December 2024 arXiv papers — page 60

Yi Zhang, Chun-Wun Cheng, Junyi He, Zhihai He

We introduce SONO, a novel method leveraging Second-Order Neural Ordinary Differential Equations (Second-Order NODEs) to enhance cross-modal few-shot learning. By employing a simple yet effective architecture consisting of a Second-Order NODEs model paired with a cross-modal classifier, SONO addresses the significant challenge of overfitting, which is common

Javier Castro Luaces, Manuel Fernández López, Jorge Bravo-Abad, Jaime Merino

We explore the Mott transition in orthorhombic diamond lattices relevant to (ET)Ag$_4$(CN)$_5$ molecular compounds. The non-interacting phases include nodal line, Dirac and/or Weyl semimetals depending on the strength of spin-orbit coupling and the degree of dimerization of the lattice. Based on an extension of slave-rotor mean-field theory which accounts fo

Michela Rigoselli, Roberto Taverna, Sandro Mereghetti, Roberto Turolla

The Imaging X-ray Polarimetry Explorer (IXPE) observed for the first time highly polarized X-ray emission from the magnetar 1E 1841-045, targeted after a burst-active phase in August 2024. To date, IXPE has observed four other magnetars during quiescent periods, highlighting substantially different polarization properties. 1E 1841-045 exhibits a high, energy

Julian Golembiewski, Timm Faulwasser

Nonsmooth phenomena, such as abrupt changes, impacts, and switching behaviors, frequently arise in real-world systems and present significant challenges for traditional optimal control methods, which typically assume smoothness and differentiability. These phenomena introduce numerical challenges in both simulation and optimization, highlighting the need for

Holger Sennhenn-Reulen

With flexible modeling software - such as the probabilistic programming language Stan - growing in popularity, quantities of interest (QOIs) calculated post-estimation are increasingly desired and customly implemented, both by statistical software developers and applied scientists. Examples of QOI include the marginal expectation of a multilevel model with a

Ed Mackay, Callum Murphy-Barltrop, Jordan Richards, Philip Jonathan

This paper presents a novel deep learning framework for estimating multivariate joint extremes of metocean variables, based on the Semi-Parametric Angular-Radial (SPAR) model. When considered in polar coordinates, the problem of modelling multivariate extremes is transformed to one of modelling an angular density, and the tail of a univariate radial variable

Sanjay Jana, Venkata Siva Krishna, Praphul Kumar, Indranil Saha Dalal

Even though the Dissipative Particle Dynamics (DPD) has shown its worth in a variety of research areas, it has been rarely used for polymer dynamics, particularly in dilute and semi-dilute conditions and under imposed flow fields. For such applications, the most popular technique has been Brownian dynamics (BD), even though the formulation of the same may be

Nivaldo A. Lemos

The status of the equivalence principle in modified symmetric teleparallel gravity is examined. In this theory, minimum length geodesics are distinct from autoparallel geodesics, that is, the ``shortest'' paths are not the ``straightest'' paths. We show that a standard argument that singles out metric geodesics in general relativity does not apply in modifie

Marek Kowalik, Sam Genway, Vedangi Pathak, Mykola Maksymenko

Quantum chemistry applications in the noisy intermediate-scale quantum era require end-to-end approaches that balance algorithmic fidelity with practical executability on existing hardware. We present an end-to-end Hamiltonian dynamics case study for predicting the reactivity of pharmaceutically relevant covalent inhibitors containing sulfonyl fluoride warhe

Charlie F. Ruan, Yucheng Qin, Akaash R. Parthasarathy, Xun Zhou

Advancements in large language models (LLMs) have unlocked remarkable capabilities. While deploying these models typically requires server-grade GPUs and cloud-based inference, the recent emergence of smaller open-source models and increasingly powerful consumer devices have made on-device deployment practical. The web browser as a platform for on-device dep

D. Eremin, Yu. Sharova, L. Heijmans, A. M. Yakunin

A low pressure discharge sustained in molecular hydrogen with help of the electron cyclotron resonance heating at a frequency of 2.45 GHz is simulated using a fully electromagnetic implicit charge- and energy-conserving particle-in-cell/Monte Carlo code. The simulations show a number of kinetic effects, and the results are in good agreement with various expe

Chenyi Cai, Biao Li, Qiyan Zhang, Xiao Wang

Urban morphology, examining city spatial configurations, links urban design to sustainability. Morphology metrics play a fundamental role in performance-driven computational urban design (CUD) which integrates urban form generation, performance evaluation and optimization. However, a critical gap remains between performance evaluation and complex urban form

