May 2023 arXiv papers — page 70

Predrag Jovanović, Vesna Borka Jovanović, Duško Borka, Alexander F. Zakharov

Here we study possible improvements of the existing constraints on the upper bound of graviton mass by the analysis of the stellar orbits around the SMBH at the GC in the framework of Yukawa gravity. A motivation for this study is a recent detection of Schwarzschild precession in the orbit of S2 star around the SMBH at the GC by the GRAVITY Collaboration. Th

Pedro Henrique Nascimento Castro, Gabriel Cássia Fortuna, Rafael Alves Bonfim de Queiroz, Gladston Juliano Prates Moreira

In response to the prevalent challenge of overfitting in deep neural networks, this paper introduces Simultaneous Learning, a regularization approach drawing on principles of Transfer Learning and Multi-task Learning. We leverage auxiliary datasets with the target dataset, the UFOP-HVD, to facilitate simultaneous classification guided by a customized loss fu

Zuzanna Szymańska, Mirosław Lachowicz, Nikolaos Sfakianakis, Mark A. J. Chaplain

The transition from the epithelial to mesenchymal phenotype and its reverse (from mesenchymal to epithelial) are crucial processes necessary for the progression and spread of cancer. In this paper, we investigate how phenotypic switching at the cancer cell level impacts on behaviour at the tissue level, specifically on the emergence of isolated foci of the i

Tim Langen, Giacomo Valtolina, Dajun Wang, Jun Ye

An increasingly large variety of molecular species are being cooled down to low energies in recent years, and innovative ideas and powerful techniques continue to emerge to gain ever more precise control of molecular motion. In this brief review we focus our discussions on two widely employed cooling techniques that have brought molecular gases into the quan

Teague R. Henry, Lindley R. Slipetz, Ami Falk, Jiaxing Qiu

Intensive longitudinal (IL) data are increasingly prevalent in psychological science, coinciding with technological advancements that make it simple to deploy study designs such as daily diary and ecological momentary assessments. IL data are characterized by a rapid rate of data collection (1+ collections per day), over a period of time, allowing for the ca

Chao Cheng, Bo Liu, Lisa Wruck, Fan Li

Comparative effectiveness research frequently addresses a time-to-event outcome and can require unique considerations in the presence of treatment noncompliance. Motivated by the challenges in addressing noncompliance in the ADAPTABLE pragmatic clinical trial, we develop a multiply robust estimator to estimate the principal survival causal effects under the

Pablo M. Galán-de Anta, Pedro R. Capelo, Eugene Vasiliev, Massimo Dotti

Thin galactic discs and nuclear stellar discs (NSDs) are fragile structures that can be easily disturbed by merger events. By studying the age of the stellar populations in present-day discs, we can learn about the assembly history of galaxies and place constraints on their past merger events. Following on the steps of our initial work, we explore the fragil

A. E. Cárcamo Hernández, Juan Marchant González, M. L. Mora-Urrutia, Daniel Salinas-Arizmendi

We proposed a viable and predictive model based on the $SU(3)_C \times SU(3)_L \times U(1)_X$ gauge symmetry, supplemented by the global $U(1)_{Lg}$ symmetry, the $S_4$ family symmetry and several auxiliary cyclic symmetries, which successfully reproduces the experimentally observed SM fermion mass and mixing pattern. The tiny active neutrino masses are gene

Maryam Aliakbarpour, Rose Silver, Thomas Steinke, Jonathan Ullman

We construct differentially private estimators with low sample complexity that estimate the median of an arbitrary distribution over $\mathbb{R}$ satisfying very mild moment conditions. Our result stands in contrast to the surprising negative result of Bun et al. (FOCS 2015) that showed there is no differentially private estimator with any finite sample comp

CMS Collaboration

The observation of the production of four top quarks in proton-proton collisions is reported, based on a data sample collected by the CMS experiment at a center-of-mass energy of 13 TeV in 2016-2018 at the CERN LHC and corresponding to an integrated luminosity of 138 fb$^{-1}$. Events with two same-sign, three, or four charged leptons (electrons and muons) a

Bernd S. W. Schröder

We introduce a recursive method to deconstruct the automorphism group of an ordered set. By connecting this method with deep results for permutation groups, we prove the Automorphism Conjecture for ordered sets of width less than or equal to $11$. Subsequent investigations show that the method presented here could lead to a resolution of the Automorphism Con

Anthony R. Dobrovolskis, Jack J. Lissauer, Jose L. Alvarellos

Several asteroids are known to be shaped like toy tops. This paper models Top-Shaped Asteroids (TSAs) as Homogeneous Symmetric Lenses (HSLs), and derives their rotational, self-gravitational, and total energies as functions of their mass, density, and angular momentum. Then we raise, test, and ultimately reject the hypothesis that TSAs take the shape of lowe

Jakub Nadolny, Michał Jerzy Michałowski, J. Ricardo Rizzo, Agata Karska

Star-forming galaxies populate a main sequence (MS), a well-defined relation between stellar mass (M*) and star-formation rate (SFR). Starburst (SB) galaxies lie significantly above the relation whereas quenched galaxies lie below the sequence. In order to study the evolution of galaxies on the SFR-M* plane and its connection to the gas content, we use the f

Lauren E. Altman, Andrew D. Hollingsworth, David G. Grier

Shear flows cause aspherical colloidal particles to tumble so that their orientations trace out complex trajectories known as Jeffery orbits. The Jeffery orbit of a prolate ellipsoid is predicted to align the particle's principal axis preferentially in the plane transverse to the axis of shear. Holographic microscopy measurements reveal instead that colloida

Zachary S. C. Picker, Alexander Kusenko

Black holes may form in present-day collapse of microscopic structures of dark matter. We show that, if microstructure black holes (MSBH) with mass $m\sim 10^{13}~g$ are produced, the spectrum of gamma rays from their evaporation agrees remarkably well with the GeV excess observed by Fermi Gamma-ray Space Telescope, while still avoiding all observational con

Annie Pichery, Matthias Meister, Baptist Piest, Jonas Böhm

We present a highly efficient method for the numerical solution of coupled Gross-Pitaevskii equations describing the evolution dynamics of a multispecies mixture of Bose-Einstein condensates in time-dependent potentials. This method, based on a grid-scaling technique, compares favorably to a more standard but much more computationally expensive solution base

Hengrong Du, Yuanzhen Shao, Gieri Simonett

We introduce a system of equations that models a non-isothermal magnetoviscoelastic fluid. We show that the model is thermodynamically consistent, and that the critical points of the entropy functional with prescribed energy correspond exactly with the equilibria of the system. The system is investigated in the framework of quasilinear parabolic systems and

Nikos Prantzos, Carlos Abia, Tianxiang Chen, Patrick de Laverny

Using a semi-analytical model of the evolution of the Milky Way, we show how secular evolution can create distinct overdensities in the phase space of various properties (e.g. age vs metallicity or abundance ratios vs age) corresponding to the thin and thick discs. In particular, we show how key properties of the Solar vicinity can be obtained by secular evo

Beth Bjorkman, Esther Conrad

Sensors called phasor measurement units (PMUs) are used to monitor the electric power network. The power domination problem seeks to minimize the number of PMUs needed to monitor the network. We extend the power domination problem and consider the minimum number of sensors and appropriate placement to ensure monitoring when $k$ sensors are allowed to fail wi

Zachary S. C. Picker, Alexander Kusenko

Black holes can be produced in collapse of small-scale dark matter structures, which can happen at any time from the early to present-day universe. Microstructure black holes (MSBHs) can have a wide range of masses. Small MSBHs evaporate via Hawking radiation with lifetimes shorter than the age of the universe, but they are not subject to the usual early-uni

Yusen Long

In this article, we use the second intrinsic volume to define a metric on the space of homothetic classes of Gaussian bounded convex bodies in a separable real Hilbert space. Using kernels of hyperbolic type, we can deduce that this space is isometrically embedded into an infinite-dimensional real hyperbolic space. Applying Malliavin calculus, it is possible

Lucas Rudelt, Daniel González Marx, F. Paul Spitzner, Benjamin Cramer

A core challenge for the brain is to process information across various timescales. This could be achieved by a hierarchical organization of temporal processing through intrinsic mechanisms (e.g., recurrent coupling or adaptation), but recent evidence from spike recordings of the rodent visual system seems to conflict with this hypothesis. Here, we used an o

Helen Zhou, Yuwen Chen, Zachary C. Lipton

Machine learning (ML) models deployed in healthcare systems must face data drawn from continually evolving environments. However, researchers proposing such models typically evaluate them in a time-agnostic manner, splitting datasets according to patients sampled randomly throughout the entire study time period. This work proposes the Evaluation on Medical D

Aidan Barbieux, Rodrigo Canaan

This paper presents EINCASM, a prototype system employing a novel framework for studying emergent intelligence in organisms resembling slime molds. EINCASM evolves neural cellular automata with NEAT to maximize cell growth constrained by nutrient and energy costs. These organisms capitalize physically simulated fluid to transport nutrients and chemical-like

J. S. Halekas, S. D. Bale, M. Berthomier, B. D. G. Chandran

A variety of energy sources, ranging from dynamic processes like magnetic reconnection and waves to quasi-steady terms like the plasma pressure, may contribute to the acceleration of the solar wind. We utilize a combination of charged particle and magnetic field observations from the Parker Solar Probe (PSP) to attempt to quantify the steady-state contributi

