May 2024 arXiv papers — page 90

Antonia Fernandez-Figueroa, Glenn G. Kacprzak, Nikole M. Nielsen, Tania M. Barone

While most galaxies live in group environments where they undergo an accelerated evolution, the characteristics of their circumgalactic medium (CGM) remain uncertain. We present an analysis of the CGM of two galaxy groups in different stages of interaction: (G1) a close pair of galaxies ($z=0.043$) separated by 87 kpc that do not show signs of interactions a

M. O. Astashenkov, A. V. Bedda, K. V. Parfenov, P. A. Vshivtseva

This study is devoted to dilaton generation in propagation of magnetic dipole waves of pulsar in a galactic magnetic field. It is shown that in this process it's necessary to take into account the presence of a reflective index of matter distributed in the galaxy. According to obtained estimates influence of the gravitational field of pulsars and magnetars o

Mohammad Akyash, Hadi Mardani Kamali

The rise of instruction-tuned Large Language Models (LLMs) marks a significant advancement in artificial intelligence (AI) (tailored to respond to specific prompts). Despite their popularity, applying such models to debug security vulnerabilities in hardware designs, i.e., register transfer language (RTL) modules, particularly at system-on-chip (SoC) level,

Walker M Jones, Melanie A R Reber

The generation of shaped laser beams, or structured light, is of interest in a wide range of fields, from microscopy to fundamental physics. There are several ways to make shaped beams, most commonly using spatial light modulators comprised of pixels of liquid crystals. These methods have limitations on the wavelength, pulse duration, and average power that

Josefa Caballero, Łukasz Płociniczak, Kishin Sadarangani

In this paper, we examine the solvability of a functional equation in a Lipschitz space. As an application, we use our result to determine the existence and uniqueness of solutions to an equation describing a specific type of choice behavior model for the learning process of the paradise fish. Finally, we present some concrete examples where, using numerical

Daniel Sadasivan, Cole Cantu, Cecilia Marsh, Andrew Graham

Recent research has extended methods from the fields of thermodynamics and statistical mechanics into other disciplines. Most notably, one recent work creates a unified theoretical framework to understand evolutionary biology, machine learning, and thermodynamics. We present simulations of biological evolution used to test this framework. The test simulates

Yang Chen, Cheng-Der Fuh, Chu-Lan Michael Kao

Hidden Markov models (HMM) have been widely used by scientists to model stochastic systems: the underlying process is a discrete Markov chain and the observations are noisy realizations of the underlying process. Determining the number of hidden states for an HMM is a model selection problem, which is yet to be satisfactorily solved, especially for the popul

Jeffrey Covington, Nan Chen, Stephen Wiggins, Evelyn Lunasin

Mesoscale eddies are critical in ocean circulation and the global climate system. Standard eddy identification methods are usually based on deterministic optimal point estimates of the ocean flow field. However, uncertainty exists in estimating the flow field due to noisy, sparse, and indirect observations and turbulent flow models. Because of the intrinsic

Paula Cadavid, Mary Luz Rodiño Montoya, Pablo M. Rodriguez, Sebastian J. Vidal

A connected graph can be associated with two distinct evolution algebras. In the first case, the structural matrix is the adjacency matrix of the graph itself. In the second case, the structural matrix is the transition probabilities matrix of the symmetric random walk on the same graph. It is well-known that, for a non-singular graph, both evolution algebra

Zahra Fatemi, Jean Pouget-Abadie, Elena Zheleva

The presence of interference, where the outcome of an individual may depend on the treatment assignment and behavior of neighboring nodes, can lead to biased causal effect estimation. Current approaches to network experiment design focus on limiting interference through cluster-based randomization, in which clusters are identified using graph clustering, and

Bastian Castorene, Francisco J. Peña, Ariel Norambuena, Sergio E. Ulloa

This study investigates the anisotropic effects on a system of three qubits with chain and ring topology, described by the antiferromagnetic Heisenberg XXX model subjected to a homogeneous magnetic field. We explore the Stirling and Otto cycles and find that easy-axis anisotropy significantly enhances engine efficiency across all cases. At low temperatures,

Jacco Ton, Théo Travers, Jamal Soltani, Daniel Wijnperle

Accurate detection and characterization of nanoparticles within confined spaces is crucial for applications ranging from nanofluidics to biotechnology. We present a novel approach that combines interferometric scattering (iSCAT) detection with trapping by dielectrophoresis (DEP) to achieve label-free detection of nanoparticles that are trapped and/or actuate

Balbeer Singh, Nibedita Padhi, Rashmi R. Nayak

Acoustic black holes, analogs of gravitational black holes created in fluid systems, have recently been embedded within Schwarzschild spacetime using the Gross-Pitaevskii theory, leading to configurations with both event and acoustic horizons. This study examines the motion of vortices, modeled as unit-mass relativistic test particles, around a slow-rotating

