October 2023 arXiv papers — page 96

Taylor Okonek, Katherine Wilson, Jon Wakefield

Accurate and precise estimates of the under-5 mortality rate (U5MR) are an important health summary for countries. However, full survival curves allow us to better understand the pattern of mortality in children under five. Modern demographic methods for estimating a full mortality schedule for children have been developed for countries with good vital regis

Thomas Karam

Let $d \ge 2, h \ge 1$ be integers. Using a fragmentation technique, we characterise $(h+1)$-tuples $(R_1, \dots, R_h, R)$ of non-empty families of partitions of $\{1, \dots, d\}$ such that it suffices for an order-$d$ tensor to have bounded $R_i$-rank for each $i=1,\dots,h$ for it to have bounded $R$-rank. On the way, we prove power lower bounds on products

Tara Kalsi, Alessandro Romito, Henning Schomerus

A key conjecture about the evolution of complex quantum systems towards an ergodic steady state, known as scrambling, is that this process acquires universal features when it is most efficient. We develop a single-parameter scaling theory for the spectral statistics in this scenario, which embodies exact self-similarity of the spectral correlations along the

Amy Debbané, Ken Jen Lee, Jarvis Tse, Edith Law

Benefits of learning by teaching (LbT) have been highlighted by previous studies from a pedagogical lens, as well as through computer-supported systems. However, the challenges that university students face in technology-mediated LbT$\unicode{x2013}$whether it be teaching oneself, teaching a peer, or teaching an agent$\unicode{x2013}$are not well understood.

Anupama Ray, Dhiraj Madan, Srushti Patil, Maria Anna Rapsomaniki

Advances in classical machine learning and single-cell technologies have paved the way to understand interactions between disease cells and tumor microenvironments to accelerate therapeutic discovery. However, challenges in these machine learning methods and NP-hard problems in spatial Biology create an opportunity for quantum computing algorithms. We create

Aye Chan May, Adisak Seesanea

We solve the existence problem for the minimal positive solutions $u\in L^{p}(\Omega, dx)$ to the Dirichlet problems for sublinear elliptic equations of the form \[ \begin{cases} Lu=\sigma u^q+\mu\qquad \quad \text{in} \quad \Omega, \\ \liminf\limits_{x \rightarrow y}u(x) = 0 \qquad y \in \partial_{\infty}\Omega, \end{cases} \] where $0<q<1$ and $Lu:=-\text{

Longwen Zhou

The competition between unitary time-evolution and quantum measurements could induce phase transitions in the entanglement characteristics of quantum many-body dynamics. In this work, we reveal such entanglement transitions in the context of non-Hermitian Floquet systems. Focusing on noninteracting fermions in a representative bipartite lattice with balanced

Soumyabrata Saha, Tridib Sadhu

We revisit the one-dimensional model of the symmetric simple exclusion process slowly coupled with two unequal reservoirs at the boundaries. In its non-equilibrium stationary state, the large deviations functions of density and current have been recently derived using exact microscopic analysis by Derrida, Hirschberg and Sadhu in J. Stat. Phys. 182, 15 (2021

Jianan Yao, Baoling Xie, Jun Lai

The Navier equation is the governing equation of elastic waves, and computing its solution accurately and rapidly has a wide range of applications in geophysical exploration, materials science, etc. In this paper, we focus on the efficient and high-precision numerical algorithm for the time harmonic elastic wave scattering problems from cornered domains via

Sydney Mason, Maryna Leonidivna Meretska, Christina Spägele, Marcus Ossiander

Optical microcavities confine light to wavelength-scale volumes and are a key component for manipulating and enhancing the interaction of light, vacuum states, and matter. Current microcavities are constrained to a small number of spatial mode profiles. Imaging cavities can accommodate complicated modes but require an externally pre-shaped input. Here, we ex

Morris Brooks

We present a novel approach to the Bogoliubov theory of dilute Bose gases, allowing for an elementary derivation of the celebrated Lee-Huang-Yang formula in the Gross-Pitaevskii regime. Furthermore, we identify the low lying excitation spectrum beyond the Gross-Pitaevskii scaling, extending a recent result [3] to significantly more singular scaling regimes.

Hao Lu, Yunpeng Zhang, Qing Lian, Dalong Du

Detecting objects in 3D space using multiple cameras, known as Multi-Camera 3D Object Detection (MC3D-Det), has gained prominence with the advent of bird's-eye view (BEV) approaches. However, these methods often struggle when faced with unfamiliar testing environments due to the lack of diverse training data encompassing various viewpoints and environments.