Kaushal Kumar Kesharpu

The Hamiltonian of a two dimensional (2D) magnetic material in the strong correlation regime with a spin texture, for which both azimuthal and polar angle changes, is solved using $su(2)$ path integral method. The dependence of the Chern number on the atomic spin ($S$), azimuthal angle ($\vec{q}_{1}$) and polar angle ($\vec{q}_{2}$) modulation vector of the

António Girão, Freddie Illingworth, Lukas Michel, Michael Savery

Colour the edges of the complete graph with vertex set $\{1, 2, \dotsc, n\}$ with an arbitrary number of colours. What is the smallest integer $f(l,k)$ such that if $n > f(l,k)$ then there must exist a monotone monochromatic path of length $l$ or a monotone rainbow path of length $k$? Lefmann, R\"{o}dl, and Thomas conjectured in 1992 that $f(l, k) = l^{k - 1

Sebastian Krumscheid, Per Pettersson

Quantifying the effect of uncertainties in systems where only point evaluations in the stochastic domain but no regularity conditions are available is limited to sampling-based techniques. This work presents an adaptive sequential stratification estimation method that uses Latin Hypercube Sampling within each stratum. The adaptation is achieved through a seq

Alexander Schmidt, Peter Hiemeyer, Fred Wolf

Distributions of neuronal activity within cortical circuits are often found to display highly skewed shapes with many neurons emitting action potentials at low or vanishing rates, while some are active at high rates. Theoretical studies were able to reproduce such distributions, but come with a lack of mathematical tractability, preventing a deeper understan

Revathi Jambunathan, Zhi Yao, Richard Lombardini, Aaron Rodriguez

In this work, we implement a new London equation module for superconductivity in the GPU-enabled ARTEMIS framework, and couple it to a finite-difference time-domain solver for Maxwell's equations. We apply this two-fluid approach to model a superconducting coplanar waveguide (CPW) resonator. We validate our implementation by verifying that the theoretical sk

William Hunter, Aditya Arun, Dinesh Bharadia

Many recent works have explored using WiFi-based sensing to improve SLAM, robot manipulation, or exploration. Moreover, widespread availability makes WiFi the most advantageous RF signal to leverage. But WiFi sensors lack an accurate, tractable, and versatile toolbox, which hinders their widespread adoption with robot's sensor stacks. We develop WiROS to add

Shahar Katz, Yonatan Belinkov

Recent advances in interpretability suggest we can project weights and hidden states of transformer-based language models (LMs) to their vocabulary, a transformation that makes them more human interpretable. In this paper, we investigate LM attention heads and memory values, the vectors the models dynamically create and recall while processing a given input.

Paulo Lima-Filho

Using determinantal schemes, we construct explicit cycles in the higher Chow complex of BGL that represent the universal Chern classes in higher Chow groups. As an application, we use these cycles, along with a canonical \emph{stable moving lemma} for Karoubi-Villamayor \(K\)-theory, to give a direct construction of the Chern class homomorphisms \(c_{p,r}\)

Wen Yin, Kohei Hayashi

Recent advances in cosmic-ray detectors have provided exceptional sensitivities of dark matter with high angular resolution. Motivated by this, we present a comprehensive study of cosmic-ray flux from dark matter decay in dwarf spheroidal galaxies (dSphs), with a focus on detectors possessing arcsecond-level field of view and/or angular resolution. We propos

Daniel Cardoso Pereira Jorge, Ricardo Martinez-Garcia

The component Allee effect (AE) is the positive correlation between an organism's fitness component and population density. Depending on the population spatial structure, which determines the interactions between organisms, a component AE might lead to positive density-dependence in the population per capita growth rate and establish a demographic AE. Howeve

Yuqian Dai, Serge Sharoff, Marc de Kamps

Although the Transformer model can effectively acquire context features via a self-attention mechanism, deeper syntactic knowledge is still not effectively modeled. To alleviate the above problem, we propose Syntactic knowledge via Graph attention with BERT (SGB) in Machine Translation (MT) scenarios. Graph Attention Network (GAT) and BERT jointly represent

Yiming Wang, Zhuosheng Zhang, Rui Wang

Automatic summarization generates concise summaries that contain key ideas of source documents. As the most mainstream datasets for the news sub-domain, CNN/DailyMail and BBC XSum have been widely used for performance benchmarking. However, the reference summaries of those datasets turn out to be noisy, mainly in terms of factual hallucination and informatio

