December 2024 arXiv papers — page 75

Harel Berger, Yuval Shavitt

Generative AI is an invaluable tool, however, in some parts of the world, this technology is censored due to political or societal issues. In this work, we monitor Generative AI censorship through the DNS protocol. We find China to be a leading country of Generative AI censorship. Interestingly, China does not censor all AI domain names. We also report censo

Dmitriy S. Shapiro, Yannik Weber, Tim Bode, Frank K. Wilhelm

The Dicke-Ising model, one of the few paradigmatic models of matter-light interaction, exhibits a superradiant quantum phase transition above a critical coupling strength. However, in natural optical systems, its experimental validation is hindered by a "no-go theorem''. Here, we propose a digital-analog quantum simulator for this model based on an ensemble

Caterina May, Theodoros Ladas, Davide Pigoli, Kalliopi Mylona

In this work we build optimal experimental designs for precise estimation of the functional coefficient of a function-on-function linear regression model where both the response and the factors are continuous functions of time. After obtaining the variance-covariance matrix of the estimator of the functional coefficient which minimizes the integrated sum of

Liyao Jiang, Negar Hassanpour, Mohammad Salameh, Mohammadreza Samadi

Recent research explores the potential of Diffusion Models (DMs) for consistent object editing, which aims to modify object position, size, and composition, etc., while preserving the consistency of objects and background without changing their texture and attributes. Current inference-time methods often rely on DDIM inversion, which inherently compromises e

Diego Blas, John Carlton, Christopher McCabe

Atom interferometers offer exceptional sensitivity to ultra-light dark matter (ULDM) by precisely measuring effects on atomic systems. Previous studies have demonstrated their capability to detect scalar and vector ULDM candidates, yet their potential for probing spin-2 ULDM remains unexplored. In this work, we address this gap by investigating the sensitivi

Daniel Glasscock, Neil Hindman, Dona Strauss

In any semigroup $S$ satisfying the Strong Folner Condition, there are three natural notions of density for a subset $A$ of $S$: Folner density $d(A)$, Banach density $d^*(A)$, and translation density $d_t(A)$. If $S$ is commutative or left cancellative, it is known that these three notions coincide. We shall show that these notions coincide for every semigr

Hang Liao, Zheyang Zheng, Ji Shu, Kevin J. Chen

Recently, a p-GaN gate double channel HEMT (DC-HEMT) with conductivity modulation has been reported. The conductivity modulation is realized by hole storage in the gate stack and observed under quasi-static measurements. In this work, pulsed measurement and transient simulations of the DC-HEMT are carried out to disclose the conductivity modulation at high f

Matt Menickelly

We consider the framework of methods for unconstrained minimization that are, in each iteration, restricted to a model that is only a valid approximation to the objective function on some affine subspace containing an incumbent point. These methods are of practical interest in computational settings where derivative information is either expensive or impossi

Chongyao Chen, Kirsten Wickelgren

We compute an analogue of Pascal's triangle enriched in bilinear forms over a finite field. This gives an arithmetically meaningful count of the ways to choose $j$ ring homomorphisms into an algebraic closure from an \'etale extension of degree $n$. We also compute a quadratic twist. These (twisted) enriched binomial coefficients are defined in joint work of

Shaina Raza, Drai Paulen-Patterson, Chen Ding

Fake news poses a significant threat to public opinion and social stability in modern society. This study presents a comparative evaluation of BERT-like encoder-only models and autoregressive decoder-only large language models (LLMs) for fake news detection. We introduce a dataset of news articles labeled with GPT-4 assistance (an AI-labeling method) and ver

R. Timmerman, M. Arias, A. Botteon

We used the LOFAR telescope to monitor SN 2023ixf, a core-collapse supernova in M101, between 8 and 368 days post-explosion. We report non-detections down to ~80 {\mu}Jy sensitivity at 144 MHz. Our non-detections are consistent with published radio observations at higher frequencies. At the time, we are not able to constrain the properties of low-frequency a

Xiaoqin Gao, Dilip Paneru, Francesco Di Colandrea, Yingwen Zhang

Optical vector modes (VMs), characterized by spatially varying polarization distributions, have become essential tools across microscopy, metrology, optical trapping, nanophotonics, and optical communications. The Hong-Ou-Mandel (HOM) effect, a fundamental two-photon interference phenomenon in quantum optics, offers significant potential to extend the applic

Weiqi Wang, Jin Xu

Motivated by the critical need for unmanned aerial vehicles (UAVs) to patrol grid systems in hazardous and dynamically changing environments, this study addresses a routing problem aimed at minimizing the time-average Age of Information (AoI) for edges in general graphs. We establish a lower bound for all feasible patrol policies and demonstrate that this bo

