November 2024 arXiv papers — page 110

Seo-Hyun Lee, Ji-Ha Park, Deok-Seon Kim

Brain-computer interfaces (BCIs) have shown promise in enabling communication for individuals with motor impairments. Recent advancements like brain-to-speech technology aim to reconstruct speech from neural activity. However, decoding communication-related paradigms, such as imagined speech and visual imagery, using non-invasive techniques remains challengi

Nina Strasser, Alexander F. Sax

The formation of the four three-ring systems \ce{c-(CH2)_{3-k}(SiH2)_{k}}, ($k=0$: cyclopropane, $k=1$: silirane, $k=2$: disilirane, $k=3$: cyclotrisilane) by addition of methylene and silylene to the double bond in ethene, disilene, and silaethene, as well as the elimination of the carbene analogs from the three-rings, was studied with CAS(4,4) wave functio

Antonio D. Pereira

Previous investigations on the renormalizability properties of Lorentz-violating Yang-Mills (LVYM) theories in the Landau gauge have pointed out the necessity of the inclusion of a mass-like term for the gauge fields. If one aims at generalizing the theory to a more complicated gauge, such a mass-like term can bring severe issues regarding gauge-dependence o

Romain Guérout

We use the configuration space Faddeev formalism to calculate bound and continuum states of the Ne$_{3}$ van der Waals trimer. Continuum states below the breakup threshold describe the scattering of a neon atom off of a Ne$_{2}$ diatomic molecule. We identify a resonant feature which we attribute to the presence of a three body resonance.

Damiano Barcaro

In this thesis, I will study the classical scattering problem of two Kerr black holes in general relativity with novel quantum field theory techniques in the Post-Minkowskian (PM) expansion, generalizing the subleading soft theorem to the case of spinning particles. The leading order term in the soft expansion is uniquely determined by the universal Weinberg

Or Raz

This paper is a continuation of my paper "Lattices of flats for symplectic matroids". We explore geometric constructions originating from the lattice of flats of ranked symplectic matroids. We observe that a ranked symplectic matroid always sits between two ordinary matroids and use this fact to prove that it has many of the same properties of ordinary matro

Nikolai P. Osmolovskii, Vladimir M. Veliov

This is a review paper, summarizing without proofs recent results by the authors on the property of strong metric subregularity (SMSR) in optimization. It presents sufficient conditions for SMSR of the optimality mapping associated with a set of necessary optimality conditions in three types of constrained optimization problems: mathematical programming, cal

Ryo Sawada, Yosuke Ashida

A novel approach is proposed to reveal a secret birth of enhanced circumstellar material (CSM) surrounding a collapsing massive star using neutrinos as a unique probe. In this scheme, non-thermal TeV-scale neutrinos produced in ejecta-CSM interactions are tied with thermal MeV neutrinos emitted from a pre-explosion burning process, based on a scenario that C

Benjamin Kolicic, Alberto Caron, Chris Hicks, Vasilios Mavroudis

In this paper, we address the critical need for interpretable and uncertainty-aware machine learning models in the context of online learning for high-risk industries, particularly cyber-security. While deep learning and other complex models have demonstrated impressive predictive capabilities, their opacity and lack of uncertainty quantification present sig

Adrián Gómez Pueyo, Jazmín Aragón Sánchez, Ilya Degtev, Maria Eleonora Temperini

We use density functional theory calculations to characterize the early stages of fluorination of silver's (100) and (110) surfaces. In the Ag(100) surface, the hollow site is the most favorable for F adatoms. In the Ag(110) surface, three adsorption sites, namely hollow, long bridge, and short bridge, exhibit similar energies. These locations are also more

João H. Trindade, José C. Silva

The Shared Source CLI (SSCLI), also known as Rotor, is an implementation of the CLI released by Microsoft in source code. Rotor includes a single pass just-in-time compiler that generates non-optimized code for Intel IA-32 and IBM PowerPC processors. We extend Rotor with an optimizing just-in-time compiler for IA-32. This compiler has three passes: control f

Yichao Fu, Keun-Young Kim, Kunal Pal, Kuntal Pal

We consider the statistics of the results of a measurement of the spreading operator in the Krylov basis generated by the Hamiltonian of a quantum system starting from a specified initial pure state. We first obtain the probability distribution of the results of measurements of this spreading operator at a certain instant of time, and compute the characteris

Shuzhi Gong, Richard O. Sinnott, Jianzhong Qi, Cecile Paris

The spread of fake news on social media poses significant threats to individuals and society. Text-based and graph-based models have been employed for fake news detection by analysing news content and propagation networks, showing promising results in specific scenarios. However, these data-driven models heavily rely on pre-existing in-distribution data for