John C. Simmons, Joseph M. Winograd

The spread of false and misleading information is receiving significant attention from legislative and regulatory bodies. Consumers place trust in specific sources of information, so a scalable, interoperable method for determining the provenance and authenticity of information is needed. In this paper we analyze the posting of broadcast news content to a so

E. Provornikova, V. G. Merkin, A. Vourlidas, A. Malanushenko

Variations of the magnetic field within solar coronal mass ejections (CMEs) in the heliosphere depend on the CME`s magnetic structure as it leaves the solar corona and its subsequent evolution through interplanetary space. To account for this evolution, we developed a new numerical model of the inner heliosphere that simulates the propagation of a CME throug

Dolev Bashi, Vasily Belokurov, Simon Hodgkin

The study of binary stars in the Galactic halo provides crucial insights into the dynamical history and formation processes of the Milky Way. In this work, we aim to investigate the binary fraction in a sample of accreted and in-situ halo stars, focusing on short-period binaries. Utilising data from Gaia DR3, we analysed the radial velocity (RV) uncertainty

Xavier Blot, Danilo Lewanski, Sergey Shadrin

We establish the Miura equivalence of two integrable systems associated to a semi-simple cohomological field theory: the double ramification hierarchy of Buryak and the Dubrovin-Zhang hierarchy. This equivalence was conjectured by Buryak and further refined by Buryak, Dubrovin, Gu\'er\'e, and Rossi.

Jones Yeboah, Saheed Popoola

In software practice, static analysis tools remain an integral part of detecting defects in software and there have been various tools designed to run the analysis in different programming languages like Java, C++, and Python. This paper presents an empirical comparison of popular static analysis tools for identifying software defects using several datasets

D. Kinzebulatov, Yu. A. Semenov

We consider diffusion operator $-\Delta + b \cdot \nabla$ in $\mathbb R^d$, $d \geq 3$, with drift $b$ in a large class of locally unbounded vector fields that can have critical-order singularities. Covering the entire range of admissible magnitudes of singularities of $b$ (but excluding the borderline value), we construct a strongly continuous Feller semigr

Yang Chen, Ward Manchester, Meng Jin, Alexei Pevtsov

We give a gentle introduction to solar imaging data, focusing on the challenges and opportunities of data-driven approaches for solar eruptions. The various solar phenomenon prediction problems that might benefit from statistical methods are presented. Available data products and software are described. State-of-the-art solar eruption forecasting models with

Nicholas Peskosky, Nicholas Ernst, Miloš Burger, Jon Murphy

We experimentally demonstrate enhanced absorption of near relativistic optical vortex beams in $\mathrm{D_2O}$ plasmas to generate a record fast-neutron yield of $1.45 \times 10^6$ n/s/sr. Beams with a topological charge of 5 were shown to deliver up to a 3.3 times enhancement of fast-neutron yield over a Gaussian focused beam of the same energy but having t

Antonio Lages, Pedro Lopes

Quandles are right-invertible, right-self distributive (and idempotent) algebraic structures. Therefore, right translations are quandle automorphisms. It has been interesting to look into finite quandles by way of the cycle structures their right translations may have. For each quandle, the list of these cycle structures is known as the profile of the quandl

Wentao Wang, Xi Xiao, Mingjie Liu, Qing Tian

The accurate segmentation of medical images is crucial for diagnosing and treating diseases. Recent studies demonstrate that vision transformer-based methods have significantly improved performance in medical image segmentation, primarily due to their superior ability to establish global relationships among features and adaptability to various inputs. Howeve

Yuyan Wang, Cheenar Banerjee, Samer Chucri, Fabio Soldo

It has become increasingly clear that recommender systems that overly focus on short-term engagement prevents users from exploring diverse interests, ultimately hurting long-term user experience. To tackle this challenge, numerous diversification algorithms have been proposed. These algorithms typically rely on measures of item similarity, aiming to maximize

José Daniel Pascual-Triana, Alberto Fernández, Javier Del Ser, Francisco Herrera

Explainable Artificial Intelligence (XAI) is a pivotal research domain aimed at understanding the operational mechanisms of AI systems, particularly those considered ``black boxes'' due to their complex, opaque nature. XAI seeks to make these AI systems more understandable and trustworthy, providing insight into their decision-making processes. By producing

Michelle F. Miranda

Task-evoked functional magnetic resonance imaging studies, such as the Human Connectome Project (HCP), are a powerful tool for exploring how brain activity is influenced by cognitive tasks like memory retention, decision-making, and language processing. A fast Bayesian function-on-scalar model is proposed for estimating population-level activation maps linke

