December 2024 arXiv papers — page 139

Joshua Y. L. Jones

Using the framework of real scalar field theory on causal sets, the intimate relation of the Sorkin-Johnston vacuum to entropic purity is elucidated. It is shown that taking a set of sensible principles, and the most natural assumption on the space of fields, leaves the Sorkin-Johnston state as the only candidate for the global vacuum of a quasifree theory.

Adam Burrows, Tianshu Wang, David Vartanyan

On the basis of a large collection of detailed 3D core-collapse supernova simulations carried to late times, we identify four channels of stellar mass black hole formation. Our examples for Channel 1 involve the formation of lower-gap and above black holes in energetic asymmetric supernova explosions. Our Channel 2 example involves a modest supernova explosi

Yue Liu, Sara Murciano, David F. Mross, Jason Alicea

Measurements can qualitatively alter correlations and entanglement emerging in gapless quantum matter. We show how a single round of measurements on gapless quantum systems can, upon rotating the measurement basis, induce non-trivial transitions separating regimes displaying universal characteristics governed by distinct boundary conformal field theories. We

Vivian Yun Yan Tan, Adam Muzzin, Ghassan T. E. Sarrouh, Jacqueline Antwi-Danso

We present a resolved study of 877 progenitors of Milky Way Analogs (MWAs) at $0.3<z<5$ selected with abundance matching in the ten fields of the Canadian NIRISS Unbiased Cluster Survey (CANUCS). Utilizing 18-21 bands of deep NIRCam, NIRISS, and HST photometry, we create resolved stellar mass maps and star formation rate maps via spectral energy distribution

Pietro Benetti Genolini, Jerome P. Gauntlett, Yusheng Jiao, Alice Lüscher

We consider supersymmetric solutions of $D=4$, $\mathcal{N}=2$ Euclidean gauged supergravity coupled to an arbitrary number of vector multiplets. Such solutions admit an R-symmetry Killing vector, $\xi$, constructed as a bilinear in the Killing spinor. The Killing spinor bilinears can also be used to construct polyforms that are equivariantly closed under th

Grant N. Remmen, Nicholas L. Rodd

We establish the bounds on Wilson coefficients of the Higgs effective field theory (HEFT) mandated by unitarity and analyticity. These positivity constraints can be projected into the space of the standard model effective field theory (SMEFT) as HEFT$\,\supset\,$SMEFT. Doing so reveals a subspace allowed by the HEFT but forbidden by SMEFT positivity, thereby

Alexander Pondaven, Aliaksandr Siarohin, Sergey Tulyakov, Philip Torr

We propose DiTFlow, a method for transferring the motion of a reference video to a newly synthesized one, designed specifically for Diffusion Transformers (DiT). We first process the reference video with a pre-trained DiT to analyze cross-frame attention maps and extract a patch-wise motion signal called the Attention Motion Flow (AMF). We guide the latent d

Zhen Liu, Tim Z. Xiao, Weiyang Liu, Yoshua Bengio

While one commonly trains large diffusion models by collecting datasets on target downstream tasks, it is often desired to align and finetune pretrained diffusion models with some reward functions that are either designed by experts or learned from small-scale datasets. Existing post-training methods for reward finetuning of diffusion models typically suffer

Xi Chen, Zhifei Zhang, He Zhang, Yuqian Zhou

We introduce UniReal, a unified framework designed to address various image generation and editing tasks. Existing solutions often vary by tasks, yet share fundamental principles: preserving consistency between inputs and outputs while capturing visual variations. Inspired by recent video generation models that effectively balance consistency and variation a

Chenhao Lu, Xuxin Cheng, Jialong Li, Shiqi Yang

Humanoid robots require both robust lower-body locomotion and precise upper-body manipulation. While recent Reinforcement Learning (RL) approaches provide whole-body loco-manipulation policies, they lack precise manipulation with high DoF arms. In this paper, we propose decoupling upper-body control from locomotion, using inverse kinematics (IK) and motion r

Tianwei Yin, Qiang Zhang, Richard Zhang, William T. Freeman

Current video diffusion models achieve impressive generation quality but struggle in interactive applications due to bidirectional attention dependencies. The generation of a single frame requires the model to process the entire sequence, including the future. We address this limitation by adapting a pretrained bidirectional diffusion transformer to an autor

Kartik Narayan, Nithin Gopalakrishnan Nair, Jennifer Xu, Rama Chellappa

Pre-training on large-scale datasets and utilizing margin-based loss functions have been highly successful in training models for high-resolution face recognition. However, these models struggle with low-resolution face datasets, in which the faces lack the facial attributes necessary for distinguishing different faces. Full fine-tuning on low-resolution dat