Richard John, Lukas Herron, Pratyush Tiwary

Generative artificial intelligence is now a widely used tool in molecular science. Despite the popularity of probabilistic generative models, numerical experiments benchmarking their performance on molecular data are lacking. In this work, we introduce and explain several classes of generative models, broadly sorted into two categories: flow-based models and

Zengyi Yang, Yafei Zhang, Huafeng Li, Yu Liu

The primary value of infrared and visible image fusion technology lies in applying the fusion results to downstream tasks. However, existing methods face challenges such as increased training complexity and significantly compromised performance of individual tasks when addressing multiple downstream tasks simultaneously. To tackle this, we propose Task-Orien

Masahiro Ono

Fluorescent Timer proteins, which spontaneously change their emission spectra over time, are valuable tools for analyzing temporal changes in cellular activities at the single-cell level. Traditional analysis of Fluorescent Timer data has mostly relied on conventional flow cytometric methods, which lacks the sophistication needed for detailed quantitative an

Zhijun Pan, Maodong Li, Dechin Chen, Yi Isaac Yang

To address the time-scale limitations in molecular dynamics (MD) simulations, numerous enhanced sampling methods have been developed to expedite the exploration of complex free energy landscapes. A commonly employed approach accelerates the sampling of degrees of freedom associated with pre-defined collective variables (CVs), which typically tends to travers

A. B. M. R. Sazzad, P. Acharya, P. Back, J. Busenitz

This article describes a radon emanation measurement technique using liquid scintillator counting. A model for radon loading and transport is described, along with its calibration. Detector background and blank have been studied and quantified. The Minimal detectable activity has been determined for the counting setup using a toy Monte Carlo simulation. The

Karoly J. Boroczky, Matyas Domokos, Ansgar Freyer, Christoph Haberl

We classify translatively exponential and GL(2,Z) covariant valuations on lattice polygons valued at measurable real functions. A typical example of such valuations is induced by the Laplace transform, but as it turns out there are many more. The argument uses the ergodicity of the linear action of SL(2,Z) on R2, and some elementary properties of the Fibonac

Saumyajit Das, Harsha Hutridurga

In this article we study a reaction diffusion system with $m$ unknown concentration. The non-linearity in our study comes from an underlying reversible chemical reaction and triangular in nature. Our objective is to understand the large time behaviour of solution where there are degeneracies. In particular we treat those cases when one of the diffusion coeff

Mohammud Foondun, Davar Khoshnevisan, Eulalia Nualart

We consider the stochastic partial differential equation, $\partial_t u = \tfrac12 \partial^2_x u + b(u) + \sigma(u) \dot{W},$ where $u=u(t\,,x)$ is defined for $(t\,,x)\in(0\,,\infty)\times\mathbb{R}$, and $\dot{W}$ denotes space-time white noise. We prove that this SPDE is well posed solely under the assumptions that the initial condition $u(0)$ is bounded

Ioannis Mavromatis, Angeliki Katsenou, Klodian Bardhi, Evangelos Xenos

This paper addresses the challenge of robust cellular connectivity in dense, underdeveloped urban environments, specifically focusing on Kathmandu, Nepal. As cities grow, existing cellular infrastructure struggles to meet the demand for reliable, high-throughput, and low-latency communication services. The lack of investment in new technologies and the intri

Vojtěch Kala, Denis Kopylov, Petr Marek, Polina Sharapova

Nonlinear squeezing is a property of non-Gaussian states of light with an important application in continuous variable quantum computing. We study the generation of nonlinear squeezing in multimode systems produced by the photon-added coherent state technique. We present a protocol and find a regime in which the nonlinear squeezing appears in two modes simul

M. A. Perelmuter

We give $L^p$ estimates for the second derivatives of weak solutions to the Dirichlet problem for equation $\Div(\mathbf{A}\nabla u) = f$ in $\Omega\subset \mathbb{R}^d$ with Sobolev coefficients. In particular, for $f\in L^2(\Omega) \bigcap L^s(\Omega)$ $$\|\Delta u\|_{2} \leq \begin{cases} c_1\|f\|_2 + c_2 \|\nabla \mathbf{A}\|_q^2\|f\|_s, & \text{if } 1 <

Sangeet S. Kumar, Brendan C. Mulkerin, Antonio Tiene, Francesca Maria Marchetti

The reduced dielectric screening in atomically thin semiconductors leads to remarkably strong electron interactions. As a result, bound electron-hole pairs (excitons) and charged excitons (trions), which have binding energies in the hundreds and tens of meV, respectively, typically dominate the optical properties of these materials. However, the long-range n

