February 2024 arXiv papers — page 19

Mira Liu

Purpose: A geometric simulation of a possible two-plane detector was developed to test the abilities of the detector to generate high-resolution images of the Great Pyramid using muon tomography. Methods and Materials: Trajectory range, angular resolution, and acceptance of the detector were calculated with a simulation. Trajectories and the corresponding si

Caleb M. Webb, Charles A. Stafford

We present a partition of quantum observables in an open quantum system which is inherited from the division of the underlying Hilbert space or configuration space. It is shown that this partition leads to the definition of an inhomogeneous continuity equation for generic, non-local observables. This formalism is employed to describe the local evolution of t

Yoshiki Masuyama, Gordon Wichern, François G. Germain, Zexu Pan

Head-related transfer functions (HRTFs) are important for immersive audio, and their spatial interpolation has been studied to upsample finite measurements. Recently, neural fields (NFs) which map from sound source direction to HRTF have gained attention. Existing NF-based methods focused on estimating the magnitude of the HRTF from a given sound source dire

Piotr Bielak, Tomasz Kajdanowicz

In recent years, unsupervised and self-supervised graph representation learning has gained popularity in the research community. However, most proposed methods are focused on homogeneous networks, whereas real-world graphs often contain multiple node and edge types. Multiplex graphs, a special type of heterogeneous graphs, possess richer information, provide

Thiago H Silva, Daniel Silver

Urban research has long recognized that neighbourhoods are dynamic and relational. However, lack of data, methodologies, and computer processing power have hampered a formal quantitative examination of neighbourhood relational dynamics. To make progress on this issue, this study proposes a graph neural network (GNN) approach that permits combining and evalua

Aaron Hao Tan, Siddarth Narasimhan, Goldie Nejat

Mobile robots in unknown cluttered environments with irregularly shaped obstacles often face energy and communication challenges which directly affect their ability to explore these environments. In this paper, we introduce a novel deep learning architecture, Confidence-Aware Contrastive Conditional Consistency Model (4CNet), for robot map prediction during

Jingying Wang, Haoran Tang, Taylor Kantor, Tandis Soltani

Videos are prominent learning materials to prepare surgical trainees before they enter the operating room (OR). In this work, we explore techniques to enrich the video-based surgery learning experience. We propose Surgment, a system that helps expert surgeons create exercises with feedback based on surgery recordings. Surgment is powered by a few-shot-learni

Taisuke Yasuda, Kyriakos Axiotis, Gang Fu, MohammadHossein Bateni

Neural network pruning is a key technique towards engineering large yet scalable, interpretable, and generalizable models. Prior work on the subject has developed largely along two orthogonal directions: (1) differentiable pruning for efficiently and accurately scoring the importance of parameters, and (2) combinatorial optimization for efficiently searching

Wihan Adi, Samir Rosas, Aidana Beisenova, Shovasis Kumar Biswas

Optical metasurfaces can manipulate electromagnetic waves in unprecedented ways at ultra-thin engineered interfaces. Specifically, in the mid-infrared (mid-IR) region, metasurfaces have enabled numerous biochemical sensing, spectroscopy, and vibrational strong coupling (VSC) applications via enhanced light-matter interactions in resonant cavities. However, m

Peter B. Weichman

Radio frequency antennas based on Rydberg atom vapor cells can in principle reach sensitivities beyond those of any wire antenna, especially at lower frequencies where long wires are needed to accommodate a growing wavelength. They also have other desirable features such as nonmetallic, lower profile, elements. This paper presents a detailed theoretical inve

Prakash Chakraborty, Harsha Honnappa, Samy Tindel

This note lays part of the theoretical ground for a definition of differential systems modeling reinforcement learning in continuous time non-Markovian rough environments. Specifically we focus on optimal relaxed control of rough equations (the term relaxed referring to the fact that controls have to be considered as measure valued objects). With reinforceme

Junior da S. Bessa, João Vitor da Silva, Gleydson C. Ricarte

In this work, we establish universal moduli of continuity for viscosity solutions to fully nonlinear elliptic equations with oblique boundary conditions, whose general model is given by $$ \left\{ \begin{array}{rcl} F(D^2u,x) &=& f(x) \quad \mbox{in} \,\, \Omega\\ \beta(x) \cdot Du(x) + \gamma(x) \, u(x)&=& g(x) \quad \mbox{on} \,\, \partial \Omega. \end{arr

Mahdiyar Mousavi-Sadr

The number of extrasolar planets discovered is increasing, so that more than five thousand exoplanets have been confirmed to date. Now we have an opportunity to test the validity of the laws governing planetary systems and take steps to discover the relationships between the physical parameters of planets and stars. Firstly, we present the results of a searc

Hang Dong, Jiaoyan Chen, Yuan He, Yongsheng Gao

We investigate the task of inserting new concepts extracted from texts into an ontology using language models. We explore an approach with three steps: edge search which is to find a set of candidate locations to insert (i.e., subsumptions between concepts), edge formation and enrichment which leverages the ontological structure to produce and enhance the ed

Corby Rosset, Ho-Lam Chung, Guanghui Qin, Ethan C. Chau

Existing question answering (QA) datasets are no longer challenging to most powerful Large Language Models (LLMs). Traditional QA benchmarks like TriviaQA, NaturalQuestions, ELI5 and HotpotQA mainly study ``known unknowns'' with clear indications of both what information is missing, and how to find it to answer the question. Hence, good performance on these

Matthew Hayman, Robert A. Stillwell, Adam Karboski, Willem J. Marais

We demonstrate thermodynamic profile estimation with data obtained using the MicroPulse DIAL such that the retrieval is entirely self contained. The only external input is surface meteorological variables obtained from a weather station installed on the instrument. The estimator provides products of temperature, absolute humidity and backscatter ratio such t

Enrique Zuazua

These Notes originated from a course I delivered at the Institute of Mathematics of the Universidade Federal do Rio de Janeiro, Brazil (UFRJ) in July-September 1989, were initially published in 1989 in Spanish under the title "Controlabilidad Exacta y Estabilizaci\'on de la Ecuaci\'on de Ondas" in the Lecture Notes Series of the Institute. Despite the signif

Mohammad Rostami, Atik Faysal, Huaxia Wang, Avimanyu Sahoo

Overfitting is a significant challenge in Few-Shot Learning (FSL), where models trained on small, variable datasets tend to memorize rather than generalize to unseen tasks. Regularization is crucial in FSL to prevent overfitting and enhance generalization performance. To address this issue, we introduce Meta-Task, a novel, method-agnostic framework that leve

Jonathan T. Morrell, Ellen M. O'Brien, Michael Skulski, Andrew S. Voyles

Cerium-134 is an isotope desired for applications as a chemical analogue to the promising therapeutic radionuclide $^{225}$Ac, for use in bio-distribution assays as an in vivo generator of the short-lived positron-emitting isotope $^{134}$La. In the 50-100 MeV energy range relevant to the production of $^{134}$Ce by means of high-energy proton bombardment of

Sandro Papais, Robert Ren, Steven Waslander

Modern robotic systems are required to operate in dense dynamic environments, requiring highly accurate real-time track identification and estimation. For 3D multi-object tracking, recent approaches process a single measurement frame recursively with greedy association and are prone to errors in ambiguous association decisions. Our method, Sliding Window Tra

Xinyu Yang, Hossein Rahmani, Sue Black, Bryan M. Williams

Class activation maps (CAMs) are commonly employed in weakly supervised semantic segmentation (WSSS) to produce pseudo-labels. Due to incomplete or excessive class activation, existing studies often resort to offline CAM refinement, introducing additional stages or proposing offline modules. This can cause optimization difficulties for single-stage methods a

Saurabh Mishra, Anant Raj, Sharan Vaswani

Inverse optimization involves inferring unknown parameters of an optimization problem from known solutions and is widely used in fields such as transportation, power systems, and healthcare. We study the contextual inverse optimization setting that utilizes additional contextual information to better predict the unknown problem parameters. We focus on contex

David R. Patton, Lawrence Faria, Maan H. Hani, Paul Torrey

Cosmological simulations have been used to study interacting galaxies as a function of galaxy pair separation, enabling comparisons with observational studies of galaxy pairs. The study of interacting galaxies as a function of time (i.e. merger stage) has mostly been limited to high resolution merger simulations, due to the poor time sampling available in co

Junda Wang, Zhichao Yang, Zonghai Yao, Hong Yu

Large Language Models (LLMs) have demonstrated a remarkable potential in medical knowledge acquisition and question-answering. However, LLMs can potentially hallucinate and yield factually incorrect outcomes, even with domain-specific pretraining. Previously, retrieval augmented generation (RAG) has limited success in addressing hