April 2024 arXiv papers — page 170

Emmy Liu, Graham Neubig, Jacob Andreas

Modern language models (LMs) can learn to perform new tasks in different ways: in instruction following, the target task is described explicitly in natural language; in few-shot prompting, the task is specified implicitly with a small number of examples; in instruction inference, LMs are presented with in-context examples and are then prompted to generate a

Weidi Luo, Siyuan Ma, Xiaogeng Liu, Xiaoyu Guo

With the rapid advancements in Multimodal Large Language Models (MLLMs), securing these models against malicious inputs while aligning them with human values has emerged as a critical challenge. In this paper, we investigate an important and unexplored question of whether techniques that successfully jailbreak Large Language Models (LLMs) can be equally effe

Matteo Parisi, Melissa Sherman-Bennett, Ran Tessler, Lauren Williams

The amplituhedron $A_{n,k,m}$ is a geometric object introduced in the context of scattering amplitudes in $N=4$ super Yang Mills. It generalizes the positive Grassmannian (when $n=k+m$), cyclic polytopes (when $k=1$), and the bounded complex of the cyclic hyperplane arrangement (when $m=1$). Of substantial interest are the tilings of the amplituhedron, which

Xinyu Huang, Haojun Yang, Conghao Zhou, Mingcheng He

Generative artificial intelligence (GAI) and digital twin (DT) are advanced data processing and virtualization technologies to revolutionize communication networks. Thanks to the powerful data processing capabilities of GAI, integrating it into DT is a potential approach to construct an intelligent holistic virtualized network for better network management p

Ellen Færgestad Mosleth, Kristian Hovde Liland

We present a flexible tool, called General Effect Modelling (GEM), for the analysis of any multivariate data influenced by one or more qualitative (categorical) or quantitative (continuous) input variables. The variables can be design factors or observed values, e.g., age, sex, or income, or they may represent subgroups of the samples found by data explorati

Jinkyung Park, Vivek Singh, Pamela Wisniewski

Following the recent release of various Artificial Intelligence (AI) based Conversation Agents (CAs), adolescents are increasingly using CAs for interactive knowledge discovery on sensitive topics, including mental and sexual health topics. Exploring such sensitive topics through online search has been an essential part of adolescent development, and CAs can

Amirhossein Abaskohi, Amirhossein Dabiriaghdam, Lele Wang, Giuseppe Carenini

Memes, combining text and images, frequently use metaphors to convey persuasive messages, shaping public opinion. Motivated by this, our team engaged in SemEval-2024 Task 4, a hierarchical multi-label classification task designed to identify rhetorical and psychological persuasion techniques embedded within memes. To tackle this problem, we introduced a capt

Alexander Loth, Martin Kappes, Marc-Oliver Pahl

Fake news significantly influence our society. They impact consumers, voters, and many other societal groups. While Fake News exist for a centuries, Generative AI brings fake news on a new level. It is now possible to automate the creation of masses of high-quality individually targeted Fake News. On the other end, Generative AI can also help detecting Fake

Jorge Cortés, Lorenzo Sironi

Spider pulsars are compact binary systems composed of a millisecond pulsar and a low-mass companion. Their X-ray emission - modulated on the orbital period - is interpreted as synchrotron radiation from high-energy electrons accelerated at the intrabinary shock. We perform global two-dimensional particle-in-cell simulations of the intrabinary shock, assuming

Chris Halcrow, Ilya Shipulin, Federico Caglieris, Yongwei Li

Experiments have pointed to the formation of the electron quadrupling condensate in Ba$_{1-x}$K$_x$Fe$_2$As$_2$ at $x \sim 0.8$. The state spontaneously breaks time-reversal symmetry and is sandwiched between two critical points, separating it from the broken time-reversal symmetry (BTRS) superconducting state at $T_{\rm c}^{U(1)}$ and normal-metal state at

M. R. Mumpower, T. M. Sprouse, J. M. Miller, K. A. Lund

The simulation of heavy element nucleosynthesis requires input from yet-to-be-measured nuclear properties. The uncertainty in the values of these off-stability nuclear properties propagates to uncertainties in the predictions of elemental and isotopic abundances. However, for any given astrophysical explosion, there are many different trajectories, i.e. temp

Zhongming Yu, Genghan Zhang, Hanxian Huang, Xin Chen

In recent years, Graph Neural Networks (GNNs) have ignited a surge of innovation, significantly enhancing the processing of geometric data structures such as graphs, point clouds, and meshes. As the domain continues to evolve, a series of frameworks and libraries are being developed to push GNN efficiency to new heights. While graph-centric libraries have ac

Shaun R. Cooke, Chadwick W. Sinclair, Daan M. Maijer

The usefulness of semi-analytical thermal models for predicting the connection between process, microstructure and properties in powder bed fusion has been well illustrated in recent years. Such an approach provides the promise of accuracy comparable to tools that are orders of magnitude more computationally expensive. The opportunity to make predictions tha

Kehan Long, Jorge Cortes, Nikolay Atanasov

This article presents novel methods for synthesizing distributionally robust stabilizing neural controllers and certificates for control systems under model uncertainty. A key challenge in designing controllers with stability guarantees for uncertain systems is the accurate determination of and adaptation to shifts in model parametric uncertainty during onli

Damien A. Easson, Joseph E. Lesnefsky

We consider the possibility of a past and future eternal universe, constructing geodesically complete inflating, loitering, and bouncing spacetimes. We identify the constraints energy conditions in General Relativity place on the building of eternal cosmological models. Inflationary and bouncing behavior are shown to be essential ingredients in all significa

Felix Fent, Andras Palffy, Holger Caesar

The perception of autonomous vehicles has to be efficient, robust, and cost-effective. However, cameras are not robust against severe weather conditions, lidar sensors are expensive, and the performance of radar-based perception is still inferior to the others. Camera-radar fusion methods have been proposed to address this issue, but these are constrained by

Alek Hutson

One of the main goals in the study of hadronic interactions at LHC energies is the attempt to characterize the mechanisms involved in particle production in different regimes. The charged-particle multiplicity is one of the most interesting observables in these kind of studies. Measurements of charged-particle pseudorapidity densities in pp collisions at $\s

Pranav Pulakkat

Covariant phase space methods are applied to the analysis of a causal diamond in 2+1-dimensional pure Einstein gravity. It is found that the reduced phase space is parametrized by a family of charges with a dual geometrical interpretation: they are geometric observables on the corner of the diamond, and they generate diffeomorphisms. The Poisson brackets amo

Cleon Liew, Milena Radenkovic

This paper explores the Opportunistic Routing Protocols in the context of remote sea emergency scenarios, using the MH370 plane crash as a case study (OppNetMH370). We studied the likelihood of successful transmissions of emergency messages to response services where communication methods are inadequate in remote sea areas. The study focuses on two opportuni

Swarup Ranjan Behera, Vijaya V. Saradhi

Spectral clustering methods have gained widespread recognition for their effectiveness in clustering high-dimensional data. Among these techniques, constrained spectral clustering has emerged as a prominent approach, demonstrating enhanced performance by integrating pairwise constraints. However, the application of such constraints to semidefinite spectral c

Cyriana M. A. Roelofs, Christian Gück, Stefan Faulstich

Anomaly detection in wind turbines typically involves using normal behaviour models to detect faults early. However, training autoencoder models for each turbine is time-consuming and resource intensive. Thus, transfer learning becomes essential for wind turbines with limited data or applications with limited computational resources. This study examines how

Yannick Kirchhoff, Maximilian R. Rokuss, Saikat Roy, Balint Kovacs

Accurately segmenting thin tubular structures, such as vessels, nerves, roads or concrete cracks, is a crucial task in computer vision. Standard deep learning-based segmentation loss functions, such as Dice or Cross-Entropy, focus on volumetric overlap, often at the expense of preserving structural connectivity or topology. This can lead to segmentation erro

Yuan Sun, Eunchae Jang, Fenglong Ma, Ting Wang

Propelled by their remarkable capabilities to generate novel and engaging content, Generative Artificial Intelligence (GenAI) technologies are disrupting traditional workflows in many industries. While prior research has examined GenAI from a techno-centric perspective, there is still a lack of understanding about how users perceive and utilize GenAI in real

C. Garcia-Quintero, J. Mena-Fernández, A. Rocher, S. Yuan

The Dark Energy Spectroscopic Instrument (DESI) will provide precise measurements of Baryon Acoustic Oscillations (BAO) to constrain the expansion history of the Universe and set stringent constraints on dark energy. Therefore, precise control of the global error budget due to various systematic effects is required for the DESI 2024 BAO analysis. In this wor

J. Mena-Fernández, C. Garcia-Quintero, S. Yuan, B. Hadzhiyska

In this paper, we present the estimation of systematics related to the halo occupation distribution (HOD) modeling in the baryon acoustic oscillations (BAO) distance measurement of the Dark Energy Spectroscopic Instrument (DESI) 2024 analysis. This paper focuses on the study of HOD systematics for luminous red galaxies (LRG). We consider three different HOD

M. Rashkovetskyi, D. Forero-Sánchez, A. de Mattia, D. J. Eisenstein

We present an optimized way of producing the fast semi-analytical covariance matrices for the Legendre moments of the two-point correlation function, taking into account survey geometry and mimicking the non-Gaussian effects. We validate the approach on simulated (mock) catalogs for different galaxy types, representative of the Dark Energy Spectroscopic Inst

J. Lasker, A. Carnero Rosell, A. D. Myers, A. J. Ross

A critical requirement of spectroscopic large scale structure analyses is correcting for selection of which galaxies to observe from an isotropic target list. This selection is often limited by the hardware used to perform the survey which will impose angular constraints of simultaneously observable targets, requiring multiple passes to observe all of them.

E. Paillas, Z. Ding, X. Chen, H. Seo

Baryon acoustic oscillations (BAO) provide a robust standard ruler to measure the expansion history of the Universe through galaxy clustering. Density-field reconstruction is now a widely adopted procedure for increasing the precision and accuracy of the BAO detection. With the goal of finding the optimal reconstruction settings to be used in the DESI 2024 g

Andrei Cuceu, Hiram K. Herrera-Alcantar, Calum Gordon, Paul Martini

The first year of data from the Dark Energy Spectroscopic Instrument (DESI) contains the largest set of Lyman-$\alpha$ (Ly$\alpha$) forest spectra ever observed. This data, collected in the DESI Data Release 1 (DR1) sample, has been used to measure the Baryon Acoustic Oscillation (BAO) feature at redshift $z=2.33$. In this work, we use a set of 150 synthetic

J. Guy, S. Gontcho A Gontcho, E. Armengaud, A. Brodzeller

Baryon Acoustic Oscillations can be measured with sub-percent precision above redshift two with the Lyman-alpha forest auto-correlation and its cross-correlation with quasar positions. This is one of the key goals of the Dark Energy Spectroscopic Instrument (DESI) which started its main survey in May 2021. We present in this paper a study of the contaminants

DESI Collaboration, A. G. Adame, J. Aguilar, S. Ahlen

We present cosmological results from the measurement of baryon acoustic oscillations (BAO) in galaxy, quasar and Lyman-$\alpha$ forest tracers from the first year of observations from the Dark Energy Spectroscopic Instrument (DESI), to be released in the DESI Data Release 1. DESI BAO provide robust measurements of the transverse comoving distance and Hubble

DESI Collaboration, A. G. Adame, J. Aguilar, S. Ahlen

We present the measurement of Baryon Acoustic Oscillations (BAO) from the Lyman-$\alpha$ (Ly$\alpha$) forest of high-redshift quasars with the first-year dataset of the Dark Energy Spectroscopic Instrument (DESI). Our analysis uses over $420\,000$ Ly$\alpha$ forest spectra and their correlation with the spatial distribution of more than $700\,000$ quasars. A

DESI Collaboration, A. G. Adame, J. Aguilar, S. Ahlen

We present the DESI 2024 galaxy and quasar baryon acoustic oscillations (BAO) measurements using over 5.7 million unique galaxy and quasar redshifts in the range 0.1<z<2.1. Divided by tracer type, we utilize 300,017 galaxies from the magnitude-limited Bright Galaxy Survey with 0.1<z<0.4, 2,138,600 Luminous Red Galaxies with 0.4<z<1.1, 2,432,022 Emission Line

John J. Han, Ayberk Acar, Nicholas Kavoussi, Jie Ying Wu

Style transfer is a promising approach to close the sim-to-real gap in medical endoscopy. Rendering synthetic endoscopic videos by traversing pre-operative scans (such as MRI or CT) can generate structurally accurate simulations as well as ground truth camera poses and depth maps. Although image-to-image (I2I) translation models such as CycleGAN can imitate

Sathyanarayanan Chandramouli, Simeon I. Mistakidis, Garyfallia C. Katsimiga, Panayotis G. Kevrekidis

We demonstrate the controllable generation of distinct types of dispersive shock-waves emerging in a quantum droplet bearing environment with the aid of step-like initial conditions. Dispersive regularization of the ensuing hydrodynamic singularities occurs due to the competition between meanfield repulsion and attractive quantum fluctuations. This interplay

Yi-Xiao Tao, Konglong Wu

In this work, we investigated the off-shell expansion relation of the Yang-Mills scalar theory. We explicitly showed that the single-trace Berends-Giele currents in the Yang-Mills scalar theory can be decomposed into a term expressed by a linear combination of bi-adjoint scalar Berends-Giele currents and one that vanishes under the on-shell limit. We proved

Robert Streeck, Torsten Gellert, Andreas Schmitt, Asya Dipkaya

In automated decision making processes in the online fashion industry, the 'predict-then-optimize' paradigm is frequently applied, particularly for markdown pricing strategies. This typically involves a mixed-integer optimization step, which is crucial for maximizing profit and merchandise volume. In practice, the size and complexity of the optimization prob

Amit Acharya

The fully nonlinear (geometric and material) system of Field Dislocation Mechanics is reviewed to establish an exact analogy with the equations of ideal magnetohydrodynamics (ideal MHD) under suitable physically simplifying circumstances. Weak solutions with various conservation properties have been established for ideal MHD recently by Faraco, Lindberg, and

P. Suárez-Serrato, J. Torres Orozco

We provide local formul{\ae} for Poisson bivectors and symplectic forms on the leaves of Poisson structures associated to wrinkled fibrations on smooth $4$--manifolds.

