April 2023 arXiv papers — page 63

Minghao Yue, Anna-Christina Eilers, Robert A. Simcoe, Sirio Belli

We test the impact of gravitational lensing on the lifetime estimates of seven high-redshift quasars at redshift $z\gtrsim6$. The targeted quasars are identified by their small observed proximity zone sizes, which indicate extremely short quasar lifetimes $(t_Q\lesssim10^5 \text{ yrs})$. However, these estimates of quasar lifetimes rely on the assumption tha

Andreas Ekstedt

Thermal field theory is indispensable for describing hot and dense systems. Yet perturbative calculations are often stymied by a host of energy scales, and tend to converge slowly. This means that precise results require the apt use of effective field theories. In this paper we refine the effective description of slowly varying gauge field known as hard ther

Radhika Tibrewala, Tarun Dutt, Angela Tong, Luke Ginocchio

The fastMRI brain and knee dataset has enabled significant advances in exploring reconstruction methods for improving speed and image quality for Magnetic Resonance Imaging (MRI) via novel, clinically relevant reconstruction approaches. In this study, we describe the April 2023 expansion of the fastMRI dataset to include biparametric prostate MRI data acquir

Zhiding Liang, Jinglei Cheng, Zhixin Song, Hang Ren

The advantages of quantum pulses over quantum gates have attracted increasing attention from researchers. Quantum pulses offer benefits such as flexibility, high fidelity, scalability, and real-time tuning. However, while there are established workflows and processes to evaluate the performance of quantum gates, there has been limited research on profiling p

Md Hasibul Amin, Mohammed E. Elbtity, Ramtin Zand

With the increased attention to memristive-based in-memory analog computing (IMAC) architectures as an alternative for energy-hungry computer systems for machine learning applications, a tool that enables exploring their device- and circuit-level design space can significantly boost the research and development in this area. Thus, in this paper, we develop I

Maitreyee Marathe, Line A. Roald

For a large (and recently increasing) number of households, affordability is a major hurdle in accessing sufficient electricity and avoiding service disconnections. For such households, in-home energy rationing, i.e. the need to actively prioritize how to use a limited amount of electricity, is an everyday reality. In this paper, we consider a particularly v

Branko Juran, Pieter Moree, Adrian Riekert, David Schmitz

The largest coefficient (in absolute value) of a cyclotomic polynomial $\Phi_n$ is called its height $A(n)$. In case $p$ is a fixed prime it turns out that as $q$ and $r$ range over all primes satisfying $p<q<r$, the height $A(pqr)$ assumes a maximum $M(p)$. In 1968, Sister Marion Beiter conjectured that $M(p)\leq (p+1)/2$. In 2009, this was disproved for ev

Sheikh Rubaiat Ul Haque, Marios H. Michael, Junbo Zhu, Yuan Zhang

Condensates are a hallmark of emergence in quantum materials with superconductors and charge density wave as prominent examples. An excitonic insulator (EI) is an intriguing addition to this library, exhibiting spontaneous condensation of electron-hole pairs. However, condensate observables can be obscured through parasitic coupling to the lattice. Time-reso

Poojaa C, John Sahaya Rani Alex

Parkinson's disease (PD) has been found to affect 1 out of every 1000 people, being more inclined towards the population above 60 years. Leveraging wearable-systems to find accurate biomarkers for diagnosis has become the need of the hour, especially for a neurodegenerative condition like Parkinson's. This work aims at focusing on early-occurring, common sym

Cheng-Kang Ted Chao, Yotam Gingold

Image and shape editing are ubiquitous among digital artworks. Graphics algorithms facilitate artists and designers to achieve desired editing intents without going through manually tedious retouching. In the recent advance of machine learning, artists' editing intents can even be driven by text, using a variety of well-trained neural networks. They have see

Weiqi Xu, Li Ling, Yiping Xie, Jun Zhang

Acoustic sensors play an important role in autonomous underwater vehicles (AUVs). Sidescan sonar (SSS) detects a wide range and provides photo-realistic images in high resolution. However, SSS projects the 3D seafloor to 2D images, which are distorted by the AUV's altitude, target's range and sensor's resolution. As a result, the same physical area can show

Zhili Xiao, Shantanu Chakrabartty

Precise estimation of cross-correlation or similarity between two random variables lies at the heart of signal detection, hyperdimensional computing, associative memories, and neural networks. Although a vast literature exists on different methods for estimating cross-correlations, the question what is the best and simplest method to estimate cross-correlati

Ryan Plestid

In this work we consider sub-leading $O(Z^2\alpha^3)$ corrections to coherent elastic neutrino nucleus scattering (CEvNS). These corrections are not negligible by power counting since nuclei with large coherent cross sections have sizeable nuclear charges e.g.\ $Z\alpha \sim 0.4$. We find that the corrections are much smaller than naive power counting in $Z\