Jesús Lacalle, Luis Miguel Pozo Coronado

The sum of quantum computing errors is the key element both for the estimation and control of errors in quantum computing and for its statistical study. In this article we analyze the sum of two independent quantum computing errors, $X_1$ and $X_2$, and we obtain the formula of the variance of the sum of these errors: $$ V(X_1+X_2)=V(X_1)+V(X_2)-\frac{V(X_1)

Alexander Lieb, Hendrik Göttmann, Lars Luthmann, Malte Lochau

Timed automata are a widely used formalism for specifying the discrete-state/continuous-time behavior of time-critical reactive systems. For the fundamental verification problem of comparing two timed automata, it has been shown that timed trace equivalence is undecidable, while timed bisimulation is decidable. The corresponding decidability proof uses regio

Hyunsoo Lee, Minsoo Kang, Bohyung Han

We present a simple but effective training-free approach for text-driven image-to-image translation based on a pretrained text-to-image diffusion model. Our goal is to generate an image that aligns with the target task while preserving the structure and background of a source image. To this end, we derive the representation guidance with a combination of two

Sungjin Park, Xiao Liu, Yeyun Gong, Edward Choi

Despite recent advances in large language models, open-source models often struggle to consistently perform well on complex reasoning tasks. Existing ensemble methods, whether applied at the token or output levels, fail to address these challenges. In response, we present Language model Ensemble with Monte Carlo Tree Search (LE-MCTS), a novel framework for p

Mario Castro, Carlos Saji, Guidobeth Saez, Patricio Vergara

The collective excitations of a multiferroic material are analyzed. We show that these excitations also exhibit magnetoelectric behavior, leading to the hybridization of magnons ,oscillations of the magnetization field, and ferrons, which are oscillations of the electric dipolar density field. We term these emergent entities 'magnetoferrons', study their mai

V. I. Zvonilov

A rigid isotopy of real algebraic curves of a certain class is a path in the space of curves of this class. The paper's study completes the rigid isotopic classification of nonsingular real algebraic curves of bidegree (4,3) on a hyperboloid, begun by the author in earlier works. There are given the missing proofs of the uniqueness of the connected component

Denis Marti, Elefterios Soultanis

We consider three conditions on metric manifolds with finite volume: (1) the existence of a metric fundamental class, (2) local index bounds for Lipschitz maps, and (3) Gromov--Hausdorff approximation with volume control by bi-Lipschitz manifolds. Condition (1) is known for metric manifolds satisfying the LLC condition by work of Basso--Marti--Wenger, while

Max I. Hallgarten La Casta, Davide Amato

The availability of accurate and timely state predictions for objects in near-Earth orbits is becoming increasingly important due to the growing congestion in key orbital regimes. The Two-line Element Set (TLE) catalogue remains, to this day, one of the few publicly-available, comprehensive sources of near-Earth object ephemerides. At the same time, TLEs are

Hanine Awada, Marco Golla

We prove Libgober's divisibility relations for Oka and Alexander polynomials of symplectic curves in the complex projective plane. Along the way, we give new proofs of the divisibility relations for the Alexander polynomials of complex algebraic curves with respect to a generic line at infinity.

Max Anderson Loake, Hamish Patten, David Steinsaltz

Immediately following a disaster event, such as an earthquake, estimates of the damage extent play a key role in informing the coordination of response and recovery efforts. We develop a novel impact estimation tool that leverages a generalised Bayesian approach to generate earthquake impact estimates across three impact types: mortality, population displace

Heming Zhang, Di Huang, Yixin Chen, Fuhai Li

The integration of multi-omic data is pivotal for understanding complex diseases, but its high dimensionality and noise present significant challenges. Graph Neural Networks (GNNs) offer a robust framework for analyzing large-scale signaling pathways and protein-protein interaction networks, yet they face limitations in expressivity when capturing intricate

J. D. Fletcher, W. Park, P. See, J. P. Griffiths

While ballistic electrons are a key tool for applications in sensing and flying qubits, sub-nanosecond propagation times and complicated interactions make control of ballistic single electrons challenging. Recent experiments have revealed Coulomb collisions of counterpropagating electrons in a beam splitter, giving time resolved control of interactions betwe

Miguel Arcos Argudo, Jesús García López de Lacalle, Luis Miguel PozoCoronado

This work shows a study about the structure of the cycles contained in a Minimal Strong Digraph (MSD). The structure of a given cycle is determined by the strongly connected components (or strong components, SCs) that appear after suppressing the arcs of the cycle. By this process and by the contraction of all SCs into single vertices we obtain a Hasse diagr