Nikos G. Evgenidis, Nikos A. Mitsiou, Sotiris A. Tegos, Panagiotis D. Diamantoulakis

In this paper, we propose a novel approach to minimize the inference delay in semantic segmentation using split learning (SL), tailored to the needs of real-time computer vision (CV) applications for resource-constrained devices. Semantic segmentation is essential for applications such as autonomous vehicles and smart city infrastructure, but faces significa

Aanal Jayesh Shah, Peter Kirton, Simone Felicetti, Hadiseh Alaeian

We explore the dissipative phase transition of the two-photon Dicke model, a topic that has garnered significant attention recently. Our analysis reveals that while single-photon loss does not stabilize the intrinsic instability in the model, the inclusion of two-photon loss restores stability, leading to the emergence of superradiant states which coexist wi

Kishor Nepal, Aashish Gautam, Chinonso Ugwumadu, David Drabold

We present new atomistic models of amorphous silicon (a-Si) and hydrogenated amorphous silicon (a-Si:H) surfaces. The a-Si model included 4096 atoms and was obtained using local orbital density functional theory. By analyzing a slab model (periodic in two dimensions with a slab about 44 \AA{} thick), we observed a strong correlation between surface structure

Giovanni Scala, Gianlorenzo Massaro, Germano Borreggine, Cosmo Lupo

We consider an imaging scheme, inspired by microscopy, in which both correlation imaging and first-order intensity imaging can be performed simultaneously, to investigate the effects of strong turbulence on the two different kinds of images. The comparison between direct and correlation imaging in the presence of strong turbulence unambiguously revealed an a

M. V. Dolgopolik

We present a so-called universal convergence theorem for inexact primal-dual penalty and augmented Lagrangian methods that can be applied to a large number of such methods and reduces their convergence analysis to verification of some simple conditions on sequences generated by these methods. If these conditions are verified, then both primal and dual conver

Chamani Shiranthika, Hadi Hadizadeh, Parvaneh Saeedi, Ivan V. Bajić

Federated Learning (FL) enables multiple clients to train a collaborative model without sharing their local data. Split Learning (SL) allows a model to be trained in a split manner across different locations. Split-Federated (SplitFed) learning is a more recent approach that combines the strengths of FL and SL. SplitFed minimizes the computational burden of

Kåre Fridell, Lukáš Gráf, Julia Harz, Chandan Hati

Lepton-number-violating interactions occur in the Standard Model Effective Field Theory (SMEFT) at odd dimensions starting from the dimension-5 Weinberg operator. Although the operators at dimension-7 and higher are more suppressed by the heavy new scale, they can be crucial when traditional seesaw mechanisms leading to tree-level dimension-5 contributions a

Aleksandar Mijatović, Isao Sauzedde, Andrew Wade

We study the second-order asymptotics around the superdiffusive strong law~\cite{MMW} of a multidimensional driftless diffusion with oblique reflection from the boundary in a generalised parabolic domain. In the unbounded direction we prove the limit is Gaussian with the usual diffusive scaling, while in the appropriately scaled cross-sectional slice we esta

Tonatiuh Tiscareño, Benito Rodríguez, Javier Chagoya

We apply the Kosambi-Cartan-Chern theory to perform an extensive examination of Jacobi stability of geodesics around rotating black hole solutions to dynamical Chern-Simons gravity, a theory that introduces modifications to General Relativity via a scalar field non-minimally coupled to curvature scalars. We present a comparative study between Jacobi and Liap

Daniele Bertacca, Raul Jimenez, Sabino Matarrese, Angelo Ricciardone

We propose a novel scenario in which scalar perturbations, that seed the large scale structure of the Universe, are generated without relying on a scalar field (the inflaton). In this framework, inflation is driven by a de Sitter space-time (dS), where tensor metric fluctuations (i.e., gravitational waves) naturally arise from quantum vacuum oscillations, an

Jeff A. Dror, Pearl Sandick, Barmak Shams Es Haghi, Fengwei Yang

Cosmologically stable, light particles that came into thermal contact with the Standard Model in the early universe may persist today as a form of hot dark matter. For relics with masses in the eV range, their role in structure formation depends critically on their mass. We trace the evolution of such hot relics and derive their density profiles around cold

Peter Hoff, Christopher Osburn

Analyses of spectral data often assume a linear mixing hypothesis, which states that the spectrum of a mixed substance is approximately the mixture of the individual spectra of its constituent parts. We evaluate this hypothesis in the context of dissolved organic matter (DOM) fluorescence spectroscopy for endmember abundance recovery from mixtures of three d

U. Burgaz, K. Maguire, G. Dimitriadis, M. Smith

In this study, we explore the characteristics of `low-mass' ($\log(M_{\star}/M_{\odot}) \leq 8$) and `intermediate-mass' ($8 \lt \log(M_{\star}/M_{\odot}) \leq 10$) host galaxies of Type Ia supernovae (SNe Ia) from the second data release (DR2) of the Zwicky Transient Facility survey and investigate their correlations with different sub-types of SNe Ia. We u

Hugo Lóio, Guillaume Cecile, Sarang Gopalakrishnan, Guglielmo Lami

We investigate ensembles of Matrix Product States (MPSs) generated by quantum circuit evolution followed by projection onto MPSs with a fixed bond dimension $\chi$. Specifically, we consider ensembles produced by: (i) random sequential unitary circuits, (ii) random brickwork unitary circuits, and (iii) circuits involving both unitaries and projective measure

Belle II Collaboration, I. Adachi, L. Aggarwal, H. Ahmed

We measure the branching fraction and $\it CP$-violating flavor-dependent rate asymmetry of $B^{0} \to \pi^{0} \pi^{0}$ decays reconstructed using the Belle II detector in an electron-positron collision sample containing $387 \times 10^{6}$ $B\overline{B}$ pairs. Using an optimized event selection, we find $126\pm 20$ signal decays in a fit to background-dis

Benjamin Michen, Tim Pokart, Jan Carl Budich

We construct a protocol to adiabatically prepare the ground state of a widely discussed number-conserving model Hamiltonian for ultracold atoms in optical lattices that supports Majorana edge states. In particular, we introduce a symmetry breaking mass term that amounts to threading a commensurate (artificial) magnetic flux through the plaquettes of the cons

Marco Melis, Fabrizio Corelli, Robin Croft, Paolo Pani

In the context of Einstein-Maxwell-scalar theory with a nonminimal coupling between the electromagnetic and scalar field, we study linear (non)radial perturbations and nonlinear radial dynamics of spherically symmetric black holes. In a certain region of the parameter space, this theory admits hairy black holes with a stable photon sphere. This has a counter

Florian Girelli, Jianhui Qiu, Céline Zwikel

Four-dimensional asymptotically flat spacetimes have been central to recent developments in infrared physics. Gravitational waves reaching the asymptotic boundary reveal an infinite-dimensional symmetry group known as the Bondi-Metzner-Sachs (BMS) group. The vacuum structure breaks this symmetry, giving rise to Goldstone modes that play a pivotal role in the

Henry Bloss, Brandon Kriesten, T. J. Hobbs

Deeply inelastic scattering (DIS) is an essential process for exploring the structure of visible matter and testing the standard model. At the same time, the theoretical interpretation of DIS measurements depends on QCD factorization theorems whose validity deteriorates at the lower values of $Q^2$ and $W^2$ typical of neutrino DIS in accelerator-based oscil

Nathan Lacroix, Alexandre Bourassa, Francisco J. H. Heras, Lei M. Zhang

Quantum error correction is essential for bridging the gap between the error rates of physical devices and the extremely low logical error rates required for quantum algorithms. Recent error-correction demonstrations on superconducting processors have focused primarily on the surface code, which offers a high error threshold but poses limitations for logical

Pasquale Marra, Angela Nigro

Topological zero modes in topological insulators or superconductors are exponentially localized at the phase transition between a topologically trivial and nontrivial phase. These modes are solutions of a Jackiw-Rebbi equation modified with an additional term which is quadratic in the momentum. Moreover, localized fermionic modes can also be induced by harmo

Andrzej J. Buras, Peter Stangl

Within $Z^\prime$ models, neutral meson mixing severely constrains beyond the Standard Model (SM) effects in flavour changing neutral current (FCNC) processes. However, in certain regions of the $Z^\prime$ parameter space, the contributions to meson mixing observables become negligibly small even for large $Z^\prime$ couplings. While this a priori allows for

Guilherme Guedes, Pablo Olgoso

Effective field theories (EFTs) provide an excellent framework for the search of heavy physics beyond the Standard Model, using the so-called bottom-up and top-down approaches. However, the vastness of possible UV scenarios makes the complete connection between the two approaches a difficult challenge at the loop-level. UV/IR dictionaries fill precisely this

Damian Rovara, Lukas Burgholzer, Robert Wille

As new advancements in the field of quantum computing lead to the development of increasingly complex programs, approaches to validate and debug these programs are becoming more important. To this end, methods employed in classical debugging, such as assertions for testing specific properties of a program's state, have been adapted for quantum programs. Howe

Matteo Dürrnagel, Hendrik Hohmann, Atanu Maity, Jannis Seufert

We analyze the phase transition between a symmetric metallic parent state and itinerant altermagnetic order. The underlying mechanism we reveal in our microscopic model of electrons on a Lieb lattice does not involve orbital ordering, but derives from sublattice interference.