Valeri V. Makarov, Sébastien Lambert, Phil Cigan, Christopher DiLullo

Astronomical time series often have non-uniform sampling in time, or irregular cadences, with long gaps separating clusters of observations. Some of these data sets are also explicitly non-Gaussian with respect to the expected model fit, or the simple mean. The standard Lomb-Scargle periodogram is based on the least squares solution for a set of test periods

Jorge Iglesias Aldo Portela

Devaney defines a function as chaotic if it satisfies the following three conditions: transitivity, having a dense set of periodic points, and sensitive dependence on initial conditions. In \cite{3}, it was demonstrated that the first two conditions imply the third. This result was generalized in \cite{aak} by replacing the density of periodic points with th

Daniel Commey, Sena Hounsinou, Garth V. Crosby

This paper presents a framework for securing blockchain-based IoT systems by integrating Physical Unclonable Functions (PUFs) and Zero-Knowledge Proofs (ZKPs) within a Hyperledger Fabric environment. The proposed framework leverages PUFs for unique device identification and ZKPs for privacy-preserving authentication and transaction processing. Experimental r

Gaston A. Brouwer, Jonathan Joe, Abby A. Noble, Matt Noble

In this work, we consider a number of problems defined on the triangular lattice with $n$ rows, which we will denote as $T_n$. Define a \textit{proper coloring} to be an assignment of colors to the points of $T_n$ such that no three points constituting the vertices of an equilateral triangle all receive the same color, and denote by $f(n)$ the smallest possi

Szabolcs Borsanyi, Zoltan Fodor, Jana N. Guenther, Ruben Kara

The crossover from hadronic to quark matter is understood to be both a deconfinement as well as a chiral symmetry restoring transition. Here, we study observables related to both aspects using lattice simulations: the Polyakov loop and its derivatives and the chiral condensate and its derivatives. At zero baryochemical potential, and infinite volume, the chi

Henri Manninen, Markus Lippus, Georg Rute

Dynamic Line Rating (DLR) systems are crucial for renewable energy integration in transmission networks. However, traditional methods relying on sensor data face challenges due to the impracticality of installing sensors on every pole or span. Additionally, sensor-based approaches may struggle predicting DLR in rapidly changing weather conditions. This paper

Mohammad Ali Labbaf Khaniki, Nazanin Mahjourian, Mohammad Manthouri

Lung segmentation in chest X-ray images is a critical task in medical image analysis, enabling accurate diagnosis and treatment of various lung diseases. In this paper, we propose a novel approach for lung segmentation by integrating Hierarchical SegNet with a proposed multi-modal attention mechanism. The channel attention mechanism highlights specific featu

Xiucai Ding, Rong Ma

Integrative analysis of multiple heterogeneous datasets has become standard practice in many research fields, especially in single-cell genomics and medical informatics. Existing approaches oftentimes suffer from limited power in capturing nonlinear structures, insufficient account of noisiness and effects of high-dimensionality, lack of adaptivity to signal

Pierre Yves Gaudreau Lamarre

We study the semigroups of random Schr\"odinger operators of the form $\widehat{H}f=-\frac12f''+(V+\xi)f$, where $f:I\to\mathbb F^r$ ($\mathbb F=\mathbb R,\mathbb C,\mathbb H$) are vector-valued functions on a possibly infinite interval $I\subset\mathbb R$ that satisfy a mix of Robin and Dirichlet boundary conditions, $V$ is a deterministic diagonal potentia

Valeri V. Makarov, Andrei Tokovinin

A large number of candidate binary stars with apparent acceleration on the sky has emerged from analysis of astrometric data collected by the Hipparcos, Tycho-2, and Gaia space missions. Although the apparent acceleration can serve as a relatively reliable indicator of binarity, it provides scarce information about the orbital and physical parameters of the

Edward Y. Chang

Misdiagnosis is a significant issue in healthcare, leading to harmful consequences for patients. The propagation of mislabeled data through machine learning models into clinical practice is unacceptable. This paper proposes EVINCE, a system designed to 1) improve diagnosis accuracy and 2) rectify misdiagnoses and minimize training data errors. EVINCE stands

S. Jalalzadeh, H. Moradpour, H. Tebyanian

We propose that the spectrum of the surface area of the apparent horizon (AH) of de Sitter (dS) spacetime leads to corrected temperature and entropy of the dS spacetime, offering new insights into its thermodynamic properties. This is done by employing the spectrum of the AH radius, acquired from the Wheeler--DeWitt (WDW) equation, together with the Stefan--

