February 2024 arXiv papers — page 11

Emily Kabat, Alba Y. Ramos, Lucas J. Fernández-Alcázar, Tsampikos Kottos

We show that a single nonlinear defect can thermalize an initial excitation towards a Rayleigh-Jeans (RJ) state in complex multimoded systems. The thermalization can be hindered by disorder-induced localization phenomena which drive the system into a metastable RJ state. It involves only a (quasi-)isolated set of prethermal modes and can differ dramatically

Yu-Neng Chuang, Tianwei Xing, Chia-Yuan Chang, Zirui Liu

Large language models (LLMs) are great at processing multiple natural language processing tasks, but their abilities are constrained by inferior performance with long context, slow inference speed, and the high cost of computing the results. Deploying LLMs with precise and informative context helps users process large-scale datasets more effectively and cost

Suhan Ling, Yian Wang, Shiguang Wu, Yuzheng Zhuang

3D articulated objects are inherently challenging for manipulation due to the varied geometries and intricate functionalities associated with articulated objects.Point-level affordance, which predicts the per-point actionable score and thus proposes the best point to interact with, has demonstrated excellent performance and generalization capabilities in art

Ziyun Yang, Kevin Choy, Sina Farsiu

Generic object detection is a category-independent task that relies on accurate modeling of objectness. We show that for accurate semantic analysis, the network needs to learn all object-level predictions that appear at any stage of learning, including the pre-defined ground truth (GT) objects and the ambiguous decoy objects that the network misidentifies as

Serina Chang, Frederic Koehler, Zhaonan Qu, Jure Leskovec

A common network inference problem, arising from real-world data constraints, is how to infer a dynamic network from its time-aggregated adjacency matrix and time-varying marginals (i.e., row and column sums). Prior approaches to this problem have repurposed the classic iterative proportional fitting (IPF) procedure, also known as Sinkhorn's algorithm, with

Davood Rafiei Karkevandi, Mahboubeh Shahrbaf, Soroush Shakeri, Stefan Typel

The presence of dark matter (DM) within neutron stars (NSs) can be introduced by different accumulation scenarios in which DM and baryonic matter (BM) may interact only through the gravitational force. In this work, we consider asymmetric self-interacting bosonic DM which can reside as a dense core inside the NS or form an extended halo around it. It is seen

Zilin Xiao, Ming Gong, Paola Cascante-Bonilla, Xingyao Zhang

We introduce AutoVER, an Autoregressive model for Visual Entity Recognition. Our model extends an autoregressive Multi-modal Large Language Model by employing retrieval augmented constrained generation. It mitigates low performance on out-of-domain entities while excelling in queries that require visually-situated reasoning. Our method learns to distinguish

Ulrich K. Beckering Vinckers, Álvaro de la Cruz-Dombriz, Anupam Mazumdar

In the context of ghost-free infinite derivative gravity, we consider the single graviton exchange between two spinless particles, a spinless particle and a photon, or between a spinless particle and a spin-1/2 particle. To this end, we compute the gravitational potential for the three aforementioned cases and derive the $\mathcal{O}(G\hbar^2)$ correction th

Arvind Kumar, Vivek Mukundan

Let $R=\mathbb{K}[x_1,\dots,x_n]$ and let $\mathfrak{a}_1,\dots,\mathfrak{a}_m$ be homogeneous ideals satisfying certain properties, which include a description of the Noetherian symbolic Rees algebra. We give a solution to a question of Harbourne and Huneke for this set of ideals. We also compute the Waldschmidt constant and resurgence and show that it exhi

Siqi Kou, Lanxiang Hu, Zhezhi He, Zhijie Deng

Parallel decoding methods such as Jacobi decoding show promise for more efficient LLM inference as it breaks the sequential nature of the LLM decoding process and transforms it into parallelizable computation. However, in practice, it achieves little speedup compared to traditional autoregressive (AR) decoding, primarily because Jacobi decoding seldom accura

A. Ruelas-Mayorga, L. J. Sánchez, A. Páez-Amador, O. Segura-Montero

We present photometric CCD observations of stars in four stellar trapezia ADS 15184, ADS 4728, ADS 2843, and ADS 16795. This study is performed on images obtained at the Observatorio Astron\'omico Nacional at San Pedro M\'artir (OAN), Baja California, M\'exico. In this work we utilise aperture photometry to measure the $U$, $B$, $V$, $R$ and $I$ magnitudes o

Blake J. Boudreaux

We compare the $T$-polynomial convexity of Guedj with holomorphic convexity away from the support of $T$. In particular we show an Oka--Weil theorem for $T$-polynomial convexity, as well as present a situation when the notions of $T$-polynomial convexity and holomorphic convexity of $X\setminus\text{Supp }T$ coincide in the context of complex projective alge

