May 2024 arXiv papers — page 13

Mohammad Hossein Moslemi, Mostafa Milani

Entity Matching (EM) is a critical task in numerous fields, such as healthcare, finance, and public administration, as it identifies records that refer to the same entity within or across different databases. EM faces considerable challenges, particularly with false positives and negatives. These are typically addressed by generating matching scores and appl

Xin Liao

In this paper, building on the ideas of Brasco and Pratelli (Geom. Funct. Anal., 22 (2012), 107-135), we establish a stability estimate for Bucur and Henrot's inequality (Acta Math., 222 (2019), 337-361). Their inequality asserts that, among regular sets of given measure, the disjoint union of two balls with the same radius maximizes the second non trivial e

Joan Elias

In this paper we give conditions on a homogeneous polynomial for which the associated graded Artin algebra is a complete intersection.

Dion Donné, Rony Keppens

The mass cycle of solar prominences or filaments is still not completely understood. Researchers agree that these dense structures form by coronal in-situ condensations and plasma siphoning from the underlying chromosphere. In the evaporation-condensation model siphoning arises due to evaporation of chromospheric plasma from localised footpoint heating but t

Gianira N. Alfarano, Joachim Rosenthal, Beatrice Toesca

In this paper, we initiate the study of constant dimension subspace codes restricted to Schubert varieties, which we call Schubert subspace codes. These codes have a very natural geometric description, as objects that we call intersecting sets with respect to a fixed subspace. We provide a geometric construction of maximum size constant dimension subspace co

Zhuang Qi, Lei Meng, Ruohan Zhang, Yu Wang

Federated learning benefits from cross-training strategies, which enables models to train on data from distinct sources to improve generalization capability. However, due to inherent differences in data distributions, the optimization goals of local models remain misaligned, and this mismatch continues to manifest as feature space heterogeneity even after cr

John W. Brooks, Christine M. Greve

The sudden onset of deleterious and oscillatory dynamics (often called instabilities) is a known challenge in many fluid, plasma, and aerospace systems. These dynamics are difficult to address because they are nonlinear, chaotic, and are often too fast for active control schemes. In this work, we develop an alternative active controls system using an iterati

Pengyu Jie, Wanquan Liu, Chenqiang Gao, Yihui Wen

Lesion segmentation on nasal endoscopic images is challenging due to its complex lesion features. Fully-supervised deep learning methods achieve promising performance with pixel-level annotations but impose a significant annotation burden on experts. Although weakly supervised or semi-supervised methods can reduce the labelling burden, their performance is s

E. Aydiner, E. Yilmaz

Power-law distribution is one of the most important laws known in nature. Such a special universal behavior is known to occur in very few physical systems. In this Letter, we analyzed the mortality distribution of the Covid-19 pandemic tails for different countries and continents to discuss the possible universal behavior of the pandemic. Surprisingly, we fo

Julian Heeck

We review the status and importance of lepton flavor violation with tauons, focusing on overlooked flavor-breaking patterns as well as tau-flavor violation in nucleon decays.

Jieun Yook, Junpyo Seo, Joon Huh, Han Joon Byun

We propose a new transformer model for the Traveling Salesman Problem (TSP) called CycleFormer. We identified distinctive characteristics that need to be considered when applying a conventional transformer model to TSP and aimed to fully incorporate these elements into the TSP-specific transformer. Unlike the token sets in typical language models, which are

ATLAS Collaboration

$Z$ boson events at the Large Hadron Collider can be selected with high purity and are sensitive to a diverse range of QCD phenomena. As a result, these events are often used to probe the nature of the strong force, improve Monte Carlo event generators, and search for deviations from Standard Model predictions. All previous measurements of $Z$ boson producti

ATLAS Collaboration

A search is presented for non-resonant Higgs boson pair production, targeting the $bbZZ$, 4$V$ ($V$ = $W$ or $Z$), $VV\tau\tau$, 4$\tau$, $\gamma\gamma VV$ and $\gamma\gamma\tau\tau$ decay channels. Events are categorised based on the multiplicity of light charged leptons (electrons or muons), hadronically decaying tau leptons, and photons. The search is bas

Jiacheng Miao, Qiongshi Lu

Machine learning (ML) is playing an increasingly important role in scientific research. In conjunction with classical statistical approaches, ML-assisted analytical strategies have shown great promise in accelerating research findings. This has also opened a whole field of methodological research focusing on integrative approaches that leverage both ML and s

