December 2024 arXiv papers — page 129

Rômulo Damasclin Chaves dos Santos, Jorge Henrique de Oliveira Sales

This work presents a comprehensive study of the microlocal energy decomposition and propagation of singularities for semiclassically adjusted dissipative pseudodifferential operators. The analysis focuses on the behavior of energy dissipation in turbulent flows modeled by operators \( P_h \) with symbols \( a(x, \xi) \in S^m(\mathbb{R}^n) \), where \( m < 0

Evangelia Gkritzali, Panagiotis Kaliosis, Sofia Galanaki, Elisavet Palogiannidi

In the vast majority of the academic and scientific domains, LaTeX has established itself as the de facto standard for typesetting complex mathematical equations and formulae. However, LaTeX's complex syntax and code-like appearance present accessibility barriers for individuals with disabilities, as well as those unfamiliar with coding conventions. In this

Andreas Koukounas, Georgios Mastrapas, Sedigheh Eslami, Bo Wang

Contrastive Language-Image Pretraining (CLIP) has been widely used for crossmodal information retrieval and multimodal understanding tasks. However, CLIP models are mainly optimized for crossmodal vision-language tasks and underperform in single-mode text tasks. Moreover, these models are often trained on English datasets and therefore lack multilingual unde

Wang Chen, Guan Huang, Jintao Ke

This study investigates the development dilemma of ride-sharing services using real-world mobility datasets from nine cities and calibrated customers' price and detour elasticity. Through massive numerical experiments, this study reveals that while ride-sharing can benefit social welfare, it may also lead to a loss of revenue for transportation network compa

Alejandro Garnung Menéndez

In industrial imaging, accurately detecting and distinguishing surface defects from noise is critical and challenging, particularly in complex environments with noisy data. This paper presents a hybrid framework that integrates both statistical feature selection and classification techniques to improve defect detection accuracy while minimizing false positiv

Sergio Hernández-Cuenca, Nico Valdes-Meller, Wayne Wei-en Weng

We report on an instance in quantum gravity where a topological expansion resums into an effective description on a single geometry. The original theory whose gravitational path integral we study is JT quantum gravity with one asymptotic boundary at nonperturbatively low temperatures. The effective theory we derive is a deformation of JT gravity by a highly

Stanisław Kaźmierowski

This paper studies a generalized variant of the Colonel Blotto game, referred to as the Colonel Blotto game with costs. Unlike the classic Colonel Blotto game, which imposes the use-it-or-lose-it budget assumption, the Colonel Blotto game with costs captures the strategic importance of costs related both to obtaining resources and assigning them across battl

Athina Bikaki, Ioannis A. Kakadiaris

In recent years, large language models (LLMs) have demonstrated remarkable progress in common-sense reasoning tasks. This ability is fundamental to understanding social dynamics, interactions, and communication. However, the potential of integrating computers with these social capabilities is still relatively unexplored. However, the potential of integrating

Irene Prieto-Rodríguez, Antonio Prados, Carlos A. Plata

Heat engines transform thermal energy into useful work, operating in a cyclic manner. For centuries, they have played a key role in industrial and technological development. Historically, only gases and liquids have been used as working substances, but the technical advances achieved over the past decades allow for expanding the experimental possibilities an

Christian Bengs, Chongwei Zhang, Ashok Ajoy

Multiple-quantum coherence (MQC) spectroscopy is a powerful technique for probing spin clusters, offering insights into diverse materials and quantum many-body systems. However, prior experiments have revealed a rapid decay in MQC intensities as the coherence order increases, restricting observable cluster sizes to the square root of the total system size. I

Haoyuan Li, Yusen Zhang, Rui Zhang, Snigdha Chaturvedi

Fairness in multi-document summarization (MDS) measures whether a system can generate a summary fairly representing information from documents with different social attribute values. Fairness in MDS is crucial since a fair summary can offer readers a comprehensive view. Previous works focus on quantifying summary-level fairness using Proportional Representat

Prajwal Koirala, Zhanhong Jiang, Soumik Sarkar, Cody Fleming

In safe offline reinforcement learning (RL), the objective is to develop a policy that maximizes cumulative rewards while strictly adhering to safety constraints, utilizing only offline data. Traditional methods often face difficulties in balancing these constraints, leading to either diminished performance or increased safety risks. We address these issues

Braden Scherting, Otso Ovaskainen, David B. Dunson

Accelerating global biodiversity loss has highlighted the role of complex relationships and shared patterns among species in determining their responses to environmental changes. The structure of an ecological community, represented by patterns of dependence among constituent species, signals its robustness more than individual species distributions. We focu