Pasquale Marra

I consider the longstanding issue of the hermiticity of the Dirac equation in curved spacetime. Instead of imposing hermiticity by adding ad hoc terms, I renormalize the field by a scaling function, which is related to the determinant of the metric, and then regularize the renormalized field on a discrete lattice. I found that, for time-independent and diago

Eve Dones, Quentin Henry, Laura Bernard

This paper describes the different steps to include the adiabatic tidal effects to the gravitational waveform amplitude for quasi-circular non-spinning compact binaries up to the second-and-a-half post-Newtonian (PN) order. The amplitude, that relates the two gravitational wave polarizations, is decomposed onto the basis of spin-weighted spherical harmonics

Alessandro Trinca, Rosa Valiante, Raffaella Schneider, Ignas Juodžbalis

Early JWST observations are providing growing evidence for a ubiquitous population of accreting supermassive black holes (BHs) at high redshift, many of which appear overmassive compared to the empirically-derived local scaling relation between black hole mass and host galaxy stellar mass. In this study, we leverage predictions from the semi-analytical Cosmi

Cristian Baldenegro, Alba Soto-Ontoso, Gregory Soyez

We propose a new strategy to obtain a high-purity sample of gluon-initiated jets at the LHC. Our approach, inspired by the Lund jet plane picture, is to perform a dijet selection where the two jets are collinear to each other and their momentum fraction share is highly asymmetric, and to measure the primary Lund plane density of emissions of the subleading j

Takumi S. Tanaka, John D. Silverman, Kazuhiro Shimasaku, Junya Arita

``Little Red Dots'' (LRDs) are an abundant high-redshift population newly discovered by the James Webb Space Telescope (JWST) and considered to be an early growth phase of supermassive black holes (SMBHs). Using a method of pixel-by-pixel color selection and relaxing the compactness criteria, we identify four dual LRD candidates in the COSMOS-Web survey with

Pavlo Sukhachov, Hans Gløckner Giil, Bjørnulf Brekke, Jacob Linder

The symmetry requirements for realizing unconventional compensated magnets with spin-polarized bands such as altermagnets have recently been uncovered. The most recent addition to this family of magnets is parity-odd or $p$-wave magnets. We demonstrate that $p$-wave magnets are perfectly compatible with superconductivity due to the spin polarization of their

Aman Agarwal, Ulyana Dupletsa, Konstantin Leyde, Suvodip Mukherjee

Gravitational Wave (GW) sources are standard sirens that provide an independent way to map the cosmic expansion history by combining with an independent redshift measurement either from an electromagnetic counterpart for a bright siren or using different statistical techniques for dark sirens. In this analysis, we perform the first Blinded Mock Data Challeng

Javier M. Lizana

We present a model that extends the electroweak gauge symmetry of the Standard Model in a non-universal way to $SU(2)_{L}^{\prime}\times U(1)_X \times SU(2)_{L}^{q_3}\times SU(2)_R^{\ell_3}$. This symmetry is spontaneously broken to $SU(2)_L\times U(1)_Y$ near the TeV scale by a condensate of a new composite sector. Charging appropriately the fermionic degre

Basem Kamal El-Menoufi, Christian T. Preuss, Ludovic Scyboz, Peter Skands

We present a detailed technical derivation of matching conditions at next-to-next-to-leading order in the sectorised VINCIA parton shower, by considering leading-colour 2-, 3- and 4-jet rates in hadronic Z-boson decays. In particular, we introduce a full subtraction-based calculation of the matching coefficient required to obtain the NLO 3-jet rate. This is

Victor Maura, Ben A. Stefanek, Tevong You

A Tera-$Z$ factory, such as FCC-ee or CEPC, will have indirect sensitivity to heavy new physics up to the tens of TeV scale through higher-order loop contributions to precision measurements at the $Z$ pole. These indirect quantum effects may provide complementary, or even better, sensitivity to potential deviations from the Standard Model that are typically

Pouya Asadi, Austin Batz, Graham D. Kribs

Dark matter could be a baryonic composite of strongly-coupled constituents transforming under SU(2)$_L$. We classify the SU(2)$_L$ representations of baryons in a class of simple confining dark sectors and find that the lightest state can be a pure singlet or a singlet that mixes with other neutral components of SU(2)$_L$ representations, which strongly supp