Hani Sami, Ahmad Hammoud, Mouhamad Arafeh, Mohamad Wazzeh

The Metaverse offers a second world beyond reality, where boundaries are non-existent, and possibilities are endless through engagement and immersive experiences using the virtual reality (VR) technology. Many disciplines can benefit from the advancement of the Metaverse when accurately developed, including the fields of technology, gaming, education, art, a

John Vandermeer, Ivette Perfecto

Historically, musings about the structure of ecological communities has revolved around the structure of pairwise interactions, competition, predation, mutualism, etc. . . Recently a growing literature acknowledges that the baseline assumption that the pair of species is not necessarily the metaphorical molecule of community ecology, and that certain structu

J. Sean Doody, Gordon Burghardt, Vladimir Dinets

The polyvagal theory (PT), offered by Porges (2021), proposes that the autonomic nervous system (ANS) was repurposed in mammals, via a second vagal nerve, to suppress defensive strategies and support the expression of sociality. Three critical assumptions of this theory are that (1) the transition of the ANS was associated with the evolution of social mammal

C. L. Pereira, B. Sicardy, B. E. Morgado, F. Braga-Ribas

Quaoar is a classical Trans-Neptunian Object (TNO) with an area equivalent diameter of 1,100 km and an orbital semi-major axis of 43.3 astronomical units. Based on stellar occultations observed between 2018 and 2021, an inhomogeneous ring (Q1R, Quaoar's first ring) was detected around this body. Aims. A new stellar occultation by Quaoar was observed on Augus

Jnaneshwar Baslingker

We give a stochastic comparison and ordering of the largest eigenvalues, with parameter $\beta$, for Hermite $\beta$-ensembles and Laguerre $\beta$-ensembles. Although stochastic comparison results are well known in Laguerre ensembles (for $\beta=1,2,4$) using the last passage percolation models, our results are novel even for $\beta=1,2,4$, in Hermite ensem

Arne Bouillon, Giovanni Samaey, Karl Meerbergen

The ParaOpt algorithm was recently introduced as a time-parallel solver for optimal-control problems with a terminal-cost objective, and convergence results have been presented for the linear diffusive case with implicit-Euler time integrators. We reformulate ParaOpt for tracking problems and provide generalized convergence analyses for both objectives. We f

Haripriya Pulyassary, Ruifan Yang, Zhanhao Zhang, Manxi Wu

In this article, we study the optimal design of High Occupancy Toll (HOT) lanes. In our setup, the traffic authority determines the road capacity allocation between HOT lanes and ordinary lanes, as well as the toll price charged for travelers who use the HOT lanes but do not meet the high-occupancy eligibility criteria. We build a game-theoretic model to ana

Khushbu Khatri Park, Abdulaziz Ahmed, Mohammed Ali Al-Garadi

Background: The use of machine learning (ML) in mental health (MH) research is increasing, especially as new, more complex data types become available to analyze. By systematically examining the published literature, this review aims to uncover potential gaps in the current use of ML to study MH in vulnerable populations of immigrants, refugees, migrants, an

Filipe Marques Barbosa, Anton Kullberg, Johan Löfberg

This paper addresses the trade-off between time- and energy-efficiency for the problem of loading and unloading a ship. Container height constraints and energy consumption and regeneration are dealt with. We build upon a previous work that introduced a coordinate system suitable to deal with container avoidance constraints and incorporate the energy related

Michael Benedikt, Ehud Hrushovski

We revisit evaluation of logical formulas that allow both uninterpreted relations, constrained to be finite, as well as an interpreted vocabulary over an infinite domain. This formalism was denoted embedded finite model theory in the past. It is clear that the expressiveness and evaluating complexity of formulas of this type depends heavily on the infinite s

Selçuk Çakmak, Hamid Reza Rastegar Sedehi

In this contribution, we investigate two coupled spins as a working substance of the quantum Stirling heat engine cycle. We propose an experimentally implementable scheme in which the cycle is driven by tuning the dipole-dipole interaction angle via dynamic-angle spinning technique in a fixed magnetic field. Realistic parameters are chosen for the proposed h

Robin Ben Klein, Benjamin Sanderse

A novel hyper-reduction method is proposed that conserves kinetic energy and momentum for reduced order models of the incompressible Navier-Stokes equations. The main advantage of conservation of kinetic energy is that it endows the hyper-reduced order model (hROM) with a nonlinear stability property. The new method poses the discrete empirical interpolation