Ayesha Afzal, Georg Hager, Gerhard Wellein

We present a thorough performance and energy consumption analysis of the LULESH proxy application in its OpenMP and MPI variants on two different clusters based on Intel Ice Lake (ICL) and Sapphire Rapids (SPR) CPUs. We first study the strong scaling and power consumption characteristics of the six hot spot functions in the code on the node level, with a spe

Shahaf Nitzan

A.Olevskii and A.Ulanovskii obtained a scale of density results, which correspond to how well an exponential system approximates a uniformly minimal system over a compact set. We extend their result in several directions. First, we show that it holds for any set of positive finite measure. Next, we consider a relaxed version of frames, which we term 'uniform

Patricio Sanhueza, Junhao Liu, Kaho Morii, Josep Miquel Girart

A complete understanding of the initial conditions of high-mass star formation and what processes determine multiplicity require the study of the magnetic field (B-field) in young, massive cores. Using ALMA 250 GHz polarization (0.3" = 1000 au) and ALMA 220 GHz high-angular resolution observations (0.05" = 160 au), we have performed a full energy analysis in

Alexander V. Savin, Artem P. Klinov

The method of molecular dynamics and molecular mechanics has been used to numerically simulate the formation of wrinkle systems during compression of a graphene sheet lying on a flat solid substrate. It is shown that under uniaxial compression the nanosheet can transition into several stable wrinkled states: the most energetically favorable one is a linear w

Jeffrey Wong

The science of cause and effect is extremely sophisticated and extremely hard to scale. Using a controlled experiment, scientists get rich insights by analyzing global effects, effects in different segments, and trends in effects over time. They use propensity scores to project external validity. To support the analysis of relative effects, scientists derive

Loïc Chagot, Frédéric Y. Moulin, Olivier Eiff

This letter investigates converged statistics in three-dimensional deep-canopy-dominated flows under two low relative submergence conditions: $h/k=1.5$ and $h/k=1.2$. Using a multi-plane telecentric PIV setup, time-averaged velocity fields were obtained across nine planes. For $h/k=1.5$, the flow structure exhibited a classical three-region behavior: a unifo

Evan C. Johnson, Mark A. Lewis

The Canadian province of Alberta spent over 500 million dollars on controlling mountain pine beetle populations, but did it work? Using a statistical modeling framework coupled with long-term field data, we examined how direct control measures, severe winters, and host-tree depletion shaped the trajectory of Alberta's mountain pine beetle outbreak between 20

Francesco Flammini Dotti, M. B. N. Kouwenhoven, Peter Berczik, Qi Shu

Context. Low-mass bodies, such as comets, asteroids, planetesimals, and free-floating planets, are continuously injected into the intra-cluster environment after expulsion from their host planetary systems. These can be modeled as massless particles (MLPs, hereafter). The dynamics of large populations of MLPs, however, has yet received little attention in li

Martín Gilabert Vio

We prove a dynamical variant of the Tits alternative for the group of almost automorphisms of a locally finite tree $\mathcal{T}$: a group of almost automorphisms of $\mathcal{T}$ either contains a nonabelian free group playing ping-pong on the boundary $\partial \mathcal{T}$, or the action of the group on $\partial \mathcal{T}$ preserves a probability measu

Pablo Costas, Italo Romani de Oliveira

This work explores the evolution of the Flight Operations Center (FOC) and flight trajectory exchange tools within Trajectory-Based Operations (TBO), emphasizing the benefits of the ICAO's Flight and Flow Information for a Collaborative Environment (FF-ICE) messaging framework and Electronic Flight Bags (EFBs). It highlights the collaborative management of f

Marius Tărnăuceanu

A group $G$ is said to have dense solitary subgroups if each non-empty open interval in its subgroup lattice $L(G)$ contains a solitary subgroup. In this short note, we find all finite groups satisfying this property.

Yi Tang, Peng Sun, Zhenglin Cheng, Tao Lin

Recent studies indicate that the denoising process in deep generative diffusion models implicitly learns and memorizes semantic information from the data distribution. These findings suggest that capturing more complex data distributions requires larger neural networks, leading to a substantial increase in computational demands, which in turn become the prim

Andrii Dzhoha, Alexey Kurennoy, Vladimir Vlasov, Marjan Celikik

Position bias poses a persistent challenge in recommender systems, with much of the existing research focusing on refining ranking relevance and driving user engagement. However, in practical applications, the mitigation of position bias does not always result in detectable short-term improvements in ranking relevance. This paper provides an alternative, pra

