April 2024 arXiv papers — page 119

Kumar Avinava Dubey, Zhe Feng, Rahul Kidambi, Aranyak Mehta

We study an auction setting in which bidders bid for placement of their content within a summary generated by a large language model (LLM), e.g., an ad auction in which the display is a summary paragraph of multiple ads. This generalizes the classic ad settings such as position auctions to an LLM generated setting, which allows us to handle general display f

Bingjia Yang, Pinchen Xie, Roberto Car

The structural, dielectric, and thermodynamic properties of the hydrogen-bonded ferroelectric crystal potassium dihydrogen phosphate ($\mathbf{KH_2PO_4}$), KDP for short, differ significantly from those of DKDP ($\mathbf{KD_2PO_4}$). It is well established that deuteration affects the interplay of hydrogen-bond switches and heavy ion displacements that under

Thiago C. Silva, Paulo V. B. Wilhelm, Diego R. Amancio

This study examines the effects of de-globalization trends on international trade networks and their role in improving forecasts for economic growth. Using section-level trade data from nearly 200 countries from 2010 to 2022, we identify significant shifts in the network topology driven by rising trade policy uncertainty. Our analysis highlights key global p

Saeed Haddadi, Elena I. Kuznetsova, M. A. Yurischev

The development and improvement of analytical methods for evaluating nonclassical correlations is one of the most important tasks in quantum information science. In this paper, we investigate a mixed spin-$(1/2,S)$ system with an arbitrary spin $S$, where the interactions satisfy the U(1) axial symmetry. Analytical formulas for the local quantum uncertainty

Andrew R. Kustin

Let $\pmb k$ be an arbitrary field and $A$ be a standard graded Artinian Gorenstein $\pmb k$-algebra of embedding dimension four and socle degree three. Then, except for exactly one exception, $A$ has the weak Lefschetz property. Furthermore, the exception occurs only in characteristic two.

I-Te Lu, Dongbin Shin, Mark Kamper Svendsen, Hannes Hübener

Strong laser pulses can control superconductivity, inducing non-equilibrium transient pairing by leveraging strong-light matter interaction. Here we demonstrate theoretically that equilibrium ground-state phonon-mediated superconductive pairing can be affected through the vacuum fluctuating electromagnetic field in a cavity. Using the recently developed ab i

May Cai, Kisun Lee, Josephine Yu

We study the tropicalization of the variety of symmetric rank two matrices. Analogously to the result of Markwig and Yu for general tropical rank two matrices, we show that it has a simplicial complex structure as the space of symmetric bicolored trees and that this simplicial complex is shellable. We also discuss some matroid structures arising from this sp

Haoyuan Sun, Ali Jadbabaie

The focus of this paper is on linear system identification in the setting where it is known that the underlying partially-observed linear dynamical system lies within a finite collection of known candidate models. We first consider the problem of identification from a given trajectory, which in this setting reduces to identifying the index of the true model

Usman Rana, Thomas Abadie, David Chapman, Nathan Joiner

The Richtmyer-Meshkov instability (RMI) occurs when a shock wave passes through an interface between fluids of different densities, a phenomenon prevalent in a variety of scenarios including supersonic combustion, supernovae, and inertial confinement fusion. In the most advanced current numerical modelling of RMI, a multitude of secondary physical phenomena

Eugene Yang, Dawn Lawrie, James Mayfield

The HLTCOE team applied PLAID, an mT5 reranker, and document translation to the TREC 2023 NeuCLIR track. For PLAID we included a variety of models and training techniques -- the English model released with ColBERT v2, translate-train~(TT), Translate Distill~(TD) and multilingual translate-train~(MTT). TT trains a ColBERT model with English queries and passag

Chenmu Zhang, Yuanyue Liu

Two-dimensional (2D) crystalline semiconductors hold promise for next-generation electronic devices due to its atomical thickness and consequent properties. Despite years of search, literature-reported 2D semiconductors commonly suffered from low room-temperature charge mobility (< 200 cm2V-1s-1), due to the dimensionality-increased 'density of scattering',

Turgay Bayraktar, Dan Coman, George Marinescu, Viêt-Anh Nguyên

Let $X$ be a compact normal complex space, $L$ be a big holomorphic line bundle on $X$ and $h$ be a continuous Hermitian metric on $L$. We consider the spaces of holomorphic sections $H^0(X, L^{\otimes p})$ endowed with the inner product induced by $h^{\otimes p}$ and a volume form on $X$, and prove that the corresponding sequence of normalized Fubini-Study