Afrah Gueriani, Hamza Kheddar, Ahmed Cherif Mazari

The rise of new complex attacks scenarios in Internet of things (IoT) environments necessitate more advanced and intelligent cyber defense techniques such as various Intrusion Detection Systems (IDSs) which are responsible for detecting and mitigating malicious activities in IoT networks without human intervention. To address this issue, deep reinforcement l

Taichi Murayama, Kunihiro Miyazaki, Yasuko Matsubara, Yasushi Sakurai

The advent of generative AI tools has had a profound impact on societies globally, transcending geographical boundaries. Understanding these tools' global reception and utilization is crucial for service providers and policymakers in shaping future policies. Therefore, to unravel the perceptions and engagements of individuals within diverse linguistic commun

Joseph Gorkos, Karsten Grenzig, Erfan Nasirzadeh Orang, Victoria Thomas

The simplest three-level system exhibiting electromagnetically induced transparency (EIT) exhibits an effective conjugation symmetry as well as a permutation symmetry. Breaking conjugation symmetry leads to a distinct chirp asymmetry; the differential response to a frequency increase versus a frequency decrease. Hanle-Zeeman EIT resonance is an ideal platfor

Emma M. Louden, Songhu Wang, Joshua N. Winn, Erik A. Petigura

The distribution of stellar obliquities provides critical insight into the formation and evolution pathways of exoplanets. In the past decade, it was found that hot stars hosting hot Jupiters are more likely to have high obliquities than cool stars, but it is not clear whether this trend exists only for hot Jupiters or holds for other types of planets. In th

Emanuel Malvetti, Léo Van Damme

Closed bipartite quantum systems subject to fast local unitary control are studied using quantum optimal control theory and a method of reduced control systems based on the Schmidt decomposition. Particular focus is given to the time-optimal generation of maximally entangled states and product states, as well as to the problem of stabilizing quantum states w

Susmita Tripathy, Surajit Das, Shweta Jindal, Raghunathan Ramakrishnan

We present machine learning models based on kernel-ridge regression for predicting X-ray photoelectron spectra of organic molecules originating from the $K$-shell ionization energies of carbon (C), nitrogen (N), oxygen (O), and fluorine (F) atoms. We constructed the training dataset through high-throughput calculations of $K$-shell core-electron binding ener

Jiangkai Wu, Liming Liu, Yunpeng Tan, Junlin Hao

With the exponential growth of video traffic, traditional video streaming systems are approaching their limits in compression efficiency and communication capacity. To further reduce bitrate while maintaining quality, we propose Promptus, a disruptive semantic communication system that streaming prompts instead of video content, which represents real-world v

Shuhong Liu, Tianchen Deng, Heng Zhou, Liuzhuozheng Li

Gaussian Splatting SLAMs have made significant advancements in improving the efficiency and fidelity of real-time reconstructions. However, these systems often encounter incomplete reconstructions in complex indoor environments, characterized by substantial holes due to unobserved geometry caused by obstacles or limited view angles. To address this challenge

Masashi Hatano, Ryo Hachiuma, Hideo Saito

Predicting future human behavior from egocentric videos is a challenging but critical task for human intention understanding. Existing methods for forecasting 2D hand positions rely on visual representations and mainly focus on hand-object interactions. In this paper, we investigate the hand forecasting task and tackle two significant issues that persist in

Zishuo Zhu

At present, most of the prediction studies related to antagonistic event-group competitions focus on the prediction of competition results, and less on the prediction of the competition process, which can not provide real-time feedback of the athletes' state information in the actual competition, and thus can not analyze the changes of the competition situat

Taira Tsuchiya, Shinji Ito

Follow-the-Regularized-Leader (FTRL) is a powerful framework for various online learning problems. By designing its regularizer and learning rate to be adaptive to past observations, FTRL is known to work adaptively to various properties of an underlying environment. However, most existing adaptive learning rates are for online learning problems with a minim

Xiao Liu, Mark Zwolinski, Basel Halak

Many cache designs have been proposed to guard against contention-based side-channel attacks. One well-known type of cache is the randomized remapping cache. Many randomized remapping caches provide fixed or over protection, which leads to permanent performance degradation, or they provide flexible protection, but sacrifice performance against strong content

Lance Fortnow, William Gasarch

Let G be a context-free grammar (CFG) in Chomsky normal form. We take the number of rules in G to be the size of G. We also assume all CFGs are in Chomsky normal form. We consider the question of, given a string w of length n, what is the smallest CFG such that L(G)={w}? We show the following: 1) For all w, |w|=n, there is a CFG of size with O(n/log n) rules