Logan E. Hillberry, Lorenzo Piroli, Eric Vernier, Nicole Yunger Halpern

Goldilocks quantum cellular automata (QCA) have been simulated on quantum hardware and produce emergent small-world correlation networks. In Goldilocks QCA, a single-qubit unitary is applied to each qubit in a one-dimensional chain subject to a balance constraint: a qubit is updated if its neighbors are in different computational-basis states. We prove that

Nemanja Kaloper, Alexander Westphal

We propose using fuzzy axion dark matter to test the anthropic principle. A very light axion can be directly detectable, at least by black hole superradiance effects. The idea then is that gravitational and astrophysical observations can discover a light axion in the regime where it must be all of dark matter with abundance which must be set up by the anthro

CMS Collaboration

Searches for pair-produced multijet signatures using data corresponding to an integrated luminosity of 128 fb$^{-1}$ of proton-proton collisions at $\sqrt{s}$ = 13 TeV are presented. A data scouting technique is employed to record events with low jet scalar transverse momentum sum values. The electroweak production of particles predicted in $R$-parity violat

Alexander Smith, Gavin J. Donley, Emanuela Del Gado, Victor M. Zavala

Soft gels, formed via the self-assembly of particulate organic materials, exhibit intricate multi-scale structures that provides them with flexibility and resilience when subjected to external stresses. This work combines molecular simulations and topological data analysis (TDA) to characterize the complex multi-scale structure of soft gels. Our TDA analysis

Jinbin Huang, Chen Chen, Aditi Mishra, Bum Chul Kwon

Generative image models have emerged as a promising technology to produce realistic images. Despite potential benefits, concerns grow about its misuse, particularly in generating deceptive images that could raise significant ethical, legal, and societal issues. Consequently, there is growing demand to empower users to effectively discern and comprehend patte

Mallika T. Randeria, Thomas M. Hazard, Agustin Di Paolo, Kate Azar

Phase slips occur across all Josephson junctions (JJs) at a rate that increases with the impedance of the junction. In superconducting qubits composed of JJ-array superinductors -- such as fluxonium -- phase slips in the array can lead to decoherence. In particular, phase-slip processes at the individual array junctions can coherently interfere, each with an

Siyi Wang, Zifan Wang, Xinlei Yi, Michael M. Zavlanos

Considering non-stationary environments in online optimization enables decision-maker to effectively adapt to changes and improve its performance over time. In such cases, it is favorable to adopt a strategy that minimizes the negative impact of change to avoid potentially risky situations. In this paper, we investigate risk-averse online optimization where

Jason Curran, Romina Gaburro, Clifford Nolan

We construct singular solutions of a complex elliptic equation of second order, having an isolated singularity of any order. In particular, we extend results obtained for the real partial differential equation in divergence form by Alessandrini in 1990. Our solutions can be applied to the determination of the optical properties of an anisotropic medium in ti

Yaozhong Shi, Angela F. Gao, Zachary E. Ross, Kamyar Azizzadenesheli

Regression on function spaces is typically limited to models with Gaussian process priors. We introduce the notion of universal functional regression, in which we aim to learn a prior distribution over non-Gaussian function spaces that remains mathematically tractable for functional regression. To do this, we develop Neural Operator Flows (OpFlow), an infini

A. T. Bondy, J. C. del Valle, S. Saha, K. R. Hamilton

Following up on a recent paper [Bharti et al., Phys. Rev. A 109 (2024) 023110], we compare the predictions from severalR-matrix with time-dependence calculations for a modified three-sideband version of the "reconstruction of attosecond beating by interference of two-photon transitions" (RABBITT) configuration applied to helium. Except for the special case o

Joost Jorritsma, Júlia Komjáthy, Dieter Mitsche

We study cluster sizes in supercritical $d$-dimensional inhomogeneous percolation models with long-range edges -- such as long-range percolation -- and/or heavy-tailed degree distributions -- such as geometric inhomogeneous random graphs and the age-dependent random connection model. Our focus is on large deviations of the size of the largest cluster in the