V Laporta, R Agnello, G Fubiani, I Furno

A theoretical investigation of electron-D2 resonant collisions - via the low lying and the Rydberg states of D2- - is presented for vibrational excitation, dissociative electron attachment and dissociative excitation processes by using the local-complex-potential approach. Full sets of vibrationally resolved cross sections, involving the ground electronic st

Zhenglong Ban, Jiawei Chen, Jinsong Yang

Recently, two new spherically symmetric black hole models with covariance have been proposed in effective quantum gravity. Based on these models, we use the modified Newman-Janis algorithm to generate two rotating quantum-corrected black hole solutions, characterized by three parameters, the mass $M$, the spin $a$, and the quantum parameter $\zeta$. To under

Dhananjay Tomar, Alexander Binder, Andreas Kleppe

Domain generalisation in computational histopathology is challenging because the images are substantially affected by differences among hospitals due to factors like fixation and staining of tissue and imaging equipment. We hypothesise that focusing on nuclei can improve the out-of-domain (OOD) generalisation in cancer detection. We propose a simple approach

Jeet Sampat, Orr Shalit

We study operator algebraic and function theoretic aspects of algebras of bounded nc functions on subvarieties of the nc domain determined by all levels of the unit ball of an operator space (nc operator balls). Our main result is the following classification theorem: under very mild assumptions on the varieties, two such algebras $H^\infty(\mathfrak{V})$ an

Kaiwei Yu, I-Ming Chen, Jing Wu

In construction quality monitoring, accurately detecting and segmenting cracks in concrete structures is paramount for safety and maintenance. Current convolutional neural networks (CNNs) have demonstrated strong performance in crack segmentation tasks, yet they often struggle with complex backgrounds and fail to capture fine-grained tubular structures fully

V Laporta, L Vialetto, V Guerra

A full set of vibrationally-resolved cross sections for electron impact excitation of NO(X2{\Pi}, v) molecules is calculated from ab initio molecular dynamics, in the framework of the local-complex-potential approach. Electron-vibration energy exchanges in non-equilibrium thermodynamic conditions are studied from a state-to-state model accounting for all ele

Xulei Sun, Shuying Zheng, Zhaodong Shi, Bing Liu

Low-energy cosmic rays (LECRs) play a crucial role in the formation of planetary systems, and detecting and reconstructing the properties of early LECRs is essential for understanding the mechanisms of planetary system formation. Given that LECRs interact with the surrounding medium to produce nuclear de-excitation line emissions, which are gamma-ray emissio

Di Han, Yankui Bai, Yang Zhao

In this article, we study the quench dynamics of the binary bond disordered Heisenberg spin chain. First, we develop a new algorithm, the ancilla TEBD method, which combines the purification technique and the time-evolving block decimation (TEBD) algorithm to study the entanglement dynamics of binary bonded disordered spin chains. With the support of exact d

Xu Wang, Ruiqi Huang, Jiaqing Kou, Hui Tang

Surrogate model can replace the parametric full-order model (FOM) by an approximation model, which can significantly improve the efficiency of optimization design and reduce the complexity of engineering systems. However, due to limitations in efficiency and accuracy, the applications of high-dimensional surrogate models are still challenging. In the present

Benjamin Aminof, Giuseppe De Giacomo, Sasha Rubin, Moshe Y. Vardi

We introduce LTLf+ and PPLTL+, two logics to express properties of infinite traces, that are based on the linear-time temporal logics LTLf and PPLTL on finite traces. LTLf+/PPLTL+ use levels of Manna and Pnueli's LTL safety-progress hierarchy, and thus have the same expressive power as LTL. However, they also retain a crucial characteristic of the reactive s

Miaoxi Zhu, Yan Sun, Li Shen, Bo Du

Minimax optimization is gaining increasing attention in modern machine learning applications. Driven by large-scale models and massive volumes of data collected from edge devices, as well as the concern to preserve client privacy, communication-efficient distributed minimax optimization algorithms become popular, such as Local Stochastic Gradient Descent Asc

Maochao Xiao, Alessandro Ceci, Pedro Costa, Johan Larsson

We introduce CaLES, a GPU-accelerated finite-difference solver designed for large-eddy simulations (LES) of incompressible wall-bounded flows in massively parallel environments. Built upon the existing direct numerical simulation (DNS) solver CaNS, CaLES relies on low-storage, third-order Runge-Kutta schemes for temporal discretization, with the option to tr

Zhuoyi Fang, Jiajia Liu, Kexuan Shi, Qiang Han

Automatic melanoma segmentation is essential for early skin cancer detection, yet challenges arise from the heterogeneity of melanoma, as well as interfering factors like blurred boundaries, low contrast, and imaging artifacts. While numerous algorithms have been developed to address these issues, previous approaches have often overlooked the need to jointly