S. Teresi, N. Sebe, T. Frottier, J. Patterson

Driving a spin-logic circuit requires the production of a large output signal by spin-charge interconversion in spin-orbit readout devices. This should be possible by using topological insulators, which are known for their high spin-charge interconversion efficiency. However, high-quality topological insulators have so far only been obtained on a small scale

Taige Wang, Chen Wu, Masataka Mogi, Minoru Kawamura

Microwave impedance microscopy (MIM) has been utilized to directly visualize topological edge states in many quantum materials, from quantum Hall systems to topological insulators, across the GHz regime. While the microwave response for conventional metals and insulators can be accurately quantified using simple lumped-element circuits, the applicability of

Ziyi Xu, Ziyue Zhao, Tim Fingscheidt

Wideband codecs such as AMR-WB or EVS are widely used in (mobile) speech communication. Evaluation of coded speech quality is often performed subjectively by an absolute category rating (ACR) listening test. However, the ACR test is impractical for online monitoring of speech communication networks. Perceptual evaluation of speech quality (PESQ) is one of th

Zijin Gu, Keith Jamison, Mert R. Sabuncu, Amy Kuceyeski

Understanding how human brains interpret and process information is important. Here, we investigated the selectivity and inter-individual differences in human brain responses to images via functional MRI. In our first experiment, we found that images predicted to achieve maximal activations using a group level encoding model evoke higher responses than image

Arsenii Senokosov, Alexandr Sedykh, Asel Sagingalieva, Basil Kyriacou

Image classification, a pivotal task in multiple industries, faces computational challenges due to the burgeoning volume of visual data. This research addresses these challenges by introducing two quantum machine learning models that leverage the principles of quantum mechanics for effective computations. Our first model, a hybrid quantum neural network with

Seda Albayrak, Jason Bell

A theorem of Cobham says that if $k$ and $\ell$ are two multiplicatively independent natural numbers then a subset of the natural numbers that is both $k$- and $\ell$-automatic is eventually periodic. A multidimensional extension was later given by Semenov. In this paper, we give a quantitative version of the Cobham-Semenov theorem for sparse automatic sets,

Jose M. Diego, Sung Kei Li, Ashish K. Meena, Anna Niemiec

We present a constraint on the abundance of supergiant (SG) stars at redshift z approx. 1, based on recent observations of a strongly lensed arc at this redshift. First we derive a free-form model of MACS J0416.1-2403 using data from the BUFFALO program. The new lens model is based on 72 multiply lensed galaxies that produce 214 multiple images, making it th

Jing An, Jianfeng Lu

We study the convergence of stochastic gradient descent (SGD) for non-convex objective functions. We establish the local convergence with positive probability under the local \L{}ojasiewicz condition introduced by Chatterjee in \cite{chatterjee2022convergence} and an additional local structural assumption of the loss function landscape. A key component of ou

F. Murgas, A. Castro-González, E. Pallé, F. J. Pozuelos

The main scientific goal of TESS is to find planets smaller than Neptune around stars that are bright enough to allow for further characterization studies. Given our current instrumentation and detection biases, M dwarfs are prime targets in the search for small planets that are in (or near) the habitable zone of their host star. In this work, we use photome

Hugh R. A. Jones, Yakiv Pavlenko, Yuri Lyubchik, Mike Bessell

A blue depression is found in the spectra of M dwarfs from 4000 to 4500A. This depression shows an increase toward lower temperatures though is particularly sensitive to gravity and metallicity. It is the single most sensitive feature in the optical spectra of M dwarfs. The depression appears as centered on the neutral calcium resonance line at 4227A and lea

Ira Ktena, Olivia Wiles, Isabela Albuquerque, Sylvestre-Alvise Rebuffi

A ubiquitous challenge in machine learning is the problem of domain generalisation. This can exacerbate bias against groups or labels that are underrepresented in the datasets used for model development. Model bias can lead to unintended harms, especially in safety-critical applications like healthcare. Furthermore, the challenge is compounded by the difficu

David P. Woodruff, Taisuke Yasuda

Subset selection for the rank $k$ approximation of an $n\times d$ matrix $A$ offers improvements in the interpretability of matrices, as well as a variety of computational savings. This problem is well-understood when the error measure is the Frobenius norm, with various tight algorithms known even in challenging models such as the online model, where an alg

Amar Hadzihasanovic, Diana Kessler

Higher-dimensional rewriting is founded on a duality of rewrite systems and cell complexes, connecting computational mathematics to higher categories and homotopy theory: the two sides of a rewrite rule are two halves of the boundary of an (n+1)-cell, which are diagrams of n-cells. We study higher-dimensional diagram rewriting as a mechanism of computation,