Gaia Carenini, Luca Bischetti, Walter Schaeken, Valentina Bambini

The Rational Speech Act (RSA) model provides a flexible framework to model pragmatic reasoning in computational terms. However, state-of-the-art RSA models are still fairly distant from modern machine learning techniques and present a number of limitations related to their interpretability and scalability. Here, we introduce a new RSA framework for metaphor

Steffen Maletz, Konstantinos Fokianos, Roland Fried

We study the problem of modeling and inference for spatio-temporal count processes. Our approach uses parsimonious parameterisations of multivariate autoregressive count time series models, including possible regression on covariates. We control the number of parameters by specifying spatial neighbourhood structures for possibly huge matrices that take into

Jiangtao Wang, Xudong Zheng, Gregory Pitner, Xiang Ji

Electrostatic catalysis has been an exciting development in chemical synthesis (beyond enzymes catalysis) in recent years, boosting reaction rates and selectively producing certain reaction products. Most of the studies to date have been focused on using external electric field (EEF) to rearrange the charge distribution in small molecule reactions such as Di

Nicoleta Voicu, Salah Gomaa Elgendi

For a torsion-free affine connection on a given manifold, which does not necessarily arise as the Levi-Civita connection of any pseudo-Riemannian metric, it is still possible that it corresponds in a canonical way to a Finsler structure; this property is known as Finsler (or Berwald-Finsler) metrizability. In the present paper, we clarify, for 4-dimensional

Yanghao Fang, William Tuxbury, Abhishek Gupta, Tsampikos Kottos

Damping typically results in attenuation of vibrations and elastic wave propagation in mechanical systems. Contrary to this conventional understanding, we demonstrate experimentally and explain theoretically the revival of an elastic wave transmitted through a periodic metastructure when a weak non-Hermitian defect (damping mechanism) induces violation of ti

A. Berdja, M. Hadjara, M. Carbillet, R. L. Bernardi

Optical turbulence modelling and simulation are crucial for developing astronomical ground-based instruments, laser communication, laser metrology, or any application where light propagates through a turbulent medium. In the context of spectrum-based optical turbulence Monte-Carlo simulations, we present an alternative approach to the methods based on the Fa

Ze-Hua Wu, H. Lu

We study charged scalar perturbations of charged extremal black holes in Einstein-Born-Infeld theory. Our numerical results indicate that these black holes all suffer from superradiant instability by the unstable quasi-bound states, regardless how small the coupling constant is. We therefore provide a new example that the superradiant stability of the Reissn

Ilija Medan, Sébastien Lépine, Zachary Hartman, Keivan G. Stassun

Here we present speckle observations of 16 low-separation ($s<30$ AU) high probability candidate binaries from the catalog by Medan et al., where secondaries typically lack astrometric solutions in Gaia. From these speckle observations, we find a second component is always detected within the field of view. To determine if the detection is consistent with a

Grace M. Sommers, Sarang Gopalakrishnan, Michael J. Gullans, David A. Huse

In chaotic quantum systems, the entanglement of a region $A$ can be described in terms of the surface tension of a spacetime membrane pinned to the boundary of $A$. Here, we interpret the tension of this entanglement membrane in terms of the rate at which information "flows" across it. For any orientation of the membrane, one can define (generically nonunita

M. P. Battley, K. A. Collins, S. Ulmer-Moll, S. N. Quinn

Long-period transiting exoplanets bridge the gap between the bulk of transit- and Doppler-based exoplanet discoveries, providing key insights into the formation and evolution of planetary systems. The wider separation between these planets and their host stars results in the exoplanets typically experiencing less radiation from their host stars; hence, they

Mike Walmsley, Micah Bowles, Anna M. M. Scaife, Jason Shingirai Makechemu

We present the first systematic investigation of supervised scaling laws outside of an ImageNet-like context - on images of galaxies. We use 840k galaxy images and over 100M annotations by Galaxy Zoo volunteers, comparable in scale to Imagenet-1K. We find that adding annotated galaxy images provides a power law improvement in performance across all architect

Sebastian Bahamonde, Daniel Blixt, Konstantinos F. Dialektopoulos, Anamaria Hell

We study the degrees of freedom in New General Relativity -- flat and metric compatible family of theories -- around the Minkowski background in a gauge invariant manner. First, we confirm the decoupling case, in which the theory reduces to linearized gravity plus a massless KR field. We then show that, unless they vanish, the vector modes of this theory wil

Luca Ciambriello, Roberto Contino, Ling-Xiao Xu

Our recent works revisit the proof of chiral symmetry breaking in the confining phase of four-dimensional QCD-like theories, i.e. $SU(N_c)$ gauge theories with $N_f$ flavors of vectorlike quarks in the fundamental representation. The analysis relies on the structure of 't Hooft anomaly matching and persistent mass conditions for theories with same $N_c$ and