Alberto Enciso, Javier Peñafiel-Tomás, Daniel Peralta-Salas

We prove an extension theorem for local solutions of the 3d incompressible Euler equations. More precisely, we show that if a smooth vector field satisfies the Euler equations in a spacetime region $\Omega\times(0,T)$, one can choose an admissible weak solution on $\mathbf R^3\times (0,T)$ of class $C^\beta$ for any $\beta<1/3$ such that both fields coincide

Ioannis Panitsas, Akrit Mudvari, Ali Maatouk, Leandros Tassiulas

Next-generation cellular networks will evolve into more complex and virtualized systems, employing machine learning for enhanced optimization and leveraging higher frequency bands and denser deployments to meet varied service demands. This evolution, while bringing numerous advantages, will also pose challenges, especially in mobility management, as it will

Shang Wang, Deepak Ranganatha Sastry Mamillapalli, Tianpei Yang, Matthew E. Taylor

This paper introduces the problem of learning to place logic blocks in Field-Programmable Gate Arrays (FPGAs) and a learning-based method. In contrast to previous search-based placement algorithms, we instead employ Reinforcement Learning (RL) with the goal of minimizing wirelength. In addition to our preliminary learning results, we also evaluated a novel d

Vinay Kammarchedu, Derrick Butler, Asmaul Smitha Rashid, Aida Ebrahimi

Engineering superlattices (SLs) - which are spatially periodic potential landscapes for electrons - is an emerging approach for the realization of exotic properties, including superconductivity and correlated insulators, in two-dimensional materials. While moir\'e SL engineering has been a popular approach, nanopatterning is an attractive alternative offerin

Guangzhi Wang, Tianyi Chen, Kamran Ghasedi, HsiangTao Wu

Face attribute editing plays a pivotal role in various applications. However, existing methods encounter challenges in achieving high-quality results while preserving identity, editing faithfulness, and temporal consistency. These challenges are rooted in issues related to the training pipeline, including limited supervision, architecture design, and optimiz

Derek Jacoby, Tianyi Zhang, Aanchan Mohan, Yvonne Coady

A problem with many current Large Language Model (LLM) driven spoken dialogues is the response time. Some efforts such as Groq address this issue by lightning fast processing of the LLM, but we know from the cognitive psychology literature that in human-to-human dialogue often responses occur prior to the speaker completing their utterance. No amount of dela

Munjung Kim, Tuğrulcan Elmas, Filippo Menczer

Hate speech on social media is a pressing concern. Understanding the factors associated with hate speech may help mitigate it. Here we explore the association between hate speech and exposure to fake news by studying the correlation between exposure to news from low-credibility sources through following connections and the use of hate speech on Twitter. Usin

Archana Radhakrishnan, M. Padmanath, Nilmani Mathur

We present a lattice QCD study of the elastic $S$-wave $D\bar{B}$ scattering in search of tetraquark candidates with explicitly exotic flavor content $bc\bar u\bar d$ in the isospin $I\!=\!0$ and $J^P=0^+$ channel. We use four lattice QCD ensembles with dynamical $u/d$, $s$, and $c$ quark fields generated by the MILC Collaboration. A non-relativistic QCD Ham

Krzysztof Kotowski, Irena Roterman, Katarzyna Stapor

The prediction of intrinsic disorder regions has significant implications for understanding protein functions and dynamics. It can help to discover novel protein-protein interactions essential for designing new drugs and enzymes. Recently, a new generation of predictors based on protein language models (pLMs) is emerging. These algorithms reach state-of-the-

Audrey Blizard, Colin N. Jones, Stephanie Stockar

The demand-side control of district heating networks is notoriously challenging due to the large number of connected users and the high number of states to be considered. To overcome these challenges, this paper presents a hierarchical optimization scheme using the flexibility in heating demand provided by the users to improve the performance of the network.

Pratham Kankariya, Rachita Rode, Kevin Mudaliar, Pranali Hatode

Parkinson's disease is a progressive and slowly developing neurodegenerative disease, characterized by dopaminergic neuron loss in the substantia nigra region of the brain. Despite extensive research by scientists, there is not yet a cure to this problem and the available therapies mainly help to reduce some of the Parkinson's symptoms. Drug repurposing (tha

Robert Dickerson, Prasita Mukherjee, Benjamin Delaware

Many interesting program properties involve the execution of multiple programs, including observational equivalence, noninterference, co-termination, monotonicity, and idempotency. One strategy for verifying such relational properties is to construct and reason about an intermediate program whose correctness implies that the individual programs exhibit those

Subhash Kak

The helical coil is ubiquitous in biological and natural systems and often it is the basic form that leads to complex structures. This paper considers the question of its dimensionality in biological information as the helical coil goes through recursive coiling as happens to DNA and RNA molecules in chromatin. It has been shown that the dimensionality of co