Kailash Gogineni, Peng Wei, Tian Lan, Guru Venkataramani

Multi-Agent Reinforcement Learning (MARL) is an increasingly important research field that can model and control multiple large-scale autonomous systems. Despite its achievements, existing multi-agent learning methods typically involve expensive computations in terms of training time and power arising from large observation-action space and a huge number of

Kaixiang Su, Nayan Myerson-Jain, Cenke Xu

We demonstrate that the fidelity between a pure state trivial insulator and the mixed state density matrix of a Chern insulator under decoherence can be mapped to a variety of two-dimensional conformal field theories (CFT); more specifically, the quantity $\mathcal{Z} = \text{tr}\{ \hat{\rho}^D_c \hat{\rho}_\Omega \}$ is mapped to the partition function of t

Sabee Grewal, Vishnu Iyer, William Kretschmer, Daniel Liang

We give a pair of algorithms that efficiently learn a quantum state prepared by Clifford gates and $O(\log n)$ non-Clifford gates. Specifically, for an $n$-qubit state $|\psi\rangle$ prepared with at most $t$ non-Clifford gates, our algorithms use $\mathsf{poly}(n,2^t,1/\varepsilon)$ time and copies of $|\psi\rangle$ to learn $|\psi\rangle$ to trace distance

Qiujia Li, Bo Li, Dongseong Hwang, Tara N. Sainath

Speech data from different domains has distinct acoustic and linguistic characteristics. It is common to train a single multidomain model such as a Conformer transducer for speech recognition on a mixture of data from all domains. However, changing data in one domain or adding a new domain would require the multidomain model to be retrained. To this end, we

Johno van IJsseldijk, Musab Al Hasani, Eric Verschuur, Guy Drijkoningen

In this report we investigate whether and under what conditions virtual seismology via the acoustic Marchenko method can be applied to DAS data from a survey in the province of Groningen, The Netherlands. Virtual seismology allows to retrieve the band-limited Green's function between a virtual source at an arbitrary focal point in the subsurface, while accou

Zhuangqun Huang, Gil Keren, Ziran Jiang, Shashank Jain

Aiming at reducing the reliance on expensive human annotations, data synthesis for Automatic Speech Recognition (ASR) has remained an active area of research. While prior work mainly focuses on synthetic speech generation for ASR data augmentation, its combination with text generation methods is considerably less explored. In this work, we explore text augme

Yanchen Liu, William Held, Diyi Yang

Existing large language models (LLMs) that mainly focus on Standard American English (SAE) often lead to significantly worse performance when being applied to other English dialects. While existing mitigations tackle discrepancies for individual target dialects, they assume access to high-accuracy dialect identification systems. The boundaries between dialec

Keunho J. Kim, Matthew B. Bayliss, Jane R. Rigby, Michael D. Gladders

Extreme, young stellar populations are considered the primary contributor to cosmic re-ionization. How Lyman-continuum (LyC) escapes these galaxies remains highly elusive, and it is challenging to observe this process in actual LyC emitters without resolving the relevant physical scales. We investigate the Sunburst Arc: a strongly lensed, LyC emitter at $z =

Bo Zhao, Robert M. Gower, Robin Walters, Rose Yu

In many neural networks, different values of the parameters may result in the same loss value. Parameter space symmetries are loss-invariant transformations that change the model parameters. Teleportation applies such transformations to accelerate optimization. However, the exact mechanism behind this algorithm's success is not well understood. In this paper

Yuqian Dai, Serge Sharoff, Marc de Kamps

Graph Attention Network (GAT) is a graph neural network which is one of the strategies for modeling and representing explicit syntactic knowledge and can work with pre-trained models, such as BERT, in downstream tasks. Currently, there is still a lack of investigation into how GAT learns syntactic knowledge from the perspective of model structure. As one of

Adela Frances DePavia, Olga Medrano Martín del Campo, Erasmo Tani

This paper initiates the study of active learning for exact recovery of partitions exclusively through access to a same-cluster oracle in the presence of bounded adversarial error. We first highlight a novel connection between learning partitions and correlation clustering. Then we use this connection to build a R\'enyi-Ulam style analytical framework for th

Haotian Ye, Yihong Liu, Hinrich Schütze

An interesting line of research in natural language processing (NLP) aims to incorporate linguistic typology to bridge linguistic diversity and assist the research of low-resource languages. While most works construct linguistic similarity measures based on lexical or typological features, such as word order and verbal inflection, recent work has introduced

Jared Siegel, Joshua Winn, Simon Albrecht

Misalignments between planetary orbits and the equatorial planes of their host stars are clues about the formation and evolution of planetary systems. Earlier work found evidence for a peak near $90^\circ$ in the distribution of stellar obliquities, based on frequentist tests. We performed hierarchical Bayesian inference on a sample of 174 planets for which