NEXT Collaboration, N. Byrnes, E. Dey, F. W. Foss

The imaging of individual Ba$^{2+}$ ions in high pressure xenon gas is one possible way to attain background-free sensitivity to neutrinoless double beta decay and hence establish the Majorana nature of the neutrino. In this paper we demonstrate selective single Ba$^{2+}$ ion imaging inside a high-pressure xenon gas environment. Ba$^{2+}$ ions chelated with

Md. Toukir Ahmed, Ocean Monjur, Mohammed Kamruzzaman

Hyperspectral imaging (HSI) has recently emerged as a promising tool for many agricultural applications; however, the technology cannot be directly used in a real-time system due to the extensive time needed to process large volumes of data. Consequently, the development of a simple, compact, and cost-effective imaging system is not possible with the current

Bruno Scarone, Alfredo Viola, Renée J. Miller, Ricardo Baeza-Yates

The widespread use of machine learning and data-driven algorithms for decision making has been steadily increasing over many years. \emph{Bias} in the data can adversely affect this decision-making. We present a new mitigation strategy to address data bias. Our methods are explainable and come with mathematical guarantees of correctness. They can take advant

Dasith Edirisinghe, Kavinda Rajapakse, Pasindu Abeysinghe, Sunimal Rathnayake

Microservices architecture, known for its agility and efficiency, is an ideal framework for cloud-based software development and deployment. When integrated with containerization and orchestration systems, resource management becomes more streamlined. However, cloud computing costs remain a critical concern, necessitating effective strategies to minimize exp

Desmond Weisenberg

Erd\H{o}s and Graham asked whether any sparse enough admissible set of natural numbers can be translated into a subset of the primes. By using a greedy construction involving powers of primitive roots, we prove that there exist arbitrarily sparse infinite admissible sets that cannot be translated into a subset of the primes, thus answering this question in t

Štěpán Šmíd, Roberto Bondesan

Predicting properties across system parameters is an important task in quantum physics, with applications ranging from molecular dynamics to variational quantum algorithms. Recently, provably efficient algorithms to solve this task for ground states within a gapped phase were developed. Here we dramatically improve the efficiency of these algorithms by showi

Federico Lozano-Cuadra, Beatriz Soret, Israel Leyva-Mayorga, Petar Popovski

This paper introduces a full solution for decentralized routing in Low Earth Orbit satellite constellations based on continual Deep Reinforcement Learning (DRL). This requires addressing multiple challenges, including the partial knowledge at the satellites and their continuous movement, and the time-varying sources of uncertainty in the system, such as traf

M. Kolesik

The propagation-effects reshaping the excitation pulse are known to exhibit a strong influence on the high-harmonic generation (HHG) in solid-state media. Previous measurements showed that the mid-infrared pulse dynamics, most importantly the nonlinear loss and spectral broadening, can dampen or even extinguish the highest harmonic peaks. Despite the importa

Tucker Allen, Minh Nguyen, Daniel Neuhauser

A low-cost approach for stochastically sampling static exchange during TDHF-type propagation is presented. This enables the use of an excellent hybrid DFT starting point for stochastic GW quasiparticle energy calculations. Generalized Kohn-Sham molecular orbitals and energies, rather than those of a local-DFT calculation, are used for building the Green's fu

Jinghao Lyu, Kyle J. Ray, James P. Crutchfield

Entropy production (EP) is a central quantity in nonequilibrium physics as it monitors energy dissipation, irreversibility, and free energy differences during thermodynamic transformations. Estimating EP, however, is challenging both theoretically and experimentally due to limited access to the system dynamics. For overdamped Langevin dynamics and Markov jum

Stéphane Pouget, Louis-Noël Pouchet, Jason Cong

High-Level Synthesis enables the rapid prototyping of hardware accelerators, by combining a high-level description of the functional behavior of a kernel with a set of micro-architecture optimizations as inputs. Such optimizations can be described by inserting pragmas e.g. pipelining and replication of units, or even higher level transformations for HLS such

Temple He, Prahar Mitra, Kathryn M. Zurek

We demonstrate a tree-level equivalence between four distinct infrared objects in $(d+2)$-dimensional abelian gauge theories. These are ($i$) the large gauge charge $Q_\varepsilon$ where the function $\varepsilon$ on the sphere parameterizing large gauge transformations is identified with the Goldstone mode $\theta$ of spontaneously broken large gauge symmet

Adrian E. Bayer, Jia Liu, Christina D. Kreisch, Alice Pisani

Massive neutrinos suppress the growth of cosmic structure on nonlinear scales, motivating the use of information beyond the power spectrum to tighten constraints on the neutrino mass, for example by considering cosmic voids. It was recently proposed that constraints on neutrino mass from the halo mass function (HMF) can be improved by considering only the ha