Hadassah Harland, Richard Dazeley, Hashini Senaratne, Peter Vamplew

Apologies are a powerful tool used in human-human interactions to provide affective support, regulate social processes, and exchange information following a trust violation. The emerging field of AI apology investigates the use of apologies by artificially intelligent systems, with recent research suggesting how this tool may provide similar value in human-m

Murukesh Muralidhar, Antoine Naert, Sébastien Aumaître

The processes that generate rogue waves on the sea surface remain a mystery. Despite their different natures, the nonlinear bending waves generated in a thin elastic plate share some similarities with waves on the surface of the sea. For instance, both involve four-wave interactions during energy exchange, but in bending waves, the number of waves is not con

Dominique Brunato

This position paper investigates the potential of integrating insights from language impairment research and its clinical treatment to develop human-inspired learning strategies and evaluation frameworks for language models (LMs). We inspect the theoretical underpinnings underlying some influential linguistically motivated training approaches derived from ne

Mikael Santonen, Antti Lahti, Zahra Jahanshah Rad, Mikko Miettinen

Current transport in polysilicon is a complicated process with many factors to consider. The inhomogeneous nature of polysilicon with its differently shaped and sized grains is one such consideration. We have developed a method that enhances existing resistivity models with a two-dimensional extension that incorporates the grain size distribution using a Vor

ATLAS Collaboration

Jets with different radius parameters $R$ are an important tool to probe quantum chromodynamics processes at different angular scales. Jets with small $R=0.2$ are instrumental in measurements of the substructure of large-$R$ jets resulting from collimated hadronic decays of energetic $W$, $Z$, and Higgs bosons, top quarks, and of potential new resonances. Me

Meysam Korivand, Nasrin Soltankhah, Sandi Klavžar

Let ${\rm dim}(G)$ and $D(G)$ respectively denote the metric dimension and the distinguishing number of a graph $G$. It is proved that $D(G) \le {\rm dim}(G)+1$ holds for every connected graph $G$. Among trees, exactly paths and stars attain the bound, and among connected unicyclic graphs such graphs are $t$-cycles for $t\in \{3,4,5\}$. It is shown that for

Adam Dauser, Josefien Kuijper

We present an alternative formulation of Scholze's notions of cohomologically proper and cohomologically \'etale with respect to an abstract six-functor formalism. These conditions guarantee canonical isomorphisms between the direct and exceptional direct images for certain "proper" morphisms, and between the inverse and exceptional inverse images for certai

Kirill Krasnov, Arthur Lipstein

Plebanski's second heavenly equation reduces the problem of finding a self-dual Einstein metric to solving a non-linear second-order PDE for a single function. Plebanski's original equation is for self-dual metrics obtained as perturbations of the flat metric. Recently, a version of this equation was discovered for self-dual metrics arising as perturbations

Francisco Chicano, Gabiel Luque, Zakaria Abdelmoiz Dahi, Rodrigo Gil-Merino

Quantum computers leverage the principles of quantum mechanics to do computation with a potential advantage over classical computers. While a single classical computer transforms one particular binary input into an output after applying one operator to the input, a quantum computer can apply the operator to a superposition of binary strings to provide a supe

Tobias Dornheim, Michael Bonitz, Zhandos Moldabekov, Sebastian Schwalbe

We present extensive new \emph{ab initio} path integral Monte Carlo (PIMC) simulation results for the chemical potential of the warm dense uniform electron gas (UEG), spanning a broad range of densities and temperatures. This is achieved by following two independent routes, i) based on the direct estimation of the free energy [Dornheim \emph{et al.}, arXiv:2

Víctor Blanco, Gabriel González, Praful Gagrani

In this paper, we introduce the concept of self-amplifying structures for hypergraphs, positioning it as a key element for understanding propagation and internal reinforcement in complex systems. To quantify this phenomenon, we define the maximal amplification factor, a metric that captures how effectively a subhypergraph contributes to its own amplification

Amnon Balanov, Alexey Gorlach, Vladimir Baryshevsky, Ilya Feranchuk

Compact laboratory-scale X-ray sources still rely on the same fundamental principles as in the first X-ray tubes developed more than a century ago. In recent years, significant research and development have focused on large-scale X-ray sources such as synchrotrons and free-electron lasers, leading to the generation of high-brightness coherent X-rays. However

Muhamet Ibrahimi, Matthias Merkel

A key process during animal morphogenesis is oriented tissue deformation, which is often driven by internally generated active stresses. Yet, such active oriented materials are prone to well-known instabilities, raising the question of how oriented tissue deformation can be robust during morphogenesis. Here we study under which conditions active oriented def