Jiatong Li, Hongqiang Yan

We develop a uniform inference theory for high-dimensional slope parameters in threshold regression models, allowing for either cross-sectional or time series data. We first establish oracle inequalities for prediction errors, and L1 estimation errors for the Lasso estimator of the slope parameters and the threshold parameter, accommodating heteroskedastic n

Jean-Philippe Bauchet, Raphael Sulzer, Florent Lafarge, Yuliya Tarabalka

Automatic methods for reconstructing buildings from airborne LiDAR point clouds focus on producing accurate 3D models in a fast and scalable manner, but they overlook the problem of delivering simple and regularized models to practitioners. As a result, output meshes often suffer from connectivity approximations around corners with either the presence of mul

G. G. Baez Flores, M. van Schilfgaarde, K. D. Belashchenko

The minority-spin Fe/MgO interface states are at the Fermi level in density functional theory (DFT), but experimental evidence and GW calculations place them slightly higher in energy. This small shift can strongly influence tunneling magnetoresistance (TMR) in junctions with a thin MgO barrier and its dependence on the concentration of Co in the electrodes.

Izzet Coskun, Eric Larson, Isabel Vogt

In projective space over fields of characteristic different from 2, the normal bundle of a general nondegenerate rational curve is balanced. The corresponding statement for rational curves in other Grassmannians can fail. Nevertheless, we prove that the normal bundle of a general rational curve in a Grassmannian decomposes into a direct sum of line bundles w

Dahlia Shehata, Robin Cohen, Charles Clarke

Conversational prompt-engineering-based large language models (LLMs) have enabled targeted control over the output creation, enhancing versatility, adaptability and adhoc retrieval. From another perspective, digital misinformation has reached alarming levels. The anonymity, availability and reach of social media offer fertile ground for rumours to propagate.

Samuel Lippl, Raphael Gerraty, John Morrison, Nikolaus Kriegeskorte

As animals interact with their environments, they must infer properties of their surroundings. Some animals, including humans, can represent uncertainty about those properties. But when, if ever, do they use probability distributions to represent their uncertainty? It depends on which definition we choose. In this paper, we argue that existing definitions ar

Masahiro Kadosawa, Masaaki Nakamura, Yukinori Ohta, Satoshi Nishimoto

We present a detailed investigation of the XXZ Heisenberg model for spin-$1/2$ and spin-$1$ systems on square and honeycomb lattices. Utilizing the density-matrix renormalization group (DMRG) method, complemented by Spiral Boundary Conditions (SBC) for mapping two-dimensional (2D) clusters onto one-dimensional (1D) chains, we meticulously explore the evoluti

Javier Garcia-Bernardo, Christine Hedde-von Westernhagen, Tom Emery, Albert Jan van Hoek

Understanding the impact of different social interactions is key to improving epidemic models. Here, we use extensive registry data -- including PCR test results and population-level networks -- to investigate the impact of school, family, and other social contacts on SARS-CoV-2 transmission in the Netherlands (June 2020--October 2021). We isolate and compar

Balázs Havasi-Tóth

In the present work we focus on the morphology of well abraded, almost perfectly ellipsoidal natural pebbles. Flat, oblate and prolate ellipsoidal pebbles are expected to be characterized by qualitatively different shape evolution due to being unequally prone to specific rolling and sliding motions in natural environments. The three typical motions are consi

Juliet Aygun, Janet Barkdoll, Aaron Calderon, Jenavie Lorman

Any pair of intersecting cylinders on a translation surface is "coherent," in that the geometric and algebraic intersection numbers of their core curves are equal (up to sign). In this paper, we investigate when a pair of multicurves can be simultaneously realized as the core curves of cylinders on some translation surface. Our main tools are surface topolog

Peter A. V. Gade, Trygve Skjøtskift, Henrik W. Bindner, Jalal Kazempour

Energy-intensive industries can adapt to help balance the power grid. By using a real-world case study of a zinc galvanizing process in Denmark, we show how a modest investment in power control of the furnace enables the provision of various ancillary services. We consider two types of services, namely frequency containment reserve (FCR) and manual frequency

Luke Weisenbach, Timo Anguita, Jordi Miralda-Escudé, Masamune Oguri

Microlensing near macro-caustics is a complex phenomenon in which swarms of micro-images produced by micro-caustics form on both sides of a macro-critical curve. Recent discoveries of highly magnified images of individual stars in massive galaxy cluster lenses, predicted to be formed by these micro-image swarms, have stimulated studies on this topic. In this