Mustafa Engin Danis, Duc Truong, Ismael Boureima, Oleg Korobkin

In this study, we introduce a tensor-train (TT) finite difference WENO method for solving compressible Euler equations. In a step-by-step manner, the tensorization of the governing equations is demonstrated. We also introduce \emph{LF-cross} and \emph{WENO-cross} methods to compute numerical fluxes and the WENO reconstruction using the cross interpolation te

Yu Liu, Utkarsh Pratiush, Jason Bemis, Roger Proksch

The rapid development of computation power and machine learning algorithms has paved the way for automating scientific discovery with a scanning probe microscope (SPM). The key elements towards operationalization of automated SPM are the interface to enable SPM control from Python codes, availability of high computing power, and development of workflows for

Manas Gogoi, Sambhavi Tiwari, Shekhar Verma

The reason for Meta Overfitting can be attributed to two factors: Mutual Non-exclusivity and the Lack of diversity, consequent to which a single global function can fit the support set data of all the meta-training tasks and fail to generalize to new unseen tasks. This issue is evidenced by low error rates on the meta-training tasks, but high error rates on

David Möckli, Murilo Kessler de Azambuja

This paper serves as a primer on superconductivity, inviting students for further investigation. Although the theory of superconductivity is a many-body quantum theory, here we take a more didactic route based on thermodynamics and symmetry. We briefly survey the more than a century-old field and provide a one-sentence definition of a superconductor. Surpris

Saurabh W. Jha, Dana I. Casetti-Dinescu, Gary M. Bernstein, Matthew J. Hayes

The Astro2020 Decadal Survey recognizes time-domain astronomy as a key science area over the next decade and beyond. With over 30 years of HST data and the potential for 20 years of JWST operations, these flagship observatories offer an unparalleled prospect for a half-century of space-based observations in the time domain. To take best advantage of this opp

Bao-Fei Li, Meysam Motaharfar, Parampreet Singh

In order to investigate the potential observational signals of different regularization ambiguities in loop quantum cosmological models, we systematically compute and compare the primordial scalar power spectra and the resulting angular power spectra in the standard loop quantum cosmology (LQC) and its Thiemann regularized versions -- modified LQC-I/II (mLQC

Marcin Podhajski, Jan Dubiński, Franziska Boenisch, Adam Dziedzic

Graph Neural Networks (GNNs) are recognized as potent tools for processing real-world data organized in graph structures. Especially inductive GNNs, which allow for the processing of graph-structured data without relying on predefined graph structures, are becoming increasingly important in a wide range of applications. As such these networks become attracti

Xiaoyang Shen, Chonghao Wang, Ruiping Guo, Zhiming Xu

Recent experimental discovery of fractional Chern insulator in moir\'e Chern band in twisted transition metal dichalocogenide homobilayers has sparked intensive interest in exploring the ways of engineering band topology and correlated states in moir\'e systems. In this letter, we demonstrate that, with an additional exchange interaction induced by proximity

Taha Ameen, Bruce Hajek

This work studies fundamental limits for recovering the underlying correspondence among multiple correlated graphs. In the setting of inhomogeneous random graphs, we present and analyze a matching algorithm: first partially match the graphs pairwise and then combine the partial matchings by transitivity. Our analysis yields a sufficient condition on the prob

Zeno Bacciconi, Hernan Xavier, Iacopo Carusotto, Titas Chanda

Recent breakthrough experiments have demonstrated how it is now possible to explore the dynamics of quantum Hall states interacting with quantum electromagnetic cavity fields. While the impact of strongly coupled non-local cavity modes on integer quantum Hall physics has been recently addressed, its effects on fractional quantum Hall (FQH) liquids -- and, mo

Errico J. Russo

We present a new category of quantum Lissajous states for a 2DHO having commensurate angular frequencies. The states result from the projection of ordinary coherent states onto a degenerate subspace of the 2DHO. In this way, new, non-classical quantum mechanically stationary states arise from the classical but non-stationary coherent states. The connection t

Vitor Cardoso, Gregorio Carullo, Marina De Amicis, Francisco Duque

Stationary, asymptotically flat, black hole solutions of the vacuum field equations of General Relativity belong to the Kerr family. But how does one approach this state, dynamically? Linearized fluctuations decay at late times, at fixed spatial position, as a Price power law for generic initial conditions. However, little attention was paid to forced and no

K. J. Joven, V. M. Bastidas

Operator spreading has profound implications in diverse fields ranging from statistical mechanics and blackhole physics to quantum information. The usual way to quantify it is through out-of-time-order correlators (OTOCs), which are the quantum analog to Lyapunov exponents in classical chaotic dynamics. In this work we explore the phenomenon of operator spre