Michael Fuchs, Emilie Genty, Adrian Bangerter, Klaus Zuberbühler

This paper addresses the significant challenge of recognizing behaviors in non-human primates, specifically focusing on chimpanzees. Automated behavior recognition is crucial for both conservation efforts and the advancement of behavioral research. However, it is significantly hindered by the labor-intensive process of manual video annotation. Despite the av

Yang Zhou, Shimin Shan, Hongkui Wei, Zhehuan Zhao

Relation Extraction (RE) aims at recognizing the relation between pairs of entities mentioned in a text. Advances in LLMs have had a tremendous impact on NLP. In this work, we propose a textual data augmentation framework called PGA for improving the performance of models for RE in the scientific domain. The framework introduces two ways of data augmentation

Thai-Hoc Vu, Senthil Kumar Jagatheesaperumal, Minh-Duong Nguyen, Nguyen Van Huynh

The success of Artificial Intelligence (AI) in multiple disciplines and vertical domains in recent years has promoted the evolution of mobile networking and the future Internet toward an AI-integrated Internet-of-Things (IoT) era. Nevertheless, most AI techniques rely on data generated by physical devices (e.g., mobile devices and network nodes) or specific

Hirai Mukasa, Koji Tsukuda

General ridge estimators are typical linear estimators in a general linear model. The class of them includes some shrinkage estimators in addition to classical linear unbiased estimators such as the ordinary least squares estimator and the weighted least squares estimator. We derive necessary and sufficient conditions under which two general ridge estimators

B. Eslam Panah, B. Hazarika, P. Phukon

In order to include the effect of high energy and topological parameters on black holes in $F(R)$ gravity, we consider two corrections to this gravity: energy-dependent spacetime with different topological constants, and a nonlinear electrodynamics field. In other words, we combine $F(R)$ gravity's rainbow with ModMax nonlinear electrodynamics theory to see

Julien Fontchastagner, Jean-François Scheid, Jean-Régis Angilella, Jean-Pierre Brancher

We investigate the 3D stationary flow of a weakly conducting fluid in a cubic cavity, driven by the Lorentz force created by two permanent magnets and a weak constant current. Our goal is to determine the conditions leading to efficient mixing within the cavity. The flow is composed of a large recirculation cell created by one side magnet, superposed to two

Y. V. Semenova, S. G. Solodky

In this paper, we study optimization problems of numerical differentiation and summation methods on classes of univariate functions. Sharp estimates (in order) of the optimal recovery error and information complexity are calculated for these classes. Algorithms are constructed based on the truncation method and Chebyshev polynomials to implement these estima

Keming Chen, Guillaume Woessner

In this work we firstly answer to a question raised by Khoshnevisan in \cite[Open Problem 4]{khoshnevisan2007slices} by proving that almost surely there is no projection of big enough rank changing the Hausdorff dimension of the zeros of the Brownian sheet. Secondly, we prove that almost surely for every projection whose rank isn't matching the aforementione

Ziyan Wang, Meng Fang, Tristan Tomilin, Fei Fang

The role of natural language constraints in Safe Multi-agent Reinforcement Learning (MARL) is crucial, yet often overlooked. While Safe MARL has vast potential, especially in fields like robotics and autonomous vehicles, its full potential is limited by the need to define constraints in pre-designed mathematical terms, which requires extensive domain experti

Mehmet Baskurt, Paul Erhart, Julia Wiktor

Cs$_2$AgBiBr$_6$ exhibits promising photovoltaic and light-emitting properties, making it a candidate for next-generation solar cells and LED technologies. Additionally, it serves as a model system within the family of halide double perovskites, offering insights into the broader class of materials. Here, we study various possible excited states of this mate

Nikita Zvonkov

The weight of the minimum spanning tree in a complete weighted graph with random edge weights is a well-known problem. For various classes of distributions, it is proved that the weight of the minimum spanning tree tends to a constant, which can be calculated depending on the distribution. In this paper, we generalise this result to the hypergraphs setting.

Haoxuan Ji, Zheng Lin, Zhenxing Niu, Xinbo Gao

This paper focuses on jailbreaking attacks against large language models (LLMs), eliciting them to generate objectionable content in response to harmful user queries. Unlike previous LLM-jailbreak methods that directly orient to LLMs, our approach begins by constructing a multimodal large language model (MLLM) built upon the target LLM. Subsequently, we perf

Zeyneddin Oz, Ceylan Soygul Oz, Abdollah Malekjafarian, Nima Afraz

Federated Learning (FL) is commonly used in systems with distributed and heterogeneous devices with access to varying amounts of data and diverse computing and storage capacities. FL training process enables such devices to update the weights of a shared model locally using their local data and then a trusted central server combines all of those models to ge

Linda Capito, Guillermo A. Castillo, Bowen Weng

Risk assessment of a robot in controlled environments, such as laboratories and proving grounds, is a common means to assess, certify, validate, verify, and characterize the robots' safety performance before, during, and even after their commercialization in the real-world. A standard testing program that acquires the risk estimate is expected to be (i) repe

Zhiheng Zhou, Sihao Liu, Weichen Zhao

Graph Neural Networks (GNNs) are powerful tools for handling graph-type data. Recently, GNNs have been widely applied in various domains, but they also face some issues, such as overfitting, over-smoothing and non-robustness. The existing research indicates that random dropout methods are an effective way to address these issues. However, random dropout meth

Alexander Azarov, Augustinas Galeckas, Ildikó Cora, Zsolt Fogarassy

Gallium oxide (Ga2O3) can be crystallized in several polymorphs exhibiting different physical properties. In this work, polymorphic structures consisting of the cubic defective spinel (gamma) film on the top of the monoclinic (beta) substrate were fabricated by disorder-induced ordering, known to be a practical way to stack these polymorphs together. Such bi

Masahiko Yoshinaga

We introduce the notion of locally consistent system of half-spaces for a real hyperplane arrangement. We embed a sphere in the complexified complement by shifting the real unit sphere into the imaginary direction indicated by the half-spaces. We then prove that the sphere is homotopically trivial if and only if the system of half-spaces is globally consiste

Alexandra Kozyreva, Luke Shingles, Petr Baklanov, Alexey Mironov

We examine the pair-instability origin of superluminous supernova 2018ibb. As the base model, we use a non-rotating stellar model with an initial mass of 250 Msun at about 1/15 solar metallicity. We consider three versions of the model as input for radiative transfer simulations done with the STELLA and ARTIS codes: with 25 Msun of 56Ni, 34 Msun of 56Ni, and

Bin Ren, Yawei Li, Jingyun Liang, Rakesh Ranjan

Image Restoration (IR), a classic low-level vision task, has witnessed significant advancements through deep models that effectively model global information. Notably, the emergence of Vision Transformers (ViTs) has further propelled these advancements. When computing, the self-attention mechanism, a cornerstone of ViTs, tends to encompass all global cues, e

Shubhanshi Gupta

For a prime $p,$ let $\mathbb{F}_q$ be a finite extension of $\mathbb{F}_p.$ The restriction of an irreducible mod $p$ representation of $\text{GL}_2(\mathbb{F}_q)$ to its subgroup $\text{GL}_2(\mathbb{F}_p)$ can be seen as a tensor product of irreducible representations of $\text{GL}_2(\mathbb{F}_p).$ In this paper, we study the restriction of some of these

Thomas M. Bendall, James Kent

Local conservation of mass and entropy are becoming increasingly desirable properties for modern numerical weather and climate models. This work presents a Flux-Form Semi-Lagrangian (FFSL) transport scheme, called SWIFT, that facilitates this conservation for tracer variables, whilst maintaining other vital properties such as preservation of a constant, mono

Arianna Dionigi, Barbara Gatti

A problem of current interest, also motivated by applications to Coding theory, is to find explicit equations for \textit{maximal} curves, that are projective, geometrically irreducible, non-singular curves defined over a finite field $\mathbb{F}_{q^2}$ whose number of $\mathbb{F}_{q^2}$-rational points attains the Hasse-Weil upper bound of $q^2+2\mathfrak{g

Jorma Harju, Charlotte Vastel, Olli Sipilae, Elena Redaelli

(abridged) We have mapped the prestellar core H-MM1 in Ophiuchus in rotational lines of ortho-H2D+ (oH2D+), N2H+, and DCO+ at the wavelength 0.8 mm with the Large APEX sub-Millimeter Array (LAsMA) multibeam receiver of the Atacama Pathfinder EXperiment (APEX) telescope. We also ran a series of chemistry models to predict the abundance distributions of the ob

Alexander Nikitin, Jannik Kossen, Yarin Gal, Pekka Marttinen

Uncertainty quantification in Large Language Models (LLMs) is crucial for applications where safety and reliability are important. In particular, uncertainty can be used to improve the trustworthiness of LLMs by detecting factually incorrect model responses, commonly called hallucinations. Critically, one should seek to capture the model's semantic uncertain