Eden Dolev, Alaa Awad, Denisa Roberts, Zahra Ebrahimzadeh

Efficiently learning visual representations of items is vital for large-scale recommendations. In this article we compare several pretrained efficient backbone architectures, both in the convolutional neural network (CNN) and in the vision transformer (ViT) family. We describe challenges in e-commerce vision applications at scale and highlight methods to eff

Maysam Orouskhani, Negar Firoozeh, Shaojun Xia, Mahmud Mossa-Basha

Intracranial aneurysms are a commonly occurring and life-threatening condition, affecting approximately 3.2% of the general population. Consequently, detecting these aneurysms plays a crucial role in their management. Lesion detection involves the simultaneous localization and categorization of abnormalities within medical images. In this study, we employed

Kyle Hixenbaugh, Xian-Yu Wang, Malena Rice, Songhu Wang

The mechanisms responsible for generating spin-orbit misalignments in exoplanetary systems are still not fully understood. It is unclear whether these misalignments are related to the migration of hot Jupiters or are a consequence of general star and planet formation processes. One promising method to address this question is to constrain the distribution of

Chris Doyle, Sarah Shader, Michelle Lau, Megumi Sano

Infants explore their complex physical and social environment in an organized way. To gain insight into what intrinsic motivations may help structure this exploration, we create a virtual infant agent and place it in a developmentally-inspired 3D environment with no external rewards. The environment has a virtual caregiver agent with the capability to intera

Karel D'Oosterlinck, François Remy, Johannes Deleu, Thomas Demeester

Timely and accurate extraction of Adverse Drug Events (ADE) from biomedical literature is paramount for public safety, but involves slow and costly manual labor. We set out to improve drug safety monitoring (pharmacovigilance, PV) through the use of Natural Language Processing (NLP). We introduce BioDEX, a large-scale resource for Biomedical adverse Drug Eve

Yuri Abramovich, Tanit Pongsiri

The inverse Toeplitz eigenvalue problem (ToIEP) concerns finding a vector that specifies the real-valued symmetric Toeplitz matrix with the prescribed set of eigenvalues. Since phase "calibration" errors in uniform linear antenna arrays (ULAs) do not change the covariance matrix eigenvalues and the moduli of the covariance matrix elements, we formulate a num

Megala Anandan, Benjamin Boutin, Nicolas Crouseilles

In this work, high order asymptotic preserving schemes are constructed and analysed for kinetic equations under a diffusive scaling. The framework enables to consider different cases: the diffusion equation, the advection-diffusion equation and the presence of inflow boundary conditions. Starting from the micro-macro reformulation of the original kinetic equ

Kyoungmin Han, Minsik Lee

Recently, contrastive self-supervised learning, where the proximity of representations is determined based on the identities of samples, has made remarkable progress in unsupervised representation learning. SimSiam is a well-known example in this area, known for its simplicity yet powerful performance. However, it is known to be sensitive to changes in train

Peiqi Sun, Michel Grabisch, Christophe Labreuche

Capacity is an important tool in decision-making under risk and uncertainty and multi-criteria decision-making. When learning a capacity-based model, it is important to be able to generate uniformly a capacity. Due to the monotonicity constraints of a capacity, this task reveals to be very difficult. The classical Random Node Generator (RNG) algorithm is a f

Jon K. Zink, Kevin K. Hardegree-Ullman, Jessie L. Christiansen, Erik A. Petigura

In this study, we performed a homogeneous analysis of the planets around FGK dwarf stars observed by the Kepler and K2 missions, providing spectroscopic parameters for 310 K2 targets -- including 239 Scaling K2 hosts -- observed with Keck/HIRES. For orbital periods less than 40 days, we found that the distribution of planets as a function of orbital period,

Jon Gauthier, Roger Levy

Listeners recognize and integrate words in rapid and noisy everyday speech by combining expectations about upcoming content with incremental sensory evidence. We present a computational model of word recognition which formalizes this perceptual process in Bayesian decision theory. We fit this model to explain scalp EEG signals recorded as subjects passively

I. A. Zinchenko

Kinematic misalignment between gas and stellar components observed in a certain fraction of galaxies. It believed to be caused by acquisition of gas from the external reservoir by major or minor mergers, accretion from cosmological filaments or circumgalactic medium, etc. We aim to constrain possible sources of the gas that forms counter-rotating component.