Yi Qin, Ching Hua Lee, Linhu Li

The non-Hermitian skin effect (NHSE) is a fascinating phenomenon in nonequilibrium systems where eigenstates massively localize at the systems' boundaries, pumping (quasi-)particles loaded in these systems unidirectionally to the boundaries. Its interplay with many-body effects have been vigorously studied recently, and inter-particle repulsion or Fermi dege

S. Schuldt, C. Grillo, G. B. Caminha, A. Mercurio

We present new VLT/MUSE observations of the Hubble Frontier Field (HFF) galaxy cluster MACS J1149.5+2223, lensing the well-known supernova "Refsdal" into multiple images, which enabled the first cosmological applications with a strongly lensed supernova. Thanks to these data, targeting a northern region of the cluster and thus complementing our previous MUSE

Brooke Polak, Mordecai-Mark Mac Low, Ralf S. Klessen, Simon Portegies Zwart

Two main mechanisms have classically been proposed for the formation of runaway stars. In the binary supernova scenario (BSS), a massive star in a binary explodes as a supernova, ejecting its companion. In the dynamical ejection scenario, a star is ejected during a strong dynamical encounter between multiple stars. We propose a third mechanism for the format

Haipeng An, Shuailiang Ge, Jia Liu, Mingzhe Liu

Dark photon dark matter (DPDM) emerges as a compelling candidate for ultralight bosonic dark matter, detectable through resonant conversion into photons within a plasma environment. This study employs in-situ measurements from the Parker Solar Probe (PSP), the first spacecraft to venture into the solar corona, to probe for DPDM signatures. The PSP in-situ me

R. Pascale, F. Annibali, M. Tosi, C. Nipoti

From deep imaging data obtained with the Large Binocular Telescope as part of the Smallest Scale of Hierarchy Survey (SSH), we have discovered low-surface brightness tidal features around NGC 5238 and UGC 8760, two nearby and relatively isolated dwarf galaxies with stellar masses of approximately $10^8 M_\odot$ and $2\times10^7 M_\odot$, respectively. In thi

Paulo Areyuna C., A. E. Cárcamo Hernández, Vishnudath K. N., Sergey Kovalenko

We propose an extended Left-Right symmetric model with an additional global symmetry $U(1)_X$, which after spontaneous symmetry breaking collapses to a residual subgroup $\mathbb{Z}_2$, ensuring that the light active neutrino masses are generated via a double seesaw mechanism at two loop level, with the Dirac submatrix arising at one loop. It also guarantees

Kevin S. Croker, Gregory Tarlé, Steve P. Ahlen, Brian G. Cartwright

Recent baryon acoustic oscillation (BAO) measurements by the Dark Energy Spectroscopic Instrument (DESI) provide evidence that dark energy (DE) evolves with time, as parameterized by a $w_0 w_a$ equation of state. Cosmologically coupled black holes (BHs) provide a DE source that naturally evolves with time, because BH production tracks cosmic star-formation.

Jonathan Gomez Barrientos, Katherine de Kleer, Bethany L. Ehlmann, Francois L. H. Tissot

Ground-based observations of `Barbarian' L-type asteroids at 1 to 2.5-$\mu$m indicate that their near-infrared spectra are dominated by the mineral spinel, which has been attributed to a high abundance of calcium-aluminum inclusions (CAIs) -- the first solids to condense out of the protoplanetary disk during the formation of the Solar System. However, the sp

Adrian Ka-Wai Chung, Nicolas Yunes

After black holes collide, the remnant settles to a stationary state by emitting gravitational waves. Once non-linearities subside, these ringdown waves are dominated by exponentially-damped sinusoids, or quasinormal modes. We develop a general method using perturbative spectral expansions to calculate the quasinormal-mode frequencies and damping times in a

Chao Yin, Rahul Nandkishore, Andrew Lucas

We prove the existence of extensive many-body Hamiltonians with few-body interactions and a many-body mobility edge: all eigenstates below a nonzero energy density are localized in an exponentially small fraction of "energetically allowed configurations" within Hilbert space. Our construction is based on quantum perturbations to a classical low-density parit

Penghao Zhu, Shi Feng, Kang Wang, Tao Xiang

We propose a mechanism to explain the emergence of an intermediate gapless spin liquid phase in the antiferromagnetic Kitaev model in an externally applied magnetic field, sandwiched between the well-known gapped chiral spin liquid and the gapped partially polarized phase. We propose that, in moderate fields, $\pi$-fluxes nucleate in the ground state and tra

Joseph Bramante, Nirmal Raj

We show that dark matter with certain minimal properties can convert the majority of baryons in galaxies to black holes over hundred trillion year timescales. We argue that this has implications for cosmologies which propose that new universes are created in black hole interiors. We focus on the paradigm of cosmological natural selection, which connects blac