Martín Gilabert Vio

Let $\mu_1, \mu_2$ be probability measures on $\mathrm{Diff}^1_+(S^1)$ satisfying a suitable moment condition and such that their supports genererate discrete groups acting proximally on $S^1$. Let $(f^n_\omega)_{n \in \mathbb{N}}, (f^n_{\omega'})_{n \in \mathbb{N}}$ be two independent realizations of the random walk driven by $\mu_1, \mu_2$ respectively. We

Evan C. Johnson, Antonia Musso, Catherine Cullingham, Mark A. Lewis

Following widespread outbreaks across western North America, mountain pine beetle recently expanded its range from British Columbia into Alberta. However, mountain pine beetle's eastward expansion across Canada has stalled unexpectedly, defying predictions of rapid spread through jack pine, a novel host tree. This study investigates the underlying causes of

Sulyab Thottungal Valapu, Aritri Saha, Bhaskar Krishnamachari, Vivek Menon

In response to the growing demand for enhanced performance and power efficiency, the semiconductor industry has witnessed a paradigm shift toward heterogeneous integration, giving rise to 2.5D/3D chips. These chips incorporate diverse chiplets, manufactured globally and integrated into a single chip. Securing these complex 2.5D/3D integrated circuits (ICs) p

Zaid Abulawi, Rui Hu, Prasanna Balaprakash, Yang Liu

Accurate predictions and uncertainty quantification (UQ) are essential for decision-making in risk-sensitive fields such as system safety modeling. Deep ensembles (DEs) are efficient and scalable methods for UQ in Deep Neural Networks (DNNs); however, their performance is limited when constructed by simply retraining the same DNN multiple times with randomly

Qi Huang, Hepeng Yao, Xuzong Chen, Laurent Sanchez-Palencia

The Tan contact has emerged as a pivotal quantity in characterizing many-body quantum systems, bridging microscopic short-range correlations to thermodynamic behavior. It is defined as the weight of universal $1/k^4$ fall off in momentum distribution tails, which can be measured directly in ultracold gases. So far, however, its direct measurement has been hi

Jungho Kim, Changwon Kang, Dongyoung Lee, Sehwan Choi

In this paper, we introduce ProtoOcc, a novel 3D occupancy prediction model designed to predict the occupancy states and semantic classes of 3D voxels through a deep semantic understanding of scenes. ProtoOcc consists of two main components: the Dual Branch Encoder (DBE) and the Prototype Query Decoder (PQD). The DBE produces a new 3D voxel representation by

John F. Donoghue

No. In this brief pedagogic note, I describe why the cosmological constant and Newton's constant are not running parameters in physical reactions.

Getachew K. Befekadu

In this paper, we provide a mathematical framework for improving generalization in a class of learning problems which is related to point estimations for modeling of high-dimensional nonlinear functions. In particular, we consider a variational problem for a weakly-controlled gradient system, whose control input enters into the system dynamics as a coefficie

Ke Wang, Hong Xuan

Multi-modal large language models (MLLMs) utilizing instruction-following data, such as LLaVA, have achieved great progress in the industry. A major limitation in these models is that visual tokens consume a substantial portion of the maximum token limit in large language models (LLMs), leading to increased computational demands and decreased performance whe

Stuart James Hall, Paul Schwahn, Uwe Semmelmann

We study the deformability of the symmetric Einstein metrics on the spaces $\mathrm{SU}(n)/\mathrm{SO}(n)$ and $\mathrm{SU}(2n)/\mathrm{Sp}(n)$, thereby concluding the problem to second order for all irreducible symmetric spaces. The obstruction integrals are calculated from invariant polynomials on certain Lie algebra representations. To aid the computation

Jayden Rogers, Niyaz Shakeel, Divya Mankani, Samantha Espinosa

The hardware security community relies on databases of known vulnerabilities and open-source designs to develop formal verification methods for identifying hardware security flaws. While there are plenty of open-source designs and verification tools, there is a gap in open-source properties addressing these flaws, making it difficult to reproduce prior work

Franciszek Prus-Wiśniowski, Jolanta Ptak

Examples of achievable Cantorvals are constructed with reversed Kakeya conditions only on a set of asymptotic density zero which answers in positive the Problem 5.2 from Marchwicki and Miska (2021). Additionally, the Lebesgue measure of the boundaries of these Cantorvals is found to be zero which does not answer the still open problem of existence of achieva

Víctor Hernández-Santamaría, Subrata Majumdar, Luz de Teresa

This article deals with the boundary null controllability of some degenerate parabolic equations posed on a square domain, presenting the first study of boundary controllability for such equations in multidimensional settings. The proof combines two classical techniques: the method of moments and the Lebeau-Robbiano strategy. A key novelty of this work lies

