March 2025 arXiv papers — page 126

Jennifer Wang, Kaidong Peng, Jeffrey M. Knecht, Gregory D. Cunningham

Advancing fault-tolerant quantum computing and fundamental science necessitates quantum-limited amplifiers with near-ideal quantum efficiency and multiplexing capability. However, existing solutions typically achieve one at the expense of the other. In this work, we experimentally demonstrate the first Floquet-mode traveling-wave parametric amplifier (Floque

Matthew Frazier, Guillaume Bal

This paper concerns the topological classification of continuous Hamiltonians that find applications in biased cold plasmas and photonics. Besides a magnetic bias, the Hamiltonians are parametrized by a plasma frequency and a fixed vertical wavenumber. Eight distinct phases of matter are identified as these parameters vary. When insulating gaps are shared by

Jose A. S. Laranjeira, Kleuton A. L. Lima, Nicolas F. Martins, Marcelo L. P. Junior

Two-dimensional (2D) carbon-based materials have attracted considerable interest due to their diverse structural and electronic properties, making them ideal for next-generation flat electronics. Among these materials, metallic-like porous structures offer advantages such as tunable charge transport and high surface area, which are essential for energy stora

Jonathan Eckstein, Chang Yu

This paper presents two new techniques relating to inexact solution of subproblems in augmented Lagrangian methods for convex programming. The first involves combining a relative error criterion for solution of the subproblems with over- or under-relaxation of the multiplier update step. This analysis enables a new kind of inexact augmented Lagrangian method

Alisa Sheinkman, Sara Wade

As modern neural networks get more complex, specifying a model with high predictive performance and sound uncertainty quantification becomes a more challenging task. Despite some promising theoretical results on the true posterior predictive distribution of Bayesian neural networks, the properties of even the most commonly used posterior approximations are o

Peter Fettke, Constantin Houy

Large language models (LLM) have revolutionized the processing of natural language. Although first benchmarks of the process modeling abilities of LLM are promising, it is currently under debate to what extent an LLM can generate good process models. In this contribution, we argue that the evaluation of the process modeling abilities of LLM is far from being

Sanayya A, Amoolya Shetty, Abhijeet Sharma, Venkatesh Ravichandran

In agricultural management, precise Ground Truth (GT) data is crucial for accurate Machine Learning (ML) based crop classification. Yet, issues like crop mislabeling and incorrect land identification are common. We propose a multi-level GT cleaning framework while utilizing multi-temporal Sentinel-2 data to address these issues. Specifically, this framework

Christopher Xie, Armen Avetisyan, Henry Howard-Jenkins, Yawar Siddiqui

We present a novel human-in-the-loop approach to estimate 3D scene layout that uses human feedback from an egocentric standpoint. We study this approach through introduction of a novel local correction task, where users identify local errors and prompt a model to automatically correct them. Building on SceneScript, a state-of-the-art framework for 3D scene l

K. A. L. Lima, José A. S. Laranjeira, Nicolas F. Martins, Sérgio A. Azevedod

Carbon's versatility allows it to form diverse structures with unique properties, driven by its moderate electronegativity, small ionic radius, and ability to adopt \textit{sp}, \textit{sp\textsuperscript{2}}, and \textit{sp\textsuperscript{3}} hybridizations, individually or in combination. In this work, we introduce three novel 2D carbon allotropes -- $\al

Károly Csukás, István Rácz

Andersson and Chru\'sciel showed that generic asymptotically hyperboloidal initial data sets admit polyhomogeneous expansions, and that only a non-generic subclass of solutions of the conformal constraint equations is free of logarithmic singularities. The purpose of this work is twofold. First, within the evolutionary framework of the constraint equations,

Arman Duha, S. E. Begg, Thomas Bilitewski

We investigate phase transitions in the nonequilibrium dynamics of power-law interacting spin-1/2 bilayer XXZ models, which have recently been shown to allow generation of entanglement in the form of two-mode squeezing. We find a transition between a collective phase characterized by Heisenberg limited squeezing and a partially collective phase with scalable

Xiaoyu Huang, Takara Truong, Yunbo Zhang, Fangzhou Yu

We present Diffuse-CLoC, a guided diffusion framework for physics-based look-ahead control that enables intuitive, steerable, and physically realistic motion generation. While existing kinematics motion generation with diffusion models offer intuitive steering capabilities with inference-time conditioning, they often fail to produce physically viable motions

Patrick Ciarlet,, Minh-Hieu Do, François Madiot

The multigroup neutron diffusion equations are often used to model the neutron density at the nuclear reactor core scale. Classically, these equations can be recast in a mixed variational form. This chapter presents an adaptive mesh refinement approach based on a posteriori estimators. We focus on refinement strategies on Cartesian meshes, since such structu

Snehashish Sarkar, Sutapa Mandal, Pinaki Pal

We investigate the effect of external horizontal magnetic field applied on the convection rolls obliquely (at an angle $\phi$ with the $x$-axis) in electrically conducting low Prandtl number fluids under the paradigm of the Rayleigh-B\'{e}nard convection by performing three-dimensional direct numerical simulations. The control parameters, namely, the Chandra

Márton Elekes, Tamás Kátay, Anett Kocsis

A graph property is elusive (or evasive) if any algorithm testing it by asking questions of the form ''Is there an edge between vertices x and y?'' must, in the worst case, examine all pairs of vertices. Elusiveness for infinite vertex sets has been first studied by Csern\'ak and Soukup, who proved that the long-standing Aanderaa-Karp-Rosenberg Conjecture --

Wilson Nieto Luna, Robin Smeyers, Cem Sevik, Lucian Covaci

The emerging ferroelectric properties of two-dimensional (2D) heterostructures are at the forefront of science and prospective technology. In moir\'e bilayers, twisting or heterostructuring causes local atomic reconstruction, which even at picometer scale, can lead to pronounced ferroelectric polarization. Accurately determining this reconstruction utilizing

Kleuton A. L. Lima, Rodrigo A. F. Alves, Elie A. Moujaes, Alexandre C. Dias

This study comprehensively characterizes, with suggested applications, a novel two-dimensional carbon allotrope, C$_{16}$, using Density Functional Theory and machine learning-based molecular dynamics. This nanomaterial is derived from naphthalene and bicyclopropylidene molecules, forming a planar configuration with sp$^2$ hybridization and featuring 3-, 4-,

Andrei Sperilă, Sorin Olaru, Stéphane Drobot

A novel set-theoretical approach to hands-off control is proposed, focusing on spatial arguments for command limitation rather than temporal ones. By employing dynamical feedback alongside invariant set-based constraints, actuation is employed only to drive the system's state within a "hands-off region" of its state-space, where the plant can freely evolve i

Bangzheng Li, Fei Wang, Wenxuan Zhou, Nan Xu

Vision-Language Models (VLMs) leverage aligned visual encoders to transform images into visual tokens, allowing them to be processed similarly to text by the backbone large language model (LLM). This unified input paradigm enables VLMs to excel in vision-language tasks such as visual question answering (VQA). To improve fine-grained visual reasoning, recent

S M Enamul Hoque Yousuf, Yunong Wang, Shreyas Ramachandran, John Koptur-Palenchar

The coupling between the spin degrees of freedom and macroscopic mechanical motions, including striction, shearing, and rotation, has attracted wide interest with applications in actuation, transduction, and information processing. Experiments so far have established the mechanical responses to the long-range ordered or isolated single spin states. However,

Peizhi Yan, Rabab K. Ward, Dan Wang, Qiang Tang

For 3D face modeling, the recently developed 3D-aware neural rendering methods are able to render photorealistic face images with arbitrary viewing directions. The training of the parametric controllable 3D-aware face models, however, still relies on a large-scale dataset that is lab-collected. To address this issue, this paper introduces "StyleMorpheus", th

B. P. Aware, A. N. Bhavale

In 2020 Bhavale and Waphare introduced the concept of a nullity of a poset as nullity of its cover graph. In 2003 Pawar and Waphare counted all non-isomorphic lattices on n elements and n edges, which are precisely lattices of nullity one. In 2002 Thakare et al. counted all non-isomorphic lattices on n elements containing two reducible elements. In the same

Ali Umut Kaypak, Shiqing Wei, Prashanth Krishnamurthy, Farshad Khorrami

Inter-robot collisions pose a significant safety risk when multiple robotic arms operate in close proximity. We present an online collision avoidance methodology leveraging High-Order Control Barrier Functions (HOCBFs) constructed for safe interactions among 3D convex shapes to address this issue. While prior works focused on using Control Barrier Functions

Nasim Borazjanizadeh, Roei Herzig, Eduard Oks, Trevor Darrell

Human reasoning relies on constructing and manipulating mental models -- simplified internal representations of situations used to understand and solve problems. Conceptual diagrams (e.g., a sketch drawn to aid reasoning) externalize these mental models, abstracting irrelevant details to efficiently capture how entities interact. In contrast, Large Language

Janina Malin Rybak, Jonas Arlt, Qian Ma, Carmen Fuchs

Grain boundaries (GBs) in oxide perovskites significantly influence their functional properties. This study examines the atomic-scale structure and composition of a faceted asymmetric grain boundary in strontium titanate (SrTiO$_3$) using scanning transmission electron microscopy (STEM), atom probe tomography (APT), and density functional theory (DFT). STEM

Abhijat Sarma, Yimu Bao, Nayan Myerson-Jain, Thomas Kiely

We demonstrate that the fidelity between two states with different Chern numbers $\mathcal Z = \mathrm{tr} \{ \rho \rho' \} $ serves as a generating theory for an effective conformal field theory (CFT) at the $(2+0)d$ temporal interface. $\rho$ can be chosen as a pure trivial insulator, and $\rho'$ can be taken as a pure or dephased Chern insulator density m

Jassem Abbasi, Ameya D. Jagtap, Ben Moseley, Aksel Hiorth

Solving partial differential equations (PDEs) with discontinuous solutions , such as shock waves in multiphase viscous flow in porous media , is critical for a wide range of scientific and engineering applications, as they represent sudden changes in physical quantities. Physics-Informed Neural Networks (PINNs), an approach proposed for solving PDEs, encount

Samuel W. Remedios, Shuwen Wei, Shuo Han, Jinwei Zhang

In clinical imaging, magnetic resonance (MR) image volumes are often acquired as stacks of 2D slices with decreased scan times, improved signal-to-noise ratio, and image contrasts unique to 2D MR pulse sequences. While this is sufficient for clinical evaluation, automated algorithms designed for 3D analysis perform poorly on multi-slice 2D MR volumes, especi

Jingying Zeng, Zhenwei Dai, Hui Liu, Samarth Varshney

Prompting LLMs offers an efficient way to guide output generation without explicit model training. In the e-commerce domain, prompting-based applications are widely used for tasks such as query understanding, recommender systems, and customer support. However, adapting LLMs to different tasks often requires extensive prompt engineering by domain experts, alo

Jun-Gi Jang, Jingrui He, Andrew Margenot, Hanghang Tong

Many real-world data, such as recommendation data and temporal graphs, can be represented as incomplete sparse tensors where most entries are unobserved. For such sparse tensors, identifying the top-k higher-order interactions that are most likely to occur among unobserved ones is crucial. Tensor factorization (TF) has gained significant attention in various

Miha Papič, Manuel G. Algaba, Emiliano Godinez-Ramirez, Inés de Vega

Quantum error mitigation (QEM) has emerged as a powerful tool for the extraction of useful quantum information from quantum devices. Here, we introduce the Subspace Noise Tailoring (SNT) algorithm, which efficiently combines the cheap cost of Symmetry Verification (SV) and low bias of Probabilistic Error Cancellation (PEC) QEM techniques. We study the perfor

Felipe Olivares

This paper explores the effectiveness of using ordinal pattern probabilities to evaluate antipersistency in the sign decomposition of long-range anti-correlated Gaussian fluctuations. It is numerically shown that ordinal patterns are able to effectively measure both persistent and antipersistent dynamics by analyzing the sign decomposition derived from fract

Shuwei Liu, Shiyu Zhou, Zi-Wen Liu, Jinmin Yi

We demonstrate that machine learning provides a powerful tool for discovering new approximate quantum error-correcting (AQEC) codes beyond conventional algebraic frameworks. Building upon direct observations through hybrid quantum-classical learning, we discover two new 4-qubit amplitude damping codes with an innovative noise-strength-adaptive (NSA) feature

Zheng-Hang Sun, Fabian Ballar Trigueros, Qicheng Tang, Markus Heyl

Projective measurements are a key element in quantum physics and enable rich phenomena in monitored quantum dynamics. Here, we show that the measurement outcomes, recorded during monitored dynamics, can provide crucial information about the properties of the monitored dynamical system itself. We demonstrate this for a Floquet model of many-body localization,

Artem Nikonorov, Georgy Perevozchikov, Andrei Korepanov, Nancy Mehta

We present cmKAN, a versatile framework for color matching. Given an input image with colors from a source color distribution, our method effectively and accurately maps these colors to match a target color distribution in both supervised and unsupervised settings. Our framework leverages the spline capabilities of Kolmogorov-Arnold Networks (KANs) to model

Tianyi Zhao, Boyang Liu, Yanglei Gao, Yiming Sun

Multi-Modal Object Detection (MMOD), due to its stronger adaptability to various complex environments, has been widely applied in various applications. Extensive research is dedicated to the RGB-IR object detection, primarily focusing on how to integrate complementary features from RGB-IR modalities. However, they neglect the mono-modality insufficient learn

Cy Maor, Maria Giovanna Mora

Ribbons are elastic bodies of thickness $t$ and width $w$ with $t\ll w\ll 1$ (after appropriate nondimensionalization). Many ribbons in nature have a non-trivial internal geometry, making them incompatible with Euclidean space. This incompatibility -- expressed mathematically as a failure of the Gauss-Codazzi equations for surfaces -- can trigger shape trans

James Sunseri, Adrian E. Bayer, Jia Liu

We study the cosmological information contained in the cosmic web, categorized as four structure types: nodes, filaments, walls, and voids, using the Quijote simulations and a modified nexus+ algorithm. We show that splitting the density field by the four structure types and combining the power spectrum in each provides much tighter constraints on cosmologic

Seungsam Yang, Seyed Mohammad Mehdi Mirnajafizadeh, Sian Kim, Rhongho Jang

With the exponentially growing Internet traffic, sketch data structure with a probabilistic algorithm has been expected to be an alternative solution for non-compromised (non-selective) security monitoring. While facilitating counting within a confined memory space, the sketch's memory efficiency and accuracy were further pushed to their limit through finer-

Paula Benaglia, Santiago del Palacio, Juliana Saponara, Agustina B. Blanco

HD93129A is an O+O stellar system whose CWR has been mapped by high angular resolution observations at cm wavelengths. The synchrotron nature of the radio emission confirms its particle accelerator status. According to astrometric measurements since 1996, the system has an orbital period of ~120 yr and recently went through its periastron passage. We charact

Elias Taira, Claire Kopenhafer, Brian W. Oshea, Alexis Manning

Among the many different pieces of physics that go into simulations of the circumgalactic medium (CGM), the metagalactic ultraviolet background (UVB) plays a significant role in determining the ionization state of different metal species. However, the UVB is uncertain with multiple models having been developed by various research groups over the past several

Zhixuan Lian, Shangyu Li, Qixuan Huang, Zijian Huang

Fault diagnosis of mechanical equipment involves data collection, feature extraction, and pattern recognition but is often hindered by the imbalanced nature of industrial data, introducing significant uncertainty and reducing diagnostic reliability. To address these challenges, this study proposes the Uncertainty-Aware Bayesian Meta-Learning Framework (UBMF)

Yuhao Wang, Enlu Zhou

In this paper, we propose a general and novel formulation of ranking and selection with the existence of streaming input data. The collection of multiple streams of such data may consume different types of resources, and hence can be conducted simultaneously. To utilize the streaming input data, we aggregate simulation outputs generated under heterogeneous i

Thomas Koberda, Yash Lodha

We use model theoretic forcing to prove that a generic countable torsion-free group does not admit any nontrivial locally moving action on a Hausdorff topological space, and yet admits a rich Rubin poset.

Yizhuo Xiao, Mustafa Suphi Erden, Cheng Wang

The validation of autonomous driving systems benefits greatly from the ability to generate scenarios that are both realistic and precisely controllable. Conventional approaches, such as real-world test drives, are not only expensive but also lack the flexibility to capture targeted edge cases for thorough evaluation. To address these challenges, we propose a

Djalil Chafaï, Max Fathi, Nikita Simonov

The cutoff phenomenon, conceptualized at the origin for finite Markov chains, states that for a parametric family of evolution equations, started from a point, the distance towards a long time equilibrium may become more and more abrupt for certain choices of initial conditions, when the parameter tends to infinity. This threshold phenomenon can be seen as a

Taylor J. Hoyt, In Sung Jang, Wendy L. Freedman, Barry F. Madore

We present distances to ten supernova (SN) host galaxies determined via the red giant branch tip (TRGB) using JWST/NIRCAM and the F115W, F356W, and F444W bandpasses. Our analysis, including photometric catalog cleaning, adoption of disk light profiles, TRGB color slope estimation, and a novel technique for identifying the infrared TRGB, was conducted blinded

Parisa Sangtarash, Jennifer C. Yee

Wide-orbit planets are particularly sensitive to detection by the Roman Galactic Bulge Time Domain Survey (GBTDS). This study investigates the degeneracy of these events with binary sources, focusing on how observation cadence affects the resolution of these degeneracies. We analyzed the impact of various cadences from (3.6 min)^(-1) to (5 hr)^(-1), which en

Beatriz Lopes da Costa, Matías R. Bolaños, Ricardo Chaves, Claudio Narduzzi

Over the last decades, Quantum Key Distribution (QKD) has risen as a promising solution for secure communications. However, like all cryptographic protocols, QKD implementations can open security vulnerabilities. Until now, the study of physical vulnerabilities in QKD setups has primarily focused on the optical channel. In classical cryptoanalysis, power and

Víctor Martín Lozano, G. Sanchez Garcia, Adrián Terrones

We study the complementarity between COHERENT and LHC searches in testing neutrino nonstandard interactions (NSIs) through the completion of the effective field theory approach within a $Z'$ simplified model. Our results show that LHC bounds are strongly dependent on the $Z'$ mass, with relatively large masses excluding regions in the parameter space that ar

Abdelghaffar Chibloun, Hassan Ou-azzou, Edgar Martínez-Moro, Mustapha Najmeddine

In this paper, we investigate polycyclic codes associated with a trinomial of arbitrary degree $n$ over a finite chain ring $ R.$ We extend the concepts of $ n $-isometry and $ n $-equivalence known for constacyclic codes to this class of codes, providing a broader framework for their structural analysis. We describe the classes of $n$-equivalence and comput

Jasmine Brewer, Wilke van der Schee, Urs Wiedemann

In high-energy elementary collisions the space-time ordering of parton branching processes is not accessible experimentally. In contrast, in heavy-ion collisions, parton showers interact with a spatially extended dense medium. This sets a reference length scale with respect to which the space-time ordering may be analysed. Here, we explore the possibility of

Daniel Muñoz-Segovia, Valentin Crépel, Raquel Queiroz, Andrew J. Millis

Recent experimental reports of correlated physics in twisted homobilayer WSe$_2$ have spurred interest in the interplay of electronic interactions and topology in this system. Here, we explore its phase diagram using the Hartree-Fock approximation within a three-orbital Wannier model of the bilayer. Our analysis reveals a dominant intervalley-coherent antife

Shikhar Mittal, Girish Kulkarni, Peter Sims

We introduce a Python package called ECHO21 for modelling the global 21-cm signal from the dark ages through cosmic dawn to the end of reionization. Leveraging its analytical framework, ECHO21 generates a single model in $\mathcal{O}(1)\,$s, allowing a large number of signals to be generated efficiently by distributing models across multiple cores. Thus, it

Michael Winer, Aidan Herderschee

Constraint Satisfaction Problems are ubiquitous in fields ranging from the physics of solids to artificial intelligence. In many cases, such systems undergo a transition when the ratio of constraints to variables reaches some value $\alpha_{\textrm{crit}}$. Above this critical value, it is exponentially unlikely that all constraints can be mutually satisfied

Biplob Bhattacherjee, Abhinav Kumar, Swagata Mukherjee, Rhitaja Sengupta

The lack of evidence for Beyond Standard Model (BSM) particles might be due to their light mass and very weak interactions, as exemplified by BSM long-lived particles (LLPs). Such particles can be produced from $B$ or $D$ hadron decays. Typically, the high values of pileup (PU) in hadron colliders are expected to pose a major challenge in light new physics s

Adrian Ka-Wai Chung, Kelvin Ka-Ho Lam, Nicolas Yunes

We present the first precise calculations of the gravitational quasinormal-mode (QNM) frequencies for spinning black holes with dimensionless angular momenta $J/M^2 := a \lesssim 0.75$ in dynamical Chern-Simons gravity. Using the \textit{Metric pErTuRbations wIth speCtral methodS} (METRICS) framework, we compute the QNM frequencies of both axial and polar me

Yi Qiu, David Radice, Sherwood Richers, Maitraya Bhattacharyya

We present the first numerical relativity simulations including neutrino flavor transformations that could result from flavor instabilities, quantum many-body effects, or potential beyond standard model physics in neutron star mergers. We find that neutrino flavor transformations impact the composition and structure of the remnant, potentially leaving an imp

Liu Yang, Gabriel Cardoso, Thors Hans Hansson, Qing-Dong Jiang

We investigate the influence of quantum fluctuations in a chiral cavity on the quantum Hall (QH) state, extending previous studies of QH liquids in linearly polarized cavities. Using the Schrieffer-Wolff transformation for perturbative cavity-matter interaction, we identify the system's normal modes, which correspond to the elementary excitations of the dres

Xiang Li, Yixiao Chen, Bohao Li, Haoxiang Chen

Electronic topological phases of matter, characterized by robust boundary states derived from topologically nontrivial bulk states, are pivotal for next-generation electronic devices. However, understanding their complex quantum phases, especially at larger scales and fractional fillings with strong electron correlations, has long posed a formidable computat

Stephon Alexander, Humberto Gilmer, Cooper Niu

Pseudo-Nambu-Goldstone (pNG) Higgs Inflation is a novel approach to relate the Higgs boson and its interaction with Electroweak gauge bosons with cosmic inflation, with the potential of solving both the fine-tuning issues in the Higgs mass and inflationary potentials. In this work, we present a linear perturbation analysis of the minimal implementation of pN

Julian Ingham, Mathias S. Scheurer, Harley D. Scammell

Motivated by the discovery of quasi-two-dimensional kagome metals AV$_3$Sb$_5$, we consider the theory of twisted bilayers in which the Fermi surface is near the $M$-point. Surprisingly, unlike twisted bilayers of graphene or transition metal dichalcogenides, the moir\'e potential is quasi-one-dimensional: at each $M$-valley, the potential flattens the dispe

Elena Pinetti

I present the first constraints on QCD axion dark matter using measurements from the James Webb Space Telescope. By utilizing publicly available MIRI and NIRSpec blank-sky observations, originally collected for sky subtraction purposes, I derive strong limits on the axion-photon coupling constant $g_{a \gamma \gamma}$ in the mass range 0.1-4 eV. These constr

Francesco D'Eugenio, Roberto Maiolino, Michele Perna, Hannah Uebler

JWST has revealed a population of 'Little Red Dots' (LRDs): compact, red objects at redshifts z=2-9 with 'v'-shaped spectral energy distributions, broad permitted lines, and, often, hydrogen Balmer absorption. We use NIRSpec/IFS data from the BlackTHUNDER survey to study the H$\alpha$ line in the LRD Abell2744-QSO1 at z=7.04, which is a confirmed AGN due to

Hiroyasu Akada, Jian Wang, Vladislav Golyanik, Christian Theobalt

Egocentric 3D human pose estimation has been actively studied using cameras installed in front of a head-mounted device (HMD). While frontal placement is the optimal and the only option for some tasks, such as hand tracking, it remains unclear if the same holds for full-body tracking due to self-occlusion and limited field-of-view coverage. Notably, even the

Jianyuan Wang, Minghao Chen, Nikita Karaev, Andrea Vedaldi

We present VGGT, a feed-forward neural network that directly infers all key 3D attributes of a scene, including camera parameters, point maps, depth maps, and 3D point tracks, from one, a few, or hundreds of its views. This approach is a step forward in 3D computer vision, where models have typically been constrained to and specialized for single tasks. It i

Zhaofeng Wu, Michihiro Yasunaga, Andrew Cohen, Yoon Kim

Reward models have become a staple in modern NLP, serving as not only a scalable text evaluator, but also an indispensable component in many alignment recipes and inference-time algorithms. However, while recent reward models increase performance on standard benchmarks, this may partly be due to overfitting effects, which would confound an understanding of t

Chonghao Sima, Kashyap Chitta, Zhiding Yu, Shiyi Lan

How can we rely on an end-to-end autonomous vehicle's complex decision-making system during deployment? One common solution is to have a ``fallback layer'' that checks the planned trajectory for rule violations and replaces it with a pre-defined safe action if necessary. Another approach involves adjusting the planner's decisions to minimize a pre-defined ``

Oliver Michel, Satadal Sengupta, Hyojoon Kim, Ravi Netravali

Video-conferencing applications face an unwavering surge in traffic, stressing their underlying infrastructure in unprecedented ways. This paper rethinks the key building block for conferencing infrastructures -- selective forwarding units (SFUs). SFUs relay and adapt media streams between participants and, today, run in software on general-purpose servers.

Ruth M. E. Kelly, Herman L. Marshall, Silvia Zane, Nabil Brice

X-ray polarimetry offers a unique window into neutron star physics and can provide answers to questions that cannot otherwise be probed. The up-and-coming REDSoX sounding rocket mission will be the first experiment equipped with a detector able to explore polarized X-rays below 1 keV, observing in the 0.2-0.4 keV range. Although REDSoX will only be capable o

Jianhong Bai, Menghan Xia, Xiao Fu, Xintao Wang

Camera control has been actively studied in text or image conditioned video generation tasks. However, altering camera trajectories of a given video remains under-explored, despite its importance in the field of video creation. It is non-trivial due to the extra constraints of maintaining multiple-frame appearance and dynamic synchronization. To address this

Siyuan Huang, Yue Liao, Siyuan Feng, Shu Jiang

The pursuit of data efficiency, where quality outweighs quantity, has emerged as a cornerstone in robotic manipulation, especially given the high costs associated with real-world data collection. We propose that maximizing the informational density of individual demonstrations can dramatically reduce reliance on large-scale datasets while improving task perf

Juehang Qin, Dorian W. P. Amaral, Sunil A. Bhave, Erqian Cai

Dark matter candidates with masses around the Planck-scale are theoretically well-motivated, and it has been suggested that it might be possible to search for dark matter solely via gravitational interactions in this mass range. In this work, we explore the pathway towards searching for dark matter candidates with masses around the Planck-scale using mechani

Param Patel, Mingkang Xia, Chao Zhou, Pinlei Lu

Quantum information processing, especially with quantum error correction, requires both long-lived qubits and fast, quantum non-demolition readout. In superconducting circuits this leads to the requirement to both strongly couple qubits, such as transmons, to readout modes while also protecting them from associated Purcell decay through the readout port. So-

P. Campeti, J. -M. Delouis, L. Pagano, E. Allys

We introduce a novel, fast, and efficient generative model built upon scattering covariances, the most recent iteration of the scattering transforms statistics. This model is designed to augment by several orders of magnitude the number of map simulations in datasets of computationally expensive CMB instrumental systematics simulations, including their non-G

Shuyang Hao, Yiwei Wang, Bryan Hooi, Jun Liu

In the realm of large vision-language models (LVLMs), adversarial jailbreak attacks serve as a red-teaming approach to identify safety vulnerabilities of these models and their associated defense mechanisms. However, we identify a critical limitation: not every adversarial optimization step leads to a positive outcome, and indiscriminately accepting optimiza

Alexey Cheskidov, Taichi Eguchi

We construct global smooth solutions to the incompressible Navier--Stokes equations in $\mathbb{R}^3$ for initial data in $L^2$ satisfying some smallness condition. The high-frequency part is assumed to be small in $BMO^{-1}$, while the low-frequency part is assumed to be small only in $\dot B^{-1}_{\infty,\infty}$. Since $BMO^{-1}$ is strictly embedded in $

William A. Simon, Carter M. Gustin, Kamil Serafin, Alexis Ralli

We describe and analyze LOBE (Ladder Operator Block-Encoding), a framework for block-encoding ladder operators that act upon fermionic and bosonic modes. In this framework, we achieve efficient block-encodings by applying the desired action of the operator onto the quantum state and pushing any undesired effects outside of the encoded subspace. This direct a

Long-Kun Shan, Ze-Hao Wang, Tong-Tian Weng, Xiang-Dong Chen

Structured illumination microscopy (SIM) is a pivotal technique for dynamic subcellular imaging in live cells. Conventional SIM reconstruction algorithms depend on accurately estimating the illumination pattern and can introduce artefacts when this estimation is imprecise. Although recent deep learning-based SIM reconstruction methods have improved speed, ac

Mohamed Nawwar, Robin R. Neumann, Jiamin Wen, Alexander Mook

Recent studies have demonstrated that the thermal Hall effect can originate from magnons (magnon Hall effect), phonons (phonon Hall effect), or their combination (magnon-polaron Hall effect). The magnon-polaron Hall effect, first observed in Fe2Mo3O8, is particularly intriguing as its thermal Hall signal can be remarkably large. In this study, we explore the

Jan Olle, Oleg M. Yevtushenko, Florian Marquardt

Reinforcement Learning (RL) has established itself as a powerful tool for designing quantum circuits, which are essential for processing quantum information. RL applications have typically focused on circuits of small to intermediate complexity, as computation times tend to increase exponentially with growing circuit complexity. This computational explosion

Cheng Zeng, Yaozhi Yang, Jason Xu, Leo L Duan

Many statistical problems include model parameters that are defined as the solutions to optimization sub-problems. These include classical approaches such as profile likelihood as well as modern applications involving flow networks or Procrustes distances. In such cases, the likelihood of the data involves an implicit function, often complicating inferential

Anthony Torres-Hernandez

Since polynomial regression models are generally quite reliable for data with a linear trend, it is important to note that, in some cases, they may encounter overfitting issues during the training phase, which could result in negative values of the coefficient of determination $R^2$ for unseen data. For this reason, this work proposes the partial implementat

Xizhu Zhao, Dmitrii E. Makarov, Aljaž Godec

Experiments, in particular on biological systems, typically probe lower-dimensional observables which are projections of high-dimensional dynamics. In order to infer consistent models capturing the relevant dynamics of the system, it is important to detect and account for the memory in the dynamics. We develop a method to infer the presence of hidden states

S. Navarro-Obregón, J. Queiruga

We discuss various sphaleron-like solutions on $\mathbb{S}^1$. These solutions are static, but unstable. We explore possible stabilization mechanisms based on the excitation of internal modes. Additionally, we observe that, on time scales comparable to the size of the circle, the collapse of large sphalerons mimics the kink-antikink scattering on the real li

Hao Cui, Zahra Shamsi, Gowoon Cheon, Xuejian Ma

Scientific problem-solving involves synthesizing information while applying expert knowledge. We introduce CURIE, a scientific long-Context Understanding,Reasoning and Information Extraction benchmark to measure the potential of Large Language Models (LLMs) in scientific problem-solving and assisting scientists in realistic workflows. This benchmark introduc

Eli Goldin, Mark Zhandry

Black-box separations are a cornerstone of cryptography, indicating barriers to various goals. A recent line of work has explored black-box separations for quantum cryptographic primitives. Namely, a number of separations are known in the Common Haar Random State (CHRS) model, though this model is not considered a complete separation, but rather a starting p

Hongyu Wen, Yiming Zuo, Venkat Subramanian, Patrick Chen

Transparent objects are common in daily life, and understanding their multi-layer depth information -- perceiving both the transparent surface and the objects behind it -- is crucial for real-world applications that interact with transparent materials. In this paper, we introduce LayeredDepth, the first dataset with multi-layer depth annotations, including a

Patrick Rieck, Kyle Cranmer, Etienne Dreyer, Eilam Gross

We extend the re-simulation-based self-supervised learning approach to learning representations of hadronic jets in colliders by exploiting the Markov property of the standard simulation chain. Instead of masking, cropping, or other forms of data augmentation, this approach simulates pairs of events where the initial portion of the simulation is shared, but

Blaine Vollmer, Alberto Padovan, Daniel J. Bodony

Surface patterns on ablating materials are observed in high-speed ground and flight tests, but the mechanisms behind their formation are not known. In this paper, the origin of surface patterns is investigated via a local linear stability analysis of compressible laminar boundary layers over a flat camphor plate. The effects of sublimation and conjugate heat

Tamar I. Regev, Chiebuka Ohams, Shaylee Xie, Lukas Wolf

In spoken communication, information is transmitted not only via words, but also through a rich array of non-verbal signals, including prosody--the non-segmental auditory features of speech. Do these different communication channels carry distinct information? Prior work has shown that the information carried by prosodic features is substantially redundant w

Stefan Lionar, Jiabin Liang, Gim Hee Lee

We introduce TreeMeshGPT, an autoregressive Transformer designed to generate high-quality artistic meshes aligned with input point clouds. Instead of the conventional next-token prediction in autoregressive Transformer, we propose a novel Autoregressive Tree Sequencing where the next input token is retrieved from a dynamically growing tree structure that is

Giulia Borghetto, Ameek Malhotra, Gianmassimo Tasinato, Ivonne Zavala

Recent cosmological observations suggest that the dark energy equation of state may have changed in the latter stages of cosmic history. We introduce a quintessence scenario, termed bounded dark energy, capable of explaining this feature in a technically natural way. Our approach is motivated from a bottom-up perspective, based on the concept of mirage cut-o

Will Schwarzer, Neel Chaudhari, Philip S. Thomas, Andrea Fanelli

Deep noise suppression (DNS) models enjoy widespread use throughout a variety of high-stakes speech applications. However, we show that four recent DNS models can each be reduced to outputting unintelligible gibberish through the addition of psychoacoustically hidden adversarial noise, even in low-background-noise and simulated over-the-air settings. For thr

Paul C. W. Lai, Beatrice Crudele, Matteo Agostini, Hayden P. H. Ng

The Central Molecular Zone (CMZ), a star-forming region rich in molecular clouds located within hundreds of parsecs from the centre of our Galaxy, converts gas into stars less efficiently than anticipated. A key challenge in refining star-formation models is the lack of precise mapping of these dense molecular hydrogen clouds, where traditional tracers often

Adrià Labay-Mora, Alberto Mercurio, Vincenzo Savona, Gian Luca Giorgi

We introduce a Schr\"odinger chiral cat qubit, a novel bosonic quantum code generalizing Kerr cat qubits that exploits higher-order nonlinearities. Compared to a standard Kerr cat, the chiral cat qubit allows additional correction of bit-flip errors within the Hilbert space of a single bosonic oscillator. Indeed, this code displays optical bistability, i.e.,

Deep Patel, Panthadeep Bhattacharjee, Amit Reza, Priodyuti Pradhan

A timely and effective response is crucial to minimize damage and save lives during natural disasters like earthquakes. Microblogging platforms, particularly Twitter, have emerged as valuable real-time information sources for such events. This work explores the potential of leveraging Twitter data for earthquake response analysis. We develop a machine learni

Rhea Hoyer, P. Peter Stavropoulos, Aleksandar Razpopov, Roser Valentí

We develop a four-sublattice spin-wave theory for the $g$-wave altermagnet candidate hematite ($\alpha$-Fe$_2$O$_3$), considering both its easy-axis phase below and its weak ferromagnetic phase above the Morin temperature. A key question is whether the defining altermagnetic feature - magnon spin splitting (also called chirality or polarization splitting) du

Javier Fernandez-Carabantes, Manuel Titos, Luca D'Auria, Jesus Garcia

In this article, we present a novel Deep Learning model based on Recurrent Neural Networks (RNNs) with Long Short-Term Memory (LSTM) cells, designed as a real-time Volcano-seismic Signal Recognition (VSR) system for Distributed Acoustic Sensing (DAS) measurements. The model was trained on an extensive database of Volcano-Tectonic (VT) events derived from the

Anis Maddi, Gaelle Poignand, Vassos Achilleos, Vincent Pagneux

In this study, we experimentally investigate the application of a transient signal with complex frequencies to the absorption and transmission of sound waves. Indeed, the emission of a wave with an exponentially varying amplitude in time is analogous, in the frequency domain, to a monochromatic wave with spatial gain or loss. Our results show that by excitin