Richard Fulton, Diane Fulton, Nate Hayes, Susan Kaplan

This paper summarizes the most cogent advantages and risks associated with Artificial Intelligence from an in-depth review of the literature. Then the authors synthesize the salient risk-related models currently being used in AI, technology and business-related scenarios. Next, in view of an updated context of AI along with theories and models reviewed and e

Mohannad Alhakami, Dylan R. Ashley, Joel Dunham, Yanning Dai

Advanced machine learning algorithms require platforms that are extremely robust and equipped with rich sensory feedback to handle extensive trial-and-error learning without relying on strong inductive biases. Traditional robotic designs, while well-suited for their specific use cases, are often fragile when used with these algorithms. To address this gap --

Fahim Faisal, Antonios Anastasopoulos

This report presents GMUNLP's participation to the Dialect-Copa shared task at VarDial 2024, which focuses on evaluating the commonsense reasoning capabilities of large language models (LLMs) on South Slavic micro-dialects. The task aims to assess how well LLMs can handle non-standard dialectal varieties, as their performance on standard languages is already

Indu Kant Deo, Akash Venkateshwaran, Rajeev K. Jaiman

There is a significant need for precise and reliable forecasting of the far-field noise emanating from shipping vessels. Conventional full-order models based on the Navier-Stokes equations are unsuitable, and sophisticated model reduction methods may be ineffective for accurately predicting far-field noise in environments with seamounts and significant varia

Jesse Roberts, Kyle Moore, Doug Fisher

In this paper, we evaluate whether LLMs learn to make human-like preference judgements in strategic scenarios as compared with known empirical results. Solar and Mistral are shown to exhibit stable value-based preference consistent with humans and exhibit human-like preference for cooperation in the prisoner's dilemma (including stake-size effect) and travel

Kaixuan Fan, Xue-Qiao Xu, Ben Zhu, Chao Dong

This study delves into Microtearing Modes (MTMs) in tokamak plasmas, employing advanced simulations within the BOUT++ framework. The research, centering on collisional MTMs influenced by the time-dependent thermal force, enhances our understanding of plasma dynamics. It achieves this through the simplification and linearization of control equations in detail

Yang Hu, Haitong Ma, Bo Dai, Na Li

The pursuit of robustness has recently been a popular topic in reinforcement learning (RL) research, yet the existing methods generally suffer from efficiency issues that obstruct their real-world implementation. In this paper, we introduce duple perturbation robustness, i.e. perturbation on both the feature and factor vectors for low-rank Markov decision pr

Aleksander Nagaj, Zenjie Li, Dim P. Papadopoulos, Kamal Nasrollahi

As the global population ages, the number of fall-related incidents is on the rise. Effective fall detection systems, specifically in healthcare sector, are crucial to mitigate the risks associated with such events. This study evaluates the role of visual context, including background objects, on the accuracy of fall detection classifiers. We present a segme

Rachael C. Amaro, Daniel Apai, Ben W. P. Lew, Yifan Zhou

Brown dwarfs in ultra-short period orbits around white dwarfs offer a unique opportunity to study the properties of tidally-locked, fast rotating (1-3 hr), and highly-irradiated atmospheres. Here, we present phase-resolved spectrophotometry of the white dwarf-brown dwarf (WD-BD) binary SDSS 1557, which is the fifth WD-BD binary in our six-object sample. Usin

Neelay Junnarkar, Emmanuel Sin, Peter Seiler, Douglas Philbrick

This letter considers assignment problems consisting of n pursuers attempting to intercept n targets. We consider stationary targets as well as targets maneuvering toward an asset. The assignment algorithm relies on an n x n cost matrix where entry (i, j) is the minimum time for pursuer i to intercept target j. Each entry of this matrix requires the solution

Ashish Gola, Igor Shinkar, Harsimran Singh

In this paper we study a worst case to average case reduction for the problem of matrix multiplication over finite fields. Suppose we have an efficient average case algorithm, that given two random matrices $A,B$ outputs a matrix that has a non-trivial correlation with their product $A \cdot B$. Can we transform it into a worst case algorithm, that outputs t

Agustina Czenky

We give a parametrization of cyclic pointed categories associated to the cyclic group of order $n$ in terms of $n$-th roots of unity. We also provide a diagramatic description of these categories by generators and relations, and use it to characterize their $2$-group of automorphisms.