Mónica Taormina, R. -P. Kudritzki, B. Pilecki, G. Pietrzyński

We present the results from a complex study of an eclipsing O-type binary (Aa+Ab) with the orbital period $P_{A}=3.2254367$ days, that forms part of a higher-order multiple system in a configuration (A+B)+C. We derived masses of the Aa+Ab binary $M_{1}= 19.02 \pm 0.12 \,M_\odot$, $M_{2}= 17.50 \pm 0.13 \,M_\odot$, radii $R_{1}= 7.70 \pm 0.05 \,R_\odot$, $R_{

G. Mantovan, L. Malavolta, D. Locci, D. Polychroni

Multi-planet systems exhibit remarkable architectural diversity. However, short-period giant planets are typically isolated. Compact systems like TOI-5398, with an outer close-orbit giant and an inner small-size planet, are rare among systems containing short-period giants. TOI-5398's unusual architecture coupled with its young age (650 $\pm$ 150 Myr) make i

Kemal Aziz, Ahana Chakraborty, J. H. Pixley

The effects of different forms of weak measurements on the nature of the measurement induced phase transition are theoretically studied in hybrid random quantum circuits of qubits. We use a combination of entanglement measures, ancilla purification dynamics, and a transfer matrix approach to compute the critical exponents, the effective central charge, and t

Luca Ciambriello, Roberto Contino, Andrea Luzio, Marcello Romano

We demonstrate that chiral symmetry breaking occurs in the confining regime of QCD-like theories with $N_c$ colors and $N_f$ flavors. Our proof is based on a novel strategy, called `downlifting', by which solutions of the 't Hooft anomaly matching and persistent mass conditions for a theory with $N_f-1$ flavors are constructed from those of a theory with $N_

Eric R. Anschuetz, David Gamarnik, Bobak T. Kiani

We consider the problem of estimating the ground state energy of quantum $p$-local spin glass random Hamiltonians, the quantum analogues of widely studied classical spin glass models. Our main result shows that the maximum energy achievable by product states has a well-defined limit (for even $p$) as $n\to\infty$ and is $E_{\text{product}}^\ast=\sqrt{2 \log

Kunal Sharma, Minh C. Tran

We propose an algorithm for simulating the dynamics of a geometrically local Hamiltonian $A$ under a small geometrically local perturbation $\alpha B$. In certain regimes, the algorithm achieves the optimal scaling and outperforms the state-of-the-art algorithms. By moving into the interaction frame of $A$ and classically computing the Magnus expansion of th

Zohreh Davoudi, Christopher Jarzynski, Niklas Mueller, Greeshma Oruganti

A key objective in nuclear and high-energy physics is to describe nonequilibrium dynamics of matter, e.g., in the early universe and in particle colliders, starting from the Standard Model. Classical-computing methods, via the framework of lattice gauge theory, have experienced limited success in this mission. Quantum simulation of lattice gauge theories hol

T. Cridge, L. A. Harland-Lang, R. S. Thorne

We present the first determination of the value of the strong coupling via a simultaneous global fit of the proton parton distribution functions (PDFs) at approximate N$^{3}$LO (aN$^{3}$LO) order in QCD. This makes use of the MSHT global PDF fitting framework, and in particular the recent theoretical advances that allow a PDF fit to now be performed at this

Wei-Yang Chen, Shih-Wen Huang, Yi Tseng, Wenliang Zhang

Resonant inelastic x-ray scattering (RIXS) experiment was performed at the Mn $L_3$ edge. A 10 $\%$ Mn-doped Sr$_{3}$Ru$_{2}$O$_{7}$ compound, where the Mn$^{3+}$ ions are in the 3$d^4$ state, were probed for $dd$ excitations. The dilute doping concentration allows one to treat the dopant Mn$^{3+}$ ions as effectively free in the host ruthenium compound. The

Corentin Cadiou, Clotilde Laigle, Oscar Agertz

Galaxies are complex objects, yet the number of independent parameters to describe them remains unknown. We present here a non-parametric method to estimate the intrinsic dimensionality of large datasets. We apply it to wide-band photometric data drawn from the COSMOS2020 catalogue and a comparable mock catalogue from the Horizon-AGN simulation. Our galaxy c

Yang Liu, Antonio Padilla, Francisco G. Pedro

We examine the descent via membrane nucleation through a landscape of vacua where the cosmological constant is given by a combination of four-form fluxes. It has been shown that this descent can be slowed exponentially for very low curvature vacua close to Minkowski space in a wide class of models satisfying certain parametric conditions, providing a possibl