Matthew Wallingford, Anand Bhattad, Aditya Kusupati, Vivek Ramanujan

Three-dimensional (3D) understanding of objects and scenes play a key role in humans' ability to interact with the world and has been an active area of research in computer vision, graphics, and robotics. Large scale synthetic and object-centric 3D datasets have shown to be effective in training models that have 3D understanding of objects. However, applying

Sahal Shaji Mullappilly, Mohammed Irfan Kurpath, Sara Pieri, Saeed Yahya Alseiari

We introduce BiMediX2, a bilingual (Arabic-English) Bio-Medical EXpert Large Multimodal Model that supports text-based and image-based medical interactions. It enables multi-turn conversation in Arabic and English and supports diverse medical imaging modalities, including radiology, CT, and histology. To train BiMediX2, we curate BiMed-V, an extensive Arabic

Hanxue Zhang, Zetong Yang, Yanan Sun, Li Chen

This paper introduces Test-time Correction (TTC), an online 3D detection system designed to rectify test-time errors using various auxiliary feedback, aiming to enhance the safety of deployed autonomous driving systems. Unlike conventional offline 3D detectors that remain fixed during inference, TTC enables immediate online error correction without retrainin

Shuailei Ma, Kecheng Zheng, Ying Wei, Wei Wu

Although text-to-image (T2I) models have recently thrived as visual generative priors, their reliance on high-quality text-image pairs makes scaling up expensive. We argue that grasping the cross-modality alignment is not a necessity for a sound visual generative prior, whose focus should be on texture modeling. Such a philosophy inspires us to study image-t

Xiaoyu Xiang, Liat Sless Gorelik, Yuchen Fan, Omri Armstrong

We present Make-A-Texture, a new framework that efficiently synthesizes high-resolution texture maps from textual prompts for given 3D geometries. Our approach progressively generates textures that are consistent across multiple viewpoints with a depth-aware inpainting diffusion model, in an optimized sequence of viewpoints determined by an automatic view se

S. Bocquet, S. Grandis, E. Krause, C. To

Cosmic shear, galaxy clustering, and the abundance of massive halos each probe the large-scale structure of the Universe in complementary ways. We present cosmological constraints from the joint analysis of the three probes, building on the latest analyses of the lensing-informed abundance of clusters identified by the South Pole Telescope (SPT) and of the a

Matthew Sivaprakasam, Samuel Triest, Cherie Ho, Shubhra Aich

Autonomous robot navigation in off-road environments presents a number of challenges due to its lack of structure, making it difficult to handcraft robust heuristics for diverse scenarios. While learned methods using hand labels or self-supervised data improve generalizability, they often require a tremendous amount of data and can be vulnerable to domain sh

Yingkang Cao, Suying Liu, Haowei Deng, Zihan Xia

Achieving noise resilience is an outstanding challenge in Hamiltonian-based quantum computation. To this end, energy-gap protection provides a promising approach, where the desired quantum dynamics are encoded into the ground space of a penalty Hamiltonian that suppresses unwanted noise processes. However, existing approaches either explicitly require high-w

Alan Nawzad Amin, Nate Gruver, Yilun Kuang, Lily Li

To build effective therapeutics, biologists iteratively mutate antibody sequences to improve binding and stability. Proposed mutations can be informed by previous measurements or by learning from large antibody databases to predict only typical antibodies. Unfortunately, the space of typical antibodies is enormous to search, and experiments often fail to fin

Zhiyuan Zhou, Andy Peng, Qiyang Li, Sergey Levine

The modern paradigm in machine learning involves pre-training on diverse data, followed by task-specific fine-tuning. In reinforcement learning (RL), this translates to learning via offline RL on a diverse historical dataset, followed by rapid online RL fine-tuning using interaction data. Most RL fine-tuning methods require continued training on offline data

Jingxi Chen, Brandon Y. Feng, Haoming Cai, Tianfu Wang

Video Frame Interpolation aims to recover realistic missing frames between observed frames, generating a high-frame-rate video from a low-frame-rate video. However, without additional guidance, the large motion between frames makes this problem ill-posed. Event-based Video Frame Interpolation (EVFI) addresses this challenge by using sparse, high-temporal-res

Wufei Ma, Haoyu Chen, Guofeng Zhang, Yu-Cheng Chou

3D spatial reasoning is the ability to analyze and interpret the positions, orientations, and spatial relationships of objects within the 3D space. This allows models to develop a comprehensive understanding of the 3D scene, enabling their applicability to a broader range of areas, such as autonomous navigation, robotics, and AR/VR. While large multi-modal m

Jianhong Bai, Menghan Xia, Xintao Wang, Ziyang Yuan

Recent advancements in video diffusion models have shown exceptional abilities in simulating real-world dynamics and maintaining 3D consistency. This progress inspires us to investigate the potential of these models to ensure dynamic consistency across various viewpoints, a highly desirable feature for applications such as virtual filming. Unlike existing me

Xiao Fu, Xian Liu, Xintao Wang, Sida Peng

This paper aims to manipulate multi-entity 3D motions in video generation. Previous methods on controllable video generation primarily leverage 2D control signals to manipulate object motions and have achieved remarkable synthesis results. However, 2D control signals are inherently limited in expressing the 3D nature of object motions. To overcome this probl

Christoph Gärtlein, Violetta Sagun, Oleksii Ivanytskyi, David Blaschke

We study rotating hybrid stars, with a particular emphasis on the effect of a deconfinement phase transition on their properties at high spin. Our analysis is based on a hybrid equation of state (EoS) with a phase transition from hypernuclear matter to color-superconducting quark matter, where both phases are described within a relativistic density functiona

Edwin Beggs, Shahn Majid

We obtain generally covariant operator-valued geodesic equations on a pseudo-Riemannian manifold $M$ as part of the construction of quantum geodesics on the algebra $D(M)$ of differential operators. Geodesic motion arises here as an associativity condition for a certain form of first order differential calculus on this algebra in the presence of curvature. T

V. Morénas, A. Le Yaouanc, L. Oliver

We study the transitions ${\Lambda_b \to \Lambda_c\left({1 \over 2}^\pm \right)}$ in the Bakamjian-Thomas (BT) relativistic quark model formalism, which describes hadrons with a fixed number of constituents. In the heavy quark limit, the BT model yields covariant form factors and Isgur-Wise (IW) scaling, regardless of the spectroscopic model used to describe

Arijit Ray, Jiafei Duan, Ellis Brown, Reuben Tan

Reasoning about motion and space is a fundamental cognitive capability that is required by multiple real-world applications. While many studies highlight that large multimodal language models (MLMs) struggle to reason about space, they only focus on static spatial relationships, and not dynamic awareness of motion and space, i.e., reasoning about the effect

Fan Zhang, Shulin Tian, Ziqi Huang, Yu Qiao

Recent advancements in visual generative models have enabled high-quality image and video generation, opening diverse applications. However, evaluating these models often demands sampling hundreds or thousands of images or videos, making the process computationally expensive, especially for diffusion-based models with inherently slow sampling. Moreover, exis

Fatemeh Nazarieh, Zhenhua Feng, Diptesh Kanojia, Muhammad Awais

Audio-driven talking face generation is a challenging task in digital communication. Despite significant progress in the area, most existing methods concentrate on audio-lip synchronization, often overlooking aspects such as visual quality, customization, and generalization that are crucial to producing realistic talking faces. To address these limitations,

K. A. L. Lima, D. A. da Silva, G. D. Amvame Nze, F. L. Lopes de Mendonça

Two-dimensional (2D) carbon materials have been intensively investigated because of their distinctive structural framework and electronic behaviors as alternatives in energy conversion and storage applications. This study proposes a novel 2D carbon allotrope, Polymerized Pyracyclene Graphyne (PolyPyGY), characterized by a multi-ringed structure with 4-, 5-,

Korbinian Pöppel, Maximilian Beck, Sepp Hochreiter

While Transformers and other sequence-parallelizable neural network architectures seem like the current state of the art in sequence modeling, they specifically lack state-tracking capabilities. These are important for time-series tasks and logical reasoning. Traditional RNNs like LSTMs and GRUs, as well as modern variants like sLSTM do have these capabiliti

Yuval Atzmon, Rinon Gal, Yoad Tewel, Yoni Kasten

Text-to-video diffusion models have shown remarkable progress in generating coherent video clips from textual descriptions. However, the interplay between motion, structure, and identity representations in these models remains under-explored. Here, we investigate how self-attention query (Q) features simultaneously govern motion, structure, and identity and

Soumi Haldar, Lorenzo A. Mariano, Alessandro Lunghi, Laura Gagliardi

Single-molecule magnets (SMMs) are promising candidates for molecular-scale data storage and processing due to their strong magnetic anisotropy and long spin relaxation times. However, as temperature rises, interactions between electronic states and lattice vibrations accelerate spin relaxation, significantly limiting their practical applications. Recently,

R. A. Calixto, T. H. Freitas, V. H. Jorge Pérez

The main focus of this paper is to show that the gluing of formal schemes is also a formal scheme. The algebraic approach established here also leads us to conclude when the gluing of $k$-formal schemes is a $k$-formal scheme. In addition, we derive that the gluing of formal schemes is always singular, regardless of whether we know the structure of the schem

Khandker Sadia Rahman, Charalampos Chelmis

In recent years, there has been growing interest in leveraging machine learning for homeless service assignment. However, the categorical nature of administrative data recorded for homeless individuals hinders the development of accurate machine learning methods for this task. This work asserts that deriving latent representations of such features, while at

Ziqi Lu, Heng Yang, Danfei Xu, Boyi Li

Emerging 3D geometric foundation models, such as DUSt3R, offer a promising approach for in-the-wild 3D vision tasks. However, due to the high-dimensional nature of the problem space and scarcity of high-quality 3D data, these pre-trained models still struggle to generalize to many challenging circumstances, such as limited view overlap or low lighting. To ad

Marina A. Ferreira, Aleksis Vuoksenmaa

We construct a time-dependent solution to the Smoluchowski coagulation equation with a constant flux of dust particles entering through the boundary at zero. The dust is instantaneously converted into particles and flux solutions have linearly increasing mass. The construction is made for a general class of non-gelling coagulation kernels for which stationar

Zixuan Ye, Huijuan Huang, Xintao Wang, Pengfei Wan

Style control has been popular in video generation models. Existing methods often generate videos far from the given style, cause content leakage, and struggle to transfer one video to the desired style. Our first observation is that the style extraction stage matters, whereas existing methods emphasize global style but ignore local textures. In order to bri

Zijian Chen, John-Michael Gamble, Micaela Jantzi, John P. Hirdes

Manual assignment of Anatomical Therapeutic Chemical (ATC) codes to prescription records is a significant bottleneck in healthcare research and operations at Ontario Health and InterRAI Canada, requiring extensive expert time and effort. To automate this process while maintaining data privacy, we develop a practical approach using locally deployable large la

Fatima Ebrahimi, Alexander Haywood

Global stability of differentially rotating plasma is investigated using a generalized effective potential. We first, for a current-free system, obtain a general form of an effective potential in terms of the free energies of global curvature and gradients of rotation for non-axisymmetric disturbances. We then examine the stability of differentially rotating

Wanwen Chen, Adam Schmidt, Eitan Prisman, Septimiu E. Salcudean

Purpose: Intraoperative ultrasound (US) can enhance real-time visualization in transoral robotic surgery. The surgeon creates a mental map with a pre-operative scan. Then, a surgical assistant performs freehand US scanning during the surgery while the surgeon operates at the remote surgical console. Communicating the target scanning plane in the surgeon's me

Vincent Rossetto

We show that reaction-diffusion processes in three dimensions can be efficiently handled by event-driven numerical simulations, based on statistical waiting times (Gillespie's Monte-Carlo method). The algorithm is efficient for dilute systems, since diffusion is not simulated, only the result of diffusion between events needs to be implemented.

Jack Saunders, Charlie Hewitt, Yanan Jian, Marek Kowalski

Gaussian Splatting has changed the game for real-time photo-realistic rendering. One of the most popular applications of Gaussian Splatting is to create animatable avatars, known as Gaussian Avatars. Recent works have pushed the boundaries of quality and rendering efficiency but suffer from two main limitations. Either they require expensive multi-camera rig

M. Carretero-Castrillo, M. Ribó, J. M. Paredes, P. Benaglia

A relevant fraction of massive stars are runaways, moving with a significant peculiar velocity with respect to their environment. Kicks from supernova explosions or the dynamical ejection of stars from clusters can account for the runaway genesis. We have used Gaia DR3 data to study the velocity distribution of massive O and Be stars from the GOSC and BeSS c

Juan Miguel Lopez Alcaraz, Wilhelm Haverkamp, Nils Strodthoff

Background: Neoplasms are a major cause of mortality globally, where early diagnosis is essential for improving outcomes. Current diagnostic methods are often invasive, expensive, and inaccessible in resource-limited settings. This study explores the potential of electrocardiogram (ECG) data, a widely available and non-invasive tool for diagnosing neoplasms

Khush Mendiratta, Shweta Singh, Pratik Chattopadhyay

Early detection of brain tumors through magnetic resonance imaging (MRI) is essential for timely treatment, yet access to diagnostic facilities remains limited in remote areas. Gliomas, the most common primary brain tumors, arise from the carcinogenesis of glial cells in the brain and spinal cord, with glioblastoma patients having a median survival time of l

Barry Loneck, Igor Zurbenko, Edward Valachovic

This investigation establishes the theoretical and practical limits of signal strength estimate precision for Kolmogorov-Zurbenko periodograms with dynamic smoothing and compares them to those of standard log-periodograms with static smoothing. Previous research has established the sensitivity, accuracy, resolution, and robustness of Kolmogorov-Zurbenko peri

Alex A. Chapple, Alexander McDonald, Manuel H. Muñoz-Arias, Alexandre Blais

Multi-photon processes deteriorate the quantum non-demolition (QND) character of the dispersive readout in circuit QED, causing readout to lag behind single and two-qubit gates, in both speed and fidelity. Alternative methods such as the longitudinal readout have been proposed, however, it is unknown to what extent multi-photon processes hinder this approach

Debsoumya Chakraborti, Micha Christoph, Zach Hunter, Richard Montgomery

In 1975, Stein made a wide generalisation of the Ryser-Brualdi-Stein conjecture on transversals in Latin squares, conjecturing that every equi-$n$-square (an $n\times n$ array filled with $n$ symbols where each symbol appears exactly $n$ times) has a transversal of size $n-1$. That is, it should have a collection of $n-1$ entries that share no row, column, o

Filipe Conceição, Marco Gomes, Vitor Silva, Rui Dinis

This paper proposes the use of an access point (AP) selection scheme to improve the total uplink (UL) spectral efficiency (SE) of a radio stripe (RS) network. This scheme optimizes the allocation matrix between the total number of APs' antennas and users' equipment (UEs) while considering two state-of-the-art and two newly proposed equalization approaches: c

Nils-Christian Kempke, Daniel Rehfeldt, Thorsten Koch

In practice, non-specialized interior point algorithms often cannot utilize the massively parallel compute resources offered by modern many- and multi-core compute platforms. However, efficient distributed solution techniques are required, especially for large-scale linear programs. This article describes a new decomposition technique for systems of linear e

Zongyu Lin, Wei Liu, Chen Chen, Jiasen Lu

The field of video generation has made remarkable advancements, yet there remains a pressing need for a clear, systematic recipe that can guide the development of robust and scalable models. In this work, we present a comprehensive study that systematically explores the interplay of model architectures, training recipes, and data curation strategies, culmina

Mahmoud Abo Khamis, Ahmet Kara, Dan Olteanu, Dan Suciu

We study the classical evaluation problem for regular path queries: Given an edge-labeled graph and a regular path query, compute the set of pairs of vertices that are connected by paths that match the query. The Product Graph (PG) is the established evaluation approach for regular path queries. PG first constructs the product automaton of the data graph and

Malhar Vaishampayan, Stephan Wojtowytsch

For several classes of neural PDE solvers (Deep Ritz, PINNs, DeepONets), the ability to approximate the solution or solution operator to a partial differential equation (PDE) hinges on the abilitiy of a neural network to approximate the solution in the spatial variables. We analyze the capacity of neural networks to approximate solutions to an elliptic PDE a

Qianyue Hao, Fengli Xu, Yong Li, James Evans

Development in Artificial Intelligence (AI) has accelerated scientific discovery. Alongside recent AI-oriented Nobel prizes, these trends establish the role of AI tools in science. This advancement raises questions about the potential influences of AI tools on scientists and science as a whole, and highlights a potential conflict between individual and colle

Howard Ho, Adnan Machado, Pierre Sullivan

This study investigates the reattachment of flow on a stalled NACA 0025 airfoil with an array of circular synthetic jet actuators. Experimental flow visualizations are used to assess the spanwise control authority of the array and the three-dimensionality of the flow. Numerical simulations provide insights into the flow structures created by the actuation, a

Joseph Samper Finberg

We develop a comprehensive Hamiltonian formulation for plasma dynamics that unifies collisionless gyrokinetic and collisional processes. Our framework rigorously describes the evolution of free energy and entropy during the transition from Maxwellian to non-Maxwellian distributions, explicitly coupling microscopic turbulent processes with macroscopic measure

Inkit Padhi, Manish Nagireddy, Giandomenico Cornacchia, Subhajit Chaudhury

We introduce the Granite Guardian models, a suite of safeguards designed to provide risk detection for prompts and responses, enabling safe and responsible use in combination with any large language model (LLM). These models offer comprehensive coverage across multiple risk dimensions, including social bias, profanity, violence, sexual content, unethical beh

Ilhan Aslan

Innovations in interaction design are increasingly driven by progress in machine learning fields. Automatic speech emotion recognition (SER) is such an example field on the rise, creating well performing models, which typically take as input a speech audio sample and provide as output digital labels or values describing the human emotion(s) embedded in the s

Zhouxia Wang, Yushi Lan, Shangchen Zhou, Chen Change Loy

This study aims to achieve more precise and versatile object control in image-to-video (I2V) generation. Current methods typically represent the spatial movement of target objects with 2D trajectories, which often fail to capture user intention and frequently produce unnatural results. To enhance control, we present ObjCtrl-2.5D, a training-free object contr

Jinyi Hu, Shengding Hu, Yuxuan Song, Yufei Huang

Autoregressive and diffusion models have achieved remarkable progress in language models and visual generation, respectively. We present ACDiT, a novel Autoregressive blockwise Conditional Diffusion Transformer, that innovatively combines autoregressive and diffusion paradigms for continuous visual information. By introducing a block-wise autoregressive unit

Aimê Gomes da Mata Kanzaki, Tiago de Sousa Araújo Cassiano, João Valeriano, Fabio Luis de Oliveira Paula

The standard DLVO theory offers a limited description of ionic-surfacted magnetic colloids in near aggregation regimes. Correcting the electrical double layer term for ionic surfactants is not enough to successfully simulate the systems. The correction of the van der Waals energy divergence at short interparticle distances is fundamental for proper Monte Car

Edward P. Chandler, Shirin Shoushtari, Brendt Wohlberg, Ulugbek S. Kamilov

Total variation (TV) is a widely used function for regularizing imaging inverse problems that is particularly appropriate for images whose underlying structure is piecewise constant. TV regularized optimization problems are typically solved using proximal methods, but the way in which they are applied is constrained by the absence of a closed-form expression

Marston Copeland, Thomas Mehen

We use chiral perturbation theory to study the long distance regime of transverse momentum dependent parton distribution functions (TMD PDFs). Chiral corrections to the TMD PDFs are computed from proton to pion/baryon splittings. For consistent power counting, we find that the fraction of the proton's momentum that a pion may carry must be kept small. We mak

Shai Keidar

We prove that for any prime $p$ and height $n \ge 1$, the telescopic Picard group $\mathrm{Pic}(\mathrm{Sp}_{Tn})$ contains a subgroup of the form $\mathbb{Z}_p \times \mathbb{Z}/a_p(p^n-1)$, where $a_p = 1$ if $p = 2$ and $a_p = 2$ if $p$ is odd. Using Kummer theory, we obtain an $(\mathbb{F}_{p^n}^\times \rtimes \mathbb{Z}/n)$-Galois extension of $\mathbb{

Andreas Gross, Leo Herr, David Holmes, Pim Spelier

We define a Grothendieck ring of varieties for log schemes. It is generated by one additional class ``$P$'' over the usual Grothendieck ring. We show the na\"ive definition of log Hodge numbers does not make sense for all log schemes. We offer an alternative that does.

Yigong Luan, Attilio Zilli, Agostino Di Francescantonio, Vincent Vinel

Optical metasurfaces are rapidly establishing as key-enabling platforms for nanophotonics applications. Along with the ability of taming light in subwavelength thicknesses, they can feature multiple functionalities in one device. The generation and control of light polarization by metasurfaces already provided a route towards ultracompact polarimetry devices

Puja Maharjan

Citation recommendation systems have attracted much academic interest, resulting in many studies and implementations. These systems help authors automatically generate proper citations by suggesting relevant references based on the text they have written. However, the methods used in citation recommendation differ across various studies and implementations.

Anna Zink, Hongzhou Luan, Irene Y. Chen

Disparities in access to healthcare have been well-documented in the United States, but their effects on electronic health record (EHR) data reliability and resulting clinical models are poorly understood. Using an All of Us dataset of 134,513 participants, we investigate the effects of access to care on the medical machine learning pipeline, including medic

Yu-Feng Li, Zhao Xin

The energy spectrum of geo-neutrinos plays a vital role in the experimental measurement of geo-neutrinos that have profound implications for both particle physics and earth sciences. In this letter, we present a state-of-the-art calculation of the energy spectrum of geo-neutrinos originating from the beta decay of Uranium-238 and Thorium-232. Our calculation

Kevin Hu, Kavita Ramanan

We study the long-time behavior of the $\kappa$-Markov local-field equation ($\kappa$-MLFE), which is a conditional McKean-Vlasov equation associated with interacting diffusions on the $\kappa$-regular tree. Under suitable assumptions on the coefficients, we prove well-posedness of the $\kappa$-MLFE. We also establish an H-theorem by identifying an energy fu

Jacopo Fumagalli, Jaume Garriga, Cristiano Germani, Ravi K. Sheth

In a Universe with nearly-Gaussian initial curvature perturbations, the abundance of primordial black holes can be derived from the curvature power spectrum. When the latter is enhanced within a narrow range around a characteristic scale, the resulting mass function has a single distinct peak, corresponding to Schwarzschild radii set by the horizon entry tim

António Girão, Zach Hunter

It is easy to see that every $q$-edge-colouring of the complete graph on $2^q+1$ vertices must contain a monochromatic odd cycle. A natural question raised by Erd\H{o}s and Graham in $1973$ asks for the smallest $L(q)$ such that every $q$-edge-colouring of $K_{2^q+1}$ must contain a monochromatic odd cycle of length at most $L(q)$. In here, we show that $L(q

D Cahoy, J Sedransk

We present and apply methodology to improve inference for small area parameters by using data from several sources. This work extends Cahoy and Sedransk (2023) who showed how to integrate summary statistics from several sources. Our methodology uses hierarchical global-local prior distributions to make inferences for the proportion of individuals in Florida'

Giovanni Battista Carollo, Massimiliano Semeraro, Giuseppe Gonnella, Marco Zamparo

We study the large fluctuations of the work injected by the random force into a Brownian particle under the action of a confining harmonic potential. In particular, we compute analytically the rate function for generic uncorrelated initial conditions, showing that, depending on the initial spread, it can exhibit no, one, or two singularities associated to th

Massimiliano Semeraro, Antonio Suma, Giuseppe Negro

In addition to providing general constraints on probability distributions, fluctuation theorems allow to infer essential information on the role played by temperature in heat exchange phenomena. In this numerical study, we measure the temperature of an out of equilibrium active bath using a fluctuation theorem that relates the fluctuations of the heat exchan

Miloš S. Kurilić

A topological space ${\mathcal X}$ is reversible iff each continuous bijection (condensation) $f: {\mathcal X} \rightarrow {\mathcal X}$ is a homeomorphism; weakly reversible iff whenever ${\mathcal Y}$ is a space and there are condensations $f:{\mathcal X} \rightarrow {\mathcal Y}$ and $g:{\mathcal Y} \rightarrow {\mathcal X}$, there is a homeomorphism $h:{

Yicheng Wang, Zhikang Zhang, Jue Wang, David Fan

In various video-language learning tasks, the challenge of achieving cross-modality alignment with multi-grained data persists. We propose a method to tackle this challenge from two crucial perspectives: data and modeling. Given the absence of a multi-grained video-text pretraining dataset, we introduce a Granularity EXpansion (GEX) method with Integration a

Magali Folch-Gabayet, Ricardo A. Sáenz

For a proper function $f$ on the plane, we study the operator \[ Tf(x,y) = \lim_{\varepsilon\to 0} \int_\varepsilon^1 f(x-t,y-t^k) \frac{e^{2\pi i \gamma(t)}}{\psi(t)} dt, \] where $k\ge1$ and $\psi$ and $\gamma$ are functions defined near the origin such that $\psi(t)\to 0$ and $|\gamma(t)|\to\infty$ as $t\to 0$. We give sufficient regularity and growth con

M. Kunert-Bajraszewska, A. Krauze, A. E. Kimball, L. Stawarz

We present multi-frequency and high-resolution studies of a sample of 24 radio transients sources discovered by comparing the NRAO VLA Sky Survey (NVSS) and Very Large Array Sky Survey (VLASS) surveys. All of them are characterized by a significant increase in radio flux density over the last two decades.Their convex spectra, small sizes and high brightness

D. R. Heath-Brown

For a prime $\ell$, let $h_\ell(K)$ denote the $\ell$-part of the class number of the number field $K$. We investigate upper bounds for $h_\ell(K)$ when $K$ is quadratic or cubic, particularly in the case in which the discriminant of $K$ is smooth. This is achieved using properties of Dirichlet $L$-functions.

Àngel Jorba, Begoña Nicolás, Óscar Rodríguez

The Hilda group is a set of asteroids whose mean motion is in a 3:2 orbital resonance with Jupiter. In this paper we use the planar Circular Restricted Three-Body Problem (CRTBP) as a dynamical model and we show that there exists a family of stable periodic orbits that are surrounded by islands of quasi-periodic motions. We have computed the frequencies of t

Tamar Bar-On, Nikolay Nikolov

We prove that every small profinite group can be decomposed into a direct product of indecomposable profinite groups, and that such a decomposition is unique up to order and isomorphisms of the components. We also investigate the cancellation property of some free pro-$\mathcal{C}$ groups, and give a new criterion for a profinite group to be small.