T. Daniel Brennan, Lian-Tao Wang, Huangyu Xiao

Monopoles are generally expected in Grand Unified Theories (GUTs) where they can catalyze baryon decay at an unsuppressed rate by the Callan-Rubakov effect. For the first time, we show this catalysis effect can generate the observed baryon asymmetry at GeV scale temperatures. We study the minimal SU(5) GUT model and demonstrate that monopoles-fermion scatter

Micha Berkooz, Ronny Frumkin, Ohad Mamroud, Josef Seitz

The IR dynamics of SYK is that of the Schwarzian theory, the effective theory of broken reparametrization invariance. In the double scaling limit, SYK is completely solvable by chord diagrams, whose generating functional is a bilocal Liouville theory. At low temperatures a set of modes in this description becomes soft. We interpret them as reparametrization

Florian Nortier, Gabriele Rigo, Pablo Sesma

Probing new physics through precise measurements of Higgs boson couplings is a central objective of the particle collider program at the high-energy frontier. An anomaly in Higgs couplings induced solely by new fermions allows one to compute an upper bound on the mass scale of new bosons. This new bosonic scale is necessary to prevent Landau poles or vacuum

Eric Putney, David Shih, Sung Hak Lim, Matthew R. Buckley

The Boltzmann equation relates the equilibrium phase space distribution of stars in the Milky Way to the Galaxy's gravitational potential. However, observations of stellar populations are biased by extinction from foreground dust, which complicates measurements of the potential in the disk and towards the Galactic center. Using the kinematics of Red Clump an

Pouya Asadi, Samuel Homiller, Aria Radick, Tien-Tien Yu

In this work, we provide a comprehensive study of fermion-portal dark matter models in the freeze-in regime at a future muon collider. For different possible non-singlet fermion portals, we calculate the upper bound on the mediator's mass arising from the relic abundance calculation and discuss the reach of a future muon collider in probing their viable para

Yihao Meng, Hao Ouyang, Hanlin Wang, Qiuyu Wang

The production of 2D animation follows an industry-standard workflow, encompassing four essential stages: character design, keyframe animation, in-betweening, and coloring. Our research focuses on reducing the labor costs in the above process by harnessing the potential of increasingly powerful generative AI. Using video diffusion models as the foundation, A

Jiageng Mao, Siheng Zhao, Siqi Song, Tianheng Shi

Scalable learning of humanoid robots is crucial for their deployment in real-world applications. While traditional approaches primarily rely on reinforcement learning or teleoperation to achieve whole-body control, they are often limited by the diversity of simulated environments and the high costs of demonstration collection. In contrast, human videos are u

Jihan Yang, Shusheng Yang, Anjali W. Gupta, Rilyn Han

Humans possess the visual-spatial intelligence to remember spaces from sequential visual observations. However, can Multimodal Large Language Models (MLLMs) trained on million-scale video datasets also ``think in space'' from videos? We present a novel video-based visual-spatial intelligence benchmark (VSI-Bench) of over 5,000 question-answer pairs, and find

Zhihang Yuan, Yuzhang Shang, Hanling Zhang, Tongcheng Fang

Recent advances in autoregressive (AR) models with continuous tokens for image generation show promising results by eliminating the need for discrete tokenization. However, these models face efficiency challenges due to their sequential token generation nature and reliance on computationally intensive diffusion-based sampling. We present ECAR (Efficient Cont

Haoge Deng, Ting Pan, Haiwen Diao, Zhengxiong Luo

This paper presents a novel approach that enables autoregressive video generation with high efficiency. We propose to reformulate the video generation problem as a non-quantized autoregressive modeling of temporal frame-by-frame prediction and spatial set-by-set prediction. Unlike raster-scan prediction in prior autoregressive models or joint distribution mo

Sihui Ji, Yiyang Wang, Xi Chen, Xiaogang Xu

We present FashionComposer for compositional fashion image generation. Unlike previous methods, FashionComposer is highly flexible. It takes multi-modal input (i.e., text prompt, parametric human model, garment image, and face image) and supports personalizing the appearance, pose, and figure of the human and assigning multiple garments in one pass. To achie

Runtao Liu, Haoyu Wu, Zheng Ziqiang, Chen Wei

Recent progress in generative diffusion models has greatly advanced text-to-video generation. While text-to-video models trained on large-scale, diverse datasets can produce varied outputs, these generations often deviate from user preferences, highlighting the need for preference alignment on pre-trained models. Although Direct Preference Optimization (DPO)

Hanwen Jiang, Zexiang Xu, Desai Xie, Ziwen Chen

We propose scaling up 3D scene reconstruction by training with synthesized data. At the core of our work is MegaSynth, a procedurally generated 3D dataset comprising 700K scenes - over 50 times larger than the prior real dataset DL3DV - dramatically scaling the training data. To enable scalable data generation, our key idea is eliminating semantic informatio