Amna Najib, Stefan Depeweg, Phillip Swazinna

Batch reinforcement learning enables policy learning without direct interaction with the environment during training, relying exclusively on previously collected sets of interactions. This approach is, therefore, well-suited for high-risk and cost-intensive applications, such as industrial control. Learned policies are commonly restricted to act in a similar

Ioannis Gavras, George C. Alexandropoulos

This paper presents an optimization framework for near-field localization with Dynamic Metasurface Antenna (DMA) receivers. This metasurface technology offers enhanced angular and range resolution realizing efficient hybrid Analog and Digital (A/D) BeamForming (BF) with sub-wavelength-spaced metamaterials of tunable responses. However, the vast majority of t

Zepeng Huo, Jason Alan Fries, Alejandro Lozano, Jeya Maria Jose Valanarasu

With the rise of medical foundation models and the growing availability of imaging data, scalable pretraining techniques offer a promising way to identify imaging biomarkers predictive of future disease risk. While current self-supervised methods for 3D medical imaging models capture local structural features like organ morphology, they fail to link pixel bi

Yunfeng Lin, Minghuan Liu, Yong Yu

Wheeled robots have gained significant attention due to their wide range of applications in manufacturing, logistics, and service industries. However, due to the difficulty of building a highly accurate dynamics model for wheeled robots, developing and testing control algorithms for them remains challenging and time-consuming, requiring extensive physical ex

Gesina Menz, Stefan Engblom

Mathematical models of living cells have been successively refined with advancements in experimental techniques. A main concern is striking a balance between modelling power and the tractability of the associated mathematical analysis. In this work we model the dynamics for the transcription factor Hairy and enhancer of split-1 (Hes1), whose expression oscil

Zekun Fei, Biao Yi, Jianing Geng, Ruiqi He

Embedding-as-a-Service (EaaS) has emerged as a successful business pattern but faces significant challenges related to various forms of copyright infringement, particularly, the API misuse and model extraction attacks. Various studies have proposed backdoor-based watermarking schemes to protect the copyright of EaaS services. In this paper, we reveal that pr

Guido Haefeli, Frederic Blanc, Esteban Currás-Rivera, Radoslav Marchevski

A novel concept to enhance the photo-detection efficiency (PDE) of silicon photomultipliers (SiPMs) has been applied and remarkable positive results can be reported. This concept uses arrays of microlenses to cover every second SiPM pixel in a checkerboard arrangement and aims to deflect the light from the dead region of the pixelised structure towards the a

ATLAS Collaboration

This paper describes an algorithm for reconstructing and identifying a highly collimated hadronically decaying $\tau$-lepton pair with low transverse momentum. When two $\tau$-leptons are highly collimated, their visible decay products might overlap, degrading the reconstruction performance for each of the $\tau$-leptons. This requires a dedicated treatment

Xiongye Xiao, Shixuan Li, Luzhe Huang, Gengshuo Liu

While working within the spatial domain can pose problems associated with ill-conditioned scores caused by power-law decay, recent advances in diffusion-based generative models have shown that transitioning to the wavelet domain offers a promising alternative. However, within the wavelet domain, we encounter unique challenges, especially the sparse represent

Ermis Soumalias, Jakob Heiss, Jakob Weissteiner, Sven Seuken

We study the design of iterative combinatorial auctions (ICAs). The main challenge in this domain is that the bundle space grows exponentially in the number of items. To address this, recent work has proposed machine learning (ML)-based preference elicitation algorithms that aim to elicit only the most critical information from bidders to maximize efficiency

Spyros Alexakis, Hiroshi Isozaki, Matti Lassas, Teemu Tyni

We show that an inverse scattering problem for a semilinear wave equation can be solved on a manifold having an asymptotically Minkowskian infinity, that is, scattering functionals determine the topology, differentiable structure, and the conformal type of the manifold. Moreover, the metric and the coefficient of the non-linearity are determined up to a mult

Jimmy Huy Tran, Jan Terje Kvaløy, Hartwig Kørner

An aspect of interest in surveillance of diseases is whether the survival time distribution changes over time. By following data in health registries over time, this can be monitored, either in real time or retrospectively. With relevant risk factors registered, these can be taken into account in the monitoring as well. A challenge in monitoring survival tim

Paolo Secchi

We consider the initial-boundary value problem in the quarter space for the system of equations of ideal Magneto-Hydrodynamics for compressible fluids with perfectly conducting wall boundary conditions. On the two parts of the boundary the solution satisfies different boundary conditions, which make the problem an initial-boundary value problem with non-unif