Pieter Bomans, Christopher Couzens

We analyse the backreacted geometry corresponding to a stack of M5-branes wrapped on a spindle, with a view towards precision tests of the dual $\mathcal{N} = 1$ superconformal field theory. We carefully study the singular loci of the uplifted geometry and show that these correspond to $\mathbf{C}^3/\mathbf{Z}_n$ conical singularities. Therefore, these solut

Fei Yu Chen

Given a ring $R$, we have a classical result stating that the ordinary category of modules is the abelianization of the category of augmented $R$-algebras. Analogously, using the framework of infinity categories and higher algebra, Francis showed that the infinity category of $R$-modules is the stabilization of the infinity category of augmented $R$-algebras

Md Nahid Sadik, Tahmim Hossain, Faisal Sayeed

Computer vision, particularly vehicle and pedestrian identification is critical to the evolution of autonomous driving, artificial intelligence, and video surveillance. Current traffic monitoring systems confront major difficulty in recognizing small objects and pedestrians effectively in real-time, posing a serious risk to public safety and contributing to

Tanmay Gautam, Youngsuk Park, Hao Zhou, Parameswaran Raman

Fine-tuning language models (LMs) has demonstrated success in a wide array of downstream tasks. However, as LMs are scaled up, the memory requirements for backpropagation become prohibitively high. Zeroth-order (ZO) optimization methods can leverage memory-efficient forward passes to estimate gradients. More recently, MeZO, an adaptation of ZO-SGD, has been

Nastaran Saadati, Minh Pham, Nasla Saleem, Joshua R. Waite

Recent advances in decentralized deep learning algorithms have demonstrated cutting-edge performance on various tasks with large pre-trained models. However, a pivotal prerequisite for achieving this level of competitiveness is the significant communication and computation overheads when updating these models, which prohibits the applications of them to real

Stefan Sylvius Wagner, Maike Behrendt, Marc Ziegele, Stefan Harmeling

Stance detection is an important task for many applications that analyse or support online political discussions. Common approaches include fine-tuning transformer based models. However, these models require a large amount of labelled data, which might not be available. In this work, we present two different ways to leverage LLM-generated synthetic data to t

Samuel Pacitti Gentil

We prove discrete analogs of four-vertex type theorems of spherical curves, which imply corresponding results for space polygons. The smooth theory goes back to the work of Beniamino Segre and, more recently, by Mohammad Ghomi, and consists of theorems that state, for a given closed spherical curve, nontrivial lower bounds on the number of spherical inflecti

Thomas G. Kiely, Erich J. Mueller

We study transport in the one-dimensional mass-imbalanced Fermi-Hubbard model at infinite temperature, focusing on the case of strong interactions. Prior theoretical and experimental investigations have revealed unconventionally long transport timescales, with complications due to strong finite size effects. We compute the dynamical current-current correlati

Itamar Stein

With every reduced $E$-Fountain semigroup $S$ which satisfies the generalized right ample condition we associate a category with zero morphisms $\mathcal{C}(S)$. Under some assumptions we prove an isomorphism of $\Bbbk$-algebras $\Bbbk S\simeq\Bbbk_{0}\mathcal{C}(S)$ between the semigroup algebra and the contracted category algebra where $\Bbbk$ is any commu

Robin Ming Chen, Kristoffer Varholm, Samuel Walsh, Miles H. Wheeler

In this paper, we study two-dimensional traveling waves in finite-depth water that are acted upon solely by gravity. We prove that, for any supercritical Froude number (non-dimensionalized wave speed), there exists a continuous one-parameter family $\mathcal{C}$ of solitary waves in equilibrium with a submerged point vortex. This family bifurcates from an ir

Valérie Berthé, Herman Goulet-Ouellet

This paper studies obstructions to preservation of return sets by episturmian morphisms. We show, by way of an explicit construction, that infinitely many obstructions exist. This generalizes and improves an earlier result about Sturmian morphisms.

Dawn Lawrie, Sean MacAvaney, James Mayfield, Paul McNamee

The principal goal of the TREC Neural Cross-Language Information Retrieval (NeuCLIR) track is to study the impact of neural approaches to cross-language information retrieval. The track has created four collections, large collections of Chinese, Persian, and Russian newswire and a smaller collection of Chinese scientific abstracts. The principal tasks are ra

Thomas Locher

Byzantine reliable broadcast is a fundamental problem in distributed computing, which has been studied extensively over the past decades. State-of-the-art algorithms are predominantly based on the approach to share encoded fragments of the broadcast message, yielding an asymptotically optimal communication complexity when the message size exceeds the network

Brian Bell, Michael Geyer, David Glickenstein, Keaton Hamm

There are a number of hypotheses underlying the existence of adversarial examples for classification problems. These include the high-dimensionality of the data, high codimension in the ambient space of the data manifolds of interest, and that the structure of machine learning models may encourage classifiers to develop decision boundaries close to data poin