Basel Mousi, Nadir Durrani, Fahim Dalvi

Work done to uncover the knowledge encoded within pre-trained language models rely on annotated corpora or human-in-the-loop methods. However, these approaches are limited in terms of scalability and the scope of interpretation. We propose using a large language model, ChatGPT, as an annotator to enable fine-grained interpretation analysis of pre-trained lan

Marvin Kruber, Tobias Pfandzelter, David Bermbach

Metadata exchange is crucial for efficient geo-distributed fog computing. Existing solutions for metadata exchange overlook geo-awareness or lack adequate failure tolerance. We propose HFCS, a novel hybrid communication system that combines hierarchical and peer-to-peer elements, along with edge pools. HFCS utilizes a gossip protocol for dynamic metadata exc

L. Angel, P. Arias, C. O. Dib, A. S. de Jesus

Axion-Like Particles (ALPs) appear in several dark sector studies. They have gained increasing attention from the theoretical and experimental community. In this work, we propose the first search for ALPs to be conducted at the Brazilian Synchrotron Light Laboratory (LNLS). In this work, we derive the projected sensitivity of a proposed experiment for the pr

Maksym Ovchynnikov, Jean-Loup Tastet, Oleksii Mikulenko, Kyrylo Bondarenko

The idea that new physics could take the form of feebly interacting particles (FIPs) - particles with a mass below the electroweak scale, but which may have evaded detection due to their tiny couplings or very long lifetime - has gained a lot of traction in the last decade, and numerous experiments have been proposed to search for such particles. It is impor

Giacomo Ferrante, Gabriele Franciolini, Antonio Junior Iovino, Alfredo Urbano

We revise primordial black holes (PBHs) production in the axion-curvaton model, in light of recent developments in the computation of their abundance accounting for non-gaussianities (NGs) in the curvature perturbation up to all orders. We find that NGs intrinsically generated in such scenarios have a relevant impact on the phenomenology associated to PBHs a

Mohammad Ali Gorji

The seed of dark matter can be generated from light spectator fields during inflation through a similar mechanism that the seed of observed large scale structures are produced from the inflaton field. The accumulated energy density of the corresponding excited modes, which is subdominant during inflation, dominates energy density of the universe later around

Matthieu Schaller, Josh Borrow, Peter W. Draper, Mladen Ivkovic

Numerical simulations have become one of the key tools used by theorists in all the fields of astrophysics and cosmology. The development of modern tools that target the largest existing computing systems and exploit state-of-the-art numerical methods and algorithms is thus crucial. In this paper, we introduce the fully open-source highly-parallel, versatile

Emil Brinch Holm, Isabel M. Oldengott, Stefan Zentarra

The density of relic neutrinos is expected to be enhanced due to clustering in our local neighbourhood at Earth. We introduce a novel analytical technique to calculate the neutrino overdensity, based on kinetic field theory. Kinetic field theory is a particle-based theory for cosmic structure formation and in this work we apply it for the first time to massi

Bridget Ratcliffe, Ivan Minchev, Friedrich Anders, Sergey Khoperskov

Chemical abundances are an essential tool in untangling the Milky Way's enrichment history. However, the evolution of the interstellar medium abundance gradient with cosmic time is lost as a result of radial mixing processes. For the first time, we quantify the evolution of many observational abundances across the Galactic disk as a function of lookback time

Jeffrey M. Berryman, Susan Gardner, Mohammadreza Zakeri

We investigate how our baryon-loss limits from anomalous binary-pulsar period lengthening can be interpreted microscopically to yield specific constraints on the particle physics of baryon number violation within a neutron star. We focus on the possibility of anomalous baryon disappearance via dark baryon processes and on scenarios in which the produced dark

Thomas Wiegart, Linfang Wang, Diego Lentner, Richard D. Wesel

An algorithm is proposed to encode low-density parity-check (LDPC) codes into codewords with a non-uniform distribution. This enables power-efficient signalling for asymmetric channels. We show gains of 0.9 dB for additive white Gaussian noise (AWGN) channels with on-off keying modulation using 5G LDPC codes.

Ryotaro Sano, Yuya Ominato, Mamoru Matsuo

The recently discovered van der Waals antiferromagnets have suffered from the lack of a comprehensive method to study their magnetic properties. Here, we propose a dissipationless magnon spin Hall current driven by surface acoustic waves as a novel probe for such antiferromagnets. Our results pave the way towards mechanical detection and manipulation of the

Joshua D. Baktay, Alexander V. Rozhkov, Adrian E. Feiguin, Julian Rincon

We present numerical evidence for a paradigm in one-dimensional interacting fermion systems, whose phenomenology has traits of both Luttinger liquids and Fermi liquids. This state, dubbed a quasi-Fermi liquid, possesses a discontinuity in its fermion occupation number at the Fermi momentum. The excitation spectrum presents particlelike quasiparticles and abs