Md Nadim, Mohammad Hassan, Ashis Kumar Mandal, Chanchal K. Roy

Software defect prediction is a critical aspect of software quality assurance, as it enables early identification and mitigation of defects, thereby reducing the cost and impact of software failures. Over the past few years, quantum computing has risen as an exciting technology capable of transforming multiple domains; Quantum Machine Learning (QML) is one o

M. Siwak, Á. Kóspál, P. Ábrahám, G. Marton

Context. We analyse multi-colour photometric and spectroscopic observations of a Young Stellar Object Gaia20bdk. Aims. We aim to investigate the exact nature of the eruptive phenomenon that the star has been experiencing since 2018. Methods. We use public-domain archival photometry to characterise the quiescent phase in order to establish major physical para

Alex Trevithick, Roni Paiss, Philipp Henzler, Dor Verbin

Novel-view synthesis techniques achieve impressive results for static scenes but struggle when faced with the inconsistencies inherent to casual capture settings: varying illumination, scene motion, and other unintended effects that are difficult to model explicitly. We present an approach for leveraging generative video models to simulate the inconsistencie

Juan Marchant González

Various phenomenological consequences of seesaw theories for the generation of the fermion mass hierarchy of the Standard Model have been analyzed, with an emphasis on models in which the light-active neutrino masses are derived from low-scale seesaw mechanisms. In particular, fermion masses and lepton flavor-violating decay processes, the flavor-changing ne

Joe Davighi

We consider extending the Standard Model by an anomaly-free and possibly flavour non-universal $U(1)_X$ gauge symmetry, whose breaking gives a $Z^\prime$ boson that does not affect electroweak precision observables at tree-level or via 1-loop renormalisation group (RG) running. Provided it does not also couple to electrons, such a $Z^\prime$ boson would be l

Katy Klauenberg, Peter Harris, Philipp Möhrke, Francesca Pennecchi

Measurement uncertainty is key to assessing, stating and improving the reliability of measurements. An understanding of measurement uncertainty is the basis for confidence in measurements and is required by many communities; among others in national metrology institutes, accreditation bodies, calibration and testing laboratories, as well as in legal metrolog

Igor Morawski, Kai He, Shusil Dangi, Winston H. Hsu

Low-light conditions have an adverse impact on machine cognition, limiting the performance of computer vision systems in real life. Since low-light data is limited and difficult to annotate, we focus on image processing to enhance low-light images and improve the performance of any downstream task model, instead of fine-tuning each of the models which can be

Samuel Audet-Beaumont

We construct surfaces with arbitrarily large multiplicity for their first non-zero Steklov eigenvalue. The proof is based on a technique by M. Burger and B. Colbois originally used to prove a similar result for the Laplacian spectrum. We start by constructing surfaces $S_p$ with a specific subgroup of isometry $G_p:= \mathbb{Z}_p \rtimes \mathbb{Z}_p^*$ for

H. L. Ruh, M. Zechmeister, A. Reiners, E. Nagel

Radial velocity (RV) jitter represents an intrinsic limitation on the precision of Doppler searches for exoplanets that can originate from both instrumental and astrophysical sources. We aim to determine the RV jitter floor in M dwarfs and investigate the stellar properties that lead to RV jitter induced by stellar activity. We determined the RV jitter in 23

Jimin An, Changseob Song, Eni Halilaj, Inseung Kang

Accurate estimation of a user's biological joint moment from wearable sensor data is vital for improving exoskeleton control during real-world locomotor tasks. However, most state-of-the-art methods rely on deep learning techniques that necessitate extensive in-lab data collection, posing challenges in acquiring sufficient data to develop robust models. To a

Qiangang "Brandon'' Fu, Liviu I. Nicolaescu

On the flat torus $\mathbb{T}^m=\mathbb{R}^m/\mathbb{Z}^m$ with angular coordinates $\vec{\theta}$ we consider the random function $F_R=\mathfrak{a}\big(\, R^{-1} \sqrt{\Delta}\,\big) W$, where $R>0$, $\Delta$ is the Laplacian on this flat torus, $\mathfrak{a}$ is an even Schwartz function on $\mathbb{R}$ such that $\mathfrak{a}(0)>0$ and $W$ is the Gaussian

Zhijian Huang, Chengjian Feng, Feng Yan, Baihui Xiao

Large Multimodal Models (LMMs) have demonstrated exceptional comprehension and interpretation capabilities in Autonomous Driving (AD) by incorporating large language models. Despite the advancements, current data-driven AD approaches tend to concentrate on a single dataset and specific tasks, neglecting their overall capabilities and ability to generalize. T

Gian-Luca Haiden

Quantum Key Distribution (QKD) is a promising technique for ensuring long-term security in communication systems. Unlike conventional key exchange methods like RSA, which quantum computers could theoretically break [1], QKD offers enhanced security based on quantum mechanics [2]. Despite its maturity and commercial availability, QKD devices often have undisc

Saurab Chhachhi, Fei Teng

Given the vital role that smart meter data could play in handling uncertainty in energy markets, data markets have been proposed as a means to enable increased data access. However, most extant literature considers energy markets and data markets separately, which ignores the interdependence between them. In addition, existing data market frameworks rely on