J. J. Fortney, B. Militzer, C. R. Mankovich, R. Helled

We present a review of Saturn's interior structure and thermal evolution, with a particular focus on work in the past 5 years. Data from the Cassini mission, including a precise determination of the gravity field from the Grand Finale orbits, and the still ongoing identification of ring wave features in Saturn's C-ring tied to seismic modes in the planet, ha

Valentin Delchevalerie, Alexandre Mayer, Adrien Bibal, Benoît Frénay

For many years, it has been shown how much exploiting equivariances can be beneficial when solving image analysis tasks. For example, the superiority of convolutional neural networks (CNNs) compared to dense networks mainly comes from an elegant exploitation of the translation equivariance. Patterns can appear at arbitrary positions and convolutions take thi

Gwyn Bellamy

We show that Coulomb branches for $3$-dimensional $\mathcal{N}=4$ supersymmetric gauge theories have symplectic singularities. This confirms a conjecture of Braverman-Finkelberg-Nakajima.

Soumangsu Chakraborty, Amit Giveon, David Kutasov

We extend the study of 2006.13249, 2303.12422 to black strings with general momentum, and discuss their interpretation in single-trace $T\bar T$ deformed $CFT_2$.

Arianna Benoni, Federico Capra, Marco Salucci, Andrea Massa

To the best of the authors' knowledge, this work presents the first large-scale indoor experimental assessment of an implementation of the emerging Smart ElectroMagnetic Environment (SEME) paradigm, which is based on the deployment of static-passive EM skins (SP-EMSs) to enhance the coverage in a 5 [GHz] Wi-Fi network. Unlike standard (laboratory-based) vali

Sean N. Raymond, Dimitri Veras, Matthew S. Clement, Andre Izidoro

In co-orbital planetary systems, two or more planets share the same orbit around their star. Here we test the dynamical stability of co-orbital rings of planets perturbed by outside forces. We test two setups: i) 'stationary' rings of planets that, when unperturbed, remain equally-spaced along their orbit; and ii) horseshoe constellation systems, in which pl

Sean N. Raymond, Dimitri Veras, Matthew S. Clement, Andre Izidoro

Co-orbital systems contain two or more bodies sharing the same orbit around a planet or star. The best-known flavors of co-orbital systems are tadpoles (in which two bodies' angular separations oscillate about the L4/L5 Lagrange points $60^\circ$ apart) and horseshoes (with two bodies periodically exchanging orbital energy to trace out a horseshoe shape in a

Shikai Qiu, Shuo Han, Xiangyang Ju, Benjamin Nachman

Parton labeling methods are widely used when reconstructing collider events with top quarks or other massive particles. State-of-the-art techniques are based on machine learning and require training data with events that have been matched using simulations with truth information. In nature, there is no unique matching between partons and final state objects

Simon kaare Larsen

The proliferation of Large Language Models (LLMs), such as ChatGPT, has raised concerns about their potential impact on academic integrity, prompting the need for LLM-resistant exam designs. This article investigates the performance of LLMs on exams and their implications for assessment, focusing on ChatGPT's abilities and limitations. We propose guidelines

Carl Philipp Zelle, Romain Daviet, Achim Rosch, Sebastian Diehl

In thermal equilibrium the dynamics of phase transitions is largely controlled by fluctuation-dissipation relations: On the one hand, friction suppresses fluctuations, while on the other hand the thermal noise is proportional to friction constants. Out of equilibrium, this balance dissolves and one can have situations where friction vanishes due to antidampi

A. P. S. Hygate, J. A. Hodge, E. da Cunha, M. Rybak

We present Atacama Large Millimeter/Submillimeter Array (ALMA) [CII] and $\sim158$ $\rm\mu m$ continuum observations of REBELS-25, a massive, morphologically complex ultra-luminous infrared galaxy (ULIRG; $L_{\rm IR}=1.5^{+0.8}_{-0.5}\times10^{12}$ L$_\odot$) at $z=7.31$, spectroscopically confirmed by the Reionization Era Bright Emission Line Survey (REBELS

Kieran Wood, Paul M. Saffin, Anastasios Avgoustidis

The higher order generalisation of the clockwork mechanism to gravitational interactions provides a means to generate an exponentially suppressed coupling to matter from a fundamental theory of multiple interacting gravitons, without introducing large hierarchies in the underlying potential and without the need for a dilaton, suggesting a possible applicatio

S. Ledda, C. Danielski, D. Turrini

The evolution of binaries that become double white dwarf (DWD) can cause the ejection of high amounts of dust and gas. Such material can give rise to circumbinary discs and become the cradle of new planets, yet no studies so far have focused on the formation of circumbinary planets around DWDs. These binaries will be the main sources of gravitational waves (