Karsten Matthies, Jonathan Sewell, Miles H. Wheeler

We consider a two-dimensional, two-layer, incompressible, steady flow, with vorticity which is constant in each layer, in an infinite channel with rigid walls. The velocity is continuous across the interface, there is no surface tension or difference in density between the two layers, and the flow is inviscid. Unlike in previous studies, we consider solution

Lucca de Freitas Santos, Murilo Varges da Silva

With the popularization of the internet, smartphones and social media, information is being spread quickly and easily way, which implies bigger traffic of information in the world, but there is a problem that is harming society with the dissemination of fake news. With a bigger flow of information, some people are trying to disseminate deceptive information

J. de Vries, C. Körber, A. Nogga, S. Shain

We study dark matter scattering off ${}^4$He and other light nuclei using chiral effective field theory. We consider scalar DM interactions and include both one- and two-nucleon scattering processes. The DM interactions and nuclear wave functions are obtained from chiral effective field theory and we work up to fourth order in the chiral expansion for the la

Alessandro Gianola, Marco Montali, Sarah Winkler

The need to model and analyse dynamic systems operating over complex data is ubiquitous in AI and neighboring areas, in particular business process management. Analysing such data-aware systems is a notoriously difficult problem, as they are intrinsically infinite-state. Existing approaches work for specific datatypes, and/or limit themselves to the verifica

Maria Tudorovskaya, David Muñoz Ramo

In this paper, we aim to broaden the spectrum of possible applications of quantum computers and use their capabilities to investigate effects in cavity quantum electrodynamics ("cavity QED"). Interesting application examples are material properties, multiphoton effects such as superradiance, systems with strong field-matter coupling, and others. For QED appl

Shruthi Gowda, Bahram Zonooz, Elahe Arani

Artificial neural networks (ANNs) exhibit a narrow scope of expertise on stationary independent data. However, the data in the real world is continuous and dynamic, and ANNs must adapt to novel scenarios while also retaining the learned knowledge to become lifelong learners. The ability of humans to excel at these tasks can be attributed to multiple factors

Benjamin Lengerich, Caleb N. Ellington, Andrea Rubbi, Manolis Kellis

We examine Contextualized Machine Learning (ML), a paradigm for learning heterogeneous and context-dependent effects. Contextualized ML estimates heterogeneous functions by applying deep learning to the meta-relationship between contextual information and context-specific parametric models. This is a form of varying-coefficient modeling that unifies existing

Laura A. Busch, Arnaud Belloche, Robin T. Garrod, Holger S. P. Müller

We want to investigate the influence of the powerful outflow driven by the hot core Sgr B2(N1) on the gas molecular inventory of the surrounding medium. We used the data taken as part of the 3 mm imaging spectral-line survey ReMoCA (Re-exploring Molecular Complexity with ALMA). Integrated intensity maps of SO and SiO emission reveal a bipolar structure with

Jochem Hoogendijk, Ivan Kryven

We show that a large class of 1D first-order conservation PDEs can be probabilistically represented using multi-type branching processes. The representation holds when the initial conditions are linear combinations of negative exponentials. We also show that in some cases, the time of gradient blow up can be identified by studying criticality conditions of t

Martin Widmer

We start with a brief survey on the Northcott property for subfields of the algebraic numbers $\Qbar$. Then we introduce a new criterion for its validity (refining the author's previous criterion), addressing a problem of Bombieri. We show that Bombieri and Zannier's theorem, stating that the maximal abelian extension of a number field $K$ contained in $K^{(

Yu-Qi Dong, Yu-Qiang Liu, Yu-Xiao Liu

In this paper, we establish a unified parameterized framework for analyzing the polarization modes of gravitational waves in the general metric theory (gravity is only described by the metric) and the general scalar-tensor theory (gravity is described by the metric and an additional scalar field). Specifically, we study the polarization modes of gravitationa

Dominik Baumann, Erfaun Noorani, James Price, Ole Peters

Envisioned application areas for reinforcement learning (RL) include autonomous driving, precision agriculture, and finance, which all require RL agents to make decisions in the real world. A significant challenge hindering the adoption of RL methods in these domains is the non-robustness of conventional algorithms. In particular, the focus of RL is typicall

Stelios Triantafyllou, Aleksa Sukovic, Debmalya Mandal, Goran Radanovic

Establishing causal relationships between actions and outcomes is fundamental for accountable multi-agent decision-making. However, interpreting and quantifying agents' contributions to such relationships pose significant challenges. These challenges are particularly prominent in the context of multi-agent sequential decision-making, where the causal effect