Peter J. Cameron, Coen del Valle, Colva M. Roney-Dougal

Let $k$ and $l$ be integers, both at least 2. A $(k,l)$-bipartite graph is an $l$-regular bipartite multigraph with coloured bipartite sets of size $k$. Define $\chi(k,l)$ and $\mu(k,l)$ to be the minimum and maximum order of automorphism groups of $(k,l)$-bipartite graphs, respectively. We determine $\chi(k,l)$ and $\mu(k,l)$ for $k\geq 8$, and analyse the

Meng Xiao, Yulei Ye, Xinyu Zhu

Reaching a high precision of the top quark mass is an important task of the Large Hadron Collider. We perform a feasibility study of measuring the top quark mass through the three-point energy correlator. The expected sensitivity of the top quark mass in the boosted regime is presented. We further introduce its application to the low top $p_\text{T}$ regime

Hao Zhang, Longxiang Jiang, Xinkun Chu, Yong Wen

The great success of Physics-Informed Neural Networks (PINN) in solving partial differential equations (PDEs) has significantly advanced our simulation and understanding of complex physical systems in science and engineering. However, many PINN-like methods are poorly scalable and are limited to in-sample scenarios. To address these challenges, this work pro

Xu Chen, Dongjun Fan, Rongxiao Shao, Guoping Wang

In this paper, we determine the graphs whose spectral radius and distance spectral radius attain maximum and minimum among all complements of clique trees. Furthermore, we also determine the graphs whose spectral radius and distance spectral radius attain minimum and maximum among all complements of block graphs, respectively.

Hyungho Na, Il-chul Moon

In cooperative multi-agent reinforcement learning (MARL), agents collaborate to achieve common goals, such as defeating enemies and scoring a goal. However, learning goal-reaching paths toward such a semantic goal takes a considerable amount of time in complex tasks and the trained model often fails to find such paths. To address this, we present LAtent Goal

Alejandro Milani, Alejandro Mac Cawley

Forecasts and future beliefs play a critical role in the harvest labor hiring planning, especially when errors in them entails fixing previous made decisions, which can carry extra costs or losses. In this article, we study the effect that errors in the forecast/belief can have in the wine grape harvest planning process and the losses of the product. Errors

Honghao Fu, Yufei Wang, Wenhan Yang, Alex C. Kot

Blind image quality assessment (IQA) in the wild, which assesses the quality of images with complex authentic distortions and no reference images, presents significant challenges. Given the difficulty in collecting large-scale training data, leveraging limited data to develop a model with strong generalization remains an open problem. Motivated by the robust

Javier Maass, Joaquin Fontbona

We develop a Mean-Field (MF) view of the learning dynamics of overparametrized Artificial Neural Networks (NN) under data symmetric in law wrt the action of a general compact group $G$. We consider for this a class of generalized shallow NNs given by an ensemble of $N$ multi-layer units, jointly trained using stochastic gradient descent (SGD) and possibly sy

Giacomo Rosilho de Souza, Simone Pezzuto, Rolf Krause

Simulation of the monodomain equation, crucial for modeling the heart's electrical activity, faces scalability limits when traditional numerical methods only parallelize in space. To optimize the use of large multi-processor computers by distributing the computational load more effectively, time parallelization is essential. We introduce a high-order paralle

Tomonari Mizoguchi, Nobuyuki Okuma

We prove that two formulas of the orbital magnetic susceptibility, namely, Koshino-Ando's formula and G\'{o}mez-Santos and Stauber's formula, are equivalent for the tight-binding models. The difference between these two formulas can be written in a form containing the surface terms arising from the momentum-space integration, and we show that the surface ter

Dipankar Ghosh, Siddhartha Pramanik

Let $R$ be a Noetherian $\mathbb{N}$-graded ring. Let $L$, $M$ and $N$ be finitely generated graded $R$-modules with $N \subseteq M$. For a homogeneous ideal $I$, and for each fixed $k \in \mathbb{N}$, we show the asymptotic linearity of v-numbers of the graded modules $ {\rm Ext}_R^{k}(L,{I^{n}M}/{I^{n}N})$ and ${\rm Tor}_k^{R}(L,{I^{n}M}/{I^{n}N})$ as func

Yuchen Quan, Xiaoya Zhai, Xiao-Ming Fu

Thermal microstructures are artificially engineered materials designed to manipulate and control heat flow in unconventional ways. This paper presents an educational framework, called \emph{OpenTM}, to use a single GPU for designing periodic 3D high-resolution thermal microstructures to match the predefined thermal conductivity matrices with volume fraction

Wenli Sun, Xinyang Jiang, Dongsheng Li, Cairong Zhao

Person Re-Identification (ReID) systems pose a significant security risk from backdoor attacks, allowing adversaries to evade tracking or impersonate others. Beyond recognizing this issue, we investigate how backdoor attacks can be deployed in real-world scenarios, where a ReID model is typically trained on data collected in the digital domain and then deplo

Shuai Wan, Pi-Yu Wang, Ming Li, Rui Ma

Optical frequency combs (OFCs), composed of equally spaced frequency tones, have spurred advancements in communications, spectroscopy, precision measurement and fundamental physics research. A prevalent method for generating OFCs involves the electro-optic (EO) effect, i.e., EO comb, renowned for its rapid tunability via precise microwave field control. Rece

Minttu Alakuijala, Reginald McLean, Isaac Woungang, Nariman Farsad

Natural language is often the easiest and most convenient modality for humans to specify tasks for robots. However, learning to ground language to behavior typically requires impractical amounts of diverse, language-annotated demonstrations collected on each target robot. In this work, we aim to separate the problem of what to accomplish from how to accompli

Deepak S. Kathyat, Pinaki Sengupta

We report a microscopic mechanism for stabilization of biskyrmions in nature by investigating a minimal classical spin lattice model with nearest neighbour ferromagnetic Heisenberg exchange and static chiral magnetic interaction on the triangular lattice. The model is physically motivated model from the Mott insulators with broken time-reversal symmetry, tha

Helge F. Goessling, Thomas Rackow, Thomas Jung

In 2023, the global mean temperature soared to 1.48K above the pre-industrial level, surpassing the previous record by 0.17K. Previous best-guess estimates of known drivers including anthropogenic warming and the El Nino onset fall short by about 0.2K in explaining the temperature rise. Utilizing satellite and reanalysis data, we identify a record-low planet

Elisabeth Ailer, Niclas Dern, Jason Hartford, Niki Kilbertus

Scientific hypotheses typically concern specific aspects of complex, imperfectly understood or entirely unknown mechanisms, such as the effect of gene expression levels on phenotypes or how microbial communities influence environmental health. Such queries are inherently causal (rather than purely associational), but in many settings, experiments can not be

Ritwik Mukherjee, Soumyabrata Saha, Tridib Sadhu, Abhishek Dhar

We present a fluctuating hydrodynamic description of an active lattice gas model with excluded volume interactions that exhibits motility-induced phase separation under appropriate conditions. For quasi-one dimension and higher, stability analysis of the noiseless hydrodynamics gives quantitative bounds on the phase boundary of the motility-induced phase sep

Torsten Röper, Hugo Thomas, Daniel Rosenbach, Anjana Uday

The quantum anomalous Hall (QAH) effect, with its single chiral, topologically protected edge state, offers a platform for flying Majorana states as well as non-reciprocal microwave devices. While recent research showed the non-reciprocity of edge plasmons in Cr-doped $\mathrm{(Bi_xSb_\text{1-x})_2Te_3}$, the understanding of their dissipation remains incomp

Davoud Sarani, Parviz Rashidi-Khazaee

In today's forex market traders increasingly turn to algorithmic trading, leveraging computers to seek more profits. Deep learning techniques as cutting-edge advancements in machine learning, capable of identifying patterns in financial data. Traders utilize these patterns to execute more effective trades, adhering to algorithmic trading rules. Deep reinforc

G. R. Boroun

We present an analysis of the color-dipole picture (CDP) for determination of the gluon density at low-$x$ which is obtained from the Altarelli-Martinelli equation by expansion at distinct points of expansion. The dipole cross-sections with respect to the improved saturation model of Bartels-Golec-Biernat-Kowalski (BGK) are obtained in a wide range of transv

Kristian Arjas, Jani M. Taskinen, Rebecca Heilmann, Grazia Salerno

Photonic modes exhibiting a polarization winding akin to a vortex possess an integer topological charge. Lasing with topological charge 1 or 2 can be realized in periodic lattices of up to six-fold rotational symmetry. Higher order charges require symmetries not compatible with any two-dimensional Bravais lattice. Here, we experimentally demonstrate lasing w

Paolo Benincasa, Francisco Vazão

Cosmological observables in perturbation theory turn out to be plagued with infrared divergences, which represents both a conceptual and computational challenge. In this paper we present a proof of concept for a systematic procedure to remove these divergences in a large class of scalar cosmological integrals and consistently define an infrared safe computab