Manasvi Lingam, Adam Hibberd, Andreas M. Hein

Icy moons with subsurface oceans of liquid water rank among the most promising astrobiological targets in our Solar System. In this work, we assess the feasibility of deploying laser sail technology in precursor life-detection missions. We investigate such laser sail missions to Enceladus and Europa, as these two moons emit plumes that seem accessible to in

A. Möller, P. Wiseman, M. Smith, C. Lidman

Current and future Type Ia Supernova (SN Ia) surveys will need to adopt new approaches to classifying SNe and obtaining their redshifts without spectra if they wish to reach their full potential. We present here a novel approach that uses only photometry to identify SNe Ia in the 5-year Dark Energy Survey (DES) dataset using the SuperNNova classifier. Our ap

Christopher Ratigan, Lenore Cowen

While the area under the ROC curve is perhaps the most common measure that is used to rank the relative performance of different binary classifiers, longstanding field folklore has noted that it can be a measure that ill-captures the benefits of different classifiers when either the actual class values or misclassification costs are highly unbalanced between

Utkarsh Dwivedi, Salma Elsayed-Ali, Elizabeth Bonsignore, Hernisa Kacorri

Emphasizing problem formulation in AI literacy activities with children is vital, yet we lack empirical studies on their structure and affordances. We propose that participatory design involving teachable machines facilitates problem formulation activities. To test this, we integrated problem reduction heuristics into storyboarding and invited a university-b

Eli Gudinetsky, Tal Miller, Ilan Be'ery, Ido Barth

Magnetic confinement fusion reactors produce ash particles that must be removed for efficient operation. It is suggested to use autoresonance (a continuous phase-locking between anharmonic motion and a chirped drive) to remove the ash particles from a magnetic mirror, the simplest magnetic confinement configuration. An analogy to the driven pendulum is estab

Mahboubeh Shahrbaf, Davood Rafiei Karkevandi, Alexander Ayriyan, Stefan Typel

Context. The presence of dark matter in neutron stars is of growing interest due to its potential impact on the structure and observable properties of these objects. Among the various candidates, the hypothetical sexaquark has emerged as a promising bosonic dark matter particle, potentially forming under extreme conditions in neutron star cores. Aims. We inv

Mrinal Kanti Giri, Sudhindu Bikash Mandal

We study the quantum walk on the off-diagonal Aubry-Andr\'e-Harper (AAH) lattice with periodic modulation using a digital quantum computer. We investigate various initial states at the single-particle level, considering different hopping modulation strengths and phase factors. Initiating the quantum walk with a particle at the lattice edge reveals the robust

Jack Weinberg, Avijit Mandal, Henry D. Pfister

In the quantum compression scheme proposed by Schumacher, Alice compresses a message that Bob decompresses. In that approach, there is some probability of failure and, even when successful, some distortion of the state. For sufficiently large blocklengths, both of these imperfections can be made arbitrarily small while achieving a compression rate that asymp

Wanghan Xu, Bin Shi, Ao Liu, Jiqiang Zhang

In recent years, with the rapid development of graph neural networks (GNN), more and more graph datasets have been published for GNN tasks. However, when an upstream data owner publishes graph data, there are often many privacy concerns, because many real-world graph data contain sensitive information like person's friend list. Differential privacy (DP) is a

Kaitao Meng, Christos Masouros, Kai-Kit Wong, Athina P. Petropulu

Both smart propagation engineering as well as integrated sensing and communication (ISAC) constitute promising candidates for next-generation (NG) mobile networks. We provide a synergistic view of these technologies, and explore their mutual benefits. First, moving beyond just intelligent surfaces, we provide a holistic view of the engineering aspects of sma

Wilfred Mason, David Brenken, Falcon Z. Dai, Ricardo Gonzalo Cruz Castillo

Tactile sensing in mobile robots remains under-explored, mainly due to challenges related to sensor integration and the complexities of distributed sensing. In this work, we present a tactile sensing architecture for mobile robots based on wheel-mounted acoustic waveguides. Our sensor architecture enables tactile sensing along the entire circumference of a w

Damien Neyret, Philippe Abbon, Marc Anfreville, Vincent Andrieux

Large-size hybrid and pixelized GEM-Micromegas gaseous detectors (40x40 cm$^2$ active area) were developed and installed in 2014 and 2015 for the COMPASS2 physics program which started at the same time. That program involved in particular two full years of Drell-Yan studies using a high-intensity pion beam on a thick polarized target. Although the detectors

K. Uzawa, N. Hinohara, T. Nakatsukasa

Pairing correlations play an important role in a variety of nuclear phenomena. However, a quantitative understanding of proton--neutron $(pn)$ pairing, especially isoscalar $pn$ pairing $(S=1, T=0)$ remains elusive. To clarify the property of $pn$ pairing, we investigate the roles of $pn$ pairing in the $M1$ transition of $N=Z$ odd--odd nuclei. We develop a

Sirui Hong, Yizhang Lin, Bang Liu, Bangbang Liu

Large Language Model (LLM)-based agents have shown effectiveness across many applications. However, their use in data science scenarios requiring solving long-term interconnected tasks, dynamic data adjustments and domain expertise remains challenging. Previous approaches primarily focus on individual tasks, making it difficult to assess the complete data sc

Zhengping Jiang, Yining Lu, Hanjie Chen, Daniel Khashabi

Free-text rationales play a pivotal role in explainable NLP, bridging the knowledge and reasoning gaps behind a model's decision-making. However, due to the diversity of potential reasoning paths and a corresponding lack of definitive ground truth, their evaluation remains a challenge. Existing evaluation metrics rely on the degree to which a rationale suppo

Hongchao Zhang, Luyao Niu, Andrew Clark, Radha Poovendran

Safety is a fundamental requirement of many robotic systems. Control barrier function (CBF)-based approaches have been proposed to guarantee the safety of robotic systems. However, the effectiveness of these approaches highly relies on the choice of CBFs. Inspired by the universal approximation power of neural networks, there is a growing trend toward repres

Cayo Dória, Nara Paiva

The goal of this work is to give new quantitative results about the distribution of semi-arithmetic hyperbolic surfaces in the moduli space of closed hyperbolic surfaces. We show that two coverings of genus $g$ of a fixed arithmetic surface $S$ are $P(\frac{1}{g})$ apart from each other with respect to Teichmuller metric, where $P$ is a polynomial depending

Shuo Jiang, Jinkun Zhang, Lawson Wong

For a robot, its body structure is an a-prior knowledge when it is designed. However, when such information is not available, can a robot recognize it by itself? In this paper, we aim to grant a robot such ability to learn its body structure from exteroception and proprioception data collected from on-body sensors. By a novel machine learning method, the rob

Ruby E. Fulford, Dathon R. Golish, Dante S. Lauretta, Daniella N. DellaGiustina

The Quantitative Reflectance Imaging System (QRIS) is a laboratory-based spectral imaging system constructed to image the sample of asteroid Bennu delivered to Earth by the Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer (OSIRIS-REx) spacecraft. The system was installed in the OSIRIS-REx cleanroom at NASA's Johnson S

Giuseppe Cartella, Marcella Cornia, Vittorio Cuculo, Alessandro D'Amelio

Human attention modelling has proven, in recent years, to be particularly useful not only for understanding the cognitive processes underlying visual exploration, but also for providing support to artificial intelligence models that aim to solve problems in various domains, including image and video processing, vision-and-language applications, and language

A. Crespo Gómez, L. Colina, J. Álvarez-Márquez, A. Bik

Despite the importance of the dusty star-forming galaxies (DSFGs) at $z$>2 for understanding the galaxy evolution in the early Universe, their stellar distributions traced by the near-IR emission were spatially unresolved until the arrival of the JWST. In this work we present, for the first time, a spatially-resolved morphological analysis of the rest-frame

Julian Hintermayr, Paul M. P. van Kuppevelt, Bert Koopmans

Using optically generated spin-orbit torques induced by the heavy metal Pt we demonstrate coherent control of GHz ferromagnetic resonances in Pt/Co/Pt multilayers as well as sub-THz exchange resonances in [Gd/Co]$_2$ multilayers. Employing a double-pump setup, we show that depending on the helicities of the pump pulses, spin resonances can either be coherent

Emelie Curl, Jürgen Kritschgau, Carolyn Reinhart, Hein van der Holst

In this paper, we initiate the study of the inverse eigenvalue problem for probe graphs. A probe graph is a graph whose vertices are partitioned into probe vertices and non-probe vertices such that the non-probe vertices form an independent set. In general, a probe graph is used to represent the set of graphs that can be obtained by adding edges between non-

Saee Dhawalikar, Aseem Paranjape

Cosmic filaments, the most prominent features of the cosmic web, possibly hold untapped potential for cosmological inference. While it is natural to expect the structure of filaments to show universality similar to that seen in dark matter halos, the lack of agreement between different filament finders on what constitutes a filament has hampered progress on

Uwe Peters, Mary Carman

For synergistic interactions between humans and artificial intelligence (AI) systems, AI outputs often need to be explainable to people. Explainable AI (XAI) systems are commonly tested in human user studies. However, whether XAI researchers consider potential cultural differences in human explanatory needs remains unexplored. We highlight psychological rese

Simran Arora, Sabri Eyuboglu, Michael Zhang, Aman Timalsina

Recent work has shown that attention-based language models excel at recall, the ability to ground generations in tokens previously seen in context. However, the efficiency of attention-based models is bottle-necked during inference by the KV-cache's aggressive memory consumption. In this work, we explore whether we can improve language model efficiency (e.g.

Alejandro Arias Jiménez

In this work we represent the $1/2$ Spin particles with complex quaternions using a transformation to 2x2 matrices in order to obtain the Pauli matrices. With this representation we determine the states, rotation operators and the total angular momentum function in the complex quaternion space. Using this representation we work the solution for the relativis

Congying Xia, Chen Xing, Jiangshu Du, Xinyi Yang

This paper presents FoFo, a pioneering benchmark for evaluating large language models' (LLMs) ability to follow complex, domain-specific formats, a crucial yet underexamined capability for their application as AI agents. Despite LLMs' advancements, existing benchmarks fail to assess their format-following proficiency adequately. FoFo fills this gap with a di

Naqi Huang, Nestor Parolya, Theresia van Essen

In large-scale, data-driven applications, parameters are often only known approximately due to noise and limited data samples. In this paper, we focus on high-dimensional optimization problems with linear constraints under uncertain conditions. To find high quality solutions for which the violation of the true constraints is limited, we develop a linear shri

Antonio Anna Mele, Yaroslav Herasymenko

The experimental realization of increasingly complex quantum states underscores the pressing need for new methods of state learning and verification. In one such framework, quantum state tomography, the aim is to learn the full quantum state from data obtained by measurements. Without prior assumptions on the state, this task is prohibitively hard. Here, we

Manuel Pratelli, Marinella Petrocchi, Fabio Saracco, Rocco De Nicola

For U.S. presidential elections, most states use the so-called winner-take-all system, in which the state's presidential electors are awarded to the winning political party in the state after a popular vote phase, regardless of the actual margin of victory. Therefore, election campaigns are especially intense in states where there is no clear direction on wh

A. Blanco, P. Fonte, L. Lopes, M. Pimenta

The phase-out of hydro-fluorocarbons, owing to their high Global Warming Power, affecting the main gas used in Resistive Plate Chambers (RPCs), tetrafluoroethane C$_2$H$_2$F$_4$, has increased operational difficulties on existing systems and imposes strong restrictions on its use in new systems. This has motivated a new line of R\&D on sealed RPCs: RPCs that

Adam J. McRoberts, Roderich Moessner

Superdiffusion is surprisingly easily observed even in systems without the integrability underpinning this phenomenon. Indeed, the classical Heisenberg chain -- one of the simplest many-body systems, and firmly believed to be non-integrable -- evinces a long-lived regime of anomalous, superdiffusive spin dynamics at finite temperature. Similarly, superdiffus

Catherine McCarthy, Sarang Gopalakrishnan, Romain Vasseur

Finite-temperature spin transport in integrable isotropic spin chains (i.e., spin chains with continuous nonabelian symmetries) is known to be superdiffusive, with anomalous transport properties displaying remarkable robustness to isotropic integrability-breaking perturbations. Using a discrete-time classical model, we numerically study the crossover to conv

Edward A. Miller, David M. Williams

Versatile mixed finite element methods were originally developed by Chen and Williams for isothermal incompressible flows in "Versatile mixed methods for the incompressible Navier-Stokes equations," Computers & Mathematics with Applications, Volume 80, 2020. Thereafter, these methods were extended by Miller, Chen, and Williams to non-isothermal incompressibl

Roberto Gallotta, Graham Todd, Marvin Zammit, Sam Earle

Recent years have seen an explosive increase in research on large language models (LLMs), and accompanying public engagement on the topic. While starting as a niche area within natural language processing, LLMs have shown remarkable potential across a broad range of applications and domains, including games. This paper surveys the current state of the art ac

Eric Kee, Adam Pikielny, Kevin Blackburn-Matzen, Marc Levoy

We describe a system to remove real-world reflections from images for consumer photography. Our system operates on linear (RAW) photos, and accepts an optional contextual photo looking in the opposite direction (e.g., the "selfie" camera on a mobile device). This optional photo disambiguates what should be considered the reflection. The system is trained sol

CMS Collaboration

A search for heavy neutral leptons (HNLs) decaying in the CMS muon system is presented. A data sample is used corresponding to an integrated luminosity of 138 fb$^{-1}$ of proton-proton collisions at $\sqrt{s}$ = 13 TeV, recorded at the CERN LHC in 2016-2018. Decay products of long-lived HNLs could interact with the shielding materials in the CMS muon system

Nathan Walker, Tyler Parsotan, Davide Lazzati

Long-duration gamma-ray bursts (LGRBs), thought to be produced during core-collapse supernovae, may have a prominent neutron component in the outflow material. If present, neutrons can change how photons scatter in the outflow by reducing its opacity, thereby allowing the photons to decouple sooner than if there were no neutrons present. Understanding the de

Ben K. D. Pearce, Sarah M. Hörst, Christopher J. Cline, Mark J. Cintala

Impacts are critical to producing the aqueous environments necessary to stimulate prebiotic chemistry on Titan's surface. Furthermore, organic hazes resting on the surface are a likely feedstock of biomolecules. In this work, we conduct impact experiments on laboratory-produced organic haze particles and haze/sand mixtures and analyze these samples for life'

F. Crescimbeni, G. Franciolini, P. Pani, A. Riotto

The detection of a subsolar object in a compact binary merger is regarded as one of the smoking gun signatures of a population of primordial black holes~(PBHs). We critically assess whether these systems could be distinguished from stellar binaries, for example composed of white dwarfs or neutron stars, which could also populate the subsolar mass range. At v

Ping Gao

It has been shown in recent works that JT gravity with matter with two boundaries has a type II$_\infty$ algebra on each side. As the bulk spacetime between the two boundaries fluctuates in quantum nature, we can only define the entanglement wedge for each side in a pure algebraic sense. As we take the semiclassical limit, we will have a fixed long wormhole

M. Balboni, F. Gastaldello, A. Bonafede, A. Botteon

The connection between the thermal and non-thermal properties in galaxy clusters hosting radio halos seems fairly well established. However, a comprehensive analysis of such a connection has been made only for integrated quantities (e.g. $L_X - P_{radio}$ relation). In recent years new-generation radio telescopes have enabled the unprecedented possibility to

M. Rossetti, D. Eckert, F. Gastaldello, E. Rasia

The "Cluster HEritage project with \xmm: Mass Assembly and Thermodynamics at the Endpoint of structure formation" (CHEX-MATE) is a multi-year Heritage program, to obtain homogeneous XMM-Newton observations of a representative sample of 118 galaxy clusters. The observations are tuned to reconstruct the distribution of the main thermodynamic quantities of the

Abdullah Giray Yağlıkçı, Yahya Can Tuğrul, Geraldo F. Oliveira, İsmail Emir Yüksel

Read disturbance in modern DRAM chips is a widespread phenomenon and is reliably used for breaking memory isolation, a fundamental building block for building robust systems. RowHammer and RowPress are two examples of read disturbance in DRAM where repeatedly accessing (hammering) or keeping active (pressing) a memory location induces bitflips in other memor

Gecia Bravo-Hermsdorff

Human knowledge is largely implicit and relational -- do we have a friend in common? can I walk from here to there? In this work, we leverage the combinatorial structure of graphs to quantify human priors over such relational data. Our experiments focus on two domains that have been continuously relevant over evolutionary timescales: social interaction and s

Kyle DuFrene, Keegan Nave, Joshua Campbell, Ravi Balasubramanian

Advancing robotic grasping and manipulation requires the ability to test algorithms and/or train learning models on large numbers of grasps. Towards the goal of more advanced grasping, we present the Grasp Reset Mechanism (GRM), a fully automated apparatus for conducting large-scale grasping trials. The GRM automates the process of resetting a grasping envir

Fangzhou Wu, Ning Zhang, Somesh Jha, Patrick McDaniel

Large Language Model (LLM) systems are inherently compositional, with individual LLM serving as the core foundation with additional layers of objects such as plugins, sandbox, and so on. Along with the great potential, there are also increasing concerns over the security of such probabilistic intelligent systems. However, existing studies on LLM security oft

Vahid R. Asadi, Eric Culf, Alex May

A non-local quantum computation (NLQC) replaces an interaction between two quantum systems with a single simultaneous round of communication and shared entanglement. We study two classes of NLQC, $f$-routing and $f$-BB84, which are of relevance to classical information theoretic cryptography and quantum position-verification. We give the first non-trivial lo

Michele Del Zotto, Shani Nadir Meynet, Robert Moscrop

Geometric engineering is a collection of tools developed to establish dictionaries between local singularities in string theory and (supersymmetric) quantum fields. Extended operators and defects, as well as their higher quantum numbers captured by topological symmetries, can be encoded within geometric engineering dictionaries. In this paper we revisit and

Tony Mroczkowski, Patricio A. Gallardo, Martin Timpe, Aleksej Kiselev

The (sub)millimeter sky contains a vast wealth of information that is both complementary and inaccessible to other wavelengths. Over half the light we receive is observable at (sub)millimeter wavelengths, yet we have mapped only a small portion of the sky at sufficient spatial resolution and sensitivity to detect and resolve distant galaxies or star forming

Christopher J. Manser, Boris T. Gänsicke, Paula Izquierdo, Andrew Swan

There is overwhelming evidence that white dwarfs host planetary systems; revealed by the presence, disruption, and accretion of planetary bodies. A lower limit on the frequency of white dwarfs that host planetary material has been estimated to be roughly 25-50 per cent; inferred from the ongoing or recent accretion of metals onto both hydrogen-atmosphere and

J. Chisholm, D. A. Berg, R. Endsley, S. Gazagnes

Here we present high spectral resolution $\textit{JWST}$ NIRSpec observations of GN42437, a low-mass (log(M$_\ast/M_\odot)=7.9$), compact ($r_e < 500$pc), extreme starburst galaxy at $z=5.59$ with 13 emission line detections. GN42437 has a low-metallicity (5-10% Z$_\odot$) and its rest-frame H$\alpha$ equivalent width suggests nearly all of the observed stel

Arman Duha, Thomas Bilitewski

We study the non-equilibrium dynamics of a quantum spin 1/2 XXZ model confined in a two-dimensional bi-layer system, with couplings mediated by inverse power-law interactions, falling off with distance $r$ as $1/r^{\alpha}$, and spatio-temporal control of the spins enabled via local fields. An initial state of spins with opposite magnetization in the two lay

Christopher J. Manser, Paula Izquierdo, Boris T. Gänsicke, Andrew Swan

The Early Data Release (EDR) of the Dark Energy Spectroscopic Instrument (DESI) comprises spectroscopy obtained from 2020 December 14 to 2021 June 10. White dwarfs were targeted by DESI both as calibration sources and as science targets and were selected based on Gaia photometry and astrometry. Here we present the DESI EDR white dwarf catalogue, which includ

Irene Vanni, Stefania Salvadori, Valentina D'Odorico, George D. Becker

Unveiling the chemical fingerprints of the first (Pop III) stars is crucial for indirectly studying their properties and probing their massive nature. In particular, very massive Pop III stars explode as energetic Pair-Instability Supernovae (PISNe), allowing their chemical products to escape in the diffuse medium around galaxies, opening the possibility to

Amine Ben Mhenni, Dinh Van Tuan, Leonard Geilen, Marko M. Petrić

Coulomb interactions in atomically thin materials are uniquely sensitive to variations in the dielectric screening of the environment, which can be used to control quasiparticles and exotic quantum many-body phases. A static approximation of the dielectric response, where increased dielectric screening is predicted to cause an energy redshift of the exciton

Antonio Ambrosone, Marco Chianese, Antonio Marinelli

Star-forming and starburst galaxies (SFGs and SBGs) are powerful emitters of non-thermal $\gamma$-rays and neutrinos, due to their intense phases of star-formation activity, which should confine high-energy Cosmic-Rays (CRs) inside their environments. In this paper, using the publicly-available \texttt{fermitools}, we analyse 15.3 years of $\gamma$-ray betwe

Kartik Prabhu, Gautam Satishchandran

Any non-trivial scattering with massless fields in four spacetime dimensions will generically produce an out-state with memory. Scattering with any massless fields violates the standard assumption of asymptotic completeness -- that all "in" and "out" states lie in the standard (zero memory) Fock space -- and therefore leads to infrared (IR) divergences in th

A. Galan, G. B. Caminha, J. Knollmüller, J. Roth

Gravitational lensing by galaxy clusters involves hundreds of galaxies over a large redshift range and increases the likelihood of rare phenomena (supernovae, dark substructures, etc.). We present the detailed analysis of \elanz, a prominent quintuply imaged dusty star-forming galaxy ($\zs=2.29$), mainly lensed by three members of the massive galaxy cluster

The NNPDF Collaboration, Richard D. Ball, Andrea Barontini, Alessandro Candido

We extend the existing leading (LO), next-to-leading (NLO), and next-to-next-to-leading order (NNLO) NNPDF4.0 sets of parton distribution functions (PDFs) to approximate next-to-next-to-next-to-leading order (aN$^3$LO). We construct an approximation to the N$^3$LO splitting functions that includes all available partial information from both fixed-order compu

Giorgos Korkidis, Vasiliki Pavlidou

The average matter density within the turnaround scale, which demarcates where galaxies shift from clustering around a structure to joining the expansion of the Universe, is an important cosmological probe. However, a measurement of the mass enclosed by the turnaround radius is difficult. Analyses of the turnaround scale in simulated galaxy clusters place th

Arindam Bhattacharya, Jordan Cotler, Aurélien Dersy, Matthew D. Schwartz

Collective coordinates are frequently employed in path integrals to manage divergences caused by fluctuations around saddle points that align with classical symmetries. These coordinates parameterize a manifold of zero modes and more broadly provide judicious coordinates on the space of fields. However, changing from local coordinates around a saddle point t

Elke Roediger, Iraj Vaezzadeh, Paul Nulsen

We apply a toy model based on 'pendulum waves' to gas sloshing in galaxy clusters. Starting with a galaxy cluster potential filled with a hydrostatic intra-cluster medium (ICM), we perturb all ICM by an initial small, unidirectional velocity, i.e., an instantaneous kick. Consequently, each parcel of ICM will oscillate due to buoyancy with its local Brunt-V\"

P. Nazari, B. Tabone, A. Ahmadi, S. Cabrit

Protostellar disks are known to accrete, however, the exact mechanism that extracts the angular momentum and drives accretion in the low-ionization "dead" region of the disk is under debate. In recent years, magneto-hydrodynamic (MHD) disk winds have become a popular solution. Yet, observations of these winds require both high spatial resolution (${\sim}10$s

Amir Jalalirad, Davide Belli, Bence Major, Songwon Jee

In urban environments, where line-of-sight signals from GNSS satellites are frequently blocked by high-rise objects, GNSS receivers are subject to large errors in measuring satellite ranges. Heuristic methods are commonly used to estimate these errors and reduce the impact of noisy measurements on localization accuracy. In our work, we replace these error es

Pedro M. Cônsoli, Matthias Vojta

Altermagnetism, a type of magnetic order that combines properties of ferro- and antiferromagnets, has stirred great interest lately not only as a promising source of spintronics applications, but also as a potential gateway to exotic phases of matter. Here, we demonstrate how to generalize collinear altermagnetism to SU($N$) magnets with $N>2$. Guided by sym

Enrique Lopez-Rodriguez, Le Ngoc Tram

Magnetic fields (B-fields) in galaxies have recently been traced using far-infrared and sub-mm polarimetric observations with SOFIA, JCMT, and ALMA. The main assumption is that dust grains are magnetically aligned with the local B-field in the interstellar medium (ISM). However, the range of physical conditions of the ISM, dust grain sizes, and B-field stren

Songyang Pu, Jay D. Sau, Rui-Xing Zhang

We show that a three-dimensional (3D) fully gapped type-II superconductor can feature emergent in-gap Fermi surfaces of Caroli-de Gennes Matricon (CdGM) quasiparticles in the presence of an Abrikosov vortex lattice. In particular, these CdGM Fermi surfaces manifest in the emergent 3D band structure enabled by the intervortex tunneling physics, and their stab

Andrew A. Allocca

Many strongly correlated systems exhibit strange metallic behavior in certain parameter regimes characterized by anomalous transport properties that are irreconcilable with a Fermi-liquid-like description in terms of quasiparticles. The Hubbard model is a standard theoretical starting point to examine the properties of such systems and also exhibits non-Ferm

Tao Liu, Alexander A. Penin, Abdur Rehman

We study the light quark effect on the Higgs boson production in association with a jet at the LHC in the intermediate transverse momentum region between the quark and the Higgs boson mass scales. Though the effect is suppressed by the small Yukawa coupling, it is enhanced by large logarithms of the quark mass ratio to the Higgs boson mass or transverse mome

Stephen Thorp, Kaisey S. Mandel, David O. Jones, Robert P. Kirshner

We use rest-frame optical and near-infrared (NIR) observations of 42 Type Ia supernovae (SNe Ia) from the Carnegie Supernova Project at low-$z$ and 37 from the RAISIN Survey at high-$z$ to investigate correlations between SN Ia host galaxy dust, host mass, and redshift. This is the first time the SN Ia host galaxy dust extinction law at high-$z$ has been est

J. W. Petley, L. K. Morabito, A. L. Rankine, G. T. Richards

The origin of radio emission in different populations of radio-quiet quasars is relatively unknown, but recent work has uncovered various drivers of increased radio-detection fraction. In this work, we pull together three known factors: optical colour ($g-i$), \CIV Distance (a proxy for $L/L_{Edd}$) and whether or not the quasar contains broad absorption lin

Ángel L. Corps, Armando Relaño, Jad C. Halimeh

In recent years, various notions of dynamical phase transitions have emerged to describe far-from-equilibrium criticality. A unifying framework connecting these different concepts is still missing, and would provide significant progress towards understanding far-from-equilibrium quantum many-body universality. Initializing our system in a thermal ensemble an

Billy Edwards, Quentin Changeat

We present a comprehensive atmospheric retrieval study of the hot Jupiter WASP-77A\,b using eclipse observations from the Hubble Space Telescope (HST) and JWST. Using atmospheric retrievals, the spectral features of H$_2$O, CO, and TiO are identified, with volume mixing ratios estimated at log$_{\rm 10}$(VMR) = -4.40$^{+0.14}_{-0.11}$, -4.44$^{+0.34}_{-0.28}