Ali Al-Lawati, Elsayed Eshra, Prasenjit Mitra

Trajectory generation is an important task in movement studies; it circumvents the privacy, ethical, and technical challenges of collecting real trajectories from the target population. In particular, real trajectories in the wildlife domain are scarce as a result of ethical and environmental constraints of the collection process. In this paper, we consider

Fabian Garmroudi, Illia Serhiienko, Simone Di Cataldo, Michael Parzer

Thermoelectric (TE) materials are useful for applications such as waste heat harvesting or efficient and targeted cooling. While various strategies towards superior thermoelectrics through a reduction of the lattice thermal conductivity have been developed, a path to enhance the power factor is pressing. Here, we report large power factors up to 5 mW m$^{-1}

Mobashir Sadat, Cornelia Caragea

The task of scientific Natural Language Inference (NLI) involves predicting the semantic relation between two sentences extracted from research articles. This task was recently proposed along with a new dataset called SciNLI derived from papers published in the computational linguistics domain. In this paper, we aim to introduce diversity in the scientific N

Celia Chen, Alex Leitch

This paper details the development of an interactive sculpture built from deprecated hardware technology and intentionally decomposable, transient materials. We detail a case study of "Strain" - an emotive prototype that reclaims two orphaned digital artifacts to power a kinetic sculpture made of common disposable objects. We use the Myo, an abandoned myoele

Szymon Wojciechowski, Michał Woźniak

One of the significant problems associated with imbalanced data classification is the lack of reliable metrics. This runs primarily from the fact that for most real-life (as well as commonly used benchmark) problems, we do not have information from the user on the actual form of the loss function that should be minimized. Although it is pretty common to have

Soroosh Tayebi Arasteh, Tomas Arias-Vergara, Paula Andrea Perez-Toro, Tobias Weise

Integration of speech into healthcare has intensified privacy concerns due to its potential as a non-invasive biomarker containing individual biometric information. In response, speaker anonymization aims to conceal personally identifiable information while retaining crucial linguistic content. However, the application of anonymization techniques to patholog

Matheus H. Zambianco, Adam Teixidó-Bonfill, Eduardo Martín-Martínez

We reveal that the information exchange between particle detectors and their ability to harvest correlations from a quantum field can interfere constructively and destructively. This allows for scenarios where the presence of entanglement in the quantum field is actually detrimental to the process of getting the two detectors entangled.

Fabian Esser, Maeve Madigan, Alexandre Salas-Bernardez, Veronica Sanz

Due to the pseudo-scalar nature of the axion-like particle (ALP), the CP- conserving production of two Higgs bosons via the ALP necessarily involves an additional Z or $\gamma$ boson. We examine the existing constraints from di-Higgs searches at Run 2 of the LHC and find that, despite the presence of extra objects in the final state, these searches are sensi

Chetna Singhal, Yashuo Wu, Francesco Malandrino, Marco Levorato

The increasing pervasiveness of intelligent mobile applications requires to exploit the full range of resources offered by the mobile-edge-cloud network for the execution of inference tasks. However, due to the heterogeneity of such multi-tiered networks, it is essential to make the applications' demand amenable to the available resources while minimizing en

Liam O. Dubay, Jennifer A. Johnson, James W. Johnson

Type Ia supernovae (SNe Ia) produce most of the Fe-peak elements in the Universe and therefore are a crucial ingredient in galactic chemical evolution models. SNe Ia do not explode immediately after star formation, and the delay-time distribution (DTD) has not been definitively determined by supernova surveys or theoretical models. Because the DTD also affec

Patrick S. Kamieneski, Brenda L. Frye, Rogier A. Windhorst, Kevin C. Harrington

We present a new parametric lens model for the G165.7+67.0 galaxy cluster, which was discovered with $Planck$ through its bright submillimeter flux, originating from a pair of extraordinary dusty star-forming galaxies (DSFGs) at $z\approx 2.2$. Using JWST and interferometric mm/radio observations, we characterize the intrinsic physical properties of the DSFG

Roberto Caiozzo, Gianfranco Bertone, Florian Kühnel

A sub-solar mass primordial black hole (PBH) passing through a neutron star, can lose enough energy through interactions with the dense stellar medium to become gravitationally bound to the star. Once captured, the PBH would sink to the core of the neutron star, and completely consume it from the inside. In this paper, we improve previous energy-loss calcula

Hongrui Chen, Xingchen Liu, Levent Burak Kara

A long-standing challenge is designing multi-scale structures with good connectivity between cells while optimizing each cell to reach close to the theoretical performance limit. We propose a new method for direct multi-scale topology optimization using neural networks. Our approach focuses on inverse homogenization that seamlessly maintains compatibility ac