Vincent Billault, Luc Leviandier, Jerome Bourderionnet, Christophe Pierre

In this paper, we present a method based on a modal decomposition to quantify the efficiency of photonic lanterns (PL) based free space optical (FSO) communication receivers. We fabricate a seven port PL and we evaluate numerically the free space to fiber coupling efficiency based on a reconstruction of the fields at the PL FSO multimode port. We validate th

Jonathan Heitz, Gerold Schneider, Nicolas Langer

Alzheimer's Disease (AD) is a significant and growing public health concern. Investigating alterations in speech and language patterns offers a promising path towards cost-effective and non-invasive early detection of AD on a large scale. Large language models (LLMs), such as GPT, have enabled powerful new possibilities for semantic text analysis. In this st

Jaime Muñoz Masqué, Luis Miguel Pozo Coronado, María Eugenia Rosado María

Differential $p$-forms and $q$-vector fields with constant coefficients are studied. Differential $p$-forms of degrees $p=1,2,n-1,n$ with constant coefficients on a smooth $n$-dimensional manifold $M$ are characterized. In the contravariant case, the obstruction for a $q$-vector field $V_q$ to have constant coefficients is proved to be the Schouten-Nijenhuis

R. Geyer, S. A. Klioner, L. Lindegren, U. Lammers

A gravitational wave (GW) passing through an astrometric observer causes periodic shifts of the apparent star positions measured by the observer. For a GW of sufficient amplitude and duration, and of suitable frequency, these shifts might be detected with a Gaia-like astrometric telescope. This paper aims to analyse in detail the effects of GWs on an astrome

Kael Dixon, Thomas Bruun Madsen, Andrew Swann

We study $G_{2}$-manifolds obtained from circle bundles over symplectic $SU(3)$-manifolds with $T^{2}$-symmetry. When the geometry is multi-Hamiltonian, we show how the compact part of the resulting multi-moment graph for the $G_{2}$-structure may obtained cohomologically from the base. The lifting procedure is illustrated in the context of toric geometry.

Oleg Kiselyov, Tomoaki Kobayashi, Nick Palladinos

Processing large amounts of data fast, in constant and small space is the point of stream processing and the reason for its increasing use. Alas, the most performant, imperative processing code tends to be almost impossible to read, let alone modify, reuse -- or write correctly. We present both a stream compilation theory and its implementation as a portable

Zhineng Cao, Liuquan Wang

Around 2007, Zagier discovered some rank two and rank three Nahm sums, and their modularity have now all been confirmed. Zagier also observed that the dual of a modular Nahm sum is likely to be modular. This duality observation motivates us to discover some new modular rank three Nahm sums by a lift-dual operation. We first lift Zagier's rank two Nahm sums t

Leonidas Daskalakis, Anastasios Fragkos

For $c\in(1,2)$ we consider the following operators \[ \mathcal{C}_{c}f(x) = \sup_{\lambda \in [-1/2,1/2)}\bigg| \sum_{n \neq 0}f(x-n) \frac{e^{2\pi i\lambda \lfloor |n|^{c} \rfloor}}{n}\bigg|\text{,}\quad \mathcal{C}^{\mathsf{sgn}}_{c}f(x) = \sup_{\lambda \in [-1/2,1/2)}\bigg| \sum_{n \neq 0}f(x-n) \frac{e^{2\pi i\lambda \mathsf{sign(n)} \lfloor |n|^{c} \rf

Mary Paterson, James Moor, Luisa Cutillo

Cases of laryngeal cancer are predicted to rise significantly in the coming years. Current diagnostic pathways are inefficient, putting undue stress on both patients and the medical system. Artificial intelligence offers a promising solution by enabling non-invasive detection of laryngeal cancer from patient voice, which could help prioritise referrals more

Szczepan Głodzik, Kim Pöyhönen, Ali G. Moghaddam, Teemu Ojanen

Entanglement patterns reveal essential information on many-body states and provide a way to classify quantum phases of matter. However, experimental studies of many-body entanglement remain scarce due to their unscalable nature. The present work aims to mitigate this theoretical and experimental divide by introducing reduced fluctuations of observables, cons

Václav Cenker, Ivan Chajda, Helmut Länger

The Sasaki projection was introduced as a mapping from the lattice of closed subspaces of a Hilbert space onto one of its segments. To use this projection and its dual so-called Sasaki operations were introduced by the second two authors. In a previous paper there are described several classes of lattices, $\lambda$-lattices and semirings where the Sasaki op