Fei Yan, Sara Murciano, Pasquale Calabrese, Robert Konik

Symmetry-resolved entanglement, capturing the refined structure of quantum entanglement in systems with global symmetries, has attracted a lot of attention recently. In this manuscript, introducing the notion of symmetry-resolved generalized entropies, we aim to develop a computational framework suitable for the study of excited state symmetry-resolved entan

Shengbang Tong, David Fan, Jiachen Zhu, Yunyang Xiong

In this work, we propose Visual-Predictive Instruction Tuning (VPiT) - a simple and effective extension to visual instruction tuning that enables a pretrained LLM to quickly morph into an unified autoregressive model capable of generating both text and visual tokens. VPiT teaches an LLM to predict discrete text tokens and continuous visual tokens from any in

Tim O. Höhn, René A. Villela, Er Zu, Leonardo Bezzo

Precise state-dependent control of optical potentials is of great importance for various applications utilizing cold neutral atoms. In particular, tune-out wavelengths for the clock state pair in alkaline-earth(-like) atoms provide maximally state-selective trap conditions that hold promise for the realization of novel approaches in quantum computation and s

Lukas Allwicher, Darius A. Faroughy, Matheus Martines, Olcyr Sumensari

In this article, we examine the validity range of the Effective Field Theory (EFT) description of high-energy Drell-Yan processes at the LHC. To this purpose, we consider explicit mediators that contribute to these processes in the $s$- and $t$-channels, comparing their effects in Drell-Yan distributions with the ones obtained by matching onto the correspond

Manish Shetty, Naman Jain, Adwait Godbole, Sanjit A. Seshia

Despite extensive usage in high-performance, low-level systems programming applications, C is susceptible to vulnerabilities due to manual memory management and unsafe pointer operations. Rust, a modern systems programming language, offers a compelling alternative. Its unique ownership model and type system ensure memory safety without sacrificing performanc

Frank F. Xu, Yufan Song, Boxuan Li, Yuxuan Tang

We interact with computers on an everyday basis, be it in everyday life or work, and many aspects of work can be done entirely with access to a computer and the Internet. At the same time, thanks to improvements in large language models (LLMs), there has also been a rapid development in AI agents that interact with and affect change in their surrounding envi

Saad el Morabit, Ryan Bouabid, Vincenzo Cirigliano, Jordy de Vries

We investigate two-neutrino double beta decay ($2\nu\beta\beta$) in chiral effective field theory. We find contributions from weak magnetism and double-weak pion-exchange at next-to-leading-order in the chiral power counting. We discuss the impact of the chiral corrections on the electron spectra and find that they should be included in analyses of $2\nu\bet

Johan Samsing, Lorenz Zwick, Pankaj Saini, Daniel J. D'Orazio

Observations of strongly gravitationally lensed gravitational wave (GW) sources provide a unique opportunity for constraining their transverse motion, which otherwise is exceedingly hard for GW mergers in general. Strong lensing makes this possible when two or more images of the lensed GW source are observed, as each image essentially allows the observer to

Xi Wang, Robin Courant, Marc Christie, Vicky Kalogeiton

Recent advances in text-conditioned video diffusion have greatly improved video quality. However, these methods offer limited or sometimes no control to users on camera aspects, including dynamic camera motion, zoom, distorted lens and focus shifts. These motion and optical aspects are crucial for adding controllability and cinematic elements to generation f

Denis Bashkirov

We introduce two topological non-$\Sigma$ operad structures on planar line arrangements subject to a certain geometric order condition, ensuring a well-defined notion of particle ordering on a distinguished line. This is interpreted in terms of scattering diagrams in purely elastic (1+1)-dimensional theories. We discuss a possible approach to factorized scat

Everton M. C. Abreu, Jorge Ananias Neto, Ronaldo Thibes

This paper investigates the implications from area quantization in Loop Quantum Gravity, particularly focusing on the application of the Landauer principle -- a fundamental thermodynamic concept establishing a connection between information theory and thermodynamics. By leveraging the Landauer principle in conjunction with the Bekenstein-Hawking entropy law,

Debsubhra Chakraborty, Susobhan Chattopadhyay, Rick S. Gupta

We present the complete set of positivity bounds on the Higgs Effective Field Theory (HEFT) at next-to-leading order (NLO). We identify the 15 operators that can be constrained by positivity, as they contribute to $s^2$-growth in the amplitude for longitudinal gauge-Higgs scattering, that is to all possible 2-to-2 scattering processes involving longitudinal