Samuel S. Taylor, Robert J. Scherrer

We examine several dark energy models with a time-varying equation of state parameter, $w(z)$, to determine what information can be derived by fitting the distance modulus in such models to a constant equation of state parameter, $w_*$. We derive $w_*$ as a function of the model parameters for the Chevallier-Polarski-Linder (CPL) parametrization, and for the

Nikhil Mehta, Sithira Ambepitiya, Thanveer Ahamad, Dinuka Wijesundara

Introduction: Global burden of sexually transmitted infections (STIs) is rising out of proportion to specialists. Current chatbots like ChatGPT are not tailored for handling STI-related concerns out of the box. We developed Otiz, an Artificial Intelligence-based (AI-based) chatbot platform designed specifically for STI detection and counseling, and assessed

Alexander J. Shook, Daksh Malhotra, Aymar Muhikira, Vaisakh Vadakkumbatt

Symmetry breaking phase transitions from less to more ordered phases will typically produce topological defects in the ordered phase. Kibble-Zurek theory predicts that for any second-order phase transition, such as the early universe, the density of defects that form should be determined by the scaling law for the system coherence time and the phase transiti

Leonardo De Carlo, W. David Wick

In two prior papers of this series, it was proposed that a wavefunction model of a heavy particle and a collection of light particles might generate ``Brownian-Motion-Like" trajectories as well as diffusive motion (displacement proportional to the square-root of time) of the heavy particle, but did not exhibit a concrete instance. Here we introduce a one-spa

Patrick Godau, Akriti Srivastava, Constantin Ulrich, Tim Adler

The field of medical imaging AI is currently undergoing rapid transformations, with methodical research increasingly translated into clinical practice. Despite these successes, research suffers from knowledge silos, hindering collaboration and progress: Existing knowledge is scattered across publications and many details remain unpublished, while privacy reg

Emma Landry, Damla Senturk, Shafali Jeste, Charlotte DiStefano

A common concern in the field of functional data analysis is the challenge of temporal misalignment, which is typically addressed using curve registration methods. Currently, most of these methods assume the data is governed by a single common shape or a finite mixture of population level shapes. We introduce more flexibility using mixed membership models. I

Sinem Coleri, Aysun Gurur Onalan, Marco di Renzo

Traditional wireless network design relies on optimization algorithms derived from domain-specific mathematical models, which are often inefficient and unsuitable for dynamic, real-time applications due to high complexity. Deep learning has emerged as a promising alternative to overcome complexity and adaptability concerns, but it faces challenges such as ac

Dake Zhou

I show that in addition to the well-known peak inside massive neutron stars, the sound speed in cold dense QCD matter likely exhibits another peak above neutron star densities before it asymptotes to $c_s=\sqrt{C_s}=\sqrt{1/3}$. Based on the framework reported in arxiv:2408.16738, this approach does not rely on any assumption about the ultra-dense matter not

Sai Qian Zhang, Ziyun Li, Chuan Guo, Saeed Mahloujifar

Inverting visual representations within deep neural networks (DNNs) presents a challenging and important problem in the field of security and privacy for deep learning. The main goal is to invert the features of an unidentified target image generated by a pre-trained DNN, aiming to reconstruct the original image. Feature inversion holds particular significan

Eddye Bustamante, José Jiménez Urrea, Jorge Mejía

In this work we establish a dispersive blow-up result for the initial value problem (IVP) for the coupled Schr\"odinger-fifth order Korteweg-de Vries system \begin{align*} \left. \begin{array}{rl} i u_t+\partial_x^2 u &\hspace{-2mm}=\alpha uv + \gamma |u|^2 u, \quad x\in\mathbb R,\quad t\in\mathbb R,\\ \partial_t v + \partial_x^5 v + \partial_x v^2&\hspace{-

Robert W. Rienstra, Nishat Sultana, En-Min Shih, Evan Stocker

Here we report on low temperature transport measurements of encapsulated bilayer graphene nano constrictions fabricated employing electrode-free AFM-based local anodic oxidation (LAO) nanolithography. This technique allows for the creation of constrictions as narrow as 20 nm much smaller than previous studies. In wider constrictions, we observe bulk transpor

Jean-Pierre Magnot

We attack the problem of getting a strict ranking (i.e. a ranking without equally ranked items) of $n$ items from a pairwise comparisons matrix. Basic structures are described, a first heuristical approach based on a condition, the $\mathcal{R}-$condition, is proposed. Analyzing the limits of this ranking procedure, we finish with a minimization problem whic