Dumitru Astefanesei, Paulina Cabrera, Robert B. Mann, Raúl Rojas

We expand our results in \cite{Astefanesei:2019ehu} to investigate a general class of exact hairy black hole solutions in Einstein-Maxwell-dilaton gravity. The dilaton is endowed with a potential that originates from an electromagnetic Fayet-Iliopoulos term in $\mathcal{N} = 2$ extended supergravity in four spacetime dimensions. We present the usual thermody

Elad Zinger, Gandhali Joshi, Annalisa Pillepich, Eric Rohr

We present the ``Cosmological Jellyfish'' project - a citizen-science classification program to identify jellyfish galaxies within the IllustrisTNG cosmological simulations. Jellyfish (JF) are satellite galaxies that exhibit long trailing gas features -- `tails' -- extending from their stellar body. Their distinctive morphology arises due to ram-pressure str

Andrés Anabalón, Mattia Cesàro, Antonio Gallerati, Alfredo Giambrone

The uncharged AdS$_4$ soliton has been recently shown to be continuously connected to a magnetic, supersymmetric AdS$_4$ soliton within $\mathcal{N}=8$ gauged supergravity. By constructing the asymptotic superalgebra, we establish a positive energy theorem for the magnetic AdS$_4$ solitons admitting well-defined asymptotic Killing spinors, antiperiodic on a

Leor Barack, Zvi Bern, Enrico Herrmann, Oliver Long

We compare numerical self-force results and analytical fourth-order post-Minkowskian (PM) calculations for hyperbolic-type scattering of a point-like particle carrying a scalar charge $Q$ off a Schwarzschild black hole, showing a remarkably good agreement. Specifically, we numerically compute the scattering angle including the full $O(Q^2)$ scalar-field self

Junia Göller, Gandhali Joshi, Eric Rohr, Elad Zinger

Due to ram-pressure stripping, jellyfish galaxies are thought to lose large amounts, if not all, of their interstellar medium. Nevertheless, some, but not all, observations suggest that jellyfish galaxies exhibit enhanced star formation compared to control samples, even in their ram pressure-stripped tails. We use the TNG50 cosmological gravity+magnetohydrod

Aseem Paranjape, Ravi K. Sheth

We develop a framework for self-consistently extracting cosmological information from the clustering of tracers in redshift space, $\textit{without}$ relying on model-dependent templates to describe the baryon acoustic oscillation (BAO) feature. Our approach uses the recently proposed Laguerre reconstruction technique for the BAO feature and its linear point

Miguel Gonçalves, Jedediah H. Pixley, Bruno Amorim, Eduardo V. Castro

We show that short-range interactions are irrelevant around gapless ground-state delocalization-localization transitions driven by quasiperiodicity in interacting fermionic chains. In the presence of interactions, these transitions separate Luttinger Liquid and Anderson glass phases. Remarkably, close to criticality, we find that excitations become effective

Eric Rohr, Annalisa Pillepich, Dylan Nelson, Elad Zinger

Jellyfish galaxies are prototypical examples of satellite galaxies undergoing strong ram pressure stripping (RPS). We analyze the evolution of 512 unique, first-infalling jellyfish galaxies from the TNG50 cosmological simulation. These have been visually inspected to be undergoing RPS sometime in the past 5 billion years (since $z=0.5$), have satellite stell

Thomas Flacke, Jeong Han Kim, Manuel Kunkel, Pyungwon Ko

We propose a deep learning-based search strategy for pair production of doubly charged scalars undergoing three-body decays to $W^+ t\bar b$ in the same-sign lepton plus multi-jet final state. This process is motivated by composite Higgs models with an underlying fermionic UV theory. We demonstrate that for such busy final states, jet image classification wi

Thomas C. Gehrman, Barmak Shams Es Haghi, Kuver Sinha, Tao Xu

In the post-LIGO era, there has been a lot of focus on primordial black holes (PBHs) heavier than $\sim 10^{15}$g as potential dark matter (DM) candidates. We point out that the branch of the PBH family that disappeared - PBHs lighter than $\sim 10^9$g that ostensibly Hawking evaporated away in the early Universe - also constitute an interesting frontier for

Stephen Stopyra, Hiranya V. Peiris, Andrew Pontzen, Jens Jasche

We investigate the accuracy requirements for field-level inference of cluster and void masses using data from galaxy surveys. We introduce a two-step framework that takes advantage of the fact that cluster masses are determined by flows on larger scales than the clusters themselves. First, we determine the integration accuracy required to perform field-level

V. Missaglia, A. Paggi, F. Massaro, A. Capetti

We present a statistical analysis of the large-scale (up to 2 Mpc) environment of an homogeneous and complete sample, both in radio and optical selection, of wide-angle tailed radio galaxies (WATs) in the local Universe (i.e., with redshifts $z\lesssim$ 0.15). The analysis is carried out using the parameters obtained from cosmological neighbors within 2 Mpc