Ohad Antebi, Ady Stern, Erez Berg

In this work we investigate the ground state of a momentum-confined interacting 2D electron gas, a momentum-space analog of an infinite quantum well. The study is performed by combining analytical results with a numerical exact diagonalization procedure. We find a ferromagnetic ground state near a particular electron density and for a range of effective elec

Md Mursalin Islam, K. Sengupta, Rajdeep Sensarma

We study the quench and the ramp dynamics of interacting $N$-component charged bosons with dipole symmetry using Schwinger-Keldysh field theory in the large $N$ limit. The equilibrium phase diagram of these bosons shows two phases in the large $N$ limit. The first is a normal phase where both the global $U(N)$ and the dipole symmetries are conserved and the

K. Inight, Boris T. Gänsicke, A. Schwope, S. F. Anderson

SDSS-V is carrying out a dedicated survey for white dwarfs, single and in binaries, and we report the analysis of the spectroscopy of cataclysmic variables (CVs) and CV candidates obtained during the final plug plate observations of SDSS. We identify eight new CVs, spectroscopically confirm 53 and refute eleven published CV candidates, and we report 21 new o

Madhumita Sarkar, Roopayan Ghosh, Ivan M. Khaymovich

Rosenzweig-Porter (RP) model has garnered much attention in the last decade, as it is a simple analytically tractable model showing both ergodic--nonergodic extended and Anderson localization transitions. Thus, it is a good toy model to understand the Hilbert-space structure of many body localization phenomenon. In our study, we present analytical evidence,

Roberta Calabrese, Marco Chianese, Jacob Gunn, Gennaro Miele

We investigate the role that the evaporation of light primordial black holes may have played in the production of the baryon asymmetry of the Universe through the high-scale leptogenesis. In particular, for mass of primordial black hole in the range [$10^6$-$10^9$] g, we find a dilution of thermally generated lepton asymmetry via entropy injection in the pri

Matilde Signorini, Stefano Marchesi, Roberto Gilli, Marcella Brusa

The 500ks Chandra ACIS-I observation of the field around the $z=6.31$ quasar SDSS J1030+0524 is currently the 5th deepest extragalactic X-ray survey. The rich multi-band coverage of the field allowed for an effective identification and redshift determination of the X-ray source counterparts: to date a catalog of 243 extragalactic X-ray sources with either a

Debasish Borah, Suruj Jyoti Das, Rishav Roshan

We propose a novel framework where baryon asymmetry can arise due to forbidden decay of dark matter (DM) enabled by finite temperature effects in the early universe. In order to implement it in a realistic setup, we consider the DM to be a singlet Dirac fermion which acquires a dark asymmetry from a scalar field $\Phi$ via Affleck-Dine mechanism. Due to fini

Michael S. Petersen, Martin D. Weinberg, Neal Katz

We define a physically-motivated measure for galactic bar length, called the dynamical length. The dynamical length of the bar corresponds to the radial extent of the orbits that are the backbone supporting the bar feature. We propose a direct observational technique using integral field unit spectroscopy to measure it. Identifying these orbits and using the

Jernej Rudi Finžgar, Martin J. A. Schuetz, J. Kyle Brubaker, Hidetoshi Nishimori

We propose and analyze the use of Bayesian optimization techniques to design quantum annealing schedules with minimal user and resource requirements. We showcase our scheme with results for two paradigmatic spin models. We find that Bayesian optimization is able to identify schedules resulting in fidelities several orders of magnitude better than standard pr

M. Castellano, D. Belfiori, L. Pentericci, A. Calabrò

We investigate the production efficiency of ionizing photons ($\xi_{ion}^*$) of 1174 galaxies with secure redshift at z=2-5 from the VANDELS survey to determine the relation between ionizing emission and physical properties of bright and massive sources. We constrain $\xi_{ion}^*$ and galaxy physical parameters by means of spectro-photometric fits performed

Marianna Annunziatella, Anna Sajina, Mauro Stefanon, Danilo Marchesini

We present new Spitzer Infrared Array Camera (IRAC) 3.6 and 4.5{\mu}m mosaics of three fields, E-COSMOS, DEEP2-F3, and ELAIS-N1. Our mosaics include both new IRAC observations as well as re-processed archival data in these fields. These fields are part of the HSC-Deep grizy survey and have a wealth of additional ancillary data. The addition of these new IRAC

Amira Abbas, Robbie King, Hsin-Yuan Huang, William J. Huggins

The success of modern deep learning hinges on the ability to train neural networks at scale. Through clever reuse of intermediate information, backpropagation facilitates training through gradient computation at a total cost roughly proportional to running the function, rather than incurring an additional factor proportional to the number of parameters - whi

