March 2025 arXiv papers — page 99

Suprovo Ghosh, Samanwaya Mukherjee, Sukanta Bose, Debarati Chatterjee

During the inspiral of a binary neutron star, viscous processes in the neutron star matter can damp out the tidal energy induced by its companion and convert it to thermal energy. This tidal dissipation/heating process introduces a net phase shift in the gravitational wave signal. In our recent work, we showed based on a Newtonian estimate that tidal dissipa

Dany Atallah, Yonadav Barry Ginat, Newlin C. Weatherford

Gaia observations have revealed over a million stellar binary candidates within ~1 kpc of the Sun, predominantly characterized by orbital separations >10^3 AU and eccentricities >0.7. The prevalence of such wide, eccentric binaries has proven challenging to explain through canonical binary formation channels. However, recent advances in our understanding of

Sara Sarto, Marcella Cornia, Rita Cucchiara

The evaluation of machine-generated image captions is a complex and evolving challenge. With the advent of Multimodal Large Language Models (MLLMs), image captioning has become a core task, increasing the need for robust and reliable evaluation metrics. This survey provides a comprehensive overview of advancements in image captioning evaluation, analyzing th

Yazeed Alnumay, Alexandre Barbet, Anna Bialas, William Darling

Building high-quality large language models (LLMs) for enterprise Arabic applications remains challenging due to the limited availability of digitized Arabic data. In this work, we present a data synthesis and refinement strategy to help address this problem, namely, by leveraging synthetic data generation and human-in-the-loop annotation to expand our Arabi

Mahmoud Abdelshafy, Muhammad Sedik

We study Yang-Lee zeros in the thermodynamic limit of the 2D nearest-neighbor antiferromagnetic Ising model on square and triangular lattices. We employ the Numerical Linked Cluster Expansion (NLCE) equipped with Exact Enumeration (EE) of the partition function to estimate the Laplacian of the free energy, which is proportional to the zeros density. Using a

Han Xiao, Xiaoyan Hu, Kai-Kit Wong, Hanjiang Hong

This letter proposes a fluid reconfigurable intelligent surface (FRIS) paradigm, extending the conventional reconfigurable intelligent surface (RIS) technology to incorporate position reconfigurability of the elements. In our model, a `fluid' element is realized by a dense matrix of subelements over a given space and dynamically selecting specific elements f

Andrea Stampiggi

Despite the simplicity of one-particle dynamics, explicit expressions for the one-dimensional propagator on a circle suitable to numerical evaluation are surprisingly lacking -- not only in the presence of potentials but even in the free case. Using a lattice regularization of the circle, we derive finite expressions for the free discrete propagator through

Muhammad Ali Raza, Sehar, M. Azam, M. Zubair

Similar to particle accelerators, black holes also have the ability to accelerate particles, generating significant amounts of energy through particle collisions. In this study, we examine the horizon and spacetime structures of a rotating black hole within the framework of Einstein-Maxwell-Dilaton gravity. Additionally, we extend the analysis to explore par

Haoyang Gao, Leigh S. Martin, Lillian B. Hughes, Nathaniel T. Leitao

Electronic spins of nitrogen vacancy (NV) centers in diamond constitute a promising system for micro- and nano-scale magnetic sensing, due to their operation under ambient conditions, ease of placement in close proximity to sensing targets, and biological compatibility. At high densities, the electronic spins interact through dipolar coupling, which typicall

Vignesh Vaikundaraman, Joanna Drazkowska, Fabian Binkert, Til Birnstiel

The inner Solar System is depleted in refractory carbon in comparison to the interstellar medium and the depletion likely took place in the protoplanetary disk phase of the Solar System. We study the effect of photolysis of refractory carbon in the upper layers of the protosolar disk and its interplay with dust collisional growth and vertical mixing. We make

Mayusree Das, Armen Sedrakian, Banibrata Mukhopadhyay

We present a first two-dimensional general-relativistic analysis of superconducting regions in axially symmetric highly magnetized neutron star (magnetar) models with toroidal magnetic fields. We investigate the topology and distribution of type-II and type-I superconducting regions for varying toroidal magnetic field strengths and stellar masses by solving

Junmo Jeon, SungBin Lee

Quasicrystals exhibit superconductivity under the unique interplay of long-range order and strong inhomogeneity, distinguishing them from both crystalline and amorphous systems. Understanding how this structural complexity affects superconducting states and phase transitions remains an important open question. Here, we unveil anomalous superconductivity in a

Joris Kattemölle, Guido Burkard

Discrete translational symmetry plays a fundamental role in condensed matter physics and lattice gauge theories, enabling the analysis of systems that would otherwise be intractable. Despite this, many open problems remain. Quantum simulation promises to offer new insights, but progress is often limited by device connectivity constraints, which lead to prohi

Moein Mosleh, Mohammad Riahi-Zamin, Sandro Tacchella

We investigate the optimal approach for recovering the star formation histories (SFHs) and spatial distribution of stellar mass in high-redshift galaxies ($z\sim 2-5$), focusing on the impact of assumed SFH models on derived galaxy properties. Utilizing pixel-by-pixel spectral energy distribution (SED) fitting of multi-band photometry, we explore various par

Yumi Choi, Karoline M. Gilbert, Benjamin F. Williams, Daniel R. Weisz

We present the star formation histories (SFHs) of ten metal-poor (<12% Zsun), star-forming dwarf galaxies from the Local Ultraviolet to Infrared Treasury (LUVIT) survey. The derived SFHs exhibit significant variability, consistent with the irregular star formation expected for dwarf galaxies. Using synthetic near ultraviolet (UV) and optical CMDs with variou

Kazuaki Takasan, Naoto Tsuji

We study the nonlinear Hall effect in superconductors without magnetic fields induced by a quantum geometric phase (i.e., the Aharonov-Bohm phase) carried by single or pair particles. We find that the second-order nonlinear Hall conductivity diverges in the dc limit in a robust way against dissipation when the system is superconducting, suggesting that the s

Malte Busmann, Brendan O'Connor, Julian Sommer, Daniel Gruen

Fast X-ray Transients (FXTs) are a rare and poorly understood phenomenon with a variety of possible progenitors. The launch of the Einstein Probe (EP) mission has facilitated a rapid increase in the real-time discovery and follow-up of FXTs. We focus on the recent EP discovered transient EP241021a, which shows a peculiar panchromatic behavior. We obtained op

M. Fabbrichesi, R. Floreanini, E. Gabrielli, L. Marzola

Contextuality is a fundamental property of quantum mechanics. Contrary to entanglement, which can only exist in composite systems, contextuality is also present for single entities. The case of a three-level system is of particular interest because--in agreement with the Bell-Kochen-Specker theorem--it is the simplest in which quantum contextuality is necess

H. Lu, Pujian Mao

We revisit the Ricci-flat metrics in four dimensions that are stationary and algebraically special, together with the locally asymptotically flat conditions in the generalized Bondi-Sachs framework. We show that the Einstein equation is reduced to Laplacian equation on the celestial sphere. The solutions consist of two pairs of arbitrary holomorphic and anti

Weijie Wu, Emily J. Davis, Lillian B. Hughes, Bingtian Ye

Spin squeezed states provide a seminal example of how the structure of quantum mechanical correlations can be controlled to produce metrologically useful entanglement. Such squeezed states have been demonstrated in a wide variety of artificial quantum systems ranging from atoms in optical cavities to trapped ion crystals. By contrast, despite their numerous

Aurelio Amerio, Dmitry Malyshev, Bryan Zaldivar, Viviana Gammaldi

We present a search for dark matter (DM) annihilating subhalos of the Milky Way halo among the {\Fermi} Large Area Telescope (LAT) unassociated sources. For this purpose, we construct the first statistical model of the unassociated sources at latitudes above 10 degrees, combining potential DM subhalos with Galactic and extragalactic astrophysical components.

Jacob Gunn

The work presented in this thesis draws back the curtain on the physics of the primordial universe by leveraging Primordial Black Holes (PBHs) as cosmological probes. The violent deaths of ultralight PBHs are shown to severely inhibit leptogenesis, alter the sphaleron freeze-out temperature and provide an opportunity to rule out models of leptogenesis which

Akash Kumar Saha, Subhadip Bouri, Anirban Das, Abhishek Dubey

James Webb Space Telescope (JWST) has opened up a new chapter in infrared astronomy. Besides the discovery and a deeper understanding of various astrophysical sources, JWST can also uncover the non-gravitational nature of dark matter (DM). If DM is QCD axion or an eV-scale Axion-like particle (ALP), it can decay into two photons in the infrared band. This wi

Simone Albanesi, Rossella Gamba, Sebastiano Bernuzzi, Joan Fontbuté

We present the first unified model for the general relativistic dynamics and gravitational radiation of generic compact binaries. TEOBResumS-Dal\'i is a model based on the effective-one-body framework incorporating tidal interactions, generic spins, multipolar radiation reaction/waveform and numerical-relativity information. It allows the computation of grav

Adam A. Miller, Natasha S. Abrams, Greg Aldering, Shreya Anand

We present the La Silla Schmidt Southern Survey (LS4), a new wide-field, time-domain survey to be conducted with the 1 m ESO Schmidt telescope. The 268 megapixel LS4 camera mosaics 32 2k$\times$4k fully depleted CCDs, providing a $\sim$20 deg$^2$ field of view with $1''$ pixel$^{-1}$ resolution. The LS4 camera will have excellent performance at longer wavele

Shayan Majidy, Dominik Hangleiter, Michael J. Gullans

$k$-uniform states are valuable resources in quantum information, enabling tasks such as teleportation, error correction, and accelerated quantum simulations. The practical realization of $k$-uniform states, at scale, faces major obstacles: verifying $k$-uniformity is as difficult as measuring code distances, and devising fault-tolerant preparation protocols

Susung Hong, Ira Kemelmacher-Shlizerman, Brian Curless, Steven M. Seitz

We introduce MusicInfuser, an approach that aligns pre-trained text-to-video diffusion models to generate high-quality dance videos synchronized with specified music tracks. Rather than training a multimodal audio-video or audio-motion model from scratch, our method demonstrates how existing video diffusion models can be efficiently adapted to align with mus

Tao Yu, Yi-Fan Zhang, Chaoyou Fu, Junkang Wu

Large language models (LLMs) can handle a wide variety of general tasks with simple prompts, without the need for task-specific training. Multimodal Large Language Models (MLLMs), built upon LLMs, have demonstrated impressive potential in tackling complex tasks involving visual, auditory, and textual data. However, critical issues related to truthfulness, sa

Kangfu Mei, Hossein Talebi, Mojtaba Ardakani, Vishal M. Patel

Single-image super-resolution (SISR) remains challenging due to the inherent difficulty of recovering fine-grained details and preserving perceptual quality from low-resolution inputs. Existing methods often rely on limited image priors, leading to suboptimal results. We propose a novel approach that leverages the rich contextual information available in mul

Clemens Giuliani, Jannes Nys, Rocco Martinazzo, Giuseppe Carleo

Slater determinants have underpinned quantum chemistry for nearly a century, yet their full potential has remained challenging to exploit. In this work, we show that a variational wavefunction composed of a few hundred optimized non-orthogonal determinants can achieve energy accuracies comparable to the state of the art. This is obtained by introducing an op

Qiaowei Miao, Kehan Li, Jinsheng Quan, Zhiyuan Min

Generative artificial intelligence has recently progressed from static image and video synthesis to 3D content generation, culminating in the emergence of 4D generation-the task of synthesizing temporally coherent dynamic 3D assets guided by user input. As a burgeoning research frontier, 4D generation enables richer interactive and immersive experiences, wit

Gihan Jayatilaka, Abhinav Shrivastava, Matthew Gwilliam

We propose to bridge the gap between semi-supervised and unsupervised image recognition with a flexible method that performs well for both generalized category discovery (GCD) and image clustering. Despite the overlap in motivation between these tasks, the methods themselves are restricted to a single task -- GCD methods are reliant on the labeled portion of

Ayesha Ishaq, Jean Lahoud, Fahad Shahbaz Khan, Salman Khan

Large Multimodal Models (LMMs) have recently gained prominence in autonomous driving research, showcasing promising capabilities across various emerging benchmarks. LMMs specifically designed for this domain have demonstrated effective perception, planning, and prediction skills. However, many of these methods underutilize 3D spatial and temporal elements, r

Subhajit Goswami, Pierre-François Rodriguez, Yuriy Shulzhenko

We consider the the vacant set $\mathcal{V}^u$ of random interlacements on $\mathbb{Z}^d$ in dimensions $d \ge 3$. For varying intensity $u > 0$, the connectivity properties of $\mathcal V^u$ undergo a percolation phase transition across a critical parameter $u_* \in (0,\infty)$. In this article, we prove that this phase transition is sharp in the supercriti

Qiuyue Liang, Tom Melia

We define a relativistic version of the global symmetries responsible for the restricted mobility of fracton quasiparticles. The theories have a symmetry current that is proportional to a vector field that spontaneously breaks Lorentz boost symmetry. We argue that the existence of a pressureless dust in the early universe could be a consequence of this symme

Jiacheng Guo, Yue Wu, Jiahao Qiu, Kaixuan Huang

Verification is crucial for effective mathematical reasoning. We present a new temporal consistency method where verifiers iteratively refine their judgments based on the previous assessment. Unlike one-round verification or multi-model debate approaches, our method leverages consistency in a sequence of self-reflection actions to improve verification accura

Inkyu Shin, Chenglin Yang, Liang-Chieh Chen

Flow based generative models have charted an impressive path across multiple visual generation tasks by adhering to a simple principle: learning velocity representations of a linear interpolant. However, we observe that training velocity solely from the final layer output underutilizes the rich inter layer representations, potentially impeding model converge

Chuxin Wang, Wenfei Yang, Xiang Liu, Tianzhu Zhang

DETR-based methods, which use multi-layer transformer decoders to refine object queries iteratively, have shown promising performance in 3D indoor object detection. However, the scene point features in the transformer decoder remain fixed, leading to minimal contributions from later decoder layers, thereby limiting performance improvement. Recently, State Sp

NVIDIA, :, Hassan Abu Alhaija, Jose Alvarez

We introduce Cosmos-Transfer, a conditional world generation model that can generate world simulations based on multiple spatial control inputs of various modalities such as segmentation, depth, and edge. In the design, the spatial conditional scheme is adaptive and customizable. It allows weighting different conditional inputs differently at different spati

Aniket Sengupta, Arijit Chatterjee, G. J. Sreejith, T. S. Mahesh

Quantum shadow tomography based on the classical shadow representation provides an efficient way to estimate properties of an unknown quantum state without performing a full quantum state tomography. In scenarios where estimating the expectation values for only certain classes of observables is required, obtaining information about the entire density matrix

Bharath Sambasivam, Kyle Sherbert, Karunya Shirali, Nicholas J. Mayhall

Preparing Gibbs states, which describe systems in equilibrium at finite temperature, is of great importance, particularly at low temperatures. In this work, we propose a new method -- TEPID-ADAPT -- that prepares the thermal Gibbs state of a given Hamiltonian at low temperatures using a variational method that is partially adaptive and uses a purification wi

Jensen Zhou, Hang Gao, Vikram Voleti, Aaryaman Vasishta

We present Stable Virtual Camera (Seva), a generalist diffusion model that creates novel views of a scene, given any number of input views and target cameras. Existing works struggle to generate either large viewpoint changes or temporally smooth samples, while relying on specific task configurations. Our approach overcomes these limitations through simple m

Shraddha Surana, Ashwin Srinivasan, Michael Bain

Engineering information systems for scientific data analysis presents significant challenges: complex workflows requiring exploration of large solution spaces, close collaboration with domain specialists, and the need for maintainable, interpretable implementations. Traditional manual development is time-consuming, while &#34;No Code&#34; approaches using la

Minglei Shi, Ziyang Yuan, Haotian Yang, Xintao Wang

Diffusion models have demonstrated remarkable success in various image generation tasks, but their performance is often limited by the uniform processing of inputs across varying conditions and noise levels. To address this limitation, we propose a novel approach that leverages the inherent heterogeneity of the diffusion process. Our method, DiffMoE, introdu

Muzi Li, B. R. McNamara, Alison L. Coil, Marie-Joelle Gingras

We investigate the velocity structure of nebular gas in the central galaxies of four clusters: Abell 1835, PKS 0745-191, Abell 262, and RXJ0820.9+0752, using data from the Keck Cosmic Web Imager (KCWI). Velocity structure functions (VSFs) of the [OII] emission line are compared to VSFs of molecular clouds observed with the Atacama Large Millimeter/submillime

Yiqun Mei, Mingming He, Li Ma, Julien Philip

Video portrait relighting remains challenging because the results need to be both photorealistic and temporally stable. This typically requires a strong model design that can capture complex facial reflections as well as intensive training on a high-quality paired video dataset, such as dynamic one-light-at-a-time (OLAT). In this work, we introduce Lux Post

Fardin Saad, Pradeep K. Murukannaiah, Munindar P. Singh

Effective human-AI collaboration hinges not only on the AI agent's ability to follow explicit instructions but also on its capacity to navigate ambiguity, incompleteness, invalidity, and irrelevance in communication. Gricean conversational and inference norms facilitate collaboration by aligning unclear instructions with cooperative principles. We propose a

Haoyu Guo, He Zhu, Sida Peng, Haotong Lin

In this paper, we present a new method for multi-view geometric reconstruction. In recent years, large vision models have rapidly developed, performing excellently across various tasks and demonstrating remarkable generalization capabilities. Some works use large vision models for monocular depth estimation, which have been applied to facilitate multi-view r

Yulin Pan, Xiangteng He, Chaojie Mao, Zhen Han

Image generation has witnessed significant advancements in the past few years. However, evaluating the performance of image generation models remains a formidable challenge. In this paper, we propose ICE-Bench, a unified and comprehensive benchmark designed to rigorously assess image generation models. Its comprehensiveness could be summarized in the followi

Jacob Eisenstein, Reza Aghajani, Adam Fisch, Dheeru Dua

To be helpful assistants, AI agents must be aware of their own capabilities and limitations. This includes knowing when to answer from parametric knowledge versus using tools, when to trust tool outputs, and when to abstain or hedge. Such capabilities are hard to teach through supervised fine-tuning because they require constructing examples that reflect the

Jonathan H. Klos, Andreas Just, Evgeny V. Polyachenko, Peter Berczik

We consider tidal masses and ages of Milky Way open clusters, as well as a simple model of their distribution. Our aim is to investigate the space of model parameters and the correspondence between modelled and observed two-dimensional cluster age-mass distributions. The model for cluster evolution is comprised of a two-section cluster initial mass function,

Patrick L. Combettes

The proximal gradient method is a splitting algorithm for the minimization of the sum of two convex functions, one of which is smooth. It has applications in areas such as mechanics, inverse problems, machine learning, image reconstruction, variational inequalities, statistics, operations research, and optimal transportation. Its formalism encompasses a wide

Xinyu Fang, Zhijian Chen, Kai Lan, Lixin Ma

Creativity is a fundamental aspect of intelligence, involving the ability to generate novel and appropriate solutions across diverse contexts. While Large Language Models (LLMs) have been extensively evaluated for their creative capabilities, the assessment of Multimodal Large Language Models (MLLMs) in this domain remains largely unexplored. To address this

Ziwei Ji, Lei Yu, Yeskendir Koishekenov, Yejin Bang

LLMs often adopt an assertive language style also when making false claims. Such ``overconfident hallucinations'' mislead users and erode trust. Achieving the ability to express in language the actual degree of uncertainty around a claim is therefore of great importance. We find that ``verbal uncertainty'' is governed by a single linear feature in the repres

J. David Wong-Campos, Dalia P. Ornelas-Huerta, Mackenzie Dion

We demonstrate sequential two-photon fluorescence microscopy using forbidden state transitions. Nonlinear red excitation leads to green fluorescence in live cells expressing eYFP, maintaining optical sectioning and allowing deep tissue imaging with simple optical systems.

Qiying Yu, Zheng Zhang, Ruofei Zhu, Yufeng Yuan

Inference scaling empowers LLMs with unprecedented reasoning ability, with reinforcement learning as the core technique to elicit complex reasoning. However, key technical details of state-of-the-art reasoning LLMs are concealed (such as in OpenAI o1 blog and DeepSeek R1 technical report), thus the community still struggles to reproduce their RL training res

Umar Farooq, Jean-Yves Guillemaut, Adrian Hilton, Marco Volino

The field of Novel View Synthesis has been revolutionized by 3D Gaussian Splatting (3DGS), which enables high-quality scene reconstruction that can be rendered in real-time. 3DGS-based techniques typically suffer from high GPU memory and disk storage requirements which limits their practical application on consumer-grade devices. We propose Opti3DGS, a novel

Daniel Iľkovič, Jun Yan

In a recent paper, Chao and Yu used an entropy method to show that the Tur\'an density of a certain family $\mathcal{F}$ of $\lfloor r/2\rfloor$ triangle-like $r$-uniform hypergraphs is $r!/r^r$. Later, Liu determined for large $n$ the exact Tur\'an number $\text{ex}(n,\mathcal{F})$ of this family, and showed that the unique extremal graph is the balanced co

Jason Han, Nicholas S. DiBrita, Younghyun Cho, Hengrui Luo

Amplitude embedding (AE) is essential in quantum machine learning (QML) for encoding classical data onto quantum circuits. However, conventional AE methods suffer from deep, variable-length circuits that introduce high output error due to extensive gate usage and variable error rates across samples, resulting in noise-driven inconsistencies that degrade mode

Arian Vezvaee, Vinay Tripathi, Mario Morford-Oberst, Friederike Butt

Quantum error correction (QEC) codes are necessary to fault-tolerantly operate quantum computers. However, every such code is inherently limited by its inability to detect logical errors. Here, we propose and implement a method that leverages dynamical decoupling (DD) to drastically suppress logical errors. The key to achieving this is to use the logical ope

Ruiqi Wang, Jie Zhu, Hao Li, Bo-Qiang Ma

Recently, the KM3NeT Collaboration announced the detection of a 220 PeV neutrino from the celestial coordinates RA=94.3\degree~ and Dec=-7.8\degree~ on 13 February 2023 at 01:16:47 UTC \cite{KM3NeT:2025npi}. The source for this extra-ordinary cosmic neutrino, designated KM3-230213A, is not identified yet but there has been speculation that it might be associ

Gabriel P. Lynch, Lloyd Knox

Due to non-zero neutrino rest masses we expect the energy density today in non-relativistic matter, $\omega_{\rm m}$, to be greater than the sum of baryon and cold dark matter densities, $\omega_{\rm cb}$. We also expect the amplitude of deflections of CMB photons due to gravitational lensing to be suppressed relative to expectations assuming massless neutri

Felipe Azua, Leopoldo Bertossi

Different attribution scores have been proposed to quantify the relevance of database tuples for query answering in databases; e.g. Causal Responsibility, the Shapley Value, the Banzhaf Power-Index, and the Causal Effect. They have been analyzed in isolation. This work is a first investigation of score alignment depending on the query and the database; i.e.

Sara Beschi, Davide Falessi, Silvia Golia, Angela Locoro

With the advent of the data era, and of new, more intelligent interfaces for supporting decision making, there is a growing need to define, model and assess human ability and data visualizations usability for a better encoding and decoding of data patterns. Data Visualization Literacy (DVL) is the ability of encoding and decoding data into and from a visual

Dietmar Ferger

In this paper, we study the minimizers of U-processes and their domains of attraction. U-processes arise in various statistical contexts, particularly in M-estimation, where estimators are defined as minimizers of certain objective functions. Our main results establish necessary and sufficient conditions for the distributional convergence of these minimizers

Dawid Dopierala, Hugues Chaté, Xia-qing Shi, Alexandre Solon

We investigate non-reciprocal XY (NRXY) models defined on two-dimensional lattices in which the coupling strength of a spin with its neighbors varies with their position in the frame defined by the current spin orientation. As expected from the seminal work of Dadhichi et al., Phys. Rev. E 101, 052601 (2020), we first show that non-reciprocity is akin to a s

Alexandre Landry

We investigate in this paper the static radial coordinate-dependent spherically symmetric spacetime in teleparallel $F(T)$ gravity for a scalar field source. We begin by setting the static field equations (FEs) to be solved and solve the conservation laws for scalar field potential solutions. We simplify the FEs and then find a general formula for computing

Aleksandar Radic, Boyao Liu, Akshay Rao, Sam Lambrick

The thermal, mechanical, and electronic performance of atomically thin semiconductors is governed by their low-energy phonons, yet the impact of atomic-scale disorder on these modes remains poorly understood. Here, we report the first measurement of acoustic phonon dispersions in a quasi-freestanding monolayer semiconductor (MoS2), using helium-3 spin-echo s

Yucheng Mao, Boyang Wang, Nilesh Kulkarni, Jeong Joon Park

The computer vision community has developed numerous techniques for digitally restoring true scene information from single-view degraded photographs, an important yet extremely ill-posed task. In this work, we tackle image restoration from a different perspective by jointly denoising multiple photographs of the same scene. Our core hypothesis is that degrade

Mohammad H. Amin, Jack Raymond, Daniel Kinn, Gunnar Miller

We propose a blockchain architecture in which mining requires a quantum computer. The consensus mechanism is based on proof of quantum work, a quantum-enhanced alternative to traditional proof of work that leverages quantum supremacy to make mining intractable for classical computers. We have refined the blockchain framework to incorporate the probabilistic

Nitay Ben-Shachar, Johannes Hofmann

Hydrodynamic-like electron flows are typically modeled using the Stokes-Ohm equation or a kinetic description that is based on a dual-relaxation time approximation. Such models assume a short intrinsic mean free path $\ell_e$ due to momentum-conserving electronic scattering and a large extrinsic mean free path $\ell_\text{MR}$ due to momentum-relaxing impuri

Yu Cheng, Jonathan C. Tan, Morten Andersen, Rubén Fedriani

Star formation is a fundamental, yet poorly understood, process of the Universe. It is important to study how star formation occurs in different galactic environments. Thus, here, in the first of a series of papers, we introduce the Low-Metallicity Star Formation (LZ-STAR) survey of the Sh2-284 (hereafter S284) region, which, at $Z\sim 0.3-0.5Z_\odot$, is on

Piersilvio De Bartolomeis, Julia Kostin, Javier Abad, Yixin Wang

Practical and ethical constraints often require the use of observational data for causal inference, particularly in medicine and social sciences. Yet, observational datasets are prone to confounding, potentially compromising the validity of causal conclusions. While it is possible to correct for biases if the underlying causal graph is known, this is rarely

Jan Kruschewski, Farmer Schlutzenberg

Let $n \geq 1$ and assume that there is a Woodin cardinal. For $x \in \mathbb{R}$ let $\alpha_x$ be the least $\beta$ such that \[ L_\beta [x] \models \Sigma_n \text{-KP} + \exists \kappa (``\kappa \text{ is inaccessible and }\kappa^+ \text{ exists}"). \] We adapt the analysis of $\text{HOD}^{L[x,G]}$ as a strategy mouse to $L_{\alpha_x}[x,G]$ for a cone of

Bo Peng, Ruichong Zhang, Daniel Goldstein, Eric Alcaide

We present RWKV-7 "Goose", a new sequence modeling architecture with constant memory usage and constant inference time per token. Despite being trained on dramatically fewer tokens than other top models, our 2.9 billion parameter language model achieves a new 3B SoTA on multilingual tasks and matches the current 3B SoTA on English language downstream perform

S. Orlando, H. -T. Janka, A. Wongwathanarat, F. Bocchino

[Abridged] Cassiopeia A (Cas A) provides a unique opportunity to study supernova (SN) dynamics and interactions with the circumstellar medium (CSM). Recent JWST observations revealed the "Green Monster" (GM), a structure with a likely CSM origin. We investigate its pockmarked morphology, characterized by circular holes and rings, by examining the role of sma

Erminia Calabrese, J. Colin Hill, Hidde T. Jense, Adrien La Posta

We use new cosmic microwave background (CMB) primary temperature and polarization anisotropy measurements from the Atacama Cosmology Telescope (ACT) Data Release 6 (DR6) to test foundational assumptions of the standard cosmological model and set constraints on extensions to it. We derive constraints from the ACT DR6 power spectra alone, as well as in combina

Qiushuo Hou, Sangwoo Park, Matteo Zecchin, Yunlong Cai

Consider an edge computing setting in which a user submits queries for the solution of a linear system to an edge processor, which is subject to time-varying computing availability. The edge processor applies a probabilistic linear solver (PLS) so as to be able to respond to the user's query within the allotted time and computing budget. Feedback to the user

Thibaut Louis, Adrien La Posta, Zachary Atkins, Hidde T. Jense

We present power spectra of the cosmic microwave background (CMB) anisotropy in temperature and polarization, measured from the Data Release 6 maps made from Atacama Cosmology Telescope (ACT) data. These cover 19,000 deg$^2$ of sky in bands centered at 98, 150 and 220 GHz, with white noise levels three times lower than Planck in polarization. We find that th

Sigurd Naess, Yilun Guan, Adriaan J. Duivenvoorden, Matthew Hasselfield

We present Atacama Cosmology Telescope (ACT) Data Release 6 (DR6) maps of the Cosmic Microwave Background temperature and polarization anisotropy at arcminute resolution over three frequency bands centered on 98, 150 and 220 GHz. The maps are based on data collected with the AdvancedACT camera over the period 2017--2022 and cover 19,000 square degrees with a

Eugenio Pozzoli, Alessandro Scagliotti

In this paper, we seek to combine two emerging standpoints in control theory. On the one hand, recent advances in infinite-dimensional geometric control have unlocked a method for controlling (with arbitrary precision and in arbitrarily small times) state transfers for bilinear Schr\"odinger PDEs posed on a Riemannian manifold $M$. In particular, these argum

Abhinav Verma, Jacob Hastrup, Jonas S. Neergaard-Nielsen, Ulrik L. Andersen

Scalable interferometers lie at the heart of photonic quantum technologies, but their expansion has been fundamentally limited by optical losses that grow with circuit depth. Here, we introduce and experimentally demonstrate a measurement-induced architecture for multimode squeezed-light interferometers that overcomes this barrier. By shifting complexity fro

Ayushi Dubal, David Kremer, Simon Martiel, Victor Villar

We introduce a Reinforcement Learning (RL)-based method for re-synthesis of quantum circuits containing arbitrary Pauli rotations alongside Clifford operations. By collapsing each sub-block to a compact representation and then synthesizing it step-by-step through a learned heuristic, we obtain circuits that are both shorter and compliant with hardware connec

A. Felipe, M. Jaenada, P. Miranda, L. Pardo

The log-logistic distribution is a versatile parametric family widely used across various applied fields, including survival analysis, reliability engineering, and econometrics. When estimating parameters of the log-logistic distribution, hypothesis testing is necessary to verify assumptions about these parameters. The Wald test and Rao test provide formal m

Stanislaw Szymanowicz, Jason Y. Zhang, Pratul Srinivasan, Ruiqi Gao

We present a latent diffusion model for fast feed-forward 3D scene generation. Given one or more images, our model Bolt3D directly samples a 3D scene representation in less than seven seconds on a single GPU. We achieve this by leveraging powerful and scalable existing 2D diffusion network architectures to produce consistent high-fidelity 3D scene representa

A. Kar, R. Basak, Xue Li, A. Korshunov

The large van der Waals gap in transition metal dichalcogenides (TMDs) offers an avenue to host external metal atoms that modify the ground state of these 2D materials. Here, we experimentally and theoretically address the charge correlations in a family of intercalated TMDs. While short-range charge fluctuations develop in Co$_{1/3}$TaS$_{2}$ and Fe$_{1/3}$

Aleksandra Eliseeva, Alexander Kovrigin, Ilia Kholkin, Egor Bogomolov

Recent advances in Large Language Models (LLMs) have enabled researchers to focus on practical repository-level tasks in software engineering domain. In this work, we consider a cornerstone task for automating work with software repositories-environment setup, i.e., a task of configuring a repository-specific development environment on a system. Existing stu

Ana Esponera, Giovanni Cinà

Causal abstraction techniques such as Interchange Intervention Training (IIT) have been proposed to infuse neural network with expert knowledge encoded in causal models, but their application to real-world problems remains limited. This article explores the application of IIT in predicting blood glucose levels in Type 1 Diabetes Mellitus (T1DM) patients. The

Giacomo Nanni

We give a new proof for the maximality of the monodromy group of a Nikulin orbifold, a symplectic orbifold arising as terminalisation of a symplectic quotient of a $K3^{[2]}$-type fourfold.