Peter Espenshade, Jaiyul Yoo

Surveys with a narrow field-of-view can play an important role in probing cosmology, but inferences from these surveys suffer from large sample variance, arising from random fluctuations around the cosmic mean. The standard method for computing the sample variance is based on two key approximations: treating perturbations linearly and the survey geometry as

Johanna Erdmenger, Nick Evans, Yang Liu, Werner Porod

We investigate a holographic model for both spontaneous and explicit symmetry breaking of non-abelian flavour symmetries. This consists of a bottom-up model inspired by the top-down D3/D7 probe brane model that incorporates the running anomalous dimensions of the fields. We ensure that in the holographic bulk, the full non-abelian flavour symmetries for mass

Elisa V. Quintana, Emily A. Gilbert, Thomas Barclay, Michele L. Silverstein

We report the detection and validation of two planets orbiting TOI-2095 (TIC 235678745). The host star is a 3700K M1V dwarf with a high proper motion. The star lies at a distance of 42 pc in a sparsely populated portion of the sky and is bright in the infrared (K=9). With data from 24 Sectors of observation during TESS's Cycles 2 and 4, TOI-2095 exhibits two

Marcus Stålhammar, Cristiane Morais Smith

Non-Hermitian systems exhibit interesting band structures, where novel topological phenomena arise from the existence of exceptional points at which eigenvalues and eigenvectors coalesce. One important open question is how this would manifest at non-integer dimension. Here, we report on the appearance of fractal eigenvalue degeneracies and Fermi surfaces in

Tyler Gorda, Risto Paatelainen, Saga Säppi, Kaapo Seppänen

We compute the next-to-leading order (NLO) hard correction to the gluon self-energy tensor with arbitrary soft momenta in a hot and/or dense weakly coupled plasma in Quantum Chromodynamics. Our diagrammatic computations of the two-loop and power corrections are performed within the hard-thermal-loop (HTL) framework and in general covariant gauge, using the r

A. Korshunov, H. Hu, D. Subires, Y. Jiang

The long range electronic modulations recently discovered in the geometrically frustrated kagome lattice have opened new avenues to explore the effect of correlations in materials with topological electron flat bands. The observation of the lattice response to the emergent new phases of matter, a soft phonon mode, has remained elusive and the microscopic ori

Karan Desai, Maximilian Nickel, Tanmay Rajpurohit, Justin Johnson

Visual and linguistic concepts naturally organize themselves in a hierarchy, where a textual concept "dog" entails all images that contain dogs. Despite being intuitive, current large-scale vision and language models such as CLIP do not explicitly capture such hierarchy. We propose MERU, a contrastive model that yields hyperbolic representations of images an

Maksym Radziwiłł, Liyang Yang

Let $\pi$ be a unitary cuspidal automorphic representation of $\text{GL}_{4}(\mathbb{A}_{\mathbb{Q}})$. Let $f \geq 1$ be given. We show that there exists infinitely many primitive even (resp. odd) Dirichlet characters $\chi$ with conductor co-prime to $f$ such that $L(s, \pi \otimes \chi)$ is non-vanishing at the central point. Our result has applications f

Martina Cerulli, Claudia Archetti, Elena Fernandez, Ivana Ljubic

In last-mile delivery logistics, peer-to-peer logistic platforms play an important role in connecting senders, customers, and independent carriers to fulfill delivery requests. Since the carriers are not under the platform's control, the platform has to anticipate their reactions, while deciding how to allocate the delivery operations. Indeed, carriers' deci

E. Taylor, O. Almaini, M. Merrifield, D. Maltby

We conduct the first study of how the relative quenching probability of galaxies depends on environment over the redshift range $0.5 < z < 3$, using data from the UKIDSS Ultra-Deep Survey. By constructing the stellar mass functions for quiescent and post-starburst (PSB) galaxies in high, medium and low density environments to $z = 3$, we find an excess of qu

Carlo Musolino, Luciano Rezzolla

The development of a neutrino moment based radiative-transfer code to simulate binary neutron-star mergers can easily become an obstacle path because of the numerous ways in which the solution of the equations may fail. We describe the implementation of the grey M1 scheme in our fully general-relativistic magnetohydrodynamics code and detail those choices an

Ishaq Aden-Ali, Yeshwanth Cherapanamjeri, Abhishek Shetty, Nikita Zhivotovskiy

In statistical learning theory, determining the sample complexity of realizable binary classification for VC classes was a long-standing open problem. The results of Simon and Hanneke established sharp upper bounds in this setting. However, the reliance of their argument on the uniform convergence principle limits its applicability to more general learning s

