Wang, Mengzhuo Chen

Mobile applications have become a ubiquitous part of our daily life, providing users with access to various services and utilities. Text input, as an important interaction channel between users and applications, plays an important role in core functionality such as search queries, authentication, messaging, etc. However, certain special text (e.g., -18 for F

Yang Chen, Stjepan Picek, Zhonglin Ye, Zhaoyang Wang

Hypergraph Neural Networks (HGNNs) have been successfully applied in various hypergraph-related tasks due to their excellent higher-order representation capabilities. Recent works have shown that deep learning models are vulnerable to adversarial attacks. Most studies on graph adversarial attacks have focused on Graph Neural Networks (GNNs), and the study of

Yicheng Lin, Shuo Wang, Yunlong Jiang, Bin Han

Sparse optical flow is widely used in various computer vision tasks, however assuming brightness consistency limits its performance in High Dynamic Range (HDR) environments. In this work, a lightweight network is used to extract illumination robust convolutional features and corners with strong invariance. Modifying the typical brightness consistency of the

Xianjun Yang, Liangming Pan, Xuandong Zhao, Haifeng Chen

The burgeoning capabilities of advanced large language models (LLMs) such as ChatGPT have led to an increase in synthetic content generation with implications across a variety of sectors, including media, cybersecurity, public discourse, and education. As such, the ability to detect LLMs-generated content has become of paramount importance. We aim to provide

Jian Kang, Yinglong Xia, Ross Maciejewski, Jiebo Luo

We study deceptive fairness attacks on graphs to answer the following question: How can we achieve poisoning attacks on a graph learning model to exacerbate the bias deceptively? We answer this question via a bi-level optimization problem and propose a meta learning-based framework named FATE. FATE is broadly applicable with respect to various fairness defin

Sumit Roy, Anoop Singh

Let $X$ be a compact connected Riemann surface of genus $g \geq 2$ and $G$ a connected reductive affine algebraic group over $\mathbb{C}$. We prove the semiprojectivity of the moduli spaces of semistable $G$-Higgs bundles and $G$-bundles with $\lambda$-connections of fixed topological type $d\in \pi_1(G)$. As an application, in the smooth case we describe th

Yang Kuang, Yedan Shen, Guanghui Hu

Chemical accuracy serves as an important metric for assessing the effectiveness of the numerical method in Kohn--Sham density functional theory. It is found that to achieve chemical accuracy, not only the Kohn--Sham wavefunctions but also the Hartree potential, should be approximated accurately. Under the adaptive finite element framework, this can be implem

Xinxin Ma, Hongliang Lu

Let $G$ be a graph and $F:V(G)\to2^N$ be a set function. The graph $G$ is said to be \emph{F-avoiding} if there exists an orientation $O$ of $G$ such that $d^+_O(v)\notin F(v)$ for every $v\in V(G)$, where $d^+_O(v)$ denotes the out-degree of $v$ in the directed graph $G$ with respect to $O$. In this paper, we give a Tutte-type good characterization to decid

Ayan Mitra, Daniil Orel, Y. Sultan Abylkairov, Bekdaulet Shukirgaliyev

Core-collapse supernovae are sources of powerful gravitational waves (GWs). We assess the possibility of extracting information about the equation of state (EOS) of high density matter from the GW signal. We use the bounce and early post-bounce signals of rapidly rotating supernovae. A large set of GW signals is generated using general relativistic hydrodyna

Florian Schmid, Khaled Koutini, Gerhard Widmer

The introduction of large-scale audio datasets, such as AudioSet, paved the way for Transformers to conquer the audio domain and replace CNNs as the state-of-the-art neural network architecture for many tasks. Audio Spectrogram Transformers are excellent at exploiting large datasets, creating powerful pre-trained models that surpass CNNs when fine-tuned on d

J. Podgorný, M. Dovčiak, F. Marin

We present a series of numerical models suitable for X-ray polarimetry of accreting systems. Firstly, we provide a spectropolarimetric routine that integrates reflection from inner optically thick walls of a geometrical torus of arbitrary size viewed under general inclination. In the studied example, the equatorial torus is illuminated by a central isotropic

Weixi Weng, Chun Yuan

Unsupervised domain adaptation object detection (UDAOD) research on Detection Transformer(DETR) mainly focuses on feature alignment and existing methods can be divided into two kinds, each of which has its unresolved issues. One-stage feature alignment methods can easily lead to performance fluctuation and training stagnation. Two-stage feature alignment met

Borja Molina-Coronado, Antonio Ruggia, Usue Mori, Alessio Merlo

Malware authors have seen obfuscation as the mean to bypass malware detectors based on static analysis features. For Android, several studies have confirmed that many anti-malware products are easily evaded with simple program transformations. As opposed to these works, ML detection proposals for Android leveraging static analysis features have also been pro

Viviana Giunzioni, Giuseppe Ciacco, Clément Henry, Adrien Merlini

This work presents a fast direct solver strategy allowing full-wave modeling and dosimetry at terahertz (THz) frequencies. The novel scheme leverages a preconditioned combined field integral equation together with a regularizer for its elliptic spectrum to enable its compression into a non-hierarchical skeleton, invertible in quasi-linear complexity. Numeric

Reetta Ghezzi, Minnamaria Korhonen, Hannu Vilpponen, Tommi Mikkonen

In-house procurement is a controversial issue in the field of public procurement. Simply put, such procurement allows overlooking certain aspects of fair and equal treatment of vendors. This paper presents qualitative research on in-house ICT procurement within Finnish municipalities. Semi-structured interviews were conducted to gather insights from municipa

Nuno Saavedra, André Silva, Martin Monperrus

Bug-fix benchmarks are fundamental in advancing various sub-fields of software engineering such as automatic program repair (APR) and fault localization (FL). A good benchmark must include recent examples that accurately reflect technologies and development practices of today. To be executable in the long term, a benchmark must feature test suites that do no

Harris Papadopoulos

Gaussian Process Regression (GPR) is a popular regression method, which unlike most Machine Learning techniques, provides estimates of uncertainty for its predictions. These uncertainty estimates however, are based on the assumption that the model is well-specified, an assumption that is violated in most practical applications, since the required knowledge i

G. Morlino, S. Menchiari, E. Amato, N. Bucciantini

The origin of Galactic cosmic rays (CR) is still a matter of debate. Diffusive shock acceleration (DSA) applied to supernova remnant (SNR) shocks provides the most reliable explanation. However, within the current understanding of DSA several issues remain unsolved, like the CR maximum energy, the chemical composition and the transition region between Galact

Minzhi Li, Taiwei Shi, Caleb Ziems, Min-Yen Kan

Annotated data plays a critical role in Natural Language Processing (NLP) in training models and evaluating their performance. Given recent developments in Large Language Models (LLMs), models such as ChatGPT demonstrate zero-shot capability on many text-annotation tasks, comparable with or even exceeding human annotators. Such LLMs can serve as alternatives

Weihua Li, Wei Cao

Let $\mathbb{F}_q$ denote the finite field of characteristic $p$ and order $q$. Let $\mathbb{Z}_q$ denote the unramified extension of the $p$-adic rational integers $\mathbb{Z}_p$ with residue field $\mathbb{F}_q$. Given two positive integers $m,n$, define a box $\mathcal B_m$ to be a subset of $\mathbb{Z}_q^n$ with $q^{nm}$ elements such that $\mathcal B_m$

Jens-Joris Decorte, Jeroen Van Hautte, Johannes Deleu, Chris Develder

The impact of person-job fit on job satisfaction and performance is widely acknowledged, which highlights the importance of providing workers with next steps at the right time in their career. This task of predicting the next step in a career is known as career path prediction, and has diverse applications such as turnover prevention and internal job mobilit

Guillaume Marthe, Claire Goursaud

Energy consumption remains the main limiting factors in many promising IoT applications. In particular, micro-controllers consume far too much power. In order to overcome this problem, new circuit designs have been proposed and the use of spiking neurons and analog computing has emerged as it allows a very significant consumption reduction. However, working

Taha Shahroodi, Michael Miao, Joel Lindegger, Stephan Wong

With the recent move towards sequencing of accurate long reads, finding solutions that support efficient analysis of these reads becomes more necessary. The long execution time required for sequence alignment of long reads negatively affects genomic studies relying on sequence alignment. Although pre-alignment filtering as an extra step before alignment was

Nathan Baudis, Stephen Dolan, Davide Sgalaberna, Sara Bolognesi

Current and future accelerator neutrino oscillation experiments require an improved understanding of nuclear effects in neutrino-nucleus interactions. One important systematic uncertainty is introduced by the collective impact of nuclear effects which bias the reconstruction of the neutrino energy, such as the nuclear removal energy. In this manuscript, we i