Dallas Albritton, Laurel Ohm

We investigate a family of curve evolution equations approximating the motion of a Kirchhoff rod immersed in a low Reynolds number fluid. The rod is modeled as a framed curve whose energy consists of the bending energy of the curve and the twisting energy of the frame. The equations we consider may be realized as gradient flows of the rod energy under a cert

Kyriakos Stylianopoulos, Panagiotis Gavriilidis, Gabriele Gradoni, George C. Alexandropoulos

Radio-Frequency (RF) imaging concerns the digital recreation of the surfaces of scene objects based on the scattered field at distributed receivers. To solve this difficult inverse scattering problems, data-driven methods are often employed that extract patterns from similar training examples, while offering minimal latency. In this paper, we first provide a

Shlomi Hillel, Ron Schreier, Noam Soker

We demonstrate by three-dimensional hydrodynamical simulations of energy deposition into the envelope of a red supergiant (RSG) model the inflation of a Rayleigh-Taylor unstable envelope that forms a compact clumpy circumstellar material (CSM). Our simulations mimic vigorous core activity years to months before a core-collapse supernova (CCSN) explosion that

Jorge Reyes, Jörn Dunkel

Chemical reaction networks underpin biological and physical phenomena across scales, from microbial interactions to planetary atmosphere dynamics. Bacterial communities exhibit complex competitive interactions for resources, human organs and tissues demonstrate specialized biochemical functions, and planetary atmospheres can display diverse organic and inorg

Peter A. Clarkson, Anton Dzhamay, Andrew N. W. Hone, Ben Mitchell

We consider solutions of a discrete Painlev\'e equation arising from a construction of quantum minimal surfaces by Arnlind, Hoppe and Kontsevich, and in earlier work of Cornalba and Taylor on static membranes. While the discrete equation admits a continuum limit to the continuous Painlev\'e I equation, we find that it has the same space of initial values as

Yin Chen, Yi-Heng Tian, Rong-Qiang He, Zhong-Yi Lu

In ruthenate materials, non-Fermi liquid (NFL) phases have been observed. We used the natural orbitals renormalization group (NORG) method as an impurity solver for dynamical mean-field theory (DMFT) to study a three-orbital Kanamori-Hubbard model with crystal field splitting, set at a specific filling of 2/3, which serves as a minimal Hamiltonian for the ru

Nikhil Abhyankar, Parshin Shojaee, Chandan K. Reddy

Automated feature engineering plays a critical role in improving predictive model performance for tabular learning tasks. Traditional automated feature engineering methods are limited by their reliance on pre-defined transformations within fixed, manually designed search spaces, often neglecting domain knowledge. Recent advances using Large Language Models (

Bar Gazit, Shaltiel Shmidman, Avi Shmidman, Yuval Pinter

Common subword tokenization algorithms like BPE and UnigramLM assume that text can be split into meaningful units by concatenative measures alone. This is not true for languages such as Hebrew and Arabic, where morphology is encoded in root-template patterns, or Malay and Georgian, where split affixes are common. We present SPLINTER, a pre-processing step wh

Wei Fang, Yang Zhang, Kaizhi Qian, James Glass

Large language models (LLMs) are increasingly integrated with specialized external tools, yet many tasks demand zero-shot tool usage with minimal or noisy documentation. Existing solutions rely on manual rewriting or labeled data for validation, making them inapplicable in true zero-shot settings. To address these challenges, we propose PLAY2PROMPT, an autom

Nitay Ben-Shachar, Johannes Hofmann

Hydrodynamics is a new paradigm of electron transport in high-mobility devices, where frequent electron collisions give rise to a collective electron flow profile. However, conventional descriptions of these flows, which are based on the fluid equations for a classical gas extended to include impurity scattering, do not account for the distinct collisional r

Steven Dale Cutkosky, Jonathan Montaño

We prove a theorem on the intersection theory over a Noetherian local ring $R$, which gives a new proof of a classical theorem of Rees about degree functions. To obtain this, we define an intersection product on schemes that are proper and birational over such rings $R$, using the theory of rational equivalence developed by Thorup, and the Snapper-Mumford-Kl