Wenzhe Yin, Shujian Yu, Yicong Lin, Jie Liu

Domain adaptation aims to use training data from one or multiple source domains to learn a hypothesis that can be generalized to a different, but related, target domain. As such, having a reliable measure for evaluating the discrepancy of both marginal and conditional distributions is crucial. We introduce Cauchy-Schwarz (CS) divergence to the problem of uns

Paul Dütting, Federico Fusco, Silvio Lattanzi, Ashkan Norouzi-Fard

Maximizing monotone submodular functions under cardinality constraints is a classic optimization task with several applications in data mining and machine learning. In this paper we study this problem in a dynamic environment with consistency constraints: elements arrive in a streaming fashion and the goal is maintaining a constant approximation to the optim

Qurban Ali, Oliviero Riganelli, Leonardo Mariani

In the ever-evolving field of Deep Learning (DL), ensuring project quality and reliability remains a crucial challenge. This research investigates testing practices within DL projects in GitHub. It quantifies the adoption of testing methodologies, focusing on aspects like test automation, the types of tests (e.g., unit, integration, and system), test suite g

V. Oldani, F. Manzini, P. Ochner, A. Reguitti

Comet 81P (Wild 2) is characterized by the presence of a prominent-fan shaped dust emission originating from an active source at high latitude on the nucleus, whose axis is assumed to coincide with the comet's rotation axis. Therefore, several authors estimated the spin axis orientation of 81P in past apparitions based on the polar jet model. By measuring th

Jan Klos, Jan Tröger, Jens Keutgen, Merritt P. Losert

Understanding crystal characteristics down to the atomistic level increasingly emerges as a crucial insight for creating solid state platforms for qubits with reproducible and homogeneous properties. Here, isotope composition depth profiles in a SiGe/$^{28}$Si/SiGe heterostructure are analyzed with atom probe tomography (APT) and time-of-flight secondary-ion

Yang-Hui He

Recent years have seen the dramatic rise of the usage of AI algorithms in pure mathematics and fundamental sciences such as theoretical physics. This is perhaps counter-intuitive since mathematical sciences require the rigorous definitions, derivations, and proofs, in contrast to the experimental sciences which rely on the modelling of data with error-bars.

Martina Zündel, Leonardo Mazza, Léonie Canet, Anna Minguzzi

We investigate the correlation properties in the steady state of driven-dissipative interacting bosonic systems in the quantum regime, as for example non-linear photonic cavities. Specifically, we consider the Bose-Hubbard model on a periodic chain and with spatially homogeneous one-body loss and pump within the Markovian approximation. The steady state is n

Zekai Liu, Xiaoqi Li, Hongli Peng, Wenkai Li

The openness and transparency of Ethereum transaction data make it easy to be exploited by any entities, executing malicious attacks. The sandwich attack manipulates the Automated Market Maker (AMM) mechanism, profiting from manipulating the market price through front or after-running transactions. To identify and prevent sandwich attacks, we propose a casca

Petra Saskia Bayerl, Babak Akhgar, Ernesto La Mattina, Barbara Pirillo

This paper investigates citizens' counter-strategies to the use of Artificial Intelligence (AI) by law enforcement agencies (LEAs). Based on information from three countries (Greece, Italy and Spain) we demonstrate disparities in the likelihood of ten specific counter-strategies. We further identified factors that increase the propensity for counter-strategi

Joerg Stiller

Semi-implicit spectral deferred correction (SDC) methods provide a systematic approach to construct time integration methods of arbitrarily high order for nonlinear evolution equations including conservation laws. They converge towards $A$- or even $L$-stable collocation methods, but are often not sufficiently robust themselves. In this paper, a family of SD

Benjamin Icard

In the field of human intelligence, officers use an alphanumeric scale, known as the Admiralty System, to rate the credibility of messages and the reliability of their sources (NATO AJP-2.1, 2016). During this evaluation, they are expected to estimate the credibility and reliability dimensions independently of each other (NATO STANAG, 2003). However, empiric

Hossam M. Zawbaa, Wael Rashwan, Sourav Dutta, Haytham Assem

Detecting out-of-scope user utterances is essential for task-oriented dialogues and intent classification. Current methodologies face difficulties with the unpredictable distribution of outliers and often rely on assumptions about data distributions. We present the Dual Encoder for Threshold-Based Re-Classification (DETER) to address these challenges. This e

Michael Foltýn, Marek Patočka, Rostislav Řepa, Tomáš Šikola

The behavior of plasmonic antennas is influenced by a variety of factors, including their size, shape, and material. Even minor changes in the deposition parameters during the thin film preparation process may have a significant impact on the dielectric function of the film, and thus on the plasmonic properties of the resulting antenna. In this work, we depo