Benoît Sonntag, Dominique Colnet

The 64-bit architectures that have become standard today offer unprecedented low-level programming possibilities. For the first time in the history of computing, the size of address registers far exceeded the physical capacity of their bus.After a brief reminder of the possibilities offered by the small size of addresses compared to the available 64 bits,we

Veronika Sunko, Chunxiao Liu, Marc Vila, Ilyoun Na

Several optical experiments have shown that in magnetic materials the principal axes of response tensors can rotate in a magnetic field. Here we offer a microscopic explanation of this effect, and propose a closely related DC transport phenomenon -- an off-diagonal \emph{symmetric} conductivity linear in a magnetic field, which we refer to as linear magneto-

Alex Tritt, Joshua Morris, Christopher C. Bounds, Hamish A. M. Taylor

Quantum waveform estimation, in which quantum sensors sample entire time series, promises to revolutionize the sensing of weak and stochastic signals, such as the biomagnetic impulses emitted by firing neurons. For long duration signals with rapid transients, regular quantum sampling becomes prohibitively resource intensive as it demands many measurements wi

Zhen Jiang, Hongwei Wang, Yuechen Yang, Yang Shen

The generation and control of optical frequency combs in integrated photonic systems enables complex, high-controllable, and large-scale devices. In parallel, harnessing topological physics in multipartite systems has allowed them with compelling features such as robustness against fabrication imperfections. Here we experimentally demonstrate on-chip topolog

Mario Ziller

We pursue the question how integers can be ordered or partitioned according to their divisibility properties. Based on pseudometrics on $\mathbb{Z}$, we investigate induced preorders, associated equivalence relations, and quotient sets. The focus is on metrics or pseudometrics on $\mathbb{D}_n$, the set of divisors of a given modulus $n\in\mathbb{N}$, that c

Ryan Thompson, Edwin V. Bonilla, Robert Kohn

Estimating the structure of directed acyclic graphs (DAGs) from observational data remains a significant challenge in machine learning. Most research in this area concentrates on learning a single DAG for the entire population. This paper considers an alternative setting where the graph structure varies across individuals based on available "contextual" feat

Kai Gong, Liwei Zhang

This paper focuses on a distributed coupled constrained convex optimization problem over directed unbalanced and time-varying multi-agent networks, where the global objective function is the sum of all agents' private local objective functions, and decisions of all agents are subject to coupled equality and inequality constraints and a compact convex subset.

Neslihan Alan

Eclipsing binary systems hold a central position within astrophysics in that the fundamental parameters of stars can be determined by direct observations. The simultaneous analyses of high-quality space observations, combined with ground-based photometric data, have allowed more sensitive detection of fundamental stellar parameters by multicolor photometry.

Yan Lu, Xinzhu Ma, Lei Yang, Tianzhu Zhang

Geometry plays a significant role in monocular 3D object detection. It can be used to estimate object depth by using the perspective projection between object's physical size and 2D projection in the image plane, which can introduce mathematical priors into deep models. However, this projection process also introduces error amplification, where the error of

S. V. Bulanov, G. M. Grittani, R. Shaisultanov, T. Zh. Esirkepov

Radiative cooling of electron beams interacting with counter-propagating electromagnetic waves is analyzed, taking into account the quantum modification of the radiation friction force. Central attention is paid to the evolution of the energy spectrum of electrons accelerated by the laser wake field acceleration mechanism. As an electron beam loses energy to

Shinya Kanemura, Yushi Mura

In order to realize electroweak first order phase transition, a category of extended Higgs models with relatively large self-coupling constants is often considered. In such a scenario, the running coupling constants can blow up at an energy scale much below the Planck scale. To clarify the allowed parameter space of the model, it is important to evaluate the

Hélène Frisch

The construction of exact solutions for radiative transfer in a plane-parallel medium has been addressed by Hemsch and Ferziger in 1972 for a partial frequency redistribution model of the formation of spectral lines consisting in a linear combination of frequency coherent and fully incoherent scattering. The method of solution is based on an eigenfunction ex

Giulio Colombo, Luciano Mari, Marco Rigoli

We prove that entire solutions of the minimal hypersurface equation \[ \mathrm{div}\left(\frac{Du}{\sqrt{1+|Du|^2}}\right) = 0 \] on a complete manifold with $\mathrm{Ric} \ge 0$, whose negative part grows like $\mathcal{O}(r/\log r)$ ($r$ the distance from a fixed origin), are constant. This extends the Bernstein Theorem for entire positive minimal graphs e

Riccardo Pengo, Daniel Vallières

Using the special value at $u=1$ of Artin-Ihara $L$-functions, we associate to every $\mathbb{Z}$-cover of a finite connected graph a polynomial which we call the \emph{Ihara polynomial}. We show that the number of spanning trees for the finite intermediate graphs of such a cover can be expressed in terms of the Pierce-Lehmer sequence associated to a factor

Olivier Mathieu

For g at least 2, the Thurston spine Pg is the subspace of Teichmueller space Tg , consisting of the marked surfaces for which the set of shortest curves, the systoles, cuts the surface into polygons. Our main result is the existence of an infinite set A of integers such that codim Pg is a o(g/ log g), when g varies over A. This proves the recent conjecture

Jean-François Delmas, Kacem Lefki, Pierre-André Zitt

Inspired by Schwartz, Jang-Lewis and Victory, who study in particular generalizations of triangularizations of matrices to operators, we shall give for positive operators on Lebesgue spaces equivalent definitions of atoms (maximal irreducible sets). We also characterize positive power compact operators having a unique non-zero atom which appears as a natural

S. Moran, B. Demir, F. Serva, B. Le Saux

Rainfall prediction at the kilometre-scale up to a few hours in the future is key for planning and safety. But it is challenging given the complex influence of climate change on cloud processes and the limited skill of weather models at this scale. Following the set-up proposed by the \emph{weather4cast} challenge of NeurIPS, we build a two-step deep-learnin

Nastaran Dabiran, Brandon Robinson, Rimple Sandhu, Mohammad Khalil

Neural networks (NNs) are primarily developed within the frequentist statistical framework. Nevertheless, frequentist NNs lack the capability to provide uncertainties in the predictions, and hence their robustness can not be adequately assessed. Conversely, the Bayesian neural networks (BNNs) naturally offer predictive uncertainty by applying Bayes' theorem.

Hua Chen, Hong-Ge Chen, Jin-Ning Li, Xin Liao

In this paper, we study the semilinear subelliptic equation \[ \left\{ \begin{array}{cc} -\triangle_{X} u=f(x,u)+g(x,u) & \mbox{in}~\Omega, \\[2mm] u=0\hfill & \mbox{on}~\partial\Omega, \end{array} \right. \] where $\triangle_{X}=-\sum_{i=1}^{m}X_{i}^{*}X_{i}$ is the self-adjoint H\"{o}rmander operator associated with vector fields $X=(X_{1},X_{2},\ldots,X_{

Moussa Koulako Bala Doumbouya, Baba Mamadi Diané, Solo Farabado Cissé, Djibrila Diané

Currently, there is no usable machine translation system for Nko, a language spoken by tens of millions of people across multiple West African countries, which holds significant cultural and educational value. To address this issue, we present a set of tools, resources, and baseline results aimed towards the development of usable machine translation systems

Filip Jonsson Kling

Consider ideals $I$ of the form \[ I=(x_1^2,\dots, x_n^2)+\mathrm{RLex}(x_ix_j) \] where $\mathrm{RLex}(x_ix_j)$ is the ideal generated by all the square-free monomials which are greater than or equal to $x_ix_j$ in the reverse lexicographic order. We will determine some interesting properties regarding the shape of the Hilbert series of $I$. Using a theorem

Lauri Seppäläinen, Anton Björklund, Vitus Besel, Kai Puolamäki

Manifold visualisation techniques are commonly used to visualise high-dimensional datasets in physical sciences. In this paper we apply a recently introduced manifold visualisation method, called Slise, on datasets from physics and chemistry. Slisemap combines manifold visualisation with explainable artificial intelligence. Explainable artificial intelligenc

Jing Zhou, Saiwen Zhang, Jun Chen, Le Zhang

Through gravity/gauge duality, the string breaking and running coupling constant of heavy quark-antiquark pair are investigated in the rotating background. For the meson decay mode $\rm Q\bar{Q} \rightarrow Q \bar{q}+\bar{Q} q$, we discuss the string breaking and running coupling in the parallel and transverse case. It is found that the parallel case has a m

Donggeun Tak, Z. Lucas Uhm, James H. Gillanders

A kilonova is a short-lived explosive event in the universe, resulting from the merger of two compact objects. Despite its importance as a primary source of heavy elements through r-process nucleosynthesis, its nature is not well understood, due to its rarity. In this work, we introduce a model that determines the density of a radially-stratified relativisti