Javon Hickmon

In the rapidly advancing field of artificial intelligence, machine perception is becoming paramount to achieving increased performance. Image classification systems are becoming increasingly integral to various applications, ranging from medical diagnostics to image generation; however, these systems often exhibit harmful biases that can lead to unfair and d

Simranjeet Singh, Amit Kumar, Fayyaz Pocker Chemban, Vikrant Fernandes

Navigating unmanned aerial vehicles in environments where GPS signals are unavailable poses a compelling and intricate challenge. This challenge is further heightened when dealing with Nano Aerial Vehicles (NAVs) due to their compact size, payload restrictions, and computational capabilities. This paper proposes an approach for localization using off-board c

Andrés García-Medina

We study the allocation of synthetic portfolios under hierarchical nested, one-factor, and diagonal structures of the population covariance matrix in a high-dimensional scenario. The noise reduction approaches for the sample realizations are based on random matrices, free probability, deterministic equivalents, and their combination with a data science hiera

Kyle Stein, Andrew Arash Mahyari, Guillermo Francia, Eman El-Sheikh

Backdoor attacks pose a critical threat by embedding hidden triggers into inputs, causing models to misclassify them into target labels. While extensive research has focused on mitigating these attacks in object recognition models through weight fine-tuning, much less attention has been given to detecting backdoored samples directly. Given the vast datasets

Giovanni Barontini

We study the implementation of quantum engines and quantum heat pumps where the quantum adiabatic transformations are replaced by quantum Zeno strokes. During these strokes, frequent measurements are selectively performed on the external state of the system avoiding transition between different levels. This effectively delivers almost ideal isentropic transf

Md. Tariquzzaman, Audwit Nafi Anam, Naimul Haque, Mohsinul Kabir

Data augmentation involves generating synthetic samples that resemble those in a given dataset. In resource-limited fields where high-quality data is scarce, augmentation plays a crucial role in increasing the volume of training data. This paper introduces a Bangla Text Data Augmentation (BDA) Framework that uses both pre-trained models and rule-based method

Enrui Liu, Pan Tang, Tao Jiang, Jianhua Zhang

This study focuses on analysis and modeling of the penetration loss of typical building materials in the FR1 (450 MHz-6 GHz) and FR3 (7-24 GHz) bands based on experimental measurements. Firstly, we measure the penetration loss characteristics of four different typical building materials from 4 to 16 GHz, including wood, glass, foam and concrete, by using a p

Wei Yu Tang, Ning Dai, Tianshuo Zhou, David H. Mathews

The task of RNA design given a target structure aims to find a sequence that can fold into that structure. It is a computationally hard problem where some version(s) have been proven to be NP-hard. As a result, heuristic methods such as local search have been popular for this task, but by only exploring a fixed number of candidates. They can not keep up with

Giovanni Baccolo, Andrea Barresi, Davide Chiesa, Andrea Giachero

High Purity Germanium (HPGe) detectors are powerful detectors for gamma-ray spectroscopy. The sensitivity to low-intensity gamma-ray peaks is often hindered by the presence of Compton continuum distributions, originated by gamma-rays emitted at higher energies. This study explores novel, pulse shape-based, machine learning-assisted techniques to enhance Comp

Rishi Bhandia, Tim Priessnitz, Jiahao Liang, Ksenia S. Rabinovich

In this work, we combine conventional linear response time-domain THz spectroscopy with non-linear THz-pump THz-probe techniques to study metallic strained thin films of $\mathrm{Ca}_2\mathrm{RuO}_4$, which undergo a transition into a ferromagnetic state at 10 K. Such measurements allowing us to independently measure momentum and energy relaxation rates. We

A. Kumar, W. Tierens, T. Younkin, C. Johnson

This paper introduces STRIPE (Simulated Transport of RF Impurity Production and Emission), an advanced modeling framework designed to analyze material erosion and the global transport of eroded impurities originating from radio-frequency (RF) antenna structures in magnetic confinement fusion devices. STRIPE integrates multiple computational tools, each addre

Sergey Shuvaev, Khue Tran, Khristina Samoilova, Cyrille Mascart

The olfactory system employs responses of an ensemble of odorant receptors (ORs) to sense molecules and to generate olfactory percepts. Here we hypothesized that ORs can be viewed as 3D spatial filters that extract molecular features relevant to the olfactory system, similarly to the spatio-temporal filters found in other sensory modalities. To build these f