Zhiwen Li, Ming Yang, Biwei Jiang, Yi Ren

A complete sample of red supergiant stars (RSGs) is important for studying their properties. Identifying RSGs in extragalatic field first requires removing the Galactic foreground dwarfs. The color-color diagram (CCD) method, specifically using $r-z/z-H$ and $J-H/H-K$, has proven successful in several studies. However, in metal-poor galaxies, faint RSGs will

Andrea Guerra, Giorgio Vinciguerra, Antonio Boffa, Paolo Ferragina

Time series play a crucial role in many fields, including finance, healthcare, industry, and environmental monitoring. The storage and retrieval of time series can be challenging due to their unstoppable growth. In fact, these applications often sacrifice precious historical data to make room for new data. General-purpose compressors can mitigate this proble

Mathias Pont, Stephen C. Wein, Ilse Maillette de Buy Wenniger, Valentin Guichard

Generating identical photons from remote emitter-based bright single-photon sources is an important step for scaling up optical quantum technologies. Here, we study the Hong-Ou-Mandel interference of photons emitted from remote sources based on semiconductor quantum dots. We make use of a deterministic fabrication technique to position the quantum dots in a

Sherlock Anthony Licorish

Agile methods and associated practices have been held to deliver value to software developers and customers. Research studies have reported team productivity and software quality benefits. While such insights are helpful for understanding how agile methods add value during software development, there is need for understanding the intersection of useful pract

Sheng-Hsuan Huang, Thomas Dirmeier, Golnoush Shafiee, Kaisa Laiho

Hong-Ou-Mandel interference plays a vital role in many quantum optical applications where indistinguishability of two photons is important. Such photon pairs are commonly generated as the signal and idler in the frequency and polarization-degenerate spontaneous parametric down conversion~(SPDC). To scale this approach to a larger number of photons we demonst

Georgios Peikos, Wojciech Kusa, Symeon Symeonidis

Information Retrieval (IR) evaluation involves far more complexity than merely presenting performance measures in a table. Researchers often need to compare multiple models across various dimensions, such as the Precision-Recall trade-off and response time, to understand the reasons behind the varying performance of specific queries for different models. We

Sophie Steger, Christian Knoll, Bernhard Klein, Holger Fröning

Bayesian inference in function space has gained attention due to its robustness against overparameterization in neural networks. However, approximating the infinite-dimensional function space introduces several challenges. In this work, we discuss function space inference via particle optimization and present practical modifications that improve uncertainty

Dominique-Marie Cabaret, Thierry Grandou, Ghislain-Marie Grange, Emmanuel Perrier

Energy is no doubt an intuitive concept. Following a previous analysis on the nature of elementary particles and associated elementary quantum fields, the peculiar status and role of energy is scrutinised further at elementary and larger scales. Energy physical characterisation shows that it is a primordial component of reality highlighting the quantum field

Hong Liang Cheah, Mohammad Deghat

This paper proposes a finite-time input-to-state stable (FTISS) bearing-only formation control law that rejects unknown constant disturbances. Unlike existing finite-time bearing-based formation control laws, which typically rely on the availability of a global coordinate frame and some information about the disturbances, our approach requires only local bea

Victor Vantilborgh, Sander De Witte, Frederik Ostyn, Tom Lefebvre

Precise identification of dynamic models in robotics is essential to support control design, friction compensation, output torque estimation, etc. A longstanding challenge remains in the identification of friction models for robotic joints, given the numerous physical phenomena affecting the underlying friction dynamics which result into nonlinear characteri

Gabriele Di Rosa, Ognjen Jovanovic, M. Ahmed Leghari, Jasper Müller

We numerically investigate joint pilot-aided phase recovery for frequency comb-based long-haul wideband transmission. We report net information rate gains by optimizing the pilot overhead and phase estimation algorithm, outperforming per-channel processing at lower complexity.

Antoine Lemoine, Brieg Le Corre, Lise Morice, Abdelmounaïm Harouri

Achieving high conversion efficiencies in second-order nonlinear optical processes is a key challenge in integrated photonics for both classical and quantum applications. This paper presents the first demonstration of Transverse Orientation-Patterned gallium phosphide (TOP-GaP) waveguides showing high-efficiency second harmonic generation. In such devices, f

Jiaxing Yuan, Hajime Tanaka

The formation of coacervates through phase separation of oppositely charged polyelectrolytes (PEs) is critical for understanding biological condensates and developing responsive materials. Traditionally, coacervates are viewed as spherical droplets with growth dynamics resembling liquid-liquid phase separation. However, our fluid particle dynamics simulation

Yiheng Jiang, Haotian Zhang, Li Li, Dong Liu

In the field of autonomous driving, a variety of sensor data types exist, each representing different modalities of the same scene. Therefore, it is feasible to utilize data from other sensors to facilitate image compression. However, few techniques have explored the potential benefits of utilizing inter-modality correlations to enhance the image compression

Hansol Kim, Wonjae Choi, Younghun Kwon

The magic state injection process is a critical component of fault-tolerant quantum computing, and numerous studies have been conducted on this topic. Many existing studies have focused on square-lattice structures, where each qubit connects directly to four other qubits via two-qubit gates. However, hardware that does not follow a lattice structure, such as

Jorge García-Carrasco, Alejandro Maté, Juan Trujillo

Large Language Models (LLMs) have shown impressive performance across a wide range of tasks. However, the size of LLMs is steadily increasing, hindering their application on computationally constrained environments. On the other hand, despite their general capabilities, there are many situations where only one specific task is performed, rendering all other

Shao-Ping Li, Ke-Pan Xie

Multi-body dark matter annihilation is commonly expected to be suppressed by higher-order couplings and phase-space factors, therefore being ignored thus far. We show that, however, this does not hold for a class of nonthermal dark matter scenarios, where the dark matter particle becomes nonrelativistic at temperatures much higher than its mass. We exemplify

Shamus Sim, Tyrone Chen

Background: Despite the current ubiquity of Large Language Models (LLMs) across the medical domain, there is a surprising lack of studies which address their reasoning behaviour. We emphasise the importance of understanding reasoning behaviour as opposed to high-level prediction accuracies, since it is equivalent to explainable AI (XAI) in this context. In p

Julia Lademann, Jannik Henze, Sebastian Becker-Genschow

This work explores the integration of AI custom chatbots in educational settings, with a particular focus on their applicability in the context of mathematics and physics. In view of the increasing deployment of AI tools such as ChatGPT in educational contexts, the present study examines their potential as personalized tutoring systems. The study assesses th

Stefan Gerhold, Julian Pachschwöll, Johannes Ruf

We propose a method to bound the expectation of the supremum of the price process in stochastic volatility models. It can be applied, for example, to the rough Bergomi model, avoiding the need to discuss finiteness of higher moments. Our motivation stems from the theory of American option pricing, as an integrable supremum implies the existence of an optimal

Ziwei Song, Mingsong Lv, Tianchi Ren, Chun Jason Xue

Existing Autonomous Driving Systems (ADS) independently make driving decisions, but they face two significant limitations. First, in complex scenarios, ADS may misinterpret the environment and make inappropriate driving decisions. Second, these systems are unable to incorporate human driving preferences in their decision-making processes. This paper proposes

Maximilian Dinkel, Gil Robalo Rei, Wolfgang A. Wall

Like many optimization algorithms, Stochastic Variational Inference (SVI) is sensitive to the choice of the learning rate. If the learning rate is too small, the optimization process may be slow, and the algorithm might get stuck in local optima. On the other hand, if the learning rate is too large, the algorithm may oscillate or diverge, failing to converge

Matthew McCullough

These lectures discuss diverse theoretical approaches, old and new, towards understanding the origin of the Higgs sector of the Standard Model and the lightness of the Higgs boson.

Gabriele Di Rosa, Martin Kuipers, Jim Zou, Ognjen Jovanovic

We study system architectures for the coexistence of future coherent PON and DWDM networks. Considering deployed optical filters, we observe filtering penalties < 1dB at a laser frequency accuracy < 12GHz when using a cost-effective architecture.

Masahiro Kurisaki

In this paper, we propose a new asymptotic expansion approach for nonlinear filtering based on a small parameter in the system noise. This method expresses the filtering distribution as a power series in the noise level, where the coefficients can be computed by solving a system of ordinary differential equations. As a result, it addresses the trade-off betw

ATLAS Collaboration

The production of $D^{\pm}$ and $D_{s}^{\pm}$ charmed mesons is measured using the $D^{\pm}/D_{s}^{\pm} \to \phi(\mu\mu)\pi^{\pm}$ decay channel with 137 fb$^{-1}$ of $\sqrt{s} = 13$ TeV proton-proton collision data collected with the ATLAS detector at the Large Hadron Collider during the years 2016-2018. The charmed mesons are reconstructed in the range of

Igor Bogush, Vladimir M. Fomin, Oleksandr V. Dobrovolskiy

Three-dimensional nanoarchitectures are widely used across various areas of physics, including spintronics, photonics, and superconductivity. In this regard, thin curved 3D membranes are especially interesting for applications in nano- and optoelectronics, sensorics, and information processing, making physics simulations in complex 3D geometries indispensabl