Marina Cortês, Andrew R Liddle

The latest results on baryon acoustic oscillations from DESI (Dark Energy Spectroscopic Instrument), when combined with cosmic microwave background and supernova data, show indications of a deviation from a cosmological constant in favour of evolving dark energy. Use of a pivot scale for the equation of state $w$ shows that this evidence is concentrated in t

Wei Xia, Jie Zou, Xiaopeng Li

Dynamical quantum phase transitions, encompassing phenomena like many-body localization transitions and measurement-induced phase transitions, are often characterized and identified through the analysis of quantum entanglement. Here, we highlight that the dynamical phases defined by entanglement are further enriched by complexity. We investigate both the ent

Yue Pan, Anirudh Chiti, Alex Drlica-Wagner, Alexander P. Ji

We conducted an in-depth analysis of candidate member stars located in the peripheries of three ultra-faint dwarf (UFD) galaxy satellites of the Milky Way: Bo\"otes I (Boo1), Bo\"otes II (Boo2), and Segue I (Seg1). Studying these peripheral stars has previously been difficult due to contamination from the Milky Way foreground. We used $u$-band photometry fro

Alexander Miessen, Daniel J. Egger, Ivano Tavernelli, Guglielmo Mazzola

The real-time simulation of large many-body quantum systems is a formidable task, that may only be achievable with a genuine quantum computational platform. Currently, quantum hardware with a number of qubits sufficient to make classical emulation challenging is available. This condition is necessary for the pursuit of a so-called quantum advantage, but it a

L. Barrufet, P. Oesch, R. Marques-Chaves, K. Arellano-Cordova

The advent of the JWST has revolutionised our understanding of high-redshift galaxies. In particular, the NIRCam instrument on-board JWST has revealed a population of Hubble Space Telescope (HST)-dark galaxies that had previously evaded optical detection, potentially due to significant dust obscuration, quiescence, or simply extreme redshift. Here, we presen

Felipe Alarcón, Edwin Bergin

The discovery of protoplanets and circumplanetary disks provides a unique opportunity to characterize planet formation through observations. Massive protoplanets shape the physical and chemical structure of their host circumstellar disk by accretion, localized emission, and disk depletion. In this work, we study the thermal changes induced within the disk by

Chris M. Harrison, Cristina Ramos Almeida

Growing supermassive black holes (Active Galactic Nuclei; AGN) release energy with the potential to alter their host galaxies and larger-scale environment; a process named "AGN feedback". Feedback is a required component of galaxy formation models and simulations to explain observed properties of galaxy populations. We provide a broad overview of observation

Fabio Maltoni, Claudio Severi, Simone Tentori, Eleni Vryonidou

We study the quantum properties of top quark pairs in lepton colliders with unpolarised beams, including spin correlations, entanglement, and violation of Bell inequalities. We present analytical results in the SM and in the SMEFT and discuss several practical aspects, like the choice of quantization axes and $t \bar t$ threshold effects. We also note a corr

Nikhil Sarin, Teagan A. Clarke, Spencer J. Magnall, Paul D. Lasky

Rowlinson et al. 2023 recently claimed the detection of a coherent radio flash 76.6 minutes after a short gamma-ray burst. They proposed that the radio emission may be associated with a long-lived neutron star engine. We show through theoretical and observational arguments that the coherent radio emission, if real and indeed associated with GRB 201006A and a

Li Wang, Licai Deng, Xiaoying Pang, Long Wang

The presence of young stellar populations in the Large Magellanic Cloud cluster NGC 1783 has caught significant attention, with suggestions ranging from it being a genuine secondary stellar generation to a population of blue straggler stars or simply contamination from background stars. Thanks to multi-epoch observations with the Hubble Space Telescope, prop

Philip F. Hopkins, Michael Y. Grudic, Kyle Kremer, Stella S. R. Offner

Recently, we demonstrated self-consistent formation of strongly-magnetized quasar accretion disks (QADs) from cosmological radiation-magnetohydrodynamic-thermochemical galaxy-star formation simulations, including the full STARFORGE physics shown previously to produce a reasonable IMF under typical ISM conditions. Here we study star formation and the stellar

Yoshinobu Fudamoto, Fengwu Sun, Jose M. Diego, Liang Dai

Strong gravitational magnifications enable to detect faint background sources, resolve their internal structures, and even identify individual stars in distant galaxies. Highly magnified individual stars allow various applications, including studies of stellar populations in distant galaxies and constraining dark matter structures in the lensing plane. Howev

Kevin P. Nuckolls, Ali Yazdani

Contemporary quantum materials research is guided by themes of topology and of electronic correlations. A confluence of these two themes is engineered in "moir\'e materials", an emerging class of highly tunable, strongly correlated two-dimensional (2D) materials designed by the rotational or lattice misalignment of atomically thin crystals. In moir\'e materi

Deveshi Buch, Ethan O. Nadler, Risa H. Wechsler, Yao-Yuan Mao

We present Milky Way-est, a suite of 20 cosmological cold-dark-matter-only zoom-in simulations of Milky Way (MW)-like host halos. Milky Way-est hosts are selected such that they (i) are consistent with the MW's measured halo mass and concentration, (ii) accrete a Large Magellanic Cloud (LMC)-like ($\approx 10^{11}~M_{\odot}$) subhalo within the last $2~\math

Timothée Schaeffer, Sambit K. Giri, Aurel Schneider

Predicting the 21cm signal from the epoch of reionization and cosmic dawn is a complex and challenging task. Various simplifying assumptions have been applied over the last decades to make the modeling more affordable. In this paper, we investigate the validity of several such assumptions, using a simulation suite consisting of three different astrophysical

Elizabeth Tarantino, Alberto D. Bolatto, Rémy Indebetouw, Mónica Rubio

We present Cloudy modeling of infrared emission lines in the Wolf-Rayet (WR) nebula N76 caused by one of the most luminous and hottest WR stars in the low metallicity Small Magellanic Cloud. We use spatially resolved mid-infrared Spitzer/IRS and far-infrared Herschel/PACS spectroscopy to establish the physical conditions of the ionized gas. The spatially res

Yonadav Barry Ginat, Hagai B. Perets

Binary formation in clusters through triple encounters between three unbound stars, 'three-body' binary formation, is one of the main dynamical formation processes of binary systems in dense environments. In this paper, we use an analytical probabilistic approach to study the process for the equal mass case and calculate a probability distribution for the or

Jordan Krywonos, Jessica Muir, Matthew C. Johnson

Clustering studies in current photometric galaxy surveys focus solely on auto-correlations, neglecting cross-correlations between redshift bins. We evaluate the potential advantages and drawbacks of incorporating cross-bin correlations in Fisher forecasts for the Dark Energy Survey (DES) and the forthcoming Rubin Observatory Legacy Survey of Space and Time (

Louise Breuval, Adam G. Riess, Stefano Casertano, Wenlong Yuan

We present phase-corrected photometric measurements of 88 Cepheid variables in the core of the Small Magellanic Cloud (SMC), the first sample obtained with the Hubble Space Telescope's (HST) Wide Field Camera 3, in the same homogeneous photometric system as past measurements of all Cepheids on the SH0ES distance ladder. We limit the sample to the inner core

Alejandra Rosselli-Calderon, Ricardo Yarza, Ariadna Murguia-Berthier, Valeriia Rohoza

Triple stellar systems allow us to study stellar processes that cannot be attained in binary stars. The evolutionary phases in which the stellar members undergo mass exchanges can alter the hierarchical layout of these systems. Yet, the lack of a self-consistent treatment of common-envelope (CE) in triple star-systems hinders the comprehensive understanding

Euclid Collaboration, M. Sereno, S. Farrens, L. Ingoglia

Precise and accurate mass calibration is required to exploit galaxy clusters as astrophysical and cosmological probes in the Euclid era. Systematic errors in lensing signals by galaxy clusters can be empirically estimated by comparing different surveys with independent and uncorrelated systematics. To assess the robustness of the lensing results to systemati

Dainis Dravins, Hans-Günter Ludwig

Searches for small exoplanets around solar-type stars are limited by stellar physical variability. While chromospheric variability is well studied, observing, modeling. and understanding the much smaller fluctuations in photospheric spectral line strengths, shapes, and shifts is challenging. Extreme precision radial-velocity spectrometers now enable extreme

Alberto Salvio

A non-perturbative and background-independent quantum formulation of quadratic gravity is provided. A canonical quantization procedure introduced in previous works, named after Dirac and Pauli, is here applied to quadratic gravity to obtain, as required by consistency, a well-defined Euclidean path integral. The theory is unitary: all probabilities are non n

J. M. Diego, Sung Kei Li, Alfred Amruth, Ashish K. Meena

Observations of caustic-crossing galaxies at redshift $0.7<z<1$ show a wealth of transient events. Most of them are believed to be microlensing events of highly magnified stars. Earlier work predicted such events should be common near the critical curves (CCs) of galaxy clusters, but some are found relatively far away from these CCs. We consider the possibil