April 2024 arXiv papers — page 15

Rostislav-Paul Wilhelm, Jan Eifert, Manuel Torrilhon

The accurate prediction of occurrence and strength of kinetic instabilities in plasmas remains a significant challenge in nuclear fusion research. To accurately capture the plasmas dynamics one is required to solve the Vlasov equation for several species which, however, comes with a number of challenges as high dimensionality of the model as well as turbulen

Yue Wang, Qing Gao, Shengqing Gao, Yungui Gong

There is a duality in the observables $n_s$, $r$ and the inflaton potential between large and small $\eta_H$ for the constant-roll inflation if the slow-roll parameter $\epsilon_H$ is negligible. In general, the duality between $\eta_H$ and $\bar{\eta}_H$ does not hold for the background evolution of the inflation. For some particular solutions for the const

Qi-Nan Wang, Ding-Kun Lian, Wei Chen

We study the masses of light tetraquark states $ud\bar{u}\bar{d}$ , $us\bar{u}\bar{s}$ and $ss\bar{s}\bar{s}$ with exotic quantum numbers $J^{PC}=2^{+-}$ using the method of QCD sum rules. It is found that there is no tetraquark operator with two Lorentz indices coupling to the $2^{+-}$ quantum numbers. To investigate such tetraquark states, we construct the

Sourav Saha, Harsh Agarwal, V Venktesh, Avishek Anand

While recent advancements in Neural Ranking Models have resulted in significant improvements over traditional statistical retrieval models, it is generally acknowledged that the use of large neural architectures and the application of complex language models in Information Retrieval (IR) have reduced the transparency of retrieval methods. Consequently, Expla

Rong An, Xiang Jiang, Na Tang, Li-Gang Cao

Inspired by the profoundly observed odd-even staggering and the inverted parabolic-like shape in charge radii along calcium isotopic chain, the ground state properties of calcium isotopes are investigated by constraining the root-mean-square (rms) charge radii under the covariant energy density functionals with effective forces NL3 and PK1. In this work, the

Marco Matassa

Consider a decomposition $\mathfrak{n} = \mathfrak{n}_1 \oplus \cdots \oplus \mathfrak{n}_r$ of the positive nilradical of a complex semisimple Lie algebra of rank $r$, where each $\mathfrak{n}_k$ is a module under an appropriate Levi factor. We show that this can be quantized as a finite-dimensional subspace $\mathfrak{n}^q_k = \mathfrak{n}^q_1 \oplus \cdot

Felix Drinkall, Eghbal Rahimikia, Janet B. Pierrehumbert, Stefan Zohren

Large language models (LLMs) are often trained on extensive, temporally indiscriminate text corpora, reflecting the lack of datasets with temporal metadata. This approach is not aligned with the evolving nature of language. Conventional methods for creating temporally adapted language models often depend on further pre-training static models on time-specific

Sven Hertling, Ebrahim Norouzi, Harald Sack

Ontology and knowledge graph matching systems are evaluated annually by the Ontology Alignment Evaluation Initiative (OAEI). More and more systems use machine learning-based approaches, including large language models. The training and validation datasets are usually determined by the system developer and often a subset of the reference alignments are used.

Daniel Gibert

In this chapter, readers will explore how machine learning has been applied to build malware detection systems designed for the Windows operating system. This chapter starts by introducing the main components of a Machine Learning pipeline, highlighting the challenges of collecting and maintaining up-to-date datasets. Following this introduction, various sta

Xinhui Ruan, Li Li, Guihan Liang, Silu Zhao

A hybrid system with tunable coupling between phonons and qubits shows great potential for advancing quantum information processing. In this work, we demonstrate strong and tunable coupling between a surface acoustic wave (SAW) resonator and a transmon qubit based on galvanic-contact flip-chip technique. The coupling strength varies from $2\pi\times$7.0 MHz

Junyi Liu, Zengquan Xu, Shuqi Mo, Yuming Huang

Few-mode multi-core fiber (FM-MCF) based Space-Division Multiplexing (SDM) systems possess the potential to maximize the number of multiplexed spatial channels per fiber by harnessing both the space (fiber cores) and mode (optical mode per core) dimensions. However, to date, no SDM transmissions over field-deployed FM-MCFs in realistic outdoor settings have

Ye Liu, Jie-Ying Li, Li-Sheng Zhang, Lei-Lei Guo

Domain decomposition provides an effective way to tackle the dilemma of physics-informed neural networks (PINN) which struggle to accurately and efficiently solve partial differential equations (PDEs) in the whole domain, but the lack of efficient tools for dealing with the interfaces between two adjacent sub-domains heavily hinders the training effects, eve

Vitor Cerqueira, Nuno Moniz, Ricardo Inácio, Carlos Soares

Recent state-of-the-art forecasting methods are trained on collections of time series. These methods, often referred to as global models, can capture common patterns in different time series to improve their generalization performance. However, they require large amounts of data that might not be readily available. Besides this, global models sometimes fail

Vitalii Vertogradov, Ali Övgün

Recent observations of black hole shadows have revolutionized our ability to probe gravity in extreme environments. This manuscript presents a novel analytic method to calculate, in leading-order terms, the key parameters of photon sphere and shadow radius. This method offers advantages for complex metrics where traditional approaches are cumbersome. We furt

Akshay Sunil, Riddhi Singh, Manvitha Molakala

Multi-purpose reservoirs support socioeconomic development by providing irrigation, domestic water supply, hydropower, and other services. However, impoundment of water impacts instream aquatic ecosystems. Thus, the concept of minimum environmental flows (MEFs) was established to restore the benefits of naturally flowing rivers by specifying minimum flow rat

Guoliang Dong, Haoyu Wang, Jun Sun, Xinyu Wang

By training on text in various languages, large language models (LLMs) typically possess multilingual support and demonstrate remarkable capabilities in solving tasks described in different languages. However, LLMs can exhibit linguistic discrimination due to the uneven distribution of training data across languages. That is, LLMs are hard to keep the consis

Meng Li, Haoran Jin, Ruixuan Huang, Zhihao Xu

With the growing popularity of general-purpose Large Language Models (LLMs), comes a need for more global explanations of model behaviors. Concept-based explanations arise as a promising avenue for explaining high-level patterns learned by LLMs. Yet their evaluation poses unique challenges, especially due to their non-local nature and high dimensional repres

Dingjie Song, Shunian Chen, Guiming Hardy Chen, Fei Yu

Despite the advancements and impressive performance of Multimodal Large Language Models (MLLMs) on benchmarks, their effectiveness in real-world, long-context, and multi-image tasks is unclear due to the benchmarks' limited scope. Existing benchmarks often focus on single-image and short-text samples, and when assessing multi-image tasks, they either limit t

Sergio Morales, Robert Clarisó, Jordi Cabot

The development of Machine Learning (ML) based systems is complex and requires multidisciplinary teams with diverse skill sets. This may lead to communication issues or misapplication of best practices. Process models can alleviate these challenges by standardizing task orchestration, providing a common language to facilitate communication, and nurturing a c

Hans Harder, Jean Rabault, Ricardo Vinuesa, Mikael Mortensen

We utilize extreme-learning machines for the prediction of partial differential equations (PDEs). Our method splits the state space into multiple windows that are predicted individually using a single model. Despite requiring only few data points (in some cases, our method can learn from a single full-state snapshot), it still achieves high accuracy and can

Taichi Kosugi, Shunsuke Daimon, Hirofumi Nishi, Shinji Tsuneyuki

One of the crucial generic techniques for quantum computation is amplitude encoding. Although several approaches have been proposed, each of them often requires exponential classical-computational cost or an oracle whose explicit construction is not provided. Given the growing demands for practical quantum computation, we develop moderately specialized encod

Zhuofu Pan, Qingkai Sui, Yalin Wang, Jiang Luo

Structural decoupling has played an essential role in model-based fault isolation and estimation in past decades, which facilitates accurate fault localization and reconstruction thanks to the diagonal transfer matrix design. However, traditional methods exhibit limited effectiveness in modeling high-dimensional nonlinearity and big data, and the decoupling

Weike Peng, Jiaxin Gao, Yuntian Chen, Shengwei Wang

Machine learning algorithms emerge as a promising approach in energy fields, but its practical is hindered by data barriers, stemming from high collection costs and privacy concerns. This study introduces a novel federated learning (FL) framework based on XGBoost models, enabling safe collaborative modeling with accessible yet concealed data from multiple pa

Y. Pan, H. -L. Zhang, Y. -F. Jiao, D. -Y. Wang

Exceptional points (EPs) are singularities in non-Hermitian systems, where the system transmission spectrum varies significantly at the phase transition point. Here, we propose a practical scheme to study the changes of the optomechanically induced transparency (OMIT) spectrum on the exceptional surface (ES), which is formed by designing the structure of the

Valentina Zaccaria, Chiara Masiero, David Dandolo, Gian Antonio Susto

While Machine Learning has become crucial for Industry 4.0, its opaque nature hinders trust and impedes the transformation of valuable insights into actionable decision, a challenge exacerbated in the evolving Industry 5.0 with its human-centric focus. This paper addresses this need by testing the applicability of AcME-AD in industrial settings. This recentl

Andrew J. Archer, Benjamin D. Goddard, David N. Sibley, James T. Rawlings

Ouzo is a well-known drink in Mediterranean countries, with ingredients water, alcohol and trans-anethole oil. The oil is insoluble in water, but completely soluble in alcohol, so when water is added to the spirit, the available alcohol is depleted and the mixture exhibits spontaneous emulsification. This process is commonly known as the louche or Ouzo effec

Guang-Yu Zhang, Zhi-Hao Liu, Xun-Wei Xu

Photon blockade in weak nonlinear regime is an exciting and promising subject that has been extensively studied in the steady state. However, how to achieve dynamic blockade in a single bosonic mode with weak nonlinearity using only pulsed driving field remains unexplored. Here, we propose to optimize the parameters of the pulsed driving field to achieve dyn

Mihail Stoian

In their seminal work on subset convolution, Bj\"orklund, Husfeldt, Kaski and Koivisto introduced the now well-known $O(2^n n^2)$-time evaluation of the subset convolution in the sum-product ring. This sparked a wave of remarkable results for fundamental problems, such as the minimum Steiner tree and the chromatic number. However, in spite of its theoretical

Jakub Pokrywka, Jeremi Kaczmarek, Edward Gorzelańczyk

Introduction: Recently, the effectiveness of Large Language Models (LLMs) has increased rapidly, allowing them to be used in a great number of applications. However, the risks posed by the generation of false information through LLMs significantly limit their applications in sensitive areas such as healthcare, highlighting the necessity for rigorous validati

Francesco Vista, Daniel Holme, Stephen DiAdamo

To realize a global quantum Internet, there is a need for communication between quantum subnetworks. To accomplish this task, there have been multiple design proposals for a quantum backbone network and quantum subnetworks. In this work, we elaborate on the design that uses entanglement and quantum teleportation to build the quantum backbone between packetiz

Kiwan Park

The objective of this thesis is to ascertain the dimensions of an RF 2.856GHz photoinjector through a combination of analytical and computational approaches. The phase velocity within a single cavity exceeds 'c', rendering it inadequate for storing the requisite energy for beam acceleration. To surmount this limitation, we aim to devise a multi-celled cavity

Usevalad Milasheuski, Luca Barbieri, Bernardo Camajori Tedeschini, Monica Nicoli

Federated Learning (FL) allows multiple privacy-sensitive applications to leverage their dataset for a global model construction without any disclosure of the information. One of those domains is healthcare, where groups of silos collaborate in order to generate a global predictor with improved accuracy and generalization. However, the inherent challenge lie

Jiangfeng Liu, Ziyi Wang, Jing Xie, Lei Pei

Generative large-scale language models create the fifth paradigm of scientific research, organically combine data science and computational intelligence, transform the research paradigm of natural language processing and multimodal information processing, promote the new trend of AI-enabled social science research, and provide new ideas for digital humanitie

Joanna N. Chen, Sergey Kitaev, Philip B. Zhang

We derive functional equations for distributions of six classical statistics (ascents, descents, left-to-right maxima, right-to-left maxima, left-to-right minima, and right-to-left minima) on separable and irreducible separable permutations. The equations are used to find a third degree equation for joint distribution of ascents and descents on separable per

Eren Berk Kama, Junbeom Kim, Emil Björnson

We consider a cell-free massive MIMO system with multiple antennas on the users and access points. In previous works, the downlink spectral efficiency (SE) has been evaluated using the hardening bound that requires no downlink pilots. This approach works well when having single-antenna users. In this paper, we show that much higher SEs can be achieved if dow

Jianyu Zhang, Long Zhang, Yixuan Wu, Feng Yang

Formal Methods (FMs) are currently essential for verifying the safety and reliability of software systems. However, the specification writing in formal methods tends to be complex and challenging to learn, requiring familiarity with various intricate formal specification languages and verification technologies. In response to the increasing complexity of sof

Nicolas Facchinetti, Federico Simonetta, Stavros Ntalampiras

Speech emotion recognition (SER) is constantly gaining attention in recent years due to its potential applications in diverse fields and thanks to the possibility offered by deep learning technologies. However, recent studies have shown that deep learning models can be vulnerable to adversarial attacks. In this paper, we systematically assess this problem by

Yutaka Ohira

We recently found that streaming cosmic rays (CRs) induce a resistive electric field that can accelerate secondary electrons produced by CR ionization. In this work, we study the evolution of the energy spectrum of secondary electrons by numerically solving the one-dimensional Boltzmann equation and Ohm's law. We show that the accelerated secondary electrons

Milutin Obradović, Nikola Tuneski

It is well-known that the condition ${\operatorname{Re}} \left[1+\frac{zf''(z)}{f'(z)}\right]>0$, $z\in{\mathbb D}$, implies that $f$ is starlike function (i.e. convexity implies starlikeness). If the previous condition is not satisfied for every $z\in {\mathbb D}$, then it is possible to get new criteria for starlikeness by using $\left|\arg\left[\alpha+\fr

Peng He, Jing-Xin Liu, Hong Wu, Z. D. Wang

The topological orders in amorphous systems that lack crystalline symmetry have gained considerable attention recently. Here we propose the Floquet amorphous topological matter, among which the topological orders are explored in experimentally accessible one-dimensional array of randomly pointed Rydberg atoms with periodic driving. The topological properties

Xin-Zhu Yin, Na Jiao, Jinlian Lu, Meng-Meng Zheng

Two-dimensional (2D) intrinsic superconductors with nontrivial topological band and vertical ferroelectricity exhibit fascinating characteristics to achieving electrostatic control of quantum phases. While, only a few such 2D materials have been theoretically predicted. In this work, based on first principles calculations, we explore the superconductivity an

Ziye Jia, Yiyang Liao, Chao Dong, Lijun He

Unmanned aerial vehicles (UAVs) are widely applied in multiple fields, which emphasizes the challenge of obtaining UAV flight information to ensure the airspace safety. UAVs equipped with automatic dependent surveillance-broadcast (ADS-B) devices are capable of sending flight information to nearby aircrafts and ground stations (GSs). However, the saturation

Dana Roemling, Yves Scherrer, Aleksandra Miletic

Forensic authorship profiling uses linguistic markers to infer characteristics about an author of a text. This task is paralleled in dialect classification, where a prediction is made about the linguistic variety of a text based on the text itself. While there have been significant advances in recent years in variety classification, forensic linguistics rare

Javier Cueto, Carolin Kreisbeck, Hidde Schönberger

This work revolves around the rigorous asymptotic analysis of models in nonlocal hyperelasticity. The corresponding variational problems involve integral functionals depending on nonlocal gradients with a finite interaction range $\delta$, called the horizon. After an isotropic scaling of the associated kernel functions, we prove convergence results in the t

Mark Schöne, Neeraj Mohan Sushma, Jingyue Zhuge, Christian Mayr

Event-based sensors are well suited for real-time processing due to their fast response times and encoding of the sensory data as successive temporal differences. These and other valuable properties, such as a high dynamic range, are suppressed when the data is converted to a frame-based format. However, most current methods either collapse events into frame

Alessia Spolon, Michele Fiori, Luca Zampieri, Marco Landoni

Stellar intensity interferometry (SII) is based on the correlation of the light intensity fluctuations of a star detected at two or more telescopes, with no need to combine the collected photons directly. A measurement of the correlation in full "photon-counting mode" was experimented with fast photon counters in Italy (2016-2020) and is currently being adap

Rahul Deshpande, Ricardo Vinuesa, Ivan Marusic

Wall-scaled (attached) eddies play a significant role in the overall drag experienced in high-Reynolds-number turbulent boundary layers (TBLs). This study aims to delve into the underlying mechanisms driving this phenomenon by dissecting the active and inactive components of these attached eddies, as initially proposed by Townsend (1976). Employing a recentl

Marco Feder, Andrea Cangiani, Luca Heltai

We present a novel approach to perform agglomeration of polygonal and polyhedral grids based on spatial indices. Agglomeration strategies are a key ingredient in polytopal methods for PDEs as they are used to generate (hierarchies of) computational grids from an initial grid. Spatial indices are specialized data structures that significantly accelerate queri

Martin Tschaikner, Danja Brandt, Henning Schmidt, Felix Bießmann

Insect populations are declining globally, making systematic monitoring essential for conservation. Most classical methods involve death traps and counter insect conservation. This paper presents a multisensor approach that uses AI-based data fusion for insect classification. The system is designed as low-cost setup and consists of a camera module and an opt

Marcin Postolak

A popular science article designed to introduce people familiar with basic cosmological nomenclature with models alternative to cosmological inflation. The paper briefly discusses the modern view of the Big Bang model, inflation (both its advantages and potential deficiencies). This is followed by a discussion of historical alternative models and modern appr

Sebastian Issel, Kilian Tscharke, Pascal Debus

We explore the possibility of accelerating the formal verification of classical programs with a quantum computer. A common source of security flaws stems from the existence of common programming errors like use after free, null-pointer dereference, or division by zero. To aid in the discovery of such errors, we try to verify that no such flaws exist. In our

Ruijie Tao, Xinyuan Qian, Yidi Jiang, Junjie Li

Audio-visual target speaker extraction (AV-TSE) aims to extract the specific person's speech from the audio mixture given auxiliary visual cues. Previous methods usually search for the target voice through speech-lip synchronization. However, this strategy mainly focuses on the existence of target speech, while ignoring the variations of the noise characteri

Benjamin Hollering, Joseph Johnson, Liam Solus

Characteristic imsets are 0/1-vectors representing directed acyclic graphs whose edges represent direct cause-effect relations between jointly distributed random variables. A characteristic imset (CIM) polytope is the convex hull of a collection of characteristic imsets. CIM polytopes arise as feasible regions of a linear programming approach to the problem

W. Benedikt Schmal

Natural language processing tools have become frequently used in social sciences such as economics, political science, and sociology. Many publications apply topic modeling to elicit latent topics in text corpora and their development over time. Here, most publications rely on visual inspections and draw inference on changes, structural breaks, and developme

Lukas Freter, Benedikt Zerulla, Marjan Krstić, Christof Holzer

Pairs of entangled photons are important for applications in quantum nanophotonics, where their theoretical description must accommodate their bipartite character. Such character is shared at the other end of the intensity range by, for example, the two degenerate instances of the pump field involved in second-harmonic generation. The description and numeric

Stefan Hermann, Hans-Peter Lehmann, Giulio Ermanno Pibiri, Peter Sanders

A minimal perfect hash function (MPHF) maps a set of n keys to {1, ..., n} without collisions. Such functions find widespread application e.g. in bioinformatics and databases. In this paper we revisit PTHash - a construction technique particularly designed for fast queries. PTHash distributes the input keys into small buckets and, for each bucket, it searche

Zeeshan Rasheed, Malik Abdul Sami, Muhammad Waseem, Kai-Kristian Kemell

In this paper, we present a novel approach to improving software quality and efficiency through a Large Language Model (LLM)-based model designed to review code and identify potential issues. Our proposed LLM-based AI agent model is trained on large code repositories. This training includes code reviews, bug reports, and documentation of best practices. It a

Zhihong Xia, Peizheng Yu

Inspired by examples of Katok and Milnor \cite{Milnor1997}, we construct simple examples of skew-product volume preserving diffeomorphism where the center foliation is pathological in the sense that, there is a full measure set whose intersection with any center leaf contains at most one point. Comparing with other examples in literature, our mechanism for p

Ziyi Zhao, Xiaohua Zhu

By Perelman's $\mathcal L$-geodesic theory, we study the blow-down solutions on a noncompact $\kappa$-noncollapsed steady gradient Ricci soliton $(M^n, g)$ $(n\ge 4)$ with nonnegative curvature operator and positive Ricci curvature away from a compact set of $M$. We prove that any compact split ancient solution of codimension one from the blow-down of $(M, g

Naomi Diz-Rosales, María-José Lombardía, Domingo Morales

The COVID-19 pandemic has had far-reaching consequences, highlighting the urgency for explanatory and predictive tools to track infection rates and burden of care over time and space. However, the scarcity and inhomogeneity of data is a challenge. In this research we develop a robust framework for estimating and predicting the occupied beds of Intensive Care

20k Collaboration, F. Acerbi, P. Adhikari, P. Agnes

Experiments aimed at direct searches for WIMP dark matter require highly effective reduction of backgrounds and control of any residual radioactive contamination. In particular, neutrons interacting with atomic nuclei represent an important class of backgrounds due to the expected similarity of a WIMP-nucleon interaction, so that such experiments often featu

Sen Huang, Yan-Qing Zhu, Zhi Li

We investigate the non-Abelian Thouless pumping in a disorder tunable Lieb chain with degenerate flat bands. The results reveal that quasiperiodic disorder will cause a topological phase transition from the trivial (without non-Abelian Thouless pumping) to the non-trivial (with non-Abelian Thouless pumping) phase. The mechanism behind is that the monopole or

Ezinne Nwankwo, Michael I. Jordan, Angela Zhou

Evaluating the causal impacts of possible interventions is crucial for informing decision-making, especially towards improving access to opportunity. However, if causal effects are heterogeneous and predictable from covariates, personalized treatment decisions can improve individual outcomes and contribute to both efficiency and equity. In practice, however,

Jean-François Le Gall, Armand Riera

We establish a new spatial Markov property of the Brownian half-plane. According to this property, if one removes a hull centered at a boundary point, the remaining space equipped with an intrinsic metric is still a Brownian half-plane, which is independent of the part that has been removed. This is an analog of the well-known peeling procedure for random pl

Tingting Zhu, Xiongtao Zhang

We study the synchronized behavior of the inertial Kuramoto oscillators with frustration effect under a symmetric and connected network. Due to the lack of second-order gradient flow structure and singularity of second-order derivative of diameter, we shift to construct convex combinations of oscillators and related new energy functions that can control the

Tingting Zhu, Xiongtao Zhang

We study the collective synchronized behavior of the Kuramoto model with inertia and frustration effects on a connected and symmetric network. We aim to establish sufficient frameworks for achieving complete frequency synchronization, taking into account initial configuration, small inertia and frustration, and large coupling strength. More precisely, we fir

Shunta Kikuchi, Hiroshi Watanabe

We investigated the properties of bilayer fluctuations using molecular dynamics. We modeled the amphipathic molecules as a diatomic molecule, constructed a bilayer in the solvent, and observed the Fourier spectrum of its fluctuations. The results showed that $q^4$ behavior was dominant at the high temperature, whereas a crossover from $q^4$ to $q^2$ was obse

Maxime Lenormand, Jean-Baptiste Féret, Guillaume Papuga, Samuel Alleaume

The mapping of plant biodiversity represents a fundamental stage in establishing conservation priorities, particularly in identifying groups of species that share ecological requirements or evolutionary histories. This is often achieved by assessing different spatial diversity patterns in plant population distributions. In this paper, we present two primary

Ivan Arzhantsev, Ivan Beldiev, Yulia Zaitseva

We study projective hypersurfaces $X$ admitting an induced additive action, i.e., an effective action ${\mathbb G_a^m\times X\to X}$ of the vector group $\mathbb G_a^m$ with an open orbit that can be extended to an action on the ambient projective space. A criterion for normality of such a hypersurface $X$ is given. Also, we prove that for any projective hyp

Tony J. Puthenpurakal

Let $R$ be a commutative ring If $\mathcal{C}_1$ and $\mathcal{C}_2$ are $R$-linear triangulated categories then we can give an obvious triangulated structure on $\mathcal{C} = \mathcal{C}_1 \oplus \mathcal{C}_2$ where $Hom_\mathcal{C}(U, V) = 0$ if $U \in \mathcal{C}_i$ and $V \in \mathcal{C}_j$ with $i \neq j$. We say a $R$-linear triangulated category $\m

Pu-Zhao Kow, Mikko Salo, Sen Zou

In this work we study the increasing resolution of linear inverse scattering problems at a large fixed frequency. We consider the problem of recovering the density of a Herglotz wave function, and the linearized inverse scattering problem for a potential. It is shown that the number of features that can be stably recovered (stable region) becomes larger as t

Aurélien Grabsch, Hiroki Moriya, Kirone Mallick, Tomohiro Sasamoto

The symmetric simple exclusion process (SEP), where diffusive particles cannot overtake each other, is a paradigmatic model of transport in the single-file geometry. In this model, the study of currents has attracted a lot of attention, but so far most results are restricted to two geometries: (i) a finite system between two reservoirs, which does not conser

Renyong guan, Yuxi Hu

The time asymptotic stability for one-dimensional relaxed compressible Navier-Stokes equations is studied. We show that the composite waves of viscous shock and rarefaction are asymptotically nonlinear stable with both small wave strength and small initial perturbations. Moreover, as the relaxation parameter goes to zero, the solutions of relaxed system are

Daniel Nygård Ege, Henrik H. Øvrebø, Vegar Stubberud, Martin Francis Berg

This study compares the design practices and performance of ChatGPT 4.0, a large language model (LLM), against graduate engineering students in a 48-hour prototyping hackathon, based on a dataset comprising more than 100 prototypes. The LLM participated by instructing two participants who executed its instructions and provided objective feedback, generated i

Junping Li, Mixuan Hou

This paper concentrates on the limit behavior of discrete-time branching process with circular mechanism. Three types of limit behaviour of discrete-time branching process with circular mechanism are given explicitly under various moment conditions on branching rates. It is proved that the rate of the first one is geometric, while the other two are supergeom

Stephen Hausler, Ethan Griffiths, Milad Ramezani, Peyman Moghadam

In this paper, we emphasise the critical importance of large-scale datasets for advancing field robotics capabilities, particularly in natural environments. While numerous datasets exist for urban and suburban settings, those tailored to natural environments are scarce. Our recent benchmarks WildPlaces and WildScenes address this gap by providing synchronise

Laura Finarelli, Falko Dressler, Marco Marsan Ajmone, Gianluca Rizzo

Base station densification is one of the key approaches for delivering high capacity in radio access networks. However, current static deployments are often impractical and financially unsustainable, as they increase both capital and operational expenditures of the network. An alternative paradigm is the moving base stations (MBSs) approach, by which part of

Christian T. Byrnes, Julien Lesgourgues, Devanshu Sharma

Explaining the origin of supermassive black holes via a primordial origin is severely challenged by the tight spectral distortion constraints on the amplitude of the primordial perturbations. Following the first calculation of how the $\mu$ constraints are modified by non-Gaussianity in a companion paper, we here make the first robust constraints on primordi

Devanshu Sharma, Julien Lesgourgues, Christian T. Byrnes

A well-known route to form primordial black holes in the early universe relies on the existence of unusually large primordial curvature fluctuations, confined to a narrow range of wavelengths that would be too small to be constrained by Cosmic Microwave Background (CMB) anisotropies. This scenario would however boost the generation of $\mu$-type spectral dis

Mohammad. H. Fahmy, Refaat. M. Salem, Shaimaa. Sh. Shehata

In this paper, we investigate the conditions for the Mal'cev-Neumann series ring {\Lambda} = R((G;{\sigma};{\tau})) to be left fusible and an SA-ring. Also, we show that: if G is a quasitotally ordered group and U a {\Sigma}-compatible semiprime ideal of R, then R((G;{\sigma};{\tau})) is a {\Sigma}(U((G; {\sigma}; {\tau})))-zip ring if and only if R is a {\S

Akifumi Mine, Yigui Zhong, Jinjin Liu, Takeshi Suzuki

In the recently discovered kagome superconductor AV3Sb5 (A = K, Rb, and Cs), superconductivity is intertwined with an unconventional charge density wave order. The pairing symmetry remains elusive owing to the lack of direct measurement of the superconducting gap in the momentum space. Here, utilizing laser-based ultra-high-resolution and low-temperature ang

Giovanni Felder, Alexander P. Veselov

We study the harmonic locus consisting of the monodromy-free Schr\"odinger operators with rational potential and quadratic growth at infinity. It is known after Oblomkov that it can be identified with the set of all partitions via the Wronskian map for Hermite polynomials. We show that the harmonic locus can also be identified with the subset of the Calogero

Dipankar Das

It can be observed that the purchasing decision of an individual consumer in an electronic marketplace is determined by a set of factors, such as personal characteristics of the consumer, product pricing, minimum price-quantity combination offered, decision-making space, and underlying motivation of the consumer. These factors are combined to form a consumer

Yupeng Cao, Zhi Chen, Qingyun Pei, Nathan Jinseok Lee

In the realm of financial analytics, leveraging unstructured data, such as earnings conference calls (ECCs), to forecast stock volatility is a critical challenge that has attracted both academics and investors. While previous studies have used multimodal deep learning-based models to obtain a general view of ECCs for volatility predicting, they often fail to

Prachi Mishra, Navin Kashyap

A weakly constrained code is a collection of finite-length strings over a finite alphabet in which certain substrings or patterns occur according to some prescribed frequencies. Buzaglo and Siegel (ITW 2017) gave a construction of weakly constrained codes based on row-by-row coding, that achieved the capacity of the weak constraint. In this paper, we propose

Kamran Nazir, Tabish Qureshi

Two-photon interference is an interesting quantum phenomenon that is usually captured in two distinct types of experiments, namely the Hanbury-Brown-Twiss (HBT) experiment and the Hong- Ou-Mandel (HOM) experiment. While the HBT experiment was carried out much earlier in 1956, with classical light, the demonstration of the HOM effect came much later in 1987.

Yuyu Chen, Taizhong Hu, Ruodu Wang, Zhenfeng Zou

We study stochastic dominance between portfolios of independent and identically distributed (iid) extremely heavy-tailed (i.e., infinite-mean) Pareto random variables. With the notion of majorization order, we show that a more diversified portfolio of iid extremely heavy-tailed Pareto random variables is larger in the sense of first-order stochastic dominanc

Tingfeng Hui, Zhenyu Zhang, Shuohuan Wang, Weiran Xu

Large language models (LLMs) with one or more fine-tuning phases have become a necessary step to unlock various capabilities, enabling LLMs to follow natural language instructions or align with human preferences. However, it carries the risk of catastrophic forgetting during sequential training, the parametric knowledge or the ability learned in previous sta

Venkatesh C, Harshit Oberoi, Anurag Kumar Pandey, Anil Goyal

In recent years, digital platform companies have faced increasing challenges in managing customer complaints, driven by widespread consumer adoption. This paper introduces an end-to-end pipeline, named RE-GrievanceAssist, designed specifically for real estate customer complaint management. The pipeline consists of three key components: i) response/no-respons

Zijian Zhang, Shuchang Liu, Jiaao Yu, Qingpeng Cai

Multi-domain recommendation and multi-task recommendation have demonstrated their effectiveness in leveraging common information from different domains and objectives for comprehensive user modeling. Nonetheless, the practical recommendation usually faces multiple domains and tasks simultaneously, which cannot be well-addressed by current methods. To this en

Baotian He, Yibing Li

Accurately simulating diverse behaviors of heterogeneous agents in various scenarios is fundamental to autonomous driving simulation. This task is challenging due to the multi-modality of behavior distribution, the high-dimensionality of driving scenarios, distribution shift, and incomplete information. Our first insight is to leverage state-matching through

Yu Zhao, Zhennan Zhou

We consider a special type of fast reaction-diffusion systems in which the coefficients of the reaction terms of the two substances are much larger than those of the diffusion terms while the diffusive motion to the substrate is negligible. Specifically speaking, the rate constants of the reaction terms are $O(1/\epsilon)$ while the diffusion coefficients ar

S. Riggi, T. Cecconello, S. Palazzo, A. M. Hopkins

New advancements in radio data post-processing are underway within the SKA precursor community, aiming to facilitate the extraction of scientific results from survey images through a semi-automated approach. Several of these developments leverage deep learning (DL) methodologies for diverse tasks, including source detection, object or morphology classificati

Chaewon Lee, Chang-Su Kim

For click-based interactive segmentation methods, reducing the number of clicks required to obtain a desired segmentation result is essential. Although recent click-based methods yield decent segmentation results, we observe that substantial amount of clicks are required to segment elongated regions. To reduce the amount of user-effort required, we propose u

Utkarsh Agarwal, Kumar Tanmay, Aditi Khandelwal, Monojit Choudhury

Ethical reasoning is a crucial skill for Large Language Models (LLMs). However, moral values are not universal, but rather influenced by language and culture. This paper explores how three prominent LLMs -- GPT-4, ChatGPT, and Llama2-70B-Chat -- perform ethical reasoning in different languages and if their moral judgement depend on the language in which they

Donggyun Kim, Seongwoong Cho, Semin Kim, Chong Luo

Large language models have evolved data-efficient generalists, benefiting from the universal language interface and large-scale pre-training. However, constructing a data-efficient generalist for dense visual prediction presents a distinct challenge due to the variation in label structures across different tasks. Consequently, generalization to unseen dense

Luzhe Huang, Yuzhu Li, Nir Pillar, Tal Keidar Haran

Histopathological staining of human tissue is essential for disease diagnosis. Recent advances in virtual tissue staining technologies using artificial intelligence (AI) alleviate some of the costly and tedious steps involved in traditional histochemical staining processes, permitting multiplexed staining and tissue preservation. However, potential hallucina

Athanasios E. Tzavaras

We construct examples of oscillating solutions with persistent oscillations for various hyperbolic-parabolic systems with singular diffusion matrices that appear in mechanics. These include, an example for the equations of nonlinear viscoelasticity of Kelvin-Voigt type with stored energy that violates rank-one convexity, which amounts to a time-dependent var

Xin Hong, Wei-Jia Huang, Wei-Chen Chien, Yuan Feng

Parameterised quantum circuits (PQCs) hold great promise for demonstrating quantum advantages in practical applications of quantum computation. Examples of successful applications include the variational quantum eigensolver, the quantum approximate optimisation algorithm, and quantum machine learning. However, before executing PQCs on real quantum devices, t

Athanasios E. Tzavaras

In the first part of this article we present some exact solutions for special hyperbolic-parabolic systems with sustained oscillations induced by the initial data, most notably the compressible Navier-Stokes system with non-monotone pressure. This part complements \cite{Tzavaras23} where such examples are extensively studied. The second part deals with the p