Yingxin Mu, Artem Sapozhnikov

We prove the uniqueness of the infinite connected component for the vacant set of random interlacements on general vertex-transitive amenable transient graphs. Our approach is based on connectedness of random interlacements and differs from the one used by Teixera arXiv:0805.4106 to prove the uniqueness of the infinite connected component for the vacant set

Srinivasan Raghunathan, Yuuki Omori

We propose a cross-internal linear combination (cross-ILC) approach to measure the small-scale cosmic microwave background (CMB) anisotropies robustly against the contamination from astrophysical signals. In particular, we focus on the mitigation of systematics from cosmic infrared background (CIB) and thermal Sunyaev-Zeldovich (tSZ) signals in kinematic SZ

Paolo Iacono, Naimul Khan

The presence of domain shift in medical imaging is a common issue, which can greatly impact the performance of segmentation models when dealing with unseen image domains. Adversarial-based deep learning models, such as Cycle-GAN, have become a common model for approaching unsupervised domain adaptation of medical images. These models however, have no ability

Magdalena Furman, Rafał Mirek, Mateusz Król, Wojciech Pacuski

The insensitivity of photons towards external magnetic fields forms one of the hardest barriers against efficient magneto-optical control, aiming at modulating the polarization state of light. However, there is even scarcer evidence of magneto-optical effects that can spatially modulate light. Here, we demonstrate the latter by exploiting strongly coupled st

Wentao Zhan, Abhirup Datta

Analysis of geospatial data has traditionally been model-based, with a mean model, customarily specified as a linear regression on the covariates, and a covariance model, encoding the spatial dependence. We relax the strong assumption of linearity and propose embedding neural networks directly within the traditional geostatistical models to accommodate non-l

Harry Zhang, Stefan Caldararu, Ishaan Mahajan, Shouvik Chatterjee

Modeling a robust control system with a precise GPS-based state estimation capability in simulation can be useful in field navigation applications as it allows for testing and validation in a controlled environment. This testing process would enable navigation systems to be developed and optimized in simulation with direct transferability to real-world scena

Kyriakos Katsamaktsis, Shoham Letzter, Amedeo Sgueglia

We investigate the existence of a rainbow Hamilton cycle in a uniformly edge-coloured randomly perturbed digraph. We show that for every $\delta \in (0,1)$ there exists $C = C(\delta) > 0$ such that the following holds. Let $D_0$ be an $n$-vertex digraph with minimum semidegree at least $\delta n$ and suppose that each edge of the union of $D_0$ with the ran

Tengyao Wang, Edgar Dobriban, Milana Gataric, Richard J. Samworth

We propose a new method for high-dimensional semi-supervised learning problems based on the careful aggregation of the results of a low-dimensional procedure applied to many axis-aligned random projections of the data. Our primary goal is to identify important variables for distinguishing between the classes; existing low-dimensional methods can then be appl

Yingxin Mu, Artem Sapozhnikov

We consider connectivity properties of the vacant set of (random) ensembles of Wiener sausages in $\mathbb R^d$ in the transient dimensions $d \geq 3$. We prove that the vacant set of Brownian interlacements contains at most one infinite connected component almost surely. For finite ensembles of Wiener sausages, we provide sharp polynomial bounds on the prob

Vladislav Cherepanov, Zhongmin Qian

We establish stochastic functional integral representations for incompressible fluid flows occupying wall-bounded domains using the conditional law duality for a class of diffusion processes. These representations are used to derive a Monte-Carlo scheme based on the corresponding exact random vortex formulation. We implement several numerical experiments bas

Hyung Won Chung, Noah Constant, Xavier Garcia, Adam Roberts

Pretrained multilingual large language models have typically used heuristic temperature-based sampling to balance between different languages. However previous work has not systematically evaluated the efficacy of different pretraining language distributions across model scales. In this paper, we propose a new sampling method, UniMax, that delivers more unif

Lorenz Roth, H. Todd Smith, Kazuo Yoshioka, Tracy M. Becker

In-situ plasma measurements as well as remote mapping of energetic neutral atoms around Jupiter provide indirect evidence that an enhancement of neutral gas is present near the orbit of the moon Europa. Simulations suggest that such a neutral gas torus can be sustained by escape from Europa's atmosphere and consists primarily of molecular hydrogen, but the n

T. J. Volkoff, Diego A. R. Dalvit

The Zou-Wang-Mandel (ZWM) effect is a remarkable consequence of photon indistinguishability and continuous-variable entanglement in which an optical phase shift is imprinted on photonic modes associated with optical paths that that do not pass through the phase shift source. By bringing the canonical formalism of continuous-variable Gaussian states to bear o