M. Gabriel Santiago, Daniel Adamiak, Yossathorn Tawabutr

In this paper, we investigate the small-$x$ behavior of the flavor-singlet, leading-twist quark Transverse Momentum Dependent parton distribution functions (TMDs) using the Light-Cone Operator Treatment. This formalism allows us to express TMD operators at small $x$ in terms of polarized dipole amplitudes, enabling a systematic approach to their small-$x$ ev

Clément Colléaux, Jonathan Skipp, Jason Laurie, Sergey Nazarenko

We study one-dimensional optical wave turbulence described by the 1D Schr{\"o}dinger-Helmholtz model for nonlinear light propagation in spatially nonlocal nonlinear optical media such as nematic liquid crystals. By exploiting the specific structure of the nonlocal response, we derive a reduced wave kinetic equation under a semi-local approximation that permi

Edgar Alvarez-Galera, Daniel Laria, Ferran Mazzanti, Lluis Batet

The solubility of helium in liquid metals is a knowledge of fundamental importance in the design of the future nuclear fusion reactors, since the formation of helium bubbles inside the breeding blankets of the reactors can be a threat to the durability of the devices and, more importantly, to the efficiency of tritium recovery. In the present work we report

Leandro Fiorini Aurichi, Lucas Real

The Unfriendly Partition Problem asks whether it is possible to split the vertex set of an infinite graph $G$ into two parts so that every vertex has at least as many neighbors in the other part than on its own. Despite the uncountable counterexamples provided by Milner and Shelah in 1990, this question still has no solution for graphs on countably many vert

Ludovico Nista, Christoph D. K. Schumann, Fabian Fröde, Mohamed Gowely

The advancement of high-performance computing has enabled the generation of large direct numerical simulation (DNS) datasets of turbulent flows, driving the need for efficient compression/decompression techniques that reduce storage demands while maintaining fidelity. Traditional methods, such as the discrete wavelet transform (DWT), cannot achieve compressi

Zhengdi Shen, Qiran Wang

Accurate localization is critical for Internet of Things (IoT) applications. Using hop loss in DV-Hop-based algorithms is a promising approach. Nevertheless, challenges lie in overcoming the computational complexity caused by re-calculating the predicted hop-counts, and how to further optimize the modeling for better accuracy. In this paper, a novel hop loss

Yanpeng Sun, Jing Hao, Ke Zhu, Jiang-Jiang Liu

Training Large Multimodality Models (LMMs) relies on descriptive image caption that connects image and language. Existing methods for generating such captions often rely on distilling the captions from pretrained LMMs, constructing them from publicly available internet images, or even generating them through human annotation. However, these strategies can fa

Guido Bell, Philipp Böer, Thorsten Feldmann, Dennis Horstmann

We perform an all-order analysis of double-logarithmic corrections to the so-called soft-overlap contribution to heavy-to-light transition form factors at large hadronic recoil. Specifically, we study $B_c \to \eta_c$ transitions within a perturbative non-relativistic framework, treating both the bottom and charm quarks as heavy with the hierarchy $m_b \gg m

Shenhao Zhu, Lingteng Qiu, Xiaodong Gu, Zhengyi Zhao

Existing 2D methods utilize UNet-based diffusion models to generate multi-view physically-based rendering (PBR) maps but struggle with multi-view inconsistency, while some 3D methods directly generate UV maps, encountering generalization issues due to the limited 3D data. To address these problems, we propose a two-stage approach, including multi-view genera

Ioannis Georgakilas, Antonio Gianfrate, Dimitrios Trypogeorgos, Helgi Sigurðsson

Coupled many-body quantum systems exhibit rich emergent physics with diverse stationary and dynamical behaviors. By engineering platforms with tunable and distinct coupling mechanisms, new insights emerge into the collective behavior of coupled many body systems. Particles can be exchanged via evanescent or ballistic coupling: the former, based on proximity,

Atin Sakkeer Hussain

This paper presents the Advanced Reasoning and Transformation Engine for Multi-Step Insight Synthesis in Data Analytics (ARTEMIS-DA), a novel framework designed to augment Large Language Models (LLMs) for solving complex, multi-step data analytics tasks. ARTEMIS-DA integrates three core components: the Planner, which dissects complex user queries into struct

Jianyu Zhang, Li Zhang, Shijian Li

The visual understanding are often approached from 3 granular levels: image, patch and pixel. Visual Tokenization, trained by self-supervised reconstructive learning, compresses visual data by codebook in patch-level with marginal information loss, but the visual tokens does not have semantic meaning. Open Vocabulary semantic segmentation benefits from the e

Bernhard K Meister

Betting markets are gaining in popularity. Mean beliefs generally differ from prices in prediction markets. Logarithmic utility is employed to study the risk and return adjustments to prices. Some consequences are described. A modified payout structure is proposed. A simple asset price model based on flipping biased coins is investigated. It is shown using t