Justin Le Louëdec, Grzegorz Cielniak

Selective robotic harvesting is a promising technological solution to address labour shortages which are affecting modern agriculture in many parts of the world. For an accurate and efficient picking process, a robotic harvester requires the precise location and orientation of the fruit to effectively plan the trajectory of the end effector. The current meth

Jan Niklas Adams, Jari Peeperkorn, Tobias Brockhoff, Isabelle Terrier

Process discovery algorithms learn process models from executed activity sequences, describing concurrency, causality, and conflict. Concurrent activities require observing multiple permutations, increasing data requirements, especially for processes with concurrent subprocesses such as hierarchical, composite, or distributed processes. While process discove

Francesco D'Amato, Roberto Saltini, Thanh-Hai Tran, Luca Zanolini

Over the past years, distributed consensus research has expanded its focus to address challenges in large-scale, permissionless systems, such as blockchains. This shift reflects the need to accommodate dynamic participation, in contrast to the traditional model of a static set of continuously online validators. Works like Bitcoin and the sleepy model have la

J. Givois, A. Tononi, D. S. Petrov

We study binding of $N$ identical heavy fermions by a light atom in two dimensions assuming zero-range attractive heavy-light interactions. By using the mean-field theory valid for large $N$ we show that the $N+1$ cluster is bound when the mass ratio exceeds $1.074N^2$. The mean-field theory, being scale invariant in two dimensions, predicts only the shapes

Priyanka Vasanthakumari, Thomas Brettin, Yitan Zhu, Hyunseung Yoo

Informed selection of drug candidates for laboratory experimentation provides an efficient means of identifying suitable anti-cancer treatments. The advancement of artificial intelligence has led to the development of computational models to predict cancer cell line response to drug treatment. It is important to analyze the false positive rate (FPR) of the m

Hung Tran

All known examples of simply-connected gradient K\"{a}hler-Ricci soliton in real dimension four are toric, and the symmetry is intrinsically related to the potential function $f$ and the scalar curvature $\SS$. In this article, we consider the case that $f$ and $\SS$ are functionally dependent and deduce a complete classification, while the independence case

Andrew D. Innes, Prosenjit Majumder, Heung-Ryoul Noh, Simon. L. Cornish

We report on a study of modulation transfer spectroscopy of the $4\textrm{S}_{1/2}\rightarrow 4\textrm{P}_{1/2}$ ($D_{1}$) transition of naturally abundant potassium in a room-temperature vapour cell. This transition is critical for laser cooling and optical pumping of potassium and our study is therefore motivated by the need for robust laser frequency stab

Zhiqiang Xiao, Yong Zeng, Fuxi Wen, Zaichen Zhang

For integrated sensing and communication (ISAC) systems, the channel information essential for communication and sensing tasks fluctuates across different timescales. Specifically, wireless sensing primarily focuses on acquiring path state information (PSI) (e.g., delay, angle, and Doppler) of individual multi-path components to sense the environment, which

Sergio Salinas Monroy, Aman Kumar Gupta, Garrett Wahlstedt

To maintain the privacy of users' web browsing history, popular browsers encrypt their DNS traffic using the DNS-over-HTTPS (DoH) protocol. Unfortunately, encrypting DNS packets prevents many existing intrusion detection systems from using plaintext domain names to detect malicious traffic. In this paper, we design an autoencoder that is capable of detecting

Melanie Sclar, Yejin Choi, Yulia Tsvetkov, Alane Suhr

As large language models (LLMs) are adopted as a fundamental component of language technologies, it is crucial to accurately characterize their performance. Because choices in prompt design can strongly influence model behavior, this design process is critical in effectively using any modern pre-trained generative language model. In this work, we focus on LL

Chengkai Zhu, Zhiping Liu, Chenghong Zhu, Xin Wang

In the realm of fault-tolerant quantum computing, stabilizer operations play a pivotal role, characterized by their remarkable efficiency in classical simulation. This efficiency sets them apart from non-stabilizer operations within the quantum computational theory. In this Letter, we investigate the limitations of classically-simulable measurements in disti

S. E. M. Ahmed Maouloud

XENON is a project for direct dark matter search located in the INFN underground laboratory LNGS. The previous generation of XENON detector, XENON1T, achieved an exposure of 1 ton$\times$year, setting the most stringent limits on the spin-independent scattering cross section of Weakly Interacting Massive Particles (WIMPs) on nucleons for nearly the complete

S. Biswas, S. Mahata, A. Biswas, S. Sahoo

In recent years, lepton flavour violating (LFV) decays are one of the most trending topics to probe new physics (NP). The latest results of LHCb have motivated us to study the LFV decays through b to s transition. The branching ratios, forward backward asymmetries and longitudinal polarization fractions of B(B_s) to K^* ({phi})l_1 l_2 decays are studied in n