Andreas Blommaert, Sean Colin-Ellerin

We study free graviton entanglement between Rindler wedges in the Minkowski vacuum state via the Euclidean path integral. We follow Kabat's method for computing the conical entropy, using the heat kernel on the cone with the tip removed, whose resulting von Neumann entropy for photons correctly predicted electromagnetic edge modes. We find that, in addition

Yongda Zhu, George D. Becker, Sarah E. I. Bosman, Christopher Cain

Recent quasar absorption line observations suggest that reionization may end as late as $z \approx 5.3$. As a means to search for large neutral hydrogen islands at $z<6$, we revisit long dark gaps in the Ly$\beta$ forest in VLT/X-Shooter and Keck/ESI quasar spectra. We stack the Ly$\alpha$ forest corresponding to both edges of these Ly$\beta$ dark gaps and i

Shelley J. Cheng, Jared A. Goldberg, Matteo Cantiello, Evan B. Bauer

Eruptive mass loss in massive stars is known to occur, but the mechanism(s) are not yet well-understood. One proposed physical explanation appeals to opacity-driven super-Eddington luminosities in stellar envelopes. Here, we present a 1D model for eruptive mass loss and implement this model in the MESA stellar evolution code. The model identifies regions in

Benedetta Spina, Sarah E. I. Bosman, Frederick B. Davies, Prakash Gaikwad

Recent observations have positioned the endpoint of the Epoch of Reionisation (EoR) at redshift $z \sim 5.3$. However, observations of the Lyman-$\alpha$ forest have not yet been able to discern whether reionisation occurred slowly and late, with substantial neutral hydrogen persisting at redshift $\sim 6$, or rapidly and earlier, with the apparent late end

Jens F. Mahlmann, Miguel Á. Aloy, Xinyu Li

Crustal quakes of highly magnetized neutron stars can disrupt their magnetospheres, triggering energetic phenomena like X-ray and fast radio bursts (FRBs). Understanding plasma wave dynamics in these extreme environments is vital for predicting energy transport across scales to the radiation length. This study models relativistic plasma wave interaction in m

Ben J. Sutlieff, Jayne L. Birkby, Jordan M. Stone, Annelotte Derkink

The time variability and spectra of directly imaged companions provide insight into their physical properties and atmospheric dynamics. We present follow-up R~40 spectrophotometric monitoring of red companion HD 1160 B at 2.8-4.2 $\mu$m using the double-grating 360{\deg} vector Apodizing Phase Plate (dgvAPP360) coronagraph and ALES integral field spectrograp

Yubo Su, Bin Liu, Siyao Xu

Recent studies show that the eccentricity distribution of wide binaries (semimajor axis $\gtrsim10^3\;\mathrm{AU}$) observed by \emph{Gaia} tends to favor large eccentricities more strongly than the canonical thermal distribution ($P(e) \propto e$) -- such distributions are termed "superthermal". Motivated by this observation, we revisit the formation channe

Eric Sharpe, Hao Zhang

In this paper, we test and extend a proposal of Gu, Pei, and Zhang for an application of decomposition to three-dimensional theories with one-form symmetries and to quantum K theory. The theories themselves do not decompose, but, OPEs of parallel one-dimensional objects (such as Wilson lines) and dimensional reductions to two dimensions do decompose, sometim

Raymond T. Co, Nicolas Fernandez, Akshay Ghalsasi, Keisuke Harigaya

We show that a rotating axion field that makes a transition from a matter-like equation of state to a kination-like equation of state around the epoch of recombination can significantly ameliorate the Hubble tension, i.e., the discrepancy between the determinations of the present-day expansion rate $H_0$ from observations of the cosmic microwave background o

Isabelle John, Rebecca K. Leane, Tim Linden

We show that stars in the inner parsec of the Milky Way can be significantly affected by dark matter annihilation, producing population-level effects that are visible in a Hertzsprung-Russell (HR) diagram. We establish the dark HR diagram, where stars lie on a new stable $\textit{dark main sequence}$ with similar luminosities, but lower temperatures, than th

Ziyang Chen, Daniel Geng, Andrew Owens

Spectrograms are 2D representations of sound that look very different from the images found in our visual world. And natural images, when played as spectrograms, make unnatural sounds. In this paper, we show that it is possible to synthesize spectrograms that simultaneously look like natural images and sound like natural audio. We call these visual spectrogr

Amanda MacInnis, Neelima Sehgal

We show for the first time that high-resolution CMB lensing observations can probe structure on sub-galactic scales. In particular, a CMB-HD experiment can probe out to k ~ 55 h/Mpc, corresponding to halo masses of about $10^8 M_{\odot}$. Over the range 0.005 h/Mpc < k < 55 h/Mpc, spanning four orders of magnitude, the total lensing signal-to-noise ratio (SN