Sofía Rojas-Ruiz, Chiara Mazzucchelli, Steven L. Finkelstein, Eduardo Bañados

Theoretical models predict that z~6 quasars are hosted in the most massive halos of the underlying dark matter distribution and thus would be immersed in protoclusters of galaxies. However, observations report inconclusive results. We investigate the 1.1 pMpc2 environment of the z = 7.54 luminous quasar ULAS J1342+0928. We search for Lyman-break galaxy candi

G. Mountrichas, M. Siudek, O. Cucciati

In this work, we compare the SFRs and SFHs of AGN and non-AGN galaxies. We explore these aspects across different density fields and over three orders of magnitude in L$_X$. For that purpose, we employ X-ray AGN detected in the XMM-XXL field and construct a galaxy control sample, using sources from the VIPERS catalogue. Our final samples consist of 149 X-ray

Enrico Ragusa, Elliot Lynch, Guillaume Laibe, Cristiano Longarini

Protostellar discs are mostly modelled as circular structures of gas and dust orbiting a protostar. However, a number of physical mechanisms, e.g. the presence of a (sub)stellar companion or initial axial asymmetry, can cause the gas and dust orbital motion to become eccentric. Theoretical studies have revealed that, when present, disc eccentricity is expect

Simon Bernier, Kartiek Agarwal

Quantum simulators have the potential to shed light on the study of quantum many-body systems and materials, offering unique insights into various quantum phenomena. While adiabatic evolution has been conventionally employed for state preparation, it faces challenges when the system evolves too quickly or the coherence time is limited. In such cases, shortcu

James B. Dent, Bhaskar Dutta, Tao Xu

Superradiance provides a unique opportunity for investigating dark sectors as well as primordial black holes, which themselves are candidates for dark matter over a wide mass range. Using axion-like particles as an example, we show that line signals emerging from a superradiated axion cloud combined with black hole Hawking radiation in extragalactic and gala

Elias Furrer, Horia Magureanu

Symmetries of Seiberg-Witten (SW) geometries capture intricate physical aspects of the underlying 4d $\mathcal{N} = 2$ field theories. For rank-one theories, these geometries are rational elliptic surfaces whose automorphism group is a semi-direct product between the Coulomb branch (CB) symmetries and the Mordell-Weil group. We study quotients of the SW geom

Gabriel Loaiza-Ganem, Brendan Leigh Ross, Rasa Hosseinzadeh, Anthony L. Caterini

In recent years there has been increased interest in understanding the interplay between deep generative models (DGMs) and the manifold hypothesis. Research in this area focuses on understanding the reasons why commonly-used DGMs succeed or fail at learning distributions supported on unknown low-dimensional manifolds, as well as developing new models explici

Tariq Hilmi, Denis Erkal, Sergey E. Koposov, Ting S. Li

In the cold dark matter paradigm, our Galaxy is predicted to contain >10000 dark matter subhaloes in the $10^5-10^8M_\odot$ range which should be completely devoid of stars. Stellar streams are sensitive to the presence of these subhaloes, which can create small-scale features in streams if they pass closely enough. Modelling these encounters can therefore,

Stefanie Suzanne Brinkman, Xin Liang Tan, Bjørnulf Brekke, Anders Christian Mathisen

Chiral crystals and molecules were recently predicted to form an intriguing platform for unconventional orbital physics. Here, we report the observation of chirality-driven orbital textures in the bulk electronic structure of CoSi, a prototype member of the cubic B20 family of chiral crystals. Using circular dichroism in soft X-ray angle-resolved photoemissi

Erik J. Gustafson, Juha Tiihonen, Diana Chamaki, Farshud Sorourifar

Variational quantum eigensolvers are touted as a near-term algorithm capable of impacting many applications. However, the potential has not yet been realized, with few claims of quantum advantage and high resource estimates, especially due to the need for optimization in the presence of noise. Finding algorithms and methods to improve convergence is importan

Malte Buschmann

Understanding the nonlinear dynamics of coupled scalar fields often necessitates simulations on a 3D mesh. These simulations can be computationally expensive if a large scale separation is involved. A common solution is adaptive mesh refinement which, however, greatly increases a simulation's complexity. In this work, we present sledgehamr, an AMReX-based co

Cari Cesarotti, Gordan Krnjaic

We study future lepton collider prospects for testing predictive models of leptophilic dark matter candidates with a thermal origin. We calculate experimental milestones for testing the parameter space compatible with freeze-out and the associated collider signals at past, present, and future facilities. This analysis places new limits on such models by leve

Keyu Tian, Yi Jiang, Zehuan Yuan, Bingyue Peng

We present Visual AutoRegressive modeling (VAR), a new generation paradigm that redefines the autoregressive learning on images as coarse-to-fine "next-scale prediction" or "next-resolution prediction", diverging from the standard raster-scan "next-token prediction". This simple, intuitive methodology allows autoregressive (AR) transformers to learn visual d