Mengchen Lian

BCH codes are an important class of linear codes and find extensive utilization in communication and disk storage systems.This paper mainly analyzes the negacyclic BCH code and cyclic BCH code of length $\frac{q^m-1}{2}$. For negacyclic BCH code, we give the dimensions of $C_{(n,-1,\left\lceil \frac{\delta+1}{2}\right\rceil,0)}$ for $\delta =a\frac{q^m-1}{q-

Faegheh S. Sajjadian, Laura Galleni, Kevin M. Dorney, Dhirendra P. Singh

Device architectures and dimensions are now at an unimaginable level not thought possible even 10 years ago. The continued downscaling, following the so-called Moore's law, has motivated the development and use of extreme ultraviolet (EUV) lithography scanners with specialized photoresists. Since the quality and precision of the transferred circuit pattern i

Gihyun Lee, Max Lein

A fundamental result in pseudodifferential theory is the Calder\'on-Vaillancourt theorem, which states that a pseudodifferential operator defined from a H\"ormander symbol of order $0$ defines a bounded operator on $L^2(\mathbb{R}^d)$. In this work we prove an analog for pseudodifferential \emph{super} operator, \ie operators acting on other operators, in th

Roberto G. Pousa, Daniel K. L. Oi, John Jeffers

Advancements in practical single-photon sources (SPS) exhibiting high brightness and low $g^{(2)}(0)$ have garnered significant interest for their application in quantum key distribution (QKD). To assess their QKD performance, it is essential to compare them with the widely employed weak coherent pulses (WCPs) in the decoy state method. In this work, we anal

Isaac YL Lee, Thanh Nguyen-Duc, Ryo Ueno, Jesse Smith

Excessive caregiver workload in hospital nurses has been implicated in poorer patient care and increased worker burnout. Measurement of this workload in the Intensive Care Unit (ICU) is often done using the Nursing Activities Score (NAS), but this is usually recorded manually and sporadically. Previous work has made use of Ambient Intelligence (AmI) by using

Tim Bauer, Lucas R. D. Freitas, Eric C. Andrade, Reinhold Egger

We predict a general local spin-flip transition mechanism caused by magnetic quantum impurities in (partially) polarized phases of quantum magnets in the absence of conservation laws. This transition arises when a magnon bound state crosses zero energy as function of the magnetic field. As application, we study 2D van der Waals magnets described by the Kitae

Kiyoung Seong, Seonghyun Park, Seonghwan Kim, Woo Youn Kim

Understanding transition pathways between two meta-stable states of a molecular system is crucial to advance drug discovery and material design. However, unbiased molecular dynamics (MD) simulations are computationally infeasible because of the high energy barriers that separate these states. Although recent machine learning techniques are proposed to sample

Pedro H. Cezar, Miriani G. Pastoriza, Rogério Riffel, Cristina Ramos Almeida

We present Gemini Multi-Object Spectrograph (GMOS) spectroscopic observations of 95 galaxies from the Arp & Madore (1987) catalogue of peculiar galaxies. These galaxies have been selected because they appear to be in pairs and small groups. These observations have allowed us to confirm that 60 galaxies are indeed interacting systems. For the confirmed intera

Valery V. Ryzhikov

For any natural $n$, and real $\alpha\geq 0$ we construct an ergodic automorphism $T$ such that its tensor powers $T^{\otimes n}$ have singular spectra if $n\leq 1+\alpha /2$, and Lebesgue if $n\, > 1+\alpha/2$.

Yi Liu, Xiangyu Liu, Xiangrong Zhu, Wei Hu

Multi-aspect controllable text generation aims to control the generated texts in attributes from multiple aspects (e.g., "positive" from sentiment and "sport" from topic). For ease of obtaining training samples, existing works neglect attribute correlations formed by the intertwining of different attributes. Particularly, the stereotype formed by imbalanced

David Avis, Charles Jordan

We describe a parallel implementation in lrslib for removing redundant halfspaces and finding a minimum representation for an H-representation of a convex polyhedron. By a standard transformation, the same code works for V-representations. We use this approach to speed up the redundancy removal step in Fourier-Motzkin elimination. Computational results are g

Qiaowei Miao, JinSheng Quan, Kehan Li, Yawei Luo

Previous text-to-4D methods have leveraged multiple Score Distillation Sampling (SDS) techniques, combining motion priors from video-based diffusion models (DMs) with geometric priors from multiview DMs to implicitly guide 4D renderings. However, differences in these priors result in conflicting gradient directions during optimization, causing trade-offs bet