Mor Shpigel Nacson, Aviad Aberdam, Roy Ganz, Elad Ben Avraham

Vision-Language Models (VLMs) excel in diverse visual tasks but face challenges in document understanding, which requires fine-grained text processing. While typical visual tasks perform well with low-resolution inputs, reading-intensive applications demand high-resolution, resulting in significant computational overhead. Using OCR-extracted text in VLM prom

Christian Bank Lauridsen, Mads Greve Andersen, Max-Emil Smith Thorius, Fabricio Batista Narcizo

Speeding significantly contributes to traffic accidents, posing ongoing risks despite advancements in automotive safety technologies. This study investigates how auditory alerts influence speeding behavior across different demographic groups, focusing on drivers' age and experience levels. Using a mobile application to collect real-time driving data, we cond

Salah G. Elgendi

In this paper, we investigate the existence of parallel 1-forms on specific Finsler manifolds. We demonstrate that Landsberg manifolds admitting a parallel 1-form have a mean Berwald curvature of rank at most $n-2$. As a result, Landsberg surfaces with parallel 1-forms are necessarily Berwaldian. We further establish that the metrizability freedom of the geo

Udari Madhushani Sehwag, Kassiani Papasotiriou, Jared Vann, Sumitra Ganesh

Knowledge graphs (KGs) are crucial for representing and reasoning over structured information, supporting a wide range of applications such as information retrieval, question answering, and decision-making. However, their effectiveness is often hindered by incompleteness, limiting their potential for real-world impact. While knowledge graph completion (KGC)

Juan P. Meneses, Yasmeen George, Christoph Hagemeyer, Zhaolin Chen

Deep learning-based techniques have potential to optimize scan and post-processing times required for MRI-based fat quantification, but they are constrained by the lack of large training datasets. Generative models are a promising tool to perform data augmentation by synthesizing realistic datasets. However no previous methods have been specifically designed

Hanshang Jin, Eun Sang Choi, Hung-Cheng Wu, N. J. Curro

We report on neutron diffraction, magnetoresistance, magnetization, and magnetic torque measurements under high magnetic field in the helical antiferromagnet CeVGe$_3$. This compound exhibits Kondo lattice coherence and helical antiferromagnetic (AFM) ordering at ambient pressure, similar to the well-studied CeRhIn$_5$. Our measurements reveal that CeVGe$_3$

Atalay Mert Ileri, Nalen Rangarajan, Jack Cannell, Hande McGinty

Over the past two decades, the Web Ontology Language (OWL) has been instrumental in advancing the development of ontologies and knowledge graphs, providing a structured framework that enhances the semantic integration of data. However, the reliability of deductive reasoning within these systems remains challenging, as evidenced by inconsistencies among popul

Elisa Lorenzo García, Christophe Ritzenthaler, Fernando Rodríguez Villegas

Let $C$ be a genus $2$ curve with Jacobian isomorphic to the square of an elliptic curve with complex multiplication by a maximal order in an imaginary quadratic field of discriminant $-d<0$. We show that if the stable model of $C$ has bad reduction over a prime $p$ then $p \leq d/4$. We give an algorithm to compute the set of such $p$ using the so-called re

F. C. E. Lima

We consider a two-dimensional Lorentz-invariant field model with a $\phi^{4}$ potential modified by a term that introduces asymmetries at the manifold space. In this framework, the model recovers its original symmetry only when $p=0$. The asymmetry introduced in the potential suggests that, even when one of the minima diverges asymptotically, kink/antikink-l

Lingzhi Shen, Yunfei Long, Xiaohao Cai, Imran Razzak

Multimodal fake news detection often involves modelling heterogeneous data sources, such as vision and language. Existing detection methods typically rely on fusion effectiveness and cross-modal consistency to model the content, complicating understanding how each modality affects prediction accuracy. Additionally, these methods are primarily based on static

Jiarui Zhang, Ollie Liu, Tianyu Yu, Jinyi Hu

Multimodal large language models (MLLMs) have made rapid progress in recent years, yet continue to struggle with low-level visual perception (LLVP) -- particularly the ability to accurately describe the geometric details of an image. This capability is crucial for applications in areas such as robotics, medical image analysis, and manufacturing. In this pape

Xinyuan Lai, Guohong Li, Angela M. Coe, Jedediah H. Pixley

Stacking two atomic crystals with a twist between their crystal axes produces moir\'e potentials that modify the electronic properties. Here we show that double moir\'e potentials generated by superposing three atomic crystals create a new class of tunable quasiperiodic structures that alter the symmetry and spatial distribution of the electronic wavefunctio