Suzanne Petryk, David M. Chan, Anish Kachinthaya, Haodi Zou

Despite recent advances in multimodal pre-training for visual description, state-of-the-art models still produce captions containing errors, such as hallucinating objects not present in a scene. The existing prominent metric for object hallucination, CHAIR, is limited to a fixed set of MS COCO objects and synonyms. In this work, we propose a modernized open-

Vlas Zyrianov, Henry Che, Zhijian Liu, Shenlong Wang

We present LidarDM, a novel LiDAR generative model capable of producing realistic, layout-aware, physically plausible, and temporally coherent LiDAR videos. LidarDM stands out with two unprecedented capabilities in LiDAR generative modeling: (i) LiDAR generation guided by driving scenarios, offering significant potential for autonomous driving simulations, a

Savio Laricchia, Casey Eichstaedt, Dimitar Pashov, Mark van Schilfgaarde

The calculation of electron-phonon (e-ph) coupling from first principles is a topic of great interest in materials science, offering a robust, non-empirical framework to understand and predict a wide range of physical phenomena. While significant progress has been made using the Kohn-Sham framework of density functional theory (KS-DFT), it is increasingly ev

Raphaël Cerf, Carlo Mariconda

The basic problem of the calculus of variations consists of finding a function that minimizes an energy, like finding the fastest trajectory between two points for a point mass in a gravity field moving without friction under the influence of gravity or finding the best shape of a wing. The existence of a solution may be established in quite abstract spaces,

Harsh Rangwani, Pradipto Mondal, Mayank Mishra, Ashish Ramayee Asokan

Vision Transformer (ViT) has emerged as a prominent architecture for various computer vision tasks. In ViT, we divide the input image into patch tokens and process them through a stack of self attention blocks. However, unlike Convolutional Neural Networks (CNN), ViTs simple architecture has no informative inductive bias (e.g., locality,etc. ). Due to this,

Duygu Ceylan, Valentin Deschaintre, Thibault Groueix, Rosalie Martin

We present MatAtlas, a method for consistent text-guided 3D model texturing. Following recent progress we leverage a large scale text-to-image generation model (e.g., Stable Diffusion) as a prior to texture a 3D model. We carefully design an RGB texturing pipeline that leverages a grid pattern diffusion, driven by depth and edges. By proposing a multi-step t

Stephen Casper, Jieun Yun, Joonhyuk Baek, Yeseong Jung

Interpretability techniques are valuable for helping humans understand and oversee AI systems. The SaTML 2024 CNN Interpretability Competition solicited novel methods for studying convolutional neural networks (CNNs) at the ImageNet scale. The objective of the competition was to help human crowd-workers identify trojans in CNNs. This report showcases the met

Shubham Aggarwal, Muhammad Aneeq uz Zaman, Melih Bastopcu, Sennur Ulukus

We consider the problem of task offloading in multi-access edge computing (MEC) systems constituting $N$ devices assisted by an edge server (ES), where the devices can split task execution between a local processor and the ES. Since the local task execution and communication with the ES both consume power, each device must judiciously choose between the two.

Eren Tahir, Mert Bal

Image forgery is a topic that has been studied for many years. Before the breakthrough of deep learning, forged images were detected using handcrafted features that did not require training. These traditional methods failed to perform satisfactorily even on datasets much worse in quality than real-life image manipulations. Advances in deep learning have impa

Michael F. Zimmer

The paper [1] by Liu, Madhavan, and Tegmark sought to use machine learning methods to elicit known conservation laws for several systems. However, in their example of a damped 1D harmonic oscillator they made seven serious errors, causing both their method and result to be incorrect. In this Comment, those errors are reviewed.

Yoshihiko Matsumoto

The asymptotic Dirichlet problem for harmonic maps from the hyperbolic plane into conformally compact Einstein manifolds is used to give a holographic characterization of conformal geodesics on the boundary at infinity, in a way deeply inspired by a work of Fine and Herfray on renormalized area minimization.

Rishabh Kaushal, Jacob van de Kerkhof, Catalina Goanta, Gerasimos Spanakis

The Digital Services Act (DSA) is a much awaited platforms liability reform in the European Union that was adopted on 1 November 2022 with the ambition to set a global example in terms of accountability and transparency. Among other obligations, the DSA emphasizes the need for online platforms to report on their content moderation decisions (`statements of r

Yifan Xu, Xiao Liu, Xinghan Liu, Zhenyu Hou

Large language models (LLMs) have shown excellent mastering of human language, but still struggle in real-world applications that require mathematical problem-solving. While many strategies and datasets to enhance LLMs' mathematics are developed, it remains a challenge to simultaneously maintain and improve both language and mathematical capabilities in depl