Zhuoling Li, Xiaogang Xu, SerNam Lim, Hengshuang Zhao

Realizing unified 3D object detection, including both indoor and outdoor scenes, holds great importance in applications like robot navigation. However, involving various scenarios of data to train models poses challenges due to their significantly distinct characteristics, \eg, diverse geometry properties and heterogeneous domain distributions. In this work,

Manuel Pratelli, Fabio Saracco, Marinella Petrocchi

With the primary goal of raising readers' awareness of misinformation phenomena, extensive efforts have been made by both academic institutions and independent organizations to develop methodologies for assessing the trustworthiness of online news publishers. Unfortunately, existing approaches are costly and face critical scalability challenges. This study p

Elie Abdo, Fizay-Noah Lee

We prove logarithmic Sobolev inequalities on higher-dimensional bounded smooth domains based on novel Gagliardo-Nirenberg type interpolation inequalities. Moreover, we use them to address the long-time dynamics of some nonlinear nonlocal drift-diffusion models and prove the exponential decay of their solutions to constant steady states.

Haoxiang Wang, Yong Lin, Wei Xiong, Rui Yang

Fine-grained control over large language models (LLMs) remains a significant challenge, hindering their adaptability to diverse user needs. While Reinforcement Learning from Human Feedback (RLHF) shows promise in aligning LLMs, its reliance on scalar rewards often limits its ability to capture diverse user preferences in real-world applications. To address t

Richard A. Norte

The concept of negative temperature (T < 0) is unique to quantum physics and describes systems that are hotter than any positive temperature system. For decades negative temperatures have been shown in a number of spin systems, but experiments only recently demonstrated atomic ensembles with negative temperatures in their motional degrees of freedom. An obse

Kilian Pfeiffer, Konstantinos Balaskas, Kostas Siozios, Jörg Henkel

In Federated Learning (FL), devices that participate in the training usually have heterogeneous resources, i.e., energy availability. In current deployments of FL, devices that do not fulfill certain hardware requirements are often dropped from the collaborative training. However, dropping devices in FL can degrade training accuracy and introduce bias or unf

Weichen Winston Yin, Liang Dai, Junwu Huang, Lingyuan Ji

We propose a novel statistical method to measure cosmic birefringence and demonstrate its power in probing parity violation due to axions. Exploiting an empirical correlation between the integrated radio polarization direction of a spiral galaxy and its apparent shape, we devise an unbiased minimum-variance estimator for the rotation angle, which should achi

Xinyou Wang, Zaixiang Zheng, Fei Ye, Dongyu Xue

This paper introduces diffusion protein language model (DPLM), a versatile protein language model that demonstrates strong generative and predictive capabilities for protein sequences. We first pre-train scalable DPLMs from evolutionary-scale protein sequences within a generative self-supervised discrete diffusion probabilistic framework, which generalizes l

Gregory Coppola

Given the emergent reasoning abilities of large language models, information retrieval is becoming more complex. Rather than just retrieve a document, modern information retrieval systems advertise that they can synthesize an answer based on potentially many different documents, conflicting data sources, and using reasoning. But, different kinds of questions

Vivekanand Mohapatra, Pravin Kumar Natwariya, Alekha C. Nayak

We study the constraints on primordial magnetic fields (PMFs) in light of the global 21-cm signal observed during the dark ages. Primordial magnetic fields can heat the intergalactic medium (IGM) via magnetohydrodynamic effects. We investigate the impact of magnetic heating on the dark ages global 21-cm signal and constrain the present-day strength of primor

Sylvia K. Lewin, Peter Czajka, Corey E. Frank, Gicela Saucedo Salas

Heavy fermion UTe$_2$ is a promising candidate for topological superconductivity that also exhibits multiple high-field superconducting phases. The SC$_{\rm{FP}}$ phase has only been observed in off-axis magnetic fields in the $bc$ plane at fields greater than 40 teslas, a striking scale given its critical temperature of only 2 kelvins. Here, we extend measu

Danny Halawi, Fred Zhang, Chen Yueh-Han, Jacob Steinhardt

Forecasting future events is important for policy and decision making. In this work, we study whether language models (LMs) can forecast at the level of competitive human forecasters. Towards this goal, we develop a retrieval-augmented LM system designed to automatically search for relevant information, generate forecasts, and aggregate predictions. To facil

Karim Carrion, Pedro Carrilho, Alessio Spurio Mancini, Alkistis Pourtsidou

We present constraints on the Dark Scattering model through cosmic shear measurements from the Kilo Degree Survey (KiDS-1000), using an accelerated pipeline with novel emulators produced with $\tt{CosmoPower}$. Our main emulator, for the Dark Scattering non-linear matter power spectrum, is trained on predictions from the halo model reaction framework, previo