Tao Li, Bich-Diep Nguyen, Yawei Gao, Daoguan Ning

The formation of iron oxide nanoparticles (NPs) presents challenges such as efficiency losses and fine dust emissions in practical iron combustion systems, highlighting the need for deeper understanding of the formation mechanisms and thermochemical conditions. This study combines experiments and multi-scale simulations to analyze NP clouds generated by sing

Laura Ares, Julien Pinske, Benjamin Hinrichs, Martin Kolb

We develop an extension of the Monte Carlo wave function approach that unambiguously identifies dynamical entanglement in general composite, open systems. Our algorithm performs tangential projections onto the set of separable states, leading to classically correlated quantum trajectories. By comparing this restricted evolution with the unrestricted one, we

Daniel Flores-Alfonso

The first black hole solutions of the SU(N) Bach-Yang-Mills equations are presented. Static generalizations breaking spherical symmetry are also constructed. These constitute the first examples in the literature of C-metrics sourced by a Yang-Mills field.

Maurizio Giannotti

The search for axions and axion-like particles (ALPs) remains a major endeavor in modern physics investigation. Axions play essential roles in the quest to understand dark matter, the strong CP problem, and various astrophysical phenomena. This paper provides a very brief overview of the current status of experimental efforts, highlighting significant advanc

Zoltan Bajnok, Bercel Boldis, Gregory P. Korchemsky

A broad class of observables in four-dimensional $\mathcal{N}=2$ and $\mathcal{N}=4$ superconformal Yang-Mills theories can be exactly computed for arbitrary 't Hooft coupling as Fredholm determinants of integrable Bessel operators. These observables admit a unifying description through a one-parameter generating function, which possesses a determinant repre

Miltiadis Kofinas, Samuele Papa, Efstratios Gavves

Neural fields (NeFs) have recently emerged as a state-of-the-art method for encoding spatio-temporal signals of various modalities. Despite the success of NeFs in reconstructing individual signals, their use as representations in downstream tasks, such as classification or segmentation, is hindered by the complexity of the parameter space and its underlying

Dominik Stemer, Stephan Thürmer, Florian Trinter, Uwe Hergenhahn

Amino acids and other small chiral molecules play key roles in biochemistry. However, in order to understand how these molecules behave in vivo, it is necessary to study them under aqueous-phase conditions. Photoelectron circular dichroism (PECD) has emerged as an extremely sensitive probe of chiral molecules, but its suitability for application to aqueous s

Valerio De Luca, Brandon Khek, Justin Khoury, Mark Trodden

Tidal Love numbers quantify the conservative static response of compact objects to external tidal fields, and are found to vanish exactly for asymptotically flat black holes in four-dimensional general relativity. Many aspects of the physics of black holes have an analogue in the theory of supersonic acoustic flows, including the existence of an event horizo

Howard Masur, Kasra Rafi, Anja Randecker

We determine the distribution of the number of saddle connections on a random translation surface of large genus. More specifically, for genus $g$ tending to infinity, the number of saddle connections with lengths in a given interval $[\frac{a}{g}, \frac{b}{g}]$ converges in distribution to a Poisson distributed random variable. Furthermore, the numbers of s

Spencer Griffith, John F. Beacom, Jung-Tsung Li, Annika H. G. Peter

Accurate modeling of how high-energy proton-proton collisions produce gamma rays through the decays of pions and other secondaries is needed to correctly interpret astrophysical observations with the Fermi-LAT telescope. In the existing literature on cosmic-ray collisions with gas, the focus is on the gamma-ray yield spectrum, $d N_\gamma/dE$. However, in so

Dominik Freinberger, Julian Lemmel, Radu Grosu, Sofiene Jerbi

Recent advances in reinforcement learning have demonstrated the potential of quantum learning models based on parametrized quantum circuits as an alternative to deep learning models. On the one hand, these findings have shown the ultimate exponential speed-ups in learning that full-blown quantum models can offer in certain -- artificially constructed -- envi

Julien Pinske, Laura Ares, Benjamin Hinrichs, Martin Kolb

Providing entanglement for the design of quantum technologies in the presence of noise constitutes today's main challenge in quantum information science. A framework is required that assesses the build-up of entanglement in realistic settings. In this work, we put forth a new class of nonlinear quantum master equations in Lindblad form that unambiguously ide

Silvan Fischbacher, Beatrice Moser, Tomasz Kacprzak, Joerg Herbel

Large-scale structure surveys measure the shapes and positions of millions of galaxies in order to constrain the cosmological model with high precision. The resulting large data volume poses a challenge for the analysis of the data, from the estimation of photometric redshifts to the calibration of shape measurements. We present GalSBI, a model for the galax