Anna Reithmeir, Veronika Spieker, Vasiliki Sideri-Lampretsa, Daniel Rueckert

Image registration is fundamental in medical imaging applications, such as disease progression analysis or radiation therapy planning. The primary objective of image registration is to precisely capture the deformation between two or more images, typically achieved by minimizing an optimization problem. Due to its inherent ill-posedness, regularization is a

Dexter Neo, Tsuhan Chen

Large Vision-Language Models (LVLMs) have made remarkable developments along with the recent surge of large language models. Despite their advancements, LVLMs have a tendency to generate plausible yet inaccurate or inconsistent information based on the provided source content. This phenomenon, also known as ``hallucinations" can have serious downstream impli

Ying-Hui Shao, Yan-Hong Yang, Wei-Xing Zhou

This study examines contemporaneous and lagged spillover effects in BRICS staple grain futures markets and their linkages with U.S. markets. The results show that contemporaneous spillovers dominate, while net spillovers are driven by lagged connectedness. Systemic risk is lower in intra-BRICS markets compared to those including the U.S., highlighting the U.

Amin Soofiani

Let $K$ be a complete discretely valued field with residue field $k$ with $char \ k \ne 2$. Assuming that the norm principle holds for spinor groups $Spin(\mathfrak{h})$ for every regular skew-hermitian form $\mathfrak{h}$ over every quaternion algebra $\mathfrak{D}$ (with respect to the canonical involution on $\mathfrak{D}$) defined over any finite extensi

Chrysafis Hartonas

This article initiates the semantic study of distribution-free normal modal logic systems, laying the semantic foundations and anticipating further research in the area. The article explores roughly the same area, though taking a different approach, with a recent article by Bezhanishvili, de Groot, Dmitrieva and Morachini, who studied a distribution-free ver

Yuecen Wei, Xingcheng Fu, Lingyun Liu, Qingyun Sun

Graph neural networks (GNNs) provide important prospective insights in applications such as social behavior analysis and financial risk analysis based on their powerful learning capabilities on graph data. Nevertheless, GNNs' predictive performance relies on the quality of task-specific node labels, so it is common practice to improve the model's generalizat

David Calhas, João Marques, Arlindo L. Oliveira

The biological brain has inspired multiple advances in machine learning. However, most state-of-the-art models in computer vision do not operate like the human brain, simply because they are not capable of changing or improving their decisions/outputs based on a deeper analysis. The brain is recurrent, while these models are not. It is therefore relevant to

Stefaan Vaes

In this short note, we construct an exotic example of a locally compact group $G$ with a Borel $2$-cocycle $\omega$ such that the non-twisted group von Neumann algebra $L(G)$ is a factor, while the twisted group von Neumann algebra $L_\omega(G)$ has a diffuse center.

Th. A. Rijken, Y. Yamamoto

The Quark-quark (QQ) and Quark-nucleon (QN) interactions in this paper are derived from the Extended-soft-core (ESC) interactions. The meson-quark-quark (MQQ) vertices are determined in the framework of the constituent quark model (CQM). These vertices are such that upon folding with the ground-state baryon quark wave functions the one-boson-exchange (OBE) a

Zi-Ying Yang, Jing Song, Wei-Hong Liang, Eulogio Oset

We address the issue of the width and spin assignment of the $P_c(4440)$ and $P_c(4457)$ pentaquark states. We calculate the partial decays widths of the particles into $J/\psi N$, $\bar{D} \Sigma_c$ and $\bar{D} \Lambda_c$ with the first one obtained within a unitary approach with the coupled channels of $J/\psi N$ and $\bar{D}^* \Sigma_c$ with the interact

Michael Dumbser, Mária Lukáčová-Medvid'ová, Andrea Thomann

We study the convergence of a novel family of thermodynamically compatible schemes for hyperbolic systems (HTC schemes) in the framework of dissipative weak solutions, applied to the Euler equations of compressible gas dynamics. Two key novelties of our method are i) entropy is treated as one of the main field quantities and ii) the total energy conservation

Ruize Ma, Nikita V. Tepliakov, Arash A. Mostofi, Michele Pizzochero

Atomically thin crystals hosting flat electronic bands have been recently identified as a rich playground for exploring and engineering strongly correlated phases. Yet, their variety remains limited, primarily to two-dimensional moir\'e superlattices. Here, we predict the formation of reversible, electrically-induced ultra-flat bands and $\pi$-electron magne

