April 2023 arXiv papers — page 47

Markos Z. Tsoukalas, Panagiotis G. Asteris

In this study we consider perturbative series solution with respect to a parameter {\epsilon} > 0. In this methodology the solution is considered as an infinite sum of a series of functional terms which usually converges fast to the exact desired solution. Then we investigate perturbative solutions for kernel perturbed integral equations and prove the conver

Rishabh Thakkar, Prasad Hegde

We present a method to compute the responses of meson screening masses to the chemical potential by Taylor expanding the correlator using lattice QCD simulation. We start by comparing the free theory lattice results with the analytical expression. Then, using symmetry arguments, we obtain an expression for the correlator in a series of the chemical potential

B. G. Barreales, J. J. Meléndez, R. Cuerno, J. J. Ruiz-Lorenzo

We study the interface representation of the contact process (CP) at its directed-percolation critical point, where the scaling properties of the interface can be related to those of the original particle model. Interestingly, such a behavior happens to be intrinsically anomalous and more complex than that described by the standard Family-Vicsek dynamic scal

Jiawei Zhang, Aiqing Zhu, Feng Ji, Chang Lin

Synchronous generator system is a complicated dynamical system for energy transmission, which plays an important role in modern industrial production. In this article, we propose some predictor-corrector methods and structure-preserving methods for a generator system based on the first benchmark model of subsynchronous resonance, among which the structure-pr

Nirmal Roy, Agathe Balayn, David Maxwell, Claudia Hauff

The creation of relevance assessments by human assessors (often nowadays crowdworkers) is a vital step when building IR test collections. Prior works have investigated assessor quality & behaviour, though into the impact of a document's presentation modality on assessor efficiency and effectiveness. Given the rise of voice-based interfaces, we investigate wh

Jiachen Shen, Wenxuan Wang, Chen Chen, Jianbo Jiao

The "pre-training then fine-tuning (FT)" paradigm is widely adopted to boost the model performance of deep learning-based methods for medical volumetric segmentation. However, conventional full FT incurs high computational and memory costs. Thus, it is of increasing importance to fine-tune pre-trained models for medical volumetric segmentation tasks in a bot

Debadatta Behera, Suraj Prasad, Neelkamal Mallick, Raghunath Sahoo

To understand the true origin of flowlike signatures and applicability of hydrodynamics in small collision systems, effects of soft QCD dynamics, the sensitivity of jetlike correlations, and nonequilibrium effects, efforts are being made to perform \textit{p}-O and O-O collisions at the LHC and RHIC energies. It is equally interesting to look into the possib

Rebekah Rousi

This article connects the concepts and phenomena of Design AI, AI in creative industries and AIs capacity for creativity. It links Design AI to UX design and UX designer discourse. Its vagueness and the prominence of UX designers as speakers and writers in the spectacle of cultural AI discourse. The article then, draws comparisons between the Theatre of the

Yu Jin, Pengfei Qiu, Chunlu Wang, Yihao Yang

The transient execution attack is a type of attack leveraging the vulnerability of modern CPU optimization technologies. New attacks surface rapidly. The side-channel is a key part of transient execution attacks to leak data. In this work, we discover a vulnerability that the change of the EFLAGS register in transient execution may have a side effect on the

Beatrice W. Soh, Zi-En Ooi, Eleonore Vissol-Gaudin, Chang Jie Leong

In this work, we present an automated platform for trapping and stretching individual micro- and nanoscale objects in solution using electrokinetic forces. The platform can trap objects at the stagnation point of a planar elongational electrokinetic field for long time scales, as demonstrated by the trapping of ~100 nanometer polystyrene beads and DNA molecu

Thomas C. Pitts, Sofia Bousiadi, Nikitas I. Gidopoulos, Nektarios N. Lathiotakis

A way to improve the accuracy of the spectral properties in density functional theory (DFT) is to impose constraints on the effective, Kohn-Sham (KS), local potential [J. Chem. Phys. {\bf 136}, 224109 (2012)]. As illustrated, a convenient variational quantity in that approach is the ``screening'' or ``electron repulsion'' density, $\rho_{\rm rep}$, correspon

Sergei I. Mukhin

Proposed by the author Q-ball mechanism of the pseudogap state and high-Tc superconductivity in cuprates was recently supported by micro X-ray diffraction data in HgBa$_2$CuO$_{4+y}$. This provides a remarkable opportunity to investigate X-ray diffraction produced by the quantum thermodynamic time crystals, a direct embodiment of those are just the Euclidean

V. O. Nesterenko, M. A. Mardyban, P. -G. Reinhard, A. Repko

The dependence of the moment of inertia $\cal J$ on the pairing and axial quadrupole deformation $\beta$ in $^{24}$Mg and $^{20}$Ne was investigated. The study is based on quadrupole-constrained calculations with three cranking approaches for $\cal J$ (Inglis-Belyaev, Thouless-Valatin, adiabatic time-dependent Hartree-Fock) and a representative set of Skyrme

M. N. Kiselev

We show that the transport integrals of the two-site charge Kondo circuits connecting various multi-channel Kondo simulators satisfy the generalized Wiedemann-Franz law with the universal Lorenz ratios all greater than one. The magic Lorenz ratios are directly related to the Anderson's orthogonality catastrophe in quantum simulators providing some additional

Jun-Yi Shen, Yuan-Chuan Zou, Shu-Hua Yang, Xiao-Ping Zheng

Magnetars are believed as neutron stars (NSs) with strong magnetic fields. X-ray flares and fast radio bursts (FRBs) have been observed from the magnetar (soft gamma-ray repeater, SGR J1935+2154). We propose that the phase transition of the NS can power the FRBs and SGRs.Based on the equation of state provided by the MIT bag model and the mean field approxim

Karthick Prasad Gunasekaran

For years, Single Image Super Resolution (SISR) has been an interesting and ill-posed problem in computer vision. The traditional super-resolution (SR) imaging approaches involve interpolation, reconstruction, and learning-based methods. Interpolation methods are fast and uncomplicated to compute, but they are not so accurate and reliable. Reconstruction-bas

Mohan Li, Rama Doddipatla

This paper presents the use of non-autoregressive (NAR) approaches for joint automatic speech recognition (ASR) and spoken language understanding (SLU) tasks. The proposed NAR systems employ a Conformer encoder that applies connectionist temporal classification (CTC) to transcribe the speech utterance into raw ASR hypotheses, which are further refined with a

Luciano Petruzziello, Fabrizio Illuminati

We investigate the relation between quantum nonlocality and gravity at the astrophysical scale, both in the classical and quantum regimes. Considering particle pairs orbiting in the strong gravitational field of ultra-compact objects, we find that the violation of Bell inequality acquires an angular modulation factor that strongly depends on the nature of th

C. Moussa, H. Wang, M. Araya-Polo, T. Bäck

Quantum and quantum-inspired machine learning has emerged as a promising and challenging research field due to the increased popularity of quantum computing, especially with near-term devices. Theoretical contributions point toward generative modeling as a promising direction to realize the first examples of real-world quantum advantages from these technolog

Linsui Deng, Kejun He, Xianyang Zhang

In many applications, the process of identifying a specific feature of interest often involves testing multiple hypotheses for their joint statistical significance. Examples include mediation analysis which simultaneously examines the existence of the exposure-mediator and the mediator-outcome effects, and replicability analysis aiming to identify simultaneo

Jinglong Liu, Stephon Alexander, Antonino Marciano, Roman Pasechnik

We couple to group field theory (GFT) a scalar field that encodes the entanglement between manifold sites. The scalar field provides a relational clock that enables the derivation of the Hamiltonian of the system from the GFT action. Inspecting the Hamiltonian, we show that a theory of emergent gravity arises, and that this can be recast according to the Ash

Wenxuan Wang, Jing Wang, Chen Chen, Jianbo Jiao

The research community has witnessed the powerful potential of self-supervised Masked Image Modeling (MIM), which enables the models capable of learning visual representation from unlabeled data. In this paper, to incorporate both the crucial global structural information and local details for dense prediction tasks, we alter the perspective to the frequency

Xue-Mei Li, Guo-Yin Zhang, Alexander Men'shchikov, Jin-Zeng Li

The initial and boundary conditions of the Galactic star formation in molecular clouds are not well understood. In an effort to shed new light on this long-standing problem, we measured properties of dense cores and filamentary structures in the Vela C molecular cloud, observed with Herschel. We applied the getsf extraction method to separate the components

Christos P. Lamprakos, Sotirios Xydis, Francky Catthoor, Dimitrios Soudris

This paper presents a trace-based simulation methodology for constructing representations of workload-allocator interaction. We use two-dimensional rectangular bin packing (2DBP) as our foundation. Classical 2DBP algorithms minimize their products' makespan, but virtual memory systems employing demand paging deem such a criterion inappropriate. We view an al

Ritabrata Jana

This paper examines the behavior of a positive solution $u\in C^{1,\alpha}(\Bar{\Omega})$ of the $(p,q)$ Laplace equation with a singular term and zero Dirichlet boundary condition. Specifically, we consider the equation: \begin{equation*} -div(|\nabla u|^{p-2}\nabla u+ a(x) |\nabla u|^{q-2}\nabla u) &= \frac{g(x)}{u^\delta}+h(x)f(u) \, &\text{in} \thinspace

Steffen Gracla, Carsten Bockelmann, Armin Dekorsy

The quality of data driven learning algorithms scales significantly with the quality of data available. One of the most straight-forward ways to generate good data is to sample or explore the data source intelligently. Smart sampling can reduce the cost of gaining samples, reduce computation cost in learning, and enable the learning algorithm to adapt to unf

Karthick Prasad Gunasekaran, B Chase Babrich, Saurabh Shirodkar, Hee Hwang

The task of predicting the publication period of text documents, such as news articles, is an important but less studied problem in the field of natural language processing. Predicting the year of a news article can be useful in various contexts, such as historical research, sentiment analysis, and media monitoring. In this work, we investigate the problem o

Victor Croisfelt, Francesco Devoti, Fabio Saggese, Vincenzo Sciancalepore

Autonomous reconfigurable intelligent surfaces (RISs) offer the potential to simplify deployment by reducing the need for real-time remote control between a base station (BS) and an RIS. However, we highlight two major challenges posed by autonomy. The first is implementation complexity, as autonomy requires hybrid RISs (HRISs) equipped with additional onboa

Nikolaos Dimitriadis, Francois Fleuret, Pascal Frossard

Continual Learning is an important and challenging problem in machine learning, where models must adapt to a continuous stream of new data without forgetting previously acquired knowledge. While existing frameworks are built on PyTorch, the rising popularity of JAX might lead to divergent codebases, ultimately hindering reproducibility and progress. To addre

Michael Grinfeld, David Pritchard

We consider the shape of the free surface of steady pendent rivulets beneath a planar substrate. We formulate the governing equations in terms of two closely related dynamical systems and use classical phase-plane techniques to develop the bifurcation structure of the problem. Our results explain why lubrication theory is unable to capture this bifurcation s

Shota Hayakawa, Toshiharu Chono, Kosuke Watanabe, Shoya Kawano

We present an ab initio calculation to understand electronic structures and optical properties of a tungsten carbide WC being a major component of a TiCN-based cermet. We found that the WC has a fairly low-energy plasma excitation $\sim$0.6 eV (2 $\mu$m) and therefore can be a good constituent of a solar selective absorber. The evaluated figure of merit for

Zhengcheng Shen, Yi Gao, Linh Kästner, Jens Lambrecht

The advancement of computer vision and machine learning has made datasets a crucial element for further research and applications. However, the creation and development of robots with advanced recognition capabilities are hindered by the lack of appropriate datasets. Existing image or video processing datasets are unable to accurately depict observations fro

Federica Luciano, Lieve Teugels, Sean McMitchell, Giacomo Talmelli

We have studied the effect of chemical-mechanical polishing (CMP) on the ferroelectric, piezoelectric, and microwave dielectric properties of Ba-substituted PZT (BPZT), deposited by pulsed laser deposition. CMP allowed for the reduction of the root mean square surface roughness of 600 nm thick BPZT films from 12.1nm to 0.79 nm. Ammonium peroxide (SC-1) clean

Rouven Koch, David van Driel, Alberto Bordin, Jose L. Lado

Determining Hamiltonian parameters from noisy experimental measurements is a key task for the control of experimental quantum systems. An experimental platform that recently emerged, and where knowledge of Hamiltonian parameters is crucial to fine-tune the system, is that of quantum dot-based Kitaev chains. In this work, we demonstrate an adversarial machine

Giannis Nikolentzos, Michail Chatzianastasis, Michalis Vazirgiannis

In recent years, graph neural networks (GNNs) have achieved great success in the field of graph representation learning. Although prior work has shed light on the expressiveness of those models (\ie whether they can distinguish pairs of non-isomorphic graphs), it is still not clear what structural information is encoded into the node representations that are

Barbara Schütt, Joshua Ransiek, Thilo Braun, Eric Sax

Scenario generation is one of the essential steps in scenario-based testing and, therefore, a significant part of the verification and validation of driver assistance functions and autonomous driving systems. However, the term scenario generation is used for many different methods, e.g., extraction of scenarios from naturalistic driving data or variation of

Barbara Schütt, Maximilian Zipfl, J. Marius Zöllner, Eric Sax

An essential requirement for scenario-based testing the identification of critical scenes and their associated scenarios. However, critical scenes, such as collisions, occur comparatively rarely. Accordingly, large amounts of data must be examined. A further issue is that recorded real-world traffic often consists of scenes with a high number of vehicles, an

Benjamin Doerr, Taha El Ghazi El Houssaini, Amirhossein Rajabi, Carsten Witt

The Metropolis algorithm (MA) is a classic stochastic local search heuristic. It avoids getting stuck in local optima by occasionally accepting inferior solutions. To better and in a rigorous manner understand this ability, we conduct a mathematical runtime analysis of the MA on the CLIFF benchmark. Apart from one local optimum, cliff functions are monotonic

Hajime Inoue

Ejection mechanism of transient relativistic jets from black hole binaries is studied. Based on the observations of the limit-cycle behaviors of the superluminal jet source, GRS 1915+105, we infer that the transient jet ejections could happen just after the slim disk emerging from the standard disk at some distance runs over the standard disk and reaches the

Matthias Aschenbrenner, Lou van den Dries, Joris van der Hoeven

We show that all maximal Hardy fields are elementarily equivalent as differential fields, and give various applications of this result and its proof. We also answer some questions on Hardy fields posed by Boshernitzan.

Raúl Bombín, Alberto S. Muzas, Dino Novko, J. Iñaki Juaristi

Using many-body perturbation theory and density functional perturbation theory, we study the vibrational spectra of the internal stretch (IS) mode of CO on Pd(111) for the bridge and hollow adsorption structures that are experimentally identified at 0.5~ML coverage. Our theoretical treatment allows us to determine the temperature dependence of the IS vibrati

Ru Peng, Yawen Zeng, Junbo Zhao

Sign language translation (SLT) systems, which are often decomposed into video-to-gloss (V2G) recognition and gloss-to-text (G2T) translation through the pivot gloss, heavily relies on the availability of large-scale parallel G2T pairs. However, the manual annotation of pivot gloss, which is a sequence of transcribed written-language words in the order in wh

Jiayu Qiu, Junshan Lin, Peng Xie, Hai Zhang

In this paper, we prove the existence of a bound state in a waveguide that consists of two semi-infinite periodic structures separated by an interface. The two periodic structures are perturbed from the same periodic medium with a Dirac point and they possess a common band gap enclosing the Dirac point. The bound state, which is called interface mode here, d

Xiao-Kai An, Lin Du, Zi-Chen Deng, Yu-jia Zhang

Stochastic differential equations can describe a wide range of dynamical systems, and obtaining the governing equations of these systems is the premise of studying the nonlinear dynamic behavior of the system. Neural networks are currently the most popular approach in the inverse problem of dynamical systems. In order to obtain accurate dynamical equations,

E. Longo, L. Locatelli, P. Tsipas, A. Lintzeris

Properly tuning the Fermi level position in topological insulators is of vital importance to tailor their spin-polarized electronic transport and to improve the efficiency of any functional device based on them. Here we report the full in situ Metal Organic Chemical Vapor Deposition (MOCVD) and study of a highly crystalline Bi2Te3/Sb2Te3 topological insulato

L. Srinivasan, D. Selvaraj, D. Dhinakaran, T. P. Anish

We come across hospitals and non-profit organizations that care for people with paralysis who have experienced all or portion of their physique being incapacitated by the paralyzing attack. Due to a lack of motor coordination by their mind, these persons are typically unable to communicate their requirements because they can speak clearly or use sign languag

Yucheng Lu, Zhixin Xu, Moon Hyung Choi, Jimin Kim

Computed tomography (CT) has been used worldwide as a non-invasive test to assist in diagnosis. However, the ionizing nature of X-ray exposure raises concerns about potential health risks such as cancer. The desire for lower radiation doses has driven researchers to improve reconstruction quality. Although previous studies on low-dose computed tomography (LD

S. M. Udhaya Sankar, D. Dhinakaran, C. Cathrin Deboral, M. Ramakrishnan

Wireless networks that are decentralized and communicate without using existing infrastructure are known as mobile ad-hoc networks. The most common sorts of threats and attacks can affect MANETs. Therefore, it is advised to utilize intrusion detection, which controls the system to detect additional security issues. Monitoring is essential to avoid attacks an

Maximilian Zipfl, Nina Koch, J. Marius Zöllner

The verification and validation of autonomous driving vehicles remains a major challenge due to the high complexity of autonomous driving functions. Scenario-based testing is a promising method for validating such a complex system. Ontologies can be utilized to produce test scenarios that are both meaningful and relevant. One crucial aspect of this process i

Dhinakaran D, Joe Prathap P. M, Selvaraj D, Arul Kumar D

With the onset of the Information Era and the rapid growth of information technology, ample space for processing and extracting data has opened up. However, privacy concerns may stifle expansion throughout this area. The challenge of reliable mining techniques when transactions disperse across sources is addressed in this study. This work looks at the prospe

Dimitri Breda, Simone De Reggi, Rossana Vermiglio

We numerically address the stability analysis of linear age-structured population models with nonlocal diffusion, which arise naturally in describing dynamics of infectious diseases. Compared to Laplace diffusion, models with nonlocal diffusion are more challenging since the associated semigroups have no regularizing properties in the spatial variable. Never

Giuseppe Rizzelli, Pablo Torres-Ferrera, Fabrizio Forghieri, Roberto Gaudino

In this paper, we propose an analytical model to estimate the signal-to-noise ratio (SNR) at the output of an adaptive equalizer in intensity modulation and direct detection (IMDD) optical transmission systems affected by shot noise, thermal noise, relative intensity noise (RIN), chromatic dispersion (CD) and bandwidth limitations. We develop the model as an

D. Selvaraj, S. M. Udhaya Sankar, D. Dhinakaran, T. P. Anish

Huge diagrams have unique properties for organizations and research, such as client linkages in informal organizations and customer evaluation lattices in social channels. They necessitate a lot of financial assets to maintain because they are large and frequently continue to expand. Owners of large diagrams may need to use cloud resources due to the extensi

Matteo Caldana, Paola F. Antonietti, Luca Dede'

Algebraic multigrid (AMG) methods are among the most efficient solvers for linear systems of equations and they are widely used for the solution of problems stemming from the discretization of Partial Differential Equations (PDEs). The most severe limitation of AMG methods is the dependence on parameters that require to be fine-tuned. In particular, the stro

Yuan Cao, Di Jiang, Guanqun Hou, Fan Deng

Face clustering can provide pseudo-labels to the massive unlabeled face data and improve the performance of different face recognition models. The existing clustering methods generally aggregate the features within subgraphs that are often implemented based on a uniform threshold or a learned cutoff position. This may reduce the recall of subgraphs and hence

Zeynel Batuhan Organ, Enis Kayış, Taghi Khaniyev

Classification trees continue to be widely adopted in machine learning applications due to their inherently interpretable nature and scalability. We propose a rolling subtree lookahead algorithm that combines the relative scalability of the myopic approaches with the foresight of the optimal approaches in constructing trees. The limited foresight embedded in

Jiacheng Li

Remote sensing image segmentation is a specific task of remote sensing image interpretation. A good remote sensing image segmentation algorithm can provide guidance for environmental protection, agricultural production, and urban construction. This paper proposes a new type of UNet image segmentation algorithm based on channel self attention mechanism and re

Alice Doherty, Matthew Wicker, Luca Laurenti, Andrea Patane

We study Individual Fairness (IF) for Bayesian neural networks (BNNs). Specifically, we consider the $\epsilon$-$\delta$-individual fairness notion, which requires that, for any pair of input points that are $\epsilon$-similar according to a given similarity metrics, the output of the BNN is within a given tolerance $\delta>0.$ We leverage bounds on statisti

Niccolò Di Marco, Matteo Cinelli, Shayan Alipour, Walter Quattrociocchi

Social media platforms are like giant arenas where users can rely on different content and express their opinions through likes, comments, and shares. However, do users welcome different perspectives or only listen to their preferred narratives? This paper examines how users explore the digital space and allocate their attention among communities on two soci

Si-wen Li, Xiao-tong Zhang

As a top-down holographic approach, the D4/D8 model is expected to be the holographic version of QCD since it almost includes all the elementary features of QCD based on string theory. In this manuscript, we review the fundamental properties of the D4/D8 model with respect to the D4-brane background, embedding of flavor branes and holographic quark, gluon, m

Chengyu Zheng, Peng Li, Xiao-Ping Zhang, Xuequan Lu

Recall one time when we were in an unfamiliar mall. We might mistakenly think that there exists or does not exist a piece of glass in front of us. Such mistakes will remind us to walk more safely and freely at the same or a similar place next time. To absorb the human mistake correction wisdom, we propose a novel glass segmentation network to detect transpar

Weijing Chen, Linli Yao, Qin Jin

Image-text retrieval, as a fundamental and important branch of information retrieval, has attracted extensive research attentions. The main challenge of this task is cross-modal semantic understanding and matching. Some recent works focus more on fine-grained cross-modal semantic matching. With the prevalence of large scale multimodal pretraining models, sev

Shin Miyahara

We achieve a comprehensive understanding of the magnetic excitations observed by electric spin resonance and far-infrared spectroscopy in a frustrated spin gap system ${\rm SrCu_2(BO_3)_2}$ by considering the effects of magnetoelectric couplings and Dzyaloshinskii-Moriya interactions in the Shastry-Sutherland model. The transitions from the dimer singlet gro

Riccardo Bonetto, Hildeberto Jardón-Kojakhmetov

This paper gives a new perspective on singular canards, which is topological in flavour. One key feature is that our construction does not rely on coordinates; consequently, the conditions for the existence of singular canards that we provide are purely geometric. The singularities we study originate at the self-intersection of curves of equilibria of the un

Julio S. Lora-Millan, Mahdi Nabipour, Edwin H. F. van Asseldonk, Cristina Bayón

Assistive ankle-foot orthoses (AAFOs) are powerful solutions to assist or rehabilitate gait on humans. Existing AAFO technologies include passive, quasi-passive, and active principles to provide assistance to the users, and their mechanical configuration and control depend on the eventual support they aim for within the gait pattern. In this research we anal

Shinya Mine, Takashi Toyao, Ken-ichi Shimizu, Yoyo Hinuma

Generic neural network potentials without forcing users to train potentials could result in significantly acceleration of total energy calculations. Takamoto et al. [Nat. Commun. (2022), 13, 2991] developed such a deep neural network potential (NNP) and made it available in their Matlantis package. We compared the Matlantis bulk formation, surface, and surfa

Brian Belgodere, Pierre Dognin, Adam Ivankay, Igor Melnyk

Real-world data often exhibits bias, imbalance, and privacy risks. Synthetic datasets have emerged to address these issues. This paradigm relies on generative AI models to generate unbiased, privacy-preserving data while maintaining fidelity to the original data. However, assessing the trustworthiness of synthetic datasets and models is a critical challenge.

Lipeng Luo, Sania Asif

Let $\mathcal{R}$ be a Lie conformal superalgebra. In this paper, we first investigate the conformal derivation algebra $CDer(\mathcal{R})$, the conformal triple derivation algebra $CTDer(\mathcal{R})$, and the generalized conformal triple derivation algebra $GCTDer(\mathcal{R})$. Moreover, we determine the connection of these derivation algebras. Next, we g

Zhiheng Ma, Xiaopeng Hong, Qinnan Shangguan

Meta AI recently released the Segment Anything model (SAM), which has garnered attention due to its impressive performance in class-agnostic segmenting. In this study, we explore the use of SAM for the challenging task of few-shot object counting, which involves counting objects of an unseen category by providing a few bounding boxes of examples. We compare

Nick Evans, Matthew Ward

In holographic models of QCD, the running of the anomalous dimension of the quark bilinear operator leads to chiral symmetry breaking when gamma=1 and the Breitenlohner-Freedman bound is violated. In that case, the running drives the sigma meson mass tachyonic inducing the chiral symmetry breaking. Here we include the running anomalous dimension in the compu

Jiren Liu, Long Ji, MIngyu Ge

The relative high fluxes of the Galactic ultra-luminous X-ray pulsar Swift J0243 allow a detailed study of its spin-down regime in quiescence state, for a first time. After the 2017 giant outburst, its spin frequencies show a linear decreasing trend with some variations due to minor outbursts. The linear spin-down rate is $\sim-1.9\times10^{-12}$ Hz/s during

Alexander Tsaregorodtsev, Adrian Holzbock, Jan Strohbeck, Michael Buchholz

Connected and cooperative driving requires precise calibration of the roadside infrastructure for having a reliable perception system. To solve this requirement in an automated manner, we present a robust extrinsic calibration method for automated geo-referenced camera calibration. Our method requires a calibration vehicle equipped with a combined GNSS/RTK r

Tatsuya Hiraoka, Tomoya Iwakura

Is preferred tokenization for humans also preferred for machine-learning (ML) models? This study examines the relations between preferred tokenization for humans (appropriateness and readability) and one for ML models (performance on an NLP task). The question texts of the Japanese commonsense question-answering dataset are tokenized with six different token

Qidong Lin, Bin Jiang

Equilibration dynamics of hot oxygen atoms following O2 dissociation on Pd(100) and Pd(111) surfaces are investigated by molecular dynamics simulations based on a scalable neural network potential enabling first-principles description of O2 and O interacting with variable Pd supercells. We find that to accurately describe the equilibration dynamics after dis

Gao Yu Lee, Tanmoy Dam, Md Meftahul Ferdaus, Daniel Puiu Poenar

Incorporating deep learning (DL) classification models into unmanned aerial vehicles (UAVs) can significantly augment search-and-rescue operations and disaster management efforts. In such critical situations, the UAV's ability to promptly comprehend the crisis and optimally utilize its limited power and processing resources to narrow down search areas is cru

A. R. Balasubramanian

Parameterized verification of coverability in broadcast networks with finite state processes has been studied for different types of models and topologies. In this paper, we attempt to develop a theory of broadcast networks in which the processes can be well-structured transition systems. The resulting formalism is called well-structured broadcast networks.

Alberto Guandalini, Dario A. Leon, Pino D'Amico, Claudia Cardoso

The GW self-energy may become computationally challenging to evaluate because of frequency and momentum convolutions. These difficulties were recently addressed by the development of the multipole approximation (MPA) and the W-av methods: MPA accurately approximates full-frequency response functions using a small number of poles, while W-av improves the conv

Ziyuan An, Linhui Lv, Ya Sū, Yanyan Jiang

We study the stability, electrical properties, and magnetic properties of MSi2N4 (M = Cr, Mn, Fe, and Co) monolayers based on the density functional theory.

Tatsuya Hiraoka, Tomoya Iwakura

This paper proposes a method to optimize tokenization for the performance improvement of already trained downstream models. Our method generates tokenization results attaining lower loss values of a given downstream model on the training data for restricting vocabularies and trains a tokenizer reproducing the tokenization results. Therefore, our method can b

Paul Hamann, Linda Kordts, Alexey Filinov, Michael Bonitz

In a recent Letter [T. Dornheim \textit{et al.}, Phys. Rev. Lett. \textbf{121}, 255001 (2018)], it was predicted on the basis of \textit{ab initio} quantum Monte Carlo simulations that, in a uniform electron gas, the peak $\omega_0$ of the dynamic structure factor $S(q,\omega)$ exhibits an unusual non-monotonic wave number dependence, where $d\omega_0/dq < 0

Brunella D'Anzi, Gianluigi Chiarello, Alessandro Corvaglia, Nicola De Filippis

Recognition of electron peaks and primary ionization clusters in real data-driven waveform signals is the main goal of research for the usage of the cluster counting technique in particle identification at future colliders. The state-of-the-art open-source algorithms fail in finding the cluster distribution Poisson behavior even in low-noise conditions. In t

YongTaek Lim, Suho Kang, Yewon Kim, Dokyung Yoon

Large-scale pre-trained models such as CLIP excel in transferability and robust generalization across diverse datasets. However, adapting these models to new datasets or domains is computationally costly, especially in low-resource or few-shot settings, and existing prompt-learning methods often lack interpretability. We introduce Efficient Prompt Learning w

Takuma Nakamura, Kazuki Hashimoto, Takuro Ideguchi

Raman scattering spectroscopy is widely used as an analytical technique in various fields, but its measurement process tends to be slow due to the low scattering cross-section. In the last decade, various broadband coherent Raman scattering spectroscopy techniques have been developed to address this limitation, achieving a measurement rate of about 100 kSpec

Quentin Labriet, Loic Poulain d'Andecy

We prove an infinite family of identities satisfied by the Rankin-Cohen brackets involving the Racah polynomials. A natural interpretation in the representation theory of sl(2) is provided. From these identities and known properties of the Racah polynomials follows a short new proof of the associativity of the Eholzer product. Finally, we discuss, in the con

Lijun Bo, Yijie Huang, Xiang Yu

This paper studies Merton's problem in an extended formulation by incorporating the benchmark tracking on the wealth process. We consider a tracking formulation where the fund manager aims to maximize the trade-off between the expected utility of consumption and the expected largest shortfall of the wealth with reference to the benchmark level. Equivalently,

Gal Morgenstern, Jip Kim, James Anderson, Gil Zussman

Graph signal processing (GSP) has emerged as a powerful tool for practical network applications, including power system monitoring. Recent research has focused on developing GSP-based methods for state estimation, attack detection, and topology identification using the representation of the power system voltages as smooth graph signals. Within this framework

Di Wu, Xi Zhang

Given a flat vector bundle over a compact Riemannian manifold, Corlette and Donaldson proved that it admits harmonic metrics if and only if it is semi-simple. In this paper, we extend this equivalence to arbitrary vector bundles without any additional hypothesis, the result can be viewed as a Riemannian Hitchin-Kobayashi correspondence. Furthermore, we also

Etika Agarwal, Karthik S. Gurumoorthy, Ankit Ajit Jain, Shantala Manchenahally

We study the extended version of the non-uniform, capacitated facility location problem with multiple fulfilment channels between the facilities and clients, each with their own channel capacities and service cost. Though the problem has been extensively studied in the literature, all the prior works assume a single channel of fulfilment, and the existing me

Jiajun Xu, Guanglian Zhang

The Zariski closures of the orbits for representations of type A Dynkin quivers under the action of general linear groups (i.e. quiver loci) exhibit a profound connection with Schubert varieties. In this paper, we present a scheme-theoretical isomorphism between a type A quiver locus and the intersection of an opposite Schubert cell and a Schubert variety, a

Kwara Nantomah, Gregory Abe-I-Kpeng, Sunday Sandow

In 1974, Gautschi proved an intriguing inequality involving the gamma function $\Gamma$. Precisely, he proved that, for $z>0$, the harmonic mean of $\Gamma(z)$ and $\Gamma(1/z)$ can never be less than 1. In 2017, Alzer and Jameson extended this result to the digamma function $\psi$ by proving that, for $z>0$, the harmonic mean of $\psi(z)$ and $\psi(1/z)$ ca

Yingkun Li, Christina Roehrig

In this paper, we use theta integrals to give a different construction of mock Maass forms studied by Sander Zwegers. With this method, we construct new real-analytic modular forms, whose Fourier coefficients are logarithms of algebraic numbers in a real quadratic field.

Nikola Opačak, Dmitry Kazakov, Lorenzo L. Columbo, Maximilian Beiser

Recent years witnessed rapid progress of chip-scale integrated optical frequency comb sources. Among them, two classes are particularly significant -- semiconductor Fabry-Per\'{o}t lasers and passive ring Kerr microresonators. Here, we merge the two technologies in a ring semiconductor laser and demonstrate a new paradigm for free-running soliton formation,

Andrzej Matraś, Artur Siemaszko

It is know that any Neumann subgroup of the modular group is maximal non-parabolic. The question arises as to whether these are the only maximal non-parabolic subgroups. The wild class of maximal, non-parabolic, not Neumann subgroups of the modular group was constructed by Brenner and Lyndon. The new construction of such a class is presented. Those groups ar

L. Neslušan, T. J. Jopek, R. Rudawska, M. Hajduková

Meteoroids of a low-inclination stream hit the Earth arriving from a direction near the ecliptic. The radiant area of stream like this is often divided into two parts: one is situated northward and the other southward of the ecliptic. In other words, two showers are caused by such a stream. Well-known examples of such showers are the Northern Taurids, #17, a

Borys Kuca

We examine multidimensional polynomial progressions involving linearly independent polynomials in finite fields, proving power saving bounds for sets lacking such configurations. This jointly generalises earlier results of Peluse (for the single dimensional case) and the author (for distinct degree polynomials). In contrast to the cases studied in the aforem

Jiyoung Yun, Seung-Hyun Nam, Hyun-Young Park, Ashutosh Rai

In this work, we consider two-sender, one-receiver communication over a discrete memoryless multiple-access channel without feedback, where two senders may cooperate on channel coding by using preshared resources, such as shared randomness, quantum states and measurements, or nonlocal correlations. We present the capacity region when senders employ cooperati

Taiji Kurami, Takuya Ishikawa, Kazuhiro Hotta

Endoscopic Ultrasound-Fine Needle Aspiration (EUS-FNA) is used to examine pancreatic cancer. EUS-FNA is an examination using EUS to insert a thin needle into the tumor and collect pancreatic tissue fragments. Then collected pancreatic tissue fragments are then stained to classify whether they are pancreatic cancer. However, staining and visual inspection are

Alessia Rondinella, Elena Crispino, Francesco Guarnera, Oliver Giudice

Magnetic resonance imaging is a fundamental tool to reach a diagnosis of multiple sclerosis and monitoring its progression. Although several attempts have been made to segment multiple sclerosis lesions using artificial intelligence, fully automated analysis is not yet available. State-of-the-art methods rely on slight variations in segmentation architecture

Erica Bertolini, Alberto Blasi, Andrea Damonte, Nicola Maggiore

We consider the covariant gauge field theory of fractons, which describe a new type of quasiparticles exhibiting novel and nontrivial properties. In particular, we focus on the field theoretical peculiarities which characterize this theory, starting from the fact that, if we accept the paradigm that quantum field theories are defined by their symmetries, fra

Tuhin Subhra Mahatao, Subhankar Dutta, Suchandan Kayal

In this communication, we introduce a new statistical model and study its various mathematical properties. The expressions for hazard rate, reversed hazard rate, and odd functions are provided. We explore the asymptotic behaviors of the density and hazard functions of the newly proposed model. Further, moments, median, quantile, and mode are obtained. The cu