Thomas DeGrand

I show comparisons of the pseudoscalar meson vector form factor from simulations of QCD with $N_c = 3$, 4 and 5 colors and $N_f = 2$ flavors of degenerate mass fermions at a common (matched) fermion mass, lattice spacing, and simulation volume. The dependence of the form factor on the momentum transfer is nearly independent of the number of colors, and is co

Rajeev Verma, Volker Fischer, Eric Nalisnick

Modern challenges of robustness, fairness, and decision-making in machine learning have led to the formulation of multi-distribution learning (MDL) frameworks in which a predictor is optimized across multiple distributions. We study the calibration properties of MDL to better understand how the predictor performs uniformly across the multiple distributions.

Steven Feng, Shrimai Prabhumoye, Kezhi Kong, Dan Su

Pretraining large language models effectively requires strategic data selection, blending and ordering. However, key details about data mixtures especially their scalability to longer token horizons and larger model sizes remain underexplored due to limited disclosure by model developers. To address this, we formalize the concept of two-phase pretraining and

Tianyang Gu, Jingjin Wang, Zhihao Zhang, HaoHong Li

Scientific idea generation has been extensively studied in creativity theory and computational creativity research, providing valuable frameworks for understanding and implementing creative processes. However, recent work using Large Language Models (LLMs) for research idea generation often overlooks these theoretical foundations. We present a framework that

Darshan Deshpande, Selvan Sunitha Ravi, Sky CH-Wang, Bartosz Mielczarek

The LLM-as-judge paradigm is increasingly being adopted for automated evaluation of model outputs. While LLM judges have shown promise on constrained evaluation tasks, closed source LLMs display critical shortcomings when deployed in real world applications due to challenges of fine grained metrics and explainability, while task specific evaluation models la

Hanbin Hong, Shenao Yan, Shuya Feng, Yan Yan

Active Learning (AL) represents a crucial methodology within machine learning, emphasizing the identification and utilization of the most informative samples for efficient model training. However, a significant challenge of AL is its dependence on the limited labeled data samples and data distribution, resulting in limited performance. To address this limita

Elsa M. Teixeira, Gaspard Poulot, Carsten van de Bruck, Eleonora Di Valentino

We investigate a cosmological model inspired by hybrid inflation, where two scalar fields representing dark energy (DE) and dark matter (DM) interact through a coupling that is proportional to the DE scalar field $1/\phi$. The strength of the coupling is governed solely by the initial condition of the scalar field, $\phi_i$, which parametrises deviations fro

M. G. Guenza

The dynamics of polymer melts at the crossover between unentagled and entangled regimes is formalized here through an extension of the Cooperative Dynamics Generalized Langevin Equation (CDGLE) (\textit{J. Chem. Phys.} 110,7574 (1999)), by including the constraint to the dynamics due to entanglements through an effective inter-monomer potential that confines

Noble Saji Mathews, Meiyappan Nagappan

There is an increasing amount of research and commercial tools for automated test case generation using Large Language Models (LLMs). This paper critically examines whether recent LLM-based test generation tools, such as Codium CoverAgent and CoverUp, can effectively find bugs or unintentionally validate faulty code. Considering bugs are only exposed by fail

Sriraam Natarajan, Saurabh Mathur, Sahil Sidheekh, Wolfgang Stammer

Human-in-the-loop (HIL) systems have emerged as a promising approach for combining the strengths of data-driven machine learning models with the contextual understanding of human experts. However, a deeper look into several of these systems reveals that calling them HIL would be a misnomer, as they are quite the opposite, namely AI-in-the-loop ($AI^2L$) syst

Massimo Casarsa, Sergo Jindariani, Luciano Ristori

We propose to explore the potential advantages of a new class of tracking algorithms loosely inspired by the Hough transform concept and where we include the time of arrival of each hit as an additional coordinate to be treated in the same way as a spatial coordinate. A remarkable property of this algorithm is that the execution time is proportional to the t

Zhiyuan Zeng, Qinyuan Cheng, Zhangyue Yin, Bo Wang

OpenAI o1 represents a significant milestone in Artificial Inteiligence, which achieves expert-level performances on many challanging tasks that require strong reasoning ability.OpenAI has claimed that the main techinique behinds o1 is the reinforcement learining. Recent works use alternative approaches like knowledge distillation to imitate o1's reasoning s

Airton Deppman

The emerging field of the Science of Cities has unveiled previously undiscovered facets of urban life. Contrary to the expectation of chaotic behaviour influenced solely by cultural and geographic factors, cities globally exhibit universal power-law trends in urban scaling. Leveraging recent advances in mathematical descriptions of urban dynamics, this study