Samuel Talkington, Amanda West, Rabab Haider

Fair distribution of benefits in electric power systems is a pertinent energy policymaking problem; however, these efforts cannot be easily quantified in power system engineering studies. Therefore, we propose locational marginal burden (LMB) to provide an interface between a well-studied measure of energy pricing equity, energy burden, with an optimal power

Tianqi Liu, Guangcong Wang, Shoukang Hu, Liao Shen

We present MVSGaussian, a new generalizable 3D Gaussian representation approach derived from Multi-View Stereo (MVS) that can efficiently reconstruct unseen scenes. Specifically, 1) we leverage MVS to encode geometry-aware Gaussian representations and decode them into Gaussian parameters. 2) To further enhance performance, we propose a hybrid Gaussian render

Guanglin Zhou, Zhongyi Han, Shiming Chen, Biwei Huang

Recent studies indicate that large multimodal models (LMMs) potentially act as general-purpose assistants and are highly robust against different distributions. Despite this, domain-specific adaptation is still necessary particularly in specialized areas like healthcare. Due to the impracticality of fine-tuning LMMs given their vast parameter space, this wor

Kinwah Wu, Qin Han, Jennifer Y. H. Chan

The optical depth parameterisation is typically used to study the 21-cm signals associated with the properties of the neutral hydrogen (HI) gas and the ionisation morphology during the Epoch of Reionisation (EoR), without solving the radiative transfer equation. To assess the uncertainties resulting from this simplification, we conduct explicit radiative tra

Jnaneshwar Baslingker, Riddhipratim Basu, Sudeshna Bhattacharjee, Manjunath Krishnapur

Hermite and Laguerre $\beta$-ensembles are important and well studied models in random matrix theory with special cases $\beta=1,2,4$ corresponding to eigenvalues of classical random matrix ensembles. It is well known that the largest eigenvalues in these, under appropriate scaling, converge weakly to the Tracy-Widom $\beta$ distribution whose distribution f

Daniel Kaplan, Pavel A. Volkov, Ahana Chakraborty, Zekun Zhuang

We show that driving optical phonons above a threshold fluence induces spatiotemporal orders, where material properties oscillate at an incommensurate wavevector $q_0$ in space and at half the drive frequency in time. The order is robust against temperature on timescales much larger than the lifetime of the excited modes and can be accompanied by a static $2

Octo Model Team, Dibya Ghosh, Homer Walke, Karl Pertsch

Large policies pretrained on diverse robot datasets have the potential to transform robotic learning: instead of training new policies from scratch, such generalist robot policies may be finetuned with only a little in-domain data, yet generalize broadly. However, to be widely applicable across a range of robotic learning scenarios, environments, and tasks,

Anirban Dutta, John R. Peterson, Glenn Sembroski

We propose a modified moment matching algorithm to avoid catastrophic failures for sources with a low signal to noise ratio (SNR). The proposed modifications include a method to eliminate non-physical negative pixel values and a forced single iteration with an initial guess derived from co-add measurements when iterative methods are unstable. We correct for

Nathaniel Cohen, Vladimir Kulikov, Matan Kleiner, Inbar Huberman-Spiegelglas

Text-to-image (T2I) diffusion models achieve state-of-the-art results in image synthesis and editing. However, leveraging such pretrained models for video editing is considered a major challenge. Many existing works attempt to enforce temporal consistency in the edited video through explicit correspondence mechanisms, either in pixel space or between deep fe

Daniel Commey, Benjamin Appiah, Bill K. Frimpong, Isaac Osei

Adversarial Training is a proven defense strategy against adversarial malware. However, generating adversarial malware samples for this type of training presents a challenge because the resulting adversarial malware needs to remain evasive and functional. This work proposes an attack framework, EGAN, to address this limitation. EGAN leverages an Evolution St

Hongwei Liu, Zilong Zheng, Yuxuan Qiao, Haodong Duan

Recent advancements in large language models (LLMs) have showcased significant improvements in mathematics. However, traditional math benchmarks like GSM8k offer a unidimensional perspective, falling short in providing a holistic assessment of the LLMs' math capabilities. To address this gap, we introduce MathBench, a new benchmark that rigorously assesses t

Mariano Poisson, Marcelo López Fuentes, Cristina H. Mandrini, Pascal Démoulin

Active regions (ARs) appear in the solar atmosphere as a consequence of the emergence of magnetic flux-ropes (FR). In this study, we use Bayesian methods to analyze line-of-sight magnetograms of emerging ARs. We employ a FR model consisting of a half-torus field structure based on eight parameters. The goal is to derive constrained physical parameters of the