Haonan Wang, Xiaomeng Li

Volume-wise labeling in 3D medical images is a time-consuming task that requires expertise. As a result, there is growing interest in using semi-supervised learning (SSL) techniques to train models with limited labeled data. However, the challenges and practical applications extend beyond SSL to settings such as unsupervised domain adaptation (UDA) and semi-

Manuela Molina, Angela Malizia, Loredana Bassani

In this work we analyse 3 average-luminosity hard X-ray selected AGN: ESO 506-G27, IGR J19039+3344 and NGC 7465. They have simultaneous Swift/XRT and NuSTAR data never published before and have been poorly studied at X-ray energies. These sources make for interesting targets both from a methodological and scientific point of view. Scientifically, they are of

Shiwei Zhang, Mingfang Wu, Xiuzhen Zhang

In support of open and reproducible research, there has been a rapidly increasing number of datasets made available for research. As the availability of datasets increases, it becomes more important to have quality metadata for discovering and reusing them. Yet, it is a common issue that datasets often lack quality metadata due to limited resources for data

Chen Chen, Yuchen Hu, Chao-Han Huck Yang, Hexin Liu

Code-switching (CS) speech refers to the phenomenon of mixing two or more languages within the same sentence. Despite the recent advances in automatic speech recognition (ASR), CS-ASR is still a challenging task ought to the grammatical structure complexity of the phenomenon and the data scarcity of specific training corpus. In this work, we propose to lever

Fatima Alarab, Ján Minár, Procopios Constantinou, Dhani Nafday

The ability to modulate the spin-orbit (SO) interaction is crucial for engineering a wide range of spintronics-based quantum devices, extending from state-of-the-art data storage to materials for quantum computing. The use of proximity-induced effects for this purpose may become the mainstream approach, whereas their experimental verification using angle-res

Sen Wang, Jin Zheng

Monocular 3D object detection is an inherently ill-posed problem, as it is challenging to predict accurate 3D localization from a single image. Existing monocular 3D detection knowledge distillation methods usually project the LiDAR onto the image plane and train the teacher network accordingly. Transferring LiDAR-based model knowledge to RGB-based models is

Haixia Chen, Simone Dovetta, Angela Pistoia, Enrico Serra

We establish existence and multiplicity of one-peaked and multi-peaked positive bound states for nonlinear Schr\"odinger equations on general compact and noncompact metric graphs. Precisely, we construct solutions concentrating at every vertex of odd degree greater than or equal to $3$. We show that these solutions are not minimizers of the associated action

Vsevolod Vozhakov, Marina Bastrakova, Nikolay Klenov, Arkady Satanin

The development of quantum computers based on superconductors requires the improvement of the qubit state control approach aimed at the increase of the hardware energy efficiency. A promising solution to this problem is the use of superconducting digital circuits operating with single-flux-quantum (SFQ) pulses, moving the qubit control system into the cold c

S. Biswas, P. Nayek, P. Maji, S. Sahoo

Motivated by the recent LHCb results of lepton flavour violation on b decays into s and b decays into c transitions we study the lepton flavour violating (LFV) baryonic decays {Lambda}_b decays into {Lambda}l_i^+ l_j^- in non-universal Z^' model. We discuss the two-fold decay distribution of {Lambda}_b decays into {Lambda}l_i^+ l_j^- decays in terms of trans

Thomas J. Faulkenberry

In this paper, I present three closed-form approximations of the two-sample Pearson Bayes factor, a recently developed index of evidential value for data in two-group designs. The techniques rely on some classical asymptotic results about Gamma functions. These approximations permit simple closed-form calculation of the Pearson Bayes factor in cases where on

Alexander Neuhaus, Pascal Dreher, Florian Schütz, Helder Marchetto

Spectroscopic photoemission microscopy is a well-established method to investigate the electronic structure of surfaces. In modern photoemission microscopes the electron optics allows imaging of the image plane, momentum plane, or dispersive plane, depending on the lens setting. Furthermore, apertures allow filtering of energy-, real-, and momentum space. He

Jiajun Ma, Tianyang Hu, Wenjia Wang, Jiacheng Sun

Guidance in conditional diffusion generation is of great importance for sample quality and controllability. However, existing guidance schemes are to be desired. On one hand, mainstream methods such as classifier guidance and classifier-free guidance both require extra training with labeled data, which is time-consuming and unable to adapt to new conditions.

Emma E. Davies, Camilla Scolini, Réka M. Winslow, Andrew P. Jordan

The large-scale magnetic structure of interplanetary coronal mass ejections (ICMEs) has been shown to affect the galactic cosmic ray (GCR) flux measured in situ by spacecraft, causing temporary decreases known as Forbush decreases (Fds). In some ICMEs, the magnetic ejecta exhibits a magnetic flux rope (FR) structure; the strong magnetic field strength and cl

Zixuan Huang, Lipeng Zhu, Rui Zhang

Intelligent reflecting/refracting surface (IRS) is envisioned as a promising technology to reconfigure wireless propagation environment for enhancing the communication performance, by smartly controlling the signal reflection/refraction with a large number of tunable passive elements. In particular, the application of IRS in high-mobility scenarios can conve

Vinod N. Rao, Shrikant Utagi, Anirban Pathak, R. Srikanth

Quantum digital signature (QDS) is the quantum version of its classical counterpart, and can offer security against attacks of repudiation, signature forging and external eavesdropping, on the basis of quantum mechanical no-go principles. Here we propose a QDS scheme based on quantum counterfactuality, which leverages the concept of interaction-free measurem

Juwu Zheng, Jiangtao Ren

Intelligent transportation system combines advanced information technology to provide intelligent services such as monitoring, detection, and early warning for modern transportation. Intelligent transportation detection is the cornerstone of many intelligent traffic services by identifying task targets through object detection methods. However existing detec

Urazbekov Bakytzhan, Issatayev Talgat, Lukyanov Sergey, Azhibekov Aidos

$ $An experiment has been carried out for studying the cluster structure of $^9$Be induced by the $^3$He ions at the energy of 30 MeV. As results of the nuclear reaction $^3$He + $^9$Be the differential cross sections for the exit channels - elastic, inelastic, $\alpha$ + $^8$Be, $^6$He + $^6$Be, $^6$Li + $^6$Li, and $^7$Be + $^5$He - were measured. Elastic

Ti-Rong Wu, Hung Guei, Pei-Chiun Peng, Po-Wei Huang

This paper presents MiniZero, a zero-knowledge learning framework that supports four state-of-the-art algorithms, including AlphaZero, MuZero, Gumbel AlphaZero, and Gumbel MuZero. While these algorithms have demonstrated super-human performance in many games, it remains unclear which among them is most suitable or efficient for specific tasks. Through MiniZe

S. Autti, A. Casey, N. Eng, N. Darvishi

The focus of dark matter searches to date has been on Weakly Interacting Massive Particles (WIMPs) in the GeV/$c^2$-TeV/$c^2$ mass range. The direct, indirect and collider searches in this mass range have been extensive but ultimately unsuccessful, providing a strong motivation for widening the search outside this range. Here we describe a new concept for a

Haochen Shi, Weiqi Wang, Tianqing Fang, Baixuan Xu

Zero-shot commonsense Question-Answering (QA) requires models to reason about general situations beyond specific benchmarks. State-of-the-art approaches fine-tune language models on QA pairs constructed from CommonSense Knowledge Bases (CSKBs) to equip the models with more commonsense knowledge in a QA context. However, current QA synthesis protocols may int

Caroline Soubiran, Orlagh Creevey, Nadege Lagarde, Nathalie Brouillet

Context. Large spectroscopic surveys devoted to the study of the Milky Way, including Gaia, use automated pipelines to massively determine the atmospheric parameters of millions of stars. The Gaia FGK Benchmark Stars are reference stars with Teff and log g derived through fundamental relations, independently of spectroscopy, to be used as anchors for the par

Marvin Wyrich

Be it in debugging, testing, code review or, more recently, pair programming with AI assistance: in all these activities, software engineers need to understand source code. Accordingly, plenty of research is taking place in the field to find out, for example, what makes code easy to understand and which tools can best support developers in their comprehensio

Guacimara García-Bethencourt, Chris B. Brook, Robert J. J. Grand, Daisuke Kawata

Within a simulated Milky Way-like galaxy, we identify and analyse analogues of the Gaia-Enceladus (GE), Kraken and Sequoia mergers that each matches remarkably well observational results, including in velocity and chemical abundance space, and their distributions in the $j_{z}$-Energy plane. The Kraken analogue is the earliest merger and has the highest tota

M. Takata, D. O. Gough

Analysis of f-mode frequencies has provided a measure of the radius of the Sun which is lower, by a few hundredths per cent, than the photospheric radius determined by direct optical measurement. Part of this difference can be understood by recognizing that it is primarily the variation of density well beneath the photosphere of the star that determines the

D. Sanchez-Manzano, G. Orfila, A. Sander, L. Marcano

Swirling spin textures, including topologically non-trivial states, such as skyrmions, chiral domain walls, and magnetic vortices, have garnered significant attention within the scientific community due to their appeal from both fundamental and applied points of view. However, their creation, controlled manipulation, and stability are typically constrained t

Rudolf L. M. van Herten, Nils Hampe, Richard A. P. Takx, Klaas Jan Franssen

Coronary artery disease (CAD) remains the leading cause of death worldwide. Patients with suspected CAD undergo coronary CT angiography (CCTA) to evaluate the risk of cardiovascular events and determine the treatment. Clinical analysis of coronary arteries in CCTA comprises the identification of atherosclerotic plaque, as well as the grading of any coronary

Jonathan H. Cohn, Maeve Curliss, Jonelle L. Walsh, Kyle M. Kabasares

We present 0$.\!\!^{\prime\prime}22$-resolution Atacama Large Millimeter/submillimeter Array (ALMA) observations of CO(2$-$1) emission from the circumnuclear gas disk in the red nugget relic galaxy PGC 11179. The disk shows regular rotation, with projected velocities near the center of 400 km s$^{-1}$. We assume the CO emission originates from a dynamically

Zhaojie Chu, Kailing Guo, Xiaofen Xing, Yilin Lan

Speech-driven 3D facial animation is a challenging cross-modal task that has attracted growing research interest. During speaking activities, the mouth displays strong motions, while the other facial regions typically demonstrate comparatively weak activity levels. Existing approaches often simplify the process by directly mapping single-level speech feature

Charmaine Ndolo, Martin Florian, Florian Tschorsch

Federated Byzantine Agreement Systems (FBASs) offer a solution to consensus in permissionless systems by adapting the well-studied Byzantine agreement model to permissionless consensus. Unlike its counterparts in the context of permissionless consensus, the FBAS system model does not offer validating nodes protocol-level incentives although they are entruste

Jon Danielsson, Andreas Uthemann

Artificial intelligence (AI) can undermine financial stability because of malicious use, misinformation, misalignment, and the AI analytics market structure. The low frequency and uniqueness of financial crises, coupled with mutable and unclear objectives, frustrate machine learning. Even if the authorities prefer a conservative approach to AI adoption, it w

Tarek Emmrich, Martina Juhnke-Kubitzke, Stefan Kunis

We study signals that are sparse in graph spectral domain and develop explicit algorithms to reconstruct the support set as well as partial components from samples on few vertices of the graph. The number of required samples is independent of the total size of the graph and takes only local properties of the graph into account. Our results rely on an operato

Zhao Song, Chiwun Yang

The delta-bar-delta algorithm is recognized as a learning rate adaptation technique that enhances the convergence speed of the training process in optimization by dynamically scheduling the learning rate based on the difference between the current and previous weight updates. While this algorithm has demonstrated strong competitiveness in full data optimizat

Zhaoyuan Gu, Rongming Guo, William Yates, Yipu Chen

This study investigates formal-method-based trajectory optimization (TO) for bipedal locomotion, focusing on scenarios where the robot encounters external perturbations at unforeseen times. Our key research question centers around the assurance of task specification correctness and the maximization of specification robustness for a bipedal robot in the prese

Yee Sin Ang

Altermagnet is an emerging antiferromagnetic material subclass that exhibits spin-splitting in momentum space without net global magnetization and spin-orbit-coupling effect. In this work, we develop a model of thermal charge injection across an altermagnet/semiconductor (AM/S) Schottky contact. We obtain analytical expressions describing the spin-dependent

Alejandro Villoria, Henning Basold, Alfons Laarman

In this paper, we extend diagrammatic reasoning in monoidal categories with algebraic operations and equations. We achieve this by considering monoidal categories that are enriched in the category of Eilenberg-Moore algebras for a monad. Under the condition that this monad is monoidal and affine, we construct an adjunction between symmetric monoidal categori

Jordi Cerdà-Bautista, José María Tárraga, Vasileios Sitokonstantinou, Gustau Camps-Valls

In the face of climate change-induced droughts, vulnerable regions encounter severe threats to food security, demanding urgent humanitarian assistance. This paper introduces a causal inference framework for the Horn of Africa, aiming to assess the impact of cash-based interventions on food crises. Our contributions include identifying causal relationships wi

ATLAS Collaboration

A search for non-resonant Higgs boson pair ($HH$) production is presented, in which one of the Higgs bosons decays to a b-quark pair ($b\bar b$) and the other decays to $WW^*$, $ZZ^*$, or $\tau^+\tau^-$, with in each case a final state with $\ell^+\ell^- +$ neutrinos ($\ell = e, \mu$). The analysis targets separately the gluon-gluon fusion and vector boson f