Tianrun Chen, Lanyun Zhu, Chaotao Ding, Runlong Cao

The emergence of large models, also known as foundation models, has brought significant advancements to AI research. One such model is Segment Anything (SAM), which is designed for image segmentation tasks. However, as with other foundation models, our experimental findings suggest that SAM may fail or perform poorly in certain segmentation tasks, such as sh

Gerardo Barrera, Waldemar Barrera, Juan Pablo Navarrete

In this paper, we characterize the stability region for trinomials of the form $f(\zeta):=a\zeta ^n + b\zeta ^m +c$, $\zeta\in \mathbb{C}$, where $a$, $b$ and $c$ are non-zero complex numbers and $n,m\in \mathbb{N}$ with $n>m$. More precisely, we provide necessary and sufficient conditions on the coefficients $a$, $b$ and $c$ in order that all the roots of t

Luca Battistella, Kevin Kuehn, Arne Kuhrs, Martin Ulirsch

Affine Bruhat--Tits buildings are geometric spaces extracting the combinatorics of algebraic groups. The building of $\mathrm{PGL}$ parametrizes flags of subspaces/lattices in or, equivalently, norms on a fixed finite-dimensional vector space, up to homothety. It has first been studied by Goldman and Iwahori as a piecewise-linear analogue of symmetric spaces

Xiuying Wei, Yunchen Zhang, Yuhang Li, Xiangguo Zhang

Post-training quantization~(PTQ) of transformer language models faces significant challenges due to the existence of detrimental outliers in activations. We observe that these outliers are concentrated in specific channels and are asymmetric across channels. To address this issue, we propose the Outlier Suppression+~(OS+) framework, which contains the channe

Gideon Amir, Guy Blachar, Maria Gerasimova, Gady Kozma

We study the probability that certain laws are satisfied on infinite groups, focusing on elements sampled by random walks. For several group laws, including the metabelian one, we construct examples of infinite groups for which the law holds with high probability, but the group does not satisfy the law virtually. On the other hand, we show that if an infinit

Natalia Emelianova, Rashid Kashapov, Nail Khusnutdinov

We consider a stack of parallel sheets composed of conducting planes with tensorial conductivities. Using the scattering matrix approach, we derive explicit formulas for the Casimir energy of two, three, and four planes, as well as a recurrence relation for arbitrary planes. Specifically, for a stack of graphene, we solve the recurrence relations and obtain

Lanlan Qiu, Nicola R. Napolitano, Stefano Borgani, Fucheng Zhong

[Abridged] Galaxy clusters are the most massive gravitationally-bound systems in the universe and are widely considered to be an effective cosmological probe. We propose the first Machine Learning method using galaxy cluster properties to derive unbiased constraints on a set of cosmological parameters, including Omega_m, sigma_8, Omega_b, and h_0. We train t

Marcelo Losada, Víctor A. Penas, Federico Holik, Pedro W. Lamberti

The Jensen-Shannon divergence has been successfully applied as a segmentation tool for symbolic sequences, that is to separate the sequence into subsequences with the same symbolic content. In this work, we propose a method, based on the the Jensen-Shannon divergence, for segmentation of what we call \textit{quantum generated sequences}, which consist in sym

Abeer Alessa, Hend Al-Khalifa

Loneliness and social isolation are serious and widespread problems among older people, affecting their physical and mental health, quality of life, and longevity. In this paper, we propose a ChatGPT-based conversational companion system for elderly people. The system is designed to provide companionship and help reduce feelings of loneliness and social isol

Alexandre M. Pombo, Ippocratis D. Saltas

The high-precision astrometric mission GAIA recently reported the remarkable discovery of a Sun-like star closely orbiting a dark object, with a semi-major axis and period of $1.4\, \rm{AU}$ and $187.8$ days respectively. While the plausible expectation for the central dark object is a black hole, the evolutionary mechanism leading to the formation of such a

Peter K. Morse, Jaeuk Kim, Paul J. Steinhardt, Salvatore Torquato

Hyperuniform many-particle systems are characterized by a structure factor $S({\mathbf{k}})$ that is precisely zero as $|\mathbf{k}|\rightarrow0$; and stealthy hyperuniform systems have $S({\mathbf{k}})=0$ for the finite range $0 < |{\mathbf{k}}| \le K$, called the "exclusion region." Through a process of collective-coordinate optimization, energy-minimizing

Zihao Wu, Lu Zhang, Chao Cao, Xiaowei Yu

Recently, ChatGPT and GPT-4 have emerged and gained immense global attention due to their unparalleled performance in language processing. Despite demonstrating impressive capability in various open-domain tasks, their adequacy in highly specific fields like radiology remains untested. Radiology presents unique linguistic phenomena distinct from open-domain