Valentin Benedetti, Pablo Bueno, Javier M. Magan

We construct generalized symmetries for linearized Einstein gravity in arbitrary dimensions. First-principle considerations in QFT force generalized symmetries to appear in dual pairs. Verifying this prediction helps us find the full set of non-trivial conserved charges -- associated, in equal parts, with 2-form and $(D-2)$-form currents. Their total number

A. Savino, D. R. Weisz, E. D. Skillman, A. Dolphin

We present the lifetime star formation histories (SFHs) for six ultra-faint dwarf (UFD; $M_V>-7.0$, $ 4.9<\log_{10}({M_*(z=0)}/{M_{\odot}})<5.5$) satellite galaxies of M31 based on deep color-magnitude diagrams constructed from \textit{Hubble Space Telescope} imaging. These are the first SFHs obtained from the oldest main sequence turn-off of UFDs outside th

Zhong-Bo Kang, Robert Kao, Andrew J. Larkoski

The single-particle inclusive fragmentation function and the particle multiplicity are observables of fundamental importance in studying properties of quantum chromodynamics at colliders. It is well-known that at high energies, the multiplicity distribution satisfies KNO scaling in which all moments are proportional to powers of the mean multiplicity. We pro

Sung Hak Lim, Eric Putney, Matthew R. Buckley, David Shih

We present a novel, data-driven analysis of Galactic dynamics, using unsupervised machine learning -- in the form of density estimation with normalizing flows -- to learn the underlying phase space distribution of 6 million nearby stars from the Gaia DR3 catalog. Solving the equilibrium collisionless Boltzmann equation, we calculate -- for the first time eve

Tsz Chun Wu, Patrick A. Lee, Matthew S. Foster

We study superconductivity in a two-dimensional, disordered marginal Fermi liquid. At the semiclassical level, the transition temperature $T_c$ is strongly suppressed because marginal Fermi liquid effects destroy well-defined quasiparticles. However, we show that interference between quantum-critical collective modes must be included, and these enhance $T_c$

Shayan Majidy, Utkarsh Agrawal, Sarang Gopalakrishnan, Andrew C. Potter

Monitored quantum circuits exhibit entanglement transitions at certain measurement rates. Such a transition separates phases characterized by how much information an observer can learn from the measurement outcomes. We study SU(2)-symmetric monitored quantum circuits, using exact numerics and a mapping onto an effective statistical-mechanics model. Due to th

Thomas G. Kiely, Debanjan Chowdhury

Electrons can organize themselves into charge-ordered states to minimize the effects of long-ranged Coulomb interactions. In the presence of a lattice, commensurability constraints lead to the emergence of incompressible Wigner-Mott insulators at various rational electron fillings, $\nu~=p/q$. The mechanism for quantum fluctuation-mediated melting of the Mot

Shohei Saga, Stéphane Colombi, Atsushi Taruya

It is well known that the first structures that form from small fluctuations in a self-gravitating, collisionless and initially smooth cold dark matter (CDM) fluid are pancakes. We study the gravitational force generated by such pancakes just after shell-crossing, and find a simple analytical formula for the force along the collapse direction, which can be a

Theo W. Costain, Kejie Li, Victor A. Prisacariu

Prior works have demonstrated that implicit representations trained only for reconstruction tasks typically generate encodings that are not useful for semantic tasks. In this work, we propose a method that contextualises the encodings of implicit representations, enabling their use in downstream tasks (e.g. semantic segmentation), without requiring access to

Haoyu Lu, Guoxing Yang, Nanyi Fei, Yuqi Huo

This work introduces Video Diffusion Transformer (VDT), which pioneers the use of transformers in diffusion-based video generation. It features transformer blocks with modularized temporal and spatial attention modules to leverage the rich spatial-temporal representation inherited in transformers. We also propose a unified spatial-temporal mask modeling mech

Yang Liu, Muzhi Zhu, Hengtao Li, Hao Chen

Powered by large-scale pre-training, vision foundation models exhibit significant potential in open-world image understanding. However, unlike large language models that excel at directly tackling various language tasks, vision foundation models require a task-specific model structure followed by fine-tuning on specific tasks. In this work, we present Matche

Jing Fan, Dennis Aumiller, Michael Gertz

Automated evaluation of text generation systems has recently seen increasing attention, particularly checking whether generated text stays truthful to input sources. Existing methods frequently rely on an evaluation using task-specific language models, which in turn allows for little interpretability of generated scores. We introduce SRLScore, a reference-fr

Shyamgopal Karthik, Karsten Roth, Massimiliano Mancini, Zeynep Akata

Despite their impressive capabilities, diffusion-based text-to-image (T2I) models can lack faithfulness to the text prompt, where generated images may not contain all the mentioned objects, attributes or relations. To alleviate these issues, recent works proposed post-hoc methods to improve model faithfulness without costly retraining, by modifying how the m