Scott Lawrence, Brian McPeak, Duff Neill

We present a method for obtaining a hierarchy of rigorous bounds on the time-evolution of a quantum mechanical system from an arbitrary initial state, systematically generalizing Mandelstam-Tamm-like relations. For any fixed level in the hierarchy, the bounds are tightest after short time-evolution and gradually loosen over time; we present evidence that for

Rosy Caliri, Jan Hadlik, Manuel Kunkel, Werner Porod

Composite Higgs models predict the existence of various bound states. Among these are spin-1 resonances. We investigate models containing $\text{SU(2)}_L\times \text{SU(2)}_R$ as part of the unbroken subgroup in the new strong sector. These models predict that there are two neutral and one charged spin-1 resonances mixing sizably with the SM vector bosons. A

Paul K. Faehrmann, Jens Eisert, Maria Kieferova, Richard Kueng

Simulating the dynamics of complex quantum systems is a central application of quantum devices. Here, we propose leveraging the power of measurements to simulate short-time quantum dynamics of physically prepared quantum states in classical post-processing using a truncated Taylor series approach. While limited to short simulation times, our hybrid quantum-c

Clara Piekarski, Nicolas Cherroret, Tangui Aladjidi, Quentin Glorieux

We present the experimental observation of spin and density modes in a binary mixture of superfluids of light. A miscible Bose-Bose mixture with repulsive interactions is obtained by propagating, in the paraxial limit, the two circular polarization components of a laser through a non-linear hot atomic vapor. Controlling the intensity and phase for both polar

Ignacio Ferreras, Marina Trevisan, Ofer Lahav, Reinaldo R. de Carvalho

Thanks to Integral Field Unit survey data it is possible to explore in detail the link between the formation of the stellar content in galaxies and the drivers of evolution. Traditionally, scaling relations have connected galaxy-wide parameters such as stellar mass (M$_s$), morphology or average velocity dispersion ($\sigma$) to the star formation histories

Silvan Fischbacher, Beatrice Moser, Tomasz Kacprzak, Luca Tortorelli

With the rise of simulation-based inference (SBI) methods, simulations need to be fast as well as realistic. $\texttt{UFig v1}$ is a public Python package that simulates astronomical images with exceptional speed, taking approximately the same time as source extraction. This makes it particularly well-suited for SBI methods where computational efficiency is

Darcy Barron, Rachel Bezanson, Laura Blecha, Laura Chomiuk

Letters of recommendation are a common tool used in graduate admissions. Most admissions systems require three letters for each applicant, burdening both letter writers and admissions committees with a heavy work load that may not be time well-spent. Most applicants do not have three research advisors who can comment meaningfully on research readiness, addin

Misha Yutushui, Ady Stern, David F. Mross

Multiple topologically distinct quantum Hall phases can occur at the same Landau level filling factor. It is a major challenge to distinguish between these phases as they only differ by the neutral modes, which do not affect the charge conductance in conventional geometries. We show that the neutral sector can be determined with coherent charge conductance i

Joris Koefler, Umut Oktem, Shruti Paranjape, Jaroslav Trnka

We investigate MHV tree-level gravity amplitudes as defined on the spinor-helicity variety. Unlike their gluon counterparts, the gravity amplitudes do not have logarithmic singularities and do not admit Amplituhedron-like construction. Importantly, they are not determined just by their singularities, but rather their numerators have interesting zeroes. We ma

Julia Gehrlein, Pedro A. N. Machado, João Paulo Pinheiro

We explore, for the first time, {\textit{neutral-current}} events at long-baseline experiments to constrain vector and axial-vector neutrino non-standard interactions (NSI) with quarks. We leverage the flavor dependence of NSIs to perform an oscillation analysis in the neutral-current channel. We first introduce a framework to parametrize the effect of NSI o

Francisco Duque

This set of notes guided a 2 hour lecture on "Extreme-Mass-Ratio Inspirals in Fundamental Fields for the New Horizons for Psi School and Workshop", hosted at Instituto Superior Tecnico, University of Lisbon, between 1 - 5 July 2024. It introduces how to model asymmetric mass-ratio binaries evolving while immersed in an environment constituted by an ultraligh

Chang Qin, Xiaoying Pang, Mario Pasquato, M. B. N. Kouwenhoven

We analyze the fractal dimension of open clusters using 3D spatial data from Gaia DR3 for 93 open clusters from Pang et al. (2024) and 127 open clusters from Hunt & Reffert (2024) within 500 pc. The box-counting method is adopted to calculate the fractal dimension of each cluster in three regions: the all-member region, $r \leq r_t$ (inside the tidal radius)