Mirko Polato

Since its inception in 2016, Federated Learning (FL) has been gaining tremendous popularity in the machine learning community. Several frameworks have been proposed to facilitate the development of FL algorithms, but researchers often resort to implementing their algorithms from scratch, including all baselines and experiments. This is because existing frame

Daniel Bossér, Magnus Lundberg Nordenvaad, Gustaf Hendeby, Isaac Skog

This article concerns the challenge of reliable broadband passive sonar target detection and tracking in complex acoustic environments. Addressing this challenge is becoming increasingly crucial for safeguarding underwater infrastructure, monitoring marine life, and providing defense during seabed warfare. To that end, a solution is proposed based on a vecto

Vincenzo Timmel, Claudio Paonessa, Reza Kakooee, Manfred Vogel

This paper presents a new approach to fine-tuning OpenAI's Whisper model for low-resource languages by introducing a novel data generation method that converts sentence-level data into a long-form corpus, using Swiss German as a case study. Non-sentence-level data, which could improve the performance of long-form audio, is difficult to obtain and often restr

Yuchen Liu, Chuyu Zhou

In this paper, we present a general wall crossing theory for K-stability and K-moduli of log Fano pairs whose boundary divisors can be non-proportional to the anti-canonical divisor. Along the way, we prove that there are only finitely many K-semistable domains associated to the fibers of a log bounded family of couples. Under the additional assumption of vo

Huan-Qiang Zhou, Qian-Qian Shi, Ian P. McCulloch, J. O. Fjærestad

The one-dimensional flat-band ferromagnetic Tasaki model exhibits spontaneous symmetry breaking from ${\rm SU}(2)$ to ${\rm U}(1)$ with one type-B Goldstone mode, featuring that the highest weight state is entangled at quarter filling, but there is always a choice to keep the highest weight state unentangled away from quarter filling. It is found that the gr

Yuchen Liu, Chuyu Zhou

In this paper, we develop an algebraic K-stability theory (e.g. special test configuration theory and optimal destabilization theory) for log Fano $\mathbb R$-pairs, and construct a proper K-moduli space to parametrize K-polystable log Fano $\mathbb R$-pairs with some fixed invariants (e.g. dimension, volume, coefficients). All of these are well-known for lo

Vignesh Arumugam Nadarajan

In this article, we consider the problem of estimating the correlation of Hecke eigenvalues of GL2 automorphic forms with a class of functions of algebraic origin defined over finite fields called trace functions. The class of trace functions is vast and includes many standard exponential sums like Gauss sums, Klostermann sums, Hyperklostermann sums etc. In

Kristina Lerman, Minh Duc Chu, Charles Bickham, Luca Luceri

Social media platforms have become critical spaces for discussing mental health concerns, including eating disorders. While these platforms can provide valuable support networks, they may also amplify harmful content that glorifies disordered cognition and self-destructive behaviors. While social media platforms have implemented various content moderation st

Leandro Lanzieri, Lukasz Butkowski, Jiri Kral, Goerschwin Fey

The growing deployment of unhardened embedded devices in critical systems demands the monitoring of hardware ageing as part of predictive maintenance. In this paper, we study degradation on a large deployment of 298 naturally aged FPGAs operating in the European XFEL particle accelerator. We base our statistical analyses on 280 days of in-field measurements

Maksims Arzamasovs, Min Liu, Yue Zhang, Rui Tian

We propose using many-body Ramsey interferometry to measure non-equilibrium correlation functions of one-dimensional (1D) integrable systems. The 1D transverse-field Ising model, which is conjectured to equilibrate into non-thermal Gibbs ensemble (GGE) steady states, is studied. It is shown that retarded Green's functions, as opposed to ordinary spin-spin co

Samira Mansourzadeh, Tim Vogel, Alan Omar, Megan F. Biggs

We present a high power and broadband THz-TDS setup utilizing the nonlinear organic crystal MNA both as emitter and detector. The THz source is based on optical rectification of near infra-red laser pulses at a central wavelength of 1036 nm from a commercial, high-power Yb-based laser system and reaches a high THz average power of 11 mW at a repetition rate

Peter Raffai, Adrienn Pataki, Rebeka L. Böttger, Alexandra Karsai

We test and compare coasting cosmological models with curvature parameters ${k=\left\{ -1,0,+1 \right\}}$ in ${H_0^2 c^{-2}}$ units and the flat $\Lambda$CDM model by fitting them to cosmic chronometers (CC), the Pantheon+ sample of type Ia supernovae (SNe), and standardized quasars (QSOs). We used the \texttt{emcee} code for fitting CC data, a custom Markov