Shuangqing Liu, Shuhui Yu, Lijun Ji

Flag codes have received a lot of attention due to its application in random network coding. In 2021, Alonso-Gonz\'{a}lez et al. constructed optimal $(n,\mathcal{A})$-Optimum distance flag codes(ODFC) for $\mathcal {A}\subseteq \{1,2,\ldots,k,n-k,\ldots,n-1\}$ with $k\in \mathcal A$ and $k\mid n$. In this paper, we introduce a new construction of $(n,\mathca

Ruibo Li, Chi Zhang, Zhe Wang, Chunhua Shen

In this article, we investigate self-supervised 3D scene flow estimation and class-agnostic motion prediction on point clouds. A realistic scene can be well modeled as a collection of rigidly moving parts, therefore its scene flow can be represented as a combination of the rigid motion of these individual parts. Building upon this observation, we propose to

Sándor Kisfaludi-Bak, Jana Masaříková, Erik Jan van Leeuwen, Bartosz Walczak

The hyperbolicity of a graph, informally, measures how close a graph is (metrically) to a tree. Hence, it is intuitively similar to treewidth, but the measures are formally incomparable. Motivated by the broad study of algorithms and separators on planar graphs and their relation to treewidth, we initiate the study of planar graphs of bounded hyperbolicity.

Jaap Jumelet, Michael Hanna, Marianne de Heer Kloots, Anna Langedijk

We present the submission of the ILLC at the University of Amsterdam to the BabyLM challenge (Warstadt et al., 2023), in the strict-small track. Our final model, ChapGTP, is a masked language model that was trained for 200 epochs, aided by a novel data augmentation technique called Automatic Task Formation. We discuss in detail the performance of this model

Claudio Fontanari

Let $(X,\Delta)$ be a projective, $\mathbb{Q}$-factorial log canonical pair and let $L$ be a pseudoeffective $\mathbb{Q}$-divisor on $X$ such that $K_X + \Delta + L$ is pseudoeffective. Is there an effective $\mathbb{Q}$-divisor $M$ on $X$ such that $K_X + \Delta + L$ is numerically equivalent to $M$? We are not aware of any counterexamples, but the answer i

Jiawang Dan, Ruofan Wu, Yunpeng Liu, Baokun Wang

Graph representation learning has now become the de facto standard when handling graph-structured data, with the framework of message-passing graph neural networks (MPNN) being the most prevailing algorithmic tool. Despite its popularity, the family of MPNNs suffers from several drawbacks such as transparency and expressivity. Recently, the idea of designing

Johannes Droschl

In this paper we prove a conjecture of Kudla and Rallis. Let $\chi$ be a unitary character, $s\in \mathbb{C}$ and $W$ a symplectic vector space over a non-archimedean field with symmetry group $G(W)$. Denote by $I(\chi,s)$ the degenerate principal series representation of $G(W\oplus W)$. Pulling back $I(\chi,s)$ along the natural embedding $G(W)\times G(W)\h

Elias Dubno

Even though Zaremba's conjecture remains open, Bourgain and Kontorovich solved the problem for a full density subset. Nevertheless, there are only a handful of explicit sequences known to satisfy the strong version of the conjecture, all of which were obtained using essentially the same algorithm. In this note, we provide a refined algorithm using the foldin

Salvatore Greco, Roman Slowinski

We are considering the algebraic structure of the Pawlak-Brouwer-Zadeh lattice to distinguish vagueness due to imprecision from ambiguity due to coarseness. We show that a general class of many-valued logics useful for reasoning about data emerges from this context. All these logics can be obtained from a very general seven-valued logic which, interestingly

Metin Arik, Tarik Tok

We consider SO(3) symmetric triplet of Higgs fields and SO(4) symmetric complex doublet of Higgs fields in the closed FLRW universe. For these models, Lagrangian densities provide effective potentials leading to spontaneous symmetry breaking which gives cosmological expectation value of the Higgs field and the Higgs mass. We find a relation which emerges bet

Lior Gishboliner, Yevgeny Levanzov, Asaf Shapira

Graph modification problems ask for the minimal number of vertex/edge additions/deletions needed to make a graph satisfy some predetermined property. A (meta) problem of this type, which was raised by Yannakakis in 1981, asks to determine for which properties ${\mathcal P}$, it is NP-hard to compute the smallest number of edge deletions needed to make a grap

MohammadHossein Ashoori, Arash Amini

Super-resolution (SR) is the technique of increasing the nominal resolution of image / video content accompanied with quality improvement. Video super-resolution (VSR) can be considered as the generalization of single image super-resolution (SISR). This generalization should be such that more detail is created in the output using adjacent input frames. In th

Florian Borchert, Ignacio Llorca, Roland Roller, Bert Arnrich

Objective: To improve performance of medical entity normalization across many languages, especially when fewer language resources are available compared to English. Materials and Methods: We introduce xMEN, a modular system for cross-lingual medical entity normalization, which performs well in both low- and high-resource scenarios. When synonyms in the targe

Shreyas Nadiger, Sandra M. Jose, Ratheejit Ghosh, Inderpreet Kaur

The emergence of transient checkerboard and stripe patterns in a stack of driven quasi-one-dimensional homogeneous dipolar condensates is studied. The parametric driving of the $s$-wave scattering length leads to the excitation of the lowest collective Bogoliubov mode. The character of the lowest mode depends critically on the orientation of the dipoles, cor

Minggang Luo, Junming Zhao, Linhua Liu, Mauro Antezza

Near-field radiative heat transfer (NFRHT) in nanoparticle networks is complicated due to the multiple scattering of thermally excited electromagnetic wave (namely, many-body interaction, MBI). The MBI regime is analyzed using the many-body radiative heat transfer theory at the particle scale for networks of a few nanoparticles. Effect of MBI on radiative he

Sebastian Golat, Jack J. Kingsley-Smith, Iago Diez, Josep Martinez-Romeu

Optical fields can exert forces of chiral nature on molecules and nanoparticles, which would prove extremely valuable in the separation of enantiomers with pharmaceutical applications, yet it is inherently complex, and the varied frameworks used in the literature further complicate the theoretical understanding. This paper unifies existing approaches used to

Uladzislau Kapustsin, Utku Kaya, Johannes Pfefferer, Thomas Richter

We describe and analyze a hybrid finite element/neural network method for predicting solutions of partial differential equations. The methodology is designed for obtaining fine scale fluctuations from neural networks in a local manner. The network is capable of locally correcting a coarse finite element solution towards a fine solution taking the source term

Daniele Malitesta, Claudio Pomo, Tommaso Di Noia

Graph neural networks (GNNs) have gained prominence in recommendation systems in recent years. By representing the user-item matrix as a bipartite and undirected graph, GNNs have demonstrated their potential to capture short- and long-distance user-item interactions, thereby learning more accurate preference patterns than traditional recommendation approache

Sangyong Jeon

Recent years have seen much development in analyzing the structure of relativistic hydrodynamics. In this proceeding, some of the developments are highlighted including issues related to pseudo-gauge transformations and spin hydrodynamics.

Daniel J. Cornwell, Ulrike Kuchner, Meghan E. Gray, Alfonso Aragón-Salamanca

We investigate the efficacy of using the cosmic web nodes identified by the DisPerSE topological filament finder to systematically identify galaxy groups in the infall regions around massive clusters. The large random motions and infall velocities of galaxies in the regions around clusters complicate the detection and characterisation of substructures throug

Kristian Stølevik Olsen, Deepak Gupta, Francesco Mori, Supriya Krishnamurthy

Recent experiments have implemented resetting by means of an external trap, whereby a system relaxes to the minimum of the trap and is reset in a finite time. In this work, we set up and analyse the thermodynamics of such a protocol. We present a general framework, even valid for non-Poissonian resetting, that captures the thermodynamic work required to main

Khushboo Verma, Marina Moore, Stephanie Wottrich, Karla Robles López

In response to the pressing need for advanced clinical problem-solving tools in healthcare, we introduce BooksMed, a novel framework based on a Large Language Model (LLM). BooksMed uniquely emulates human cognitive processes to deliver evidence-based and reliable responses, utilizing the GRADE (Grading of Recommendations, Assessment, Development, and Evaluat

Natacha Luka, Romain Negrel, David Picard

In recent research, Learned Image Compression has gained prominence for its capacity to outperform traditional handcrafted pipelines, especially at low bit-rates. While existing methods incorporate convolutional priors with occasional attention blocks to address long-range dependencies, recent advances in computer vision advocate for a transformative shift t

Michael Pitt

The top quark plays a central role in particle physics, as many experiments at the Large Hadron Collider scrutinize its properties within the Standard Model. Although most of the measurements of the top quarks today concentrate on production modes initiated by quarks or gluons, this review will highlight the lesser-explored modes initiated by pomerons or pho

Guan-hua Huang, Zhigang Wu

Recently a quantum simulator for the 2D Fermi-Hubbard model on an anisotropic triangular lattice has been realized, where both geometrical frustration and doping can be continuously tuned. Here we provide a comprehensive comparison between the magnetic correlations calculated by the two-particle self-consistent (TPSC) theory and those measured in this quantu