Yiwei Feng, Lili Lv, Weixiong Yuan, Liang Xu

Accurate and rapid prediction of flow-fields is crucial for aerodynamic design. This work proposes a discontinuous Galerkin method (DGM) whose performance enhances with increasing data, for rapid simulation of transonic flow around airfoils under various flow conditions. A lightweight and continuously updated data-driven model is built offline to predict the

Amit Samaddar, S. Surendra Singh

We investigate the cosmological implications of $f(Q,C)$ gravity with $f(Q,C)=\alpha Q+\beta C$, where $Q$ is the non-metricity scalar and $C$ encapsulates cosmological expansion terms. Three parameterizations of the EoS for dark energy, $\omega=\omega_{0}+\omega_{1}z$, $\omega=\omega_{0}+\frac{\omega_{1}z(1+z)}{1+z^{2}}$ and $\omega=\omega_{0}+\frac{\omega_

Luca Bianchi, Carlo Marconi, Giulia Guarda, Davide Bacco

Bell measurements, which allow entanglement between uncorrelated distant particles, play a central role in quantum communication. Indeed sharing, measuring and creating entanglement lie at the core of various protocols, such as entanglement swapping and quantum teleportation. While for optical qubit systems a Bell measurement can be implemented using only li

Zixing Zhang, Weixiang Xu, Zhongren Dong, Kanglin Wang

Computational paralinguistics (ComParal) aims to develop algorithms and models to automatically detect, analyze, and interpret non-verbal information from speech communication, e. g., emotion, health state, age, and gender. Despite its rapid progress, it heavily depends on sophisticatedly designed models given specific paralinguistic tasks. Thus, the heterog

Joel Fine, Partha Ghosh

Starting with an $n$-dimensional oriented Riemannian manifold with a Spin-c structure, we describe an elliptic system of equations which recover the Seiberg-Witten equations when $n=3,4$. The equations are for a U(1)-connection $A$ and spinor $\phi$, as usual, and also an odd degree form $\beta$ (generally of inhomogeneous degree). From $A$ and $\beta$ we de

Jad Elkhaleq Ghalayini, Neel Krishnaswami

Static single assignment form, or SSA, has been the dominant compiler intermediate representation for decades. In this paper, we give a type theory for a variant of SSA, including its equational theory, which are strong enough to validate a variety of control and data flow transformations. We also give a categorical semantics for SSA, and show that the type

Reyhan Mehta, Anshuman Kumar

Hexagonal boron nitride (hBN) has been experimentally shown to exhibit room-temperature single-photon emission. This emission is attributed to defect states in the wide band-gap of hBN, which allow new optical transitions between these dispersion-less defect levels. In this work, we study the new spectral features introduced by interacting atomic defects in

Jing Chen, Ji-Yuan Chen, Jun-Feng Chen, Xiang Chen

DarkSHINE is a newly proposed fixed-target experiment initiative to search for the invisible decay of Dark Photon via missing energy/momentum signatures, based on the high repetition rate electron beam to be deployed/delivered by the Shanghai High repetition rate XFEL and Extreme light facility (SHINE). This report elaborates the baseline design of DarkSHINE

Hui Ye, Haodong Chen, Xiaoming Chen, Vera Chung

Remote sensing (RS) involves the acquisition of data about objects or areas from a distance, primarily to monitor environmental changes, manage resources, and support planning and disaster response. A significant challenge in RS segmentation is the scarcity of high-quality labeled images due to the diversity and complexity of RS image, which makes pixel-leve

Arjun Nair, Roman Novikov

We consider a radiation solution $\psi$ for the Helmholtz equation in an exterior region in $\mathbb R^2$. We show that $\psi$ in the exterior region is uniquely determined by its imaginary part $Im(\psi)$ on an interval of a line $L$ lying in the exterior region. This result has holographic prototype in the recent work Nair, Novikov (2025, J. Geom. Anal. 35

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb, C. Abellan Beteta

The first measurement of $\phi(1020)$ meson production in fixed-target $p$Ne collisions at $\sqrt{s_{NN}}=68.5$ GeV is presented. The $\phi(1020)$ mesons are reconstructed in their $K^{+}K^{-}$ decay in a data sample consisting of proton collisions on neon nuclei at rest, corresponding to an integrated luminosity of $21.7 \pm 1.4$ nb$^{-1}$, collected by the

Daohua Yu

Assume that $f$ is a $C^r(r\geq 3)$ specially partially hyperbolic endomorphism on the 2-torus which is homotopic to an expanding linear endomorphism $A$ with irrational eigenvalues. We prove that $f$ and $A$ are topologically conjugate, if and only if $f$ is area-expanding. If $f$ is area-expanding and the center bundle is $C^1$, then the topological conjug

Yuang Cai, Yuyu Yuan, Jinsheng Shi, Qinhong Lin

The alignment of large language models (LLMs) is crucial for generating helpful and harmless content. Existing approaches leverage preference-based human feedback data to learn the reward function and align the LLM with the feedback data. However, these approaches focus on modeling the reward difference between the chosen and rejected demonstrations, rather

Michał Strzelecki

The operators $\Lambda_m$ ($m\in\mathbb{N}\cup \{0\}$) arise when one studies the action of the Beurling-Ahlfors transform on certain radial function subspaces. It is known that the weak-type $(1,1)$ constant of $\Lambda_0$ is equal to $1/\ln(2)\approx 1.44$. We construct examples showing that the weak-type $(1,1)$ constant of $\Lambda_1$ is larger than $1.3

Zixing Zhang, Zhongren Dong, Weixiang Xu, Jing Han

With the increasing implementation of machine learning models on edge or Internet-of-Things (IoT) devices, deploying advanced models on resource-constrained IoT devices remains challenging. Transformer models, a currently dominant neural architecture, have achieved great success in broad domains but their complexity hinders its deployment on IoT devices with

Nikolay A. Gusev, Mikhail V. Korobkov

Let $p\ge 1$ and let $\boldsymbol{v} \colon \mathbb R^d \to \mathbb R^d$ be a compactly supported vector field with $\boldsymbol{v} \in L^p(\mathbb R^d)$ and $\operatorname{div} \boldsymbol{v} = 0$ (in the sense of distributions). It was conjectured by Nelson that it $p=2$ then the operator $\mathsf{A}(\rho) := \boldsymbol{v} \cdot \nabla \rho$ with the doma

Julia Wildeboer, Saheli Sarkar, Alexei M. Tsvelik

We determine the nature of a phase transition in a model describing an interaction of multiple charge density waves in a two dimensional film. The model was introduced by two of the authors in Phys. Rev. B {\bf 108}, 045119 (2023) to describe fluctuations in charge density wave order in the kagome metals AV$_3$Sb$_5$ (A=K, Rb, Cs) in two dimensions. The situ

Mekena Metcalf, Pablo Andrés-Martínez, Nathan Fitzpatrick

Data representation in quantum state space offers an alternative function space for machine learning tasks. However, benchmarking these algorithms at a practical scale has been limited by ineffective simulation methods. We develop a quantum kernel framework using a Matrix Product State (MPS) simulator and employ it to perform a classification task with 165 f

Sanjeev Kumar Pandey

This study investigates remote synchronization in scale-free networks of coupled nonlinear oscillators inspired by synchronization observed in the brain's cortical regions and power grid. We employ the Master Stability Function (MSF) approach to analyze network stability across various oscillator models. Synchronization results are obtained for a star networ

ALICE Collaboration

Event-by-event fluctuations of the event-wise mean transverse momentum, $\langle p_{\mathrm{T}}\rangle$, of charged particles produced in proton$-$proton (pp) collisions at $\sqrt{s}$ = 5.02 TeV, Xe$-$Xe collisions at $\sqrt{s_{\mathrm{NN}}} =$ 5.44 TeV, and Pb$-$Pb collisions at $\sqrt{s_{\mathrm{NN}}} =$ 5.0 TeV are studied using the ALICE detector based o

Faranak Farshadifar

Let R be a commutative ring with identity. The concept of second submodule of an R-module (as a dual notion of prime submodules) was introduced and studied by S.Yassemi in 2001. This notion has obtained a great attention by many authors and now there is a considerable amount of research concerning this class of modules. The main purpose of this paper is to c

Anastasiia Omeliukh, Samuel Barnier, Yoshiyuki Inoue

The origin of the high-energy astrophysical neutrinos discovered by IceCube remains unclear, with both blazars and Seyfert galaxies emerging as potential sources. Recently, the IceCube Collaboration reported a ${\sim}{3}\sigma$ neutrino signal from the direction of a nearby Seyfert galaxy NGC 4151. However, two gamma-ray loud BL Lac objects, 4FGL 1210.3+3928

Dmitry Ponomarev

A particular instance of the inverse magnetisation problem is considered. It is assumed that the support of a magnetic sample (a source term in the Poisson equation in $\mathbb{R}^3$) is contained in a bounded planar set parallel to the measurement plane. Moreover, only one component of the magnetic field is assumed to be known (measured) over the same plana

Pooja Sudha, Anil kumar, Kunal Dhankar, Khalid Ansari

The mid-infrared region is crucial for elucidating the unique biochemical signatures of microorganisms. The MIR resonant structures turned out to facilitate exceptional performance owing to the enhance electric field confinement in the nano-sized aperture. However, the extension of such technique in bacteria-sensing remains limited, primarily due to its micr

Thivin Anandh, Divij Ghose, Himanshu Jain, Pratham Sunkad

This paper proposes and studies two extensions of applying hp-variational physics-informed neural networks, more precisely the FastVPINNs framework, to convection-dominated convection-diffusion-reaction problems. First, a term in the spirit of a SUPG stabilization is included in the loss functional and a network architecture is proposed that predicts spatial

Sai Subramanyam Thoota, Erik G. Larsson

We propose a novel generalized framework for grant-free random-access (GFRA) in cell-free massive multiple input multiple-output systems where multiple geographically separated access points (APs) or base stations (BSs) aim to detect sporadically active user-equipment (UEs). Unlike a conventional architecture in which all the active UEs transmit their signat

Dino Pjanić, Alexandros Sopasakis, Andres Reial, Fredrik Tufvesson

The handover (HO) procedure is one of the most critical functions in a cellular network driven by measurements of the user channel of the serving and neighboring cells. The success rate of the entire HO procedure is significantly affected by the preparation stage. As massive Multiple-Input Multiple-Output (MIMO) systems with large antenna arrays allow resolv

Maxime Wavasseur, Theo Abrial, Olivier Minazzoli

Entangled Relativity is a non-linear reformulation of Einstein's General Theory of Relativity (General Relativity) that offers a more parsimonious formulation. This non-linear approach notably requires the simultaneous definition of matter fields, thus aligning more closely with Einstein's \textit{principle of relativity of inertia} than General Relativity d

Davide Venturelli, Pierre Illien, Aurélien Grabsch, Olivier Bénichou

Quantifying the correlations between the position of a tagged tracer and the density of surrounding bath particles is crucial for understanding tracer diffusion in interacting particle systems, and for characterizing the response properties of the bath. We address this problem analytically for both hard-core and soft-core interactions, using minimal yet para

Fumiya Hori, Shunsaku Kitagawa, Kenji Ishida, Souichiro Mizutani

We report the 77Se-nuclear magnetic resonance (NMR) results of trivalent Yb zigzag chain compound YbAgSe2, which is a sister compound of YbCuS2. The 77Se-NMR spectrum was reproduced by considering two different Se sites with negative Knight shifts and three-axis anisotropy. Above the Neel temperature TN, the Knight shift is proportional to the bulk magnetic

Adrian González-Pérez, Javier Parcet, Jorge Pérez García, Éric Ricard

We investigate nontrigonometric forms of Riesz transforms in the context of Schur multipliers. This refines Grothendieck-Haagerup's endpoint criterion with a new condition for the Schatten p-boundedness of Schur multipliers and strengthens Potapov/Sukochev's solution of Arazy's conjecture. We recover as well dimension-free estimates for trigonometric Riesz t

ALICE Collaboration

Quantum Chromodynamics predicts a phase transition from ordinary hadronic matter to the quark-gluon plasma (QGP) at high temperatures and energy densities, where quarks and gluons (partons) are not confined within hadrons. The QGP is generated in ultrarelativistic heavy-ion collisions. Anisotropic flow coefficients, quantifying the anisotropic azimuthal expa

Guilherme Grams, César V. Flores, César H. Lenzi

We analyze the sensitivity of non-radial fluid oscillation modes and tidal deformations in neutron stars to high-order nuclear empirical parameters (NEP). In particular, we study the impact of the curvature and skewness of the symmetry energy $K_{\rm sym}$, $Q_{\rm sym}$, and the skewness of the binding energy in symmetric nuclear matter $Q_{\rm sat}$. As we

Yuval Wigderson

Ramsey's theorem states that if $N$ is sufficiently large, then no matter how one colors the edges among $N$ vertices with two colors, there are always $k$ vertices spanning edges in only one color. Given this theorem, it is natural to ask ``how large is sufficiently large?'' Ramsey's original proof showed that $N=k!$ is sufficient, and five years later Erd\

Christian Conti, Deborah Volpe, Mariagrazia Graziano, Maurizio Zamboni

Researchers and industries are increasingly drawn to quantum computing for its computational potential. However, validating new quantum algorithms is challenging due to the limitations of current quantum devices. Software simulators are time and memory-consuming, making hardware emulators an attractive alternative. This article introduces AMARETTO (quAntuM A

Hannah Collier, Laura A. Hayes, Stefan Purkhart, Säm Krucker

Aims: This paper aims to demonstrate the importance of short-exposure extreme ultraviolet (EUV) observations of solar flares in the study of particle acceleration, heating and energy partition in flares. This work highlights the observations now available from the Extreme Ultraviolet Imager (EUI) instrument suite on board Solar Orbiter while operating in sho

Mohammad Rifqi Farhansyah, Muhammad Zuhdi Fikri Johari, Afinzaki Amiral, Ayu Purwarianti

Indonesia is one of the most diverse countries linguistically. However, despite this linguistic diversity, Indonesian languages remain underrepresented in Natural Language Processing (NLP) research and technologies. In the past two years, several efforts have been conducted to construct NLP resources for Indonesian languages. However, most of these efforts h

Jiajun Cui, Xu Chen, Shuai Xiao, Chen Ju

For recommender systems in internet platforms, search activities provide additional insights into user interest through query-click interactions with items, and are thus widely used for enhancing personalized recommendation. However, these interacted items not only have transferable features matching users' interest helpful for the recommendation domain, but

Yi Xu, Ziming Mao, Xiangxi Mo, Shu Liu

The rapid growth of LLMs has revolutionized natural language processing and AI analysis, but their increasing size and memory demands present significant challenges. A common solution is to spill over to CPU memory; however, traditional GPU-CPU memory swapping often results in higher latency and lower throughput. This paper introduces Pie, an LLM inference f

P. Sudha, S. Miyagawa, A. Samanta, D. Moraru

Ultra-sensitive short-wave infrared (SWIR) photon detection is a crucial aspect of ongoing research in quantum technology. However, developing such detectors on a CMOS-compatible silicon technological platform has been challenging due to the low absorption coefficient for silicon in the SWIR range. In this study, a codoped silicon-based single-electron trans

Pranav Dangi, Thilini Kaushalya Bandara, Saeideh Sheikhpour, Tulika Mitra

Hardware specialization is commonly viewed as a way to scale performance in the dark silicon era with modern-day SoCs featuring multiple tens of dedicated accelerators. By only powering on hardware circuitry when needed, accelerators fundamentally trade off chip area for power efficiency. Dark silicon however comes with a severe downside, namely its environm

Pierre Lallemand, François Dubois, Li-shi Luo

Lattice Boltzmann models are briefly introduced together with references to methods used to predict their ability for simulations of systems described by partial differential equations that are first order in time and low order in space derivatives. Several previous works have been devoted to analyzing the accuracy of these models with special emphasis on de

Carlos J. Costa, Joao Tiago Aparicio, Manuela Aparicio

The widespread adoption of generative artificial intelligence (AI) has fundamentally transformed technological landscapes and societal structures in recent years. Our objective is to identify the primary methodologies that may be used to help predict the economic and social impacts of generative AI adoption. Through a comprehensive literature review, we unco

Anton Johansson, Arunselvan Ramaswamy

The development of robust generative models for highly varied non-stationary time series data is a complex yet important problem. Traditional models for time series data prediction, such as Long Short-Term Memory (LSTM), are inefficient and generalize poorly as they cannot capture complex temporal relationships. In this paper, we present a probabilistic gene

Jargalmaa Batmunkh, Yusuke Iida, Takayoshi Oba, Haruhisa Iijima

The complex structure and extensive details of solar spectral data, combined with a recent surge in volume, present significant processing challenges. To address this, we propose a deep learning-based compression technique using deep autoencoder (DAE) and 1D-convolutional autoencoder (CAE) models developed with Hinode SOT/SP data. We focused on compressing S

Aldo Marzullo, Marta Bianca Maria Ranzini

Zero-shot anomaly detection (ZSAD) offers potential for identifying anomalies in medical imaging without task-specific training. In this paper, we evaluate CLIP-based models, originally developed for industrial tasks, on brain tumor detection using the BraTS-MET dataset. Our analysis examines their ability to detect medical-specific anomalies with no or mini

Pratik Nandy, Tanay Pathak, Zhuo-Yu Xian, Johanna Erdmenger

We propose a tridiagonalization approach for non-Hermitian random matrices and Hamiltonians using singular value decomposition (SVD). This technique leverages the real and non-negative nature of singular values, bypassing the complex eigenvalues typically found in non-Hermitian systems. We analyze the tridiagonal elements, namely the Lanczos coefficients and

Junqi Liu, Yun Zhang, Xiaoqi Wang, Xu Long

Just Recognizable Difference (JRD) represents the minimum visual difference that is detectable by machine vision, which can be exploited to promote machine vision oriented visual signal processing. In this paper, we propose a Deep Transformer based JRD (DT-JRD) prediction model for Video Coding for Machines (VCM), where the accurately predicted JRD can be us

Xuanzhi Zhu, Pedro Casau, Carlos Silvestre

In this paper, we explore the conditions for asymptotic stability of the hybrid closed-loop system resulting from the interconnection of a nonlinear plant, an intelligent sensor that generates finite-time convergent estimates of the plant state, and a controller node that receives opportunistic samples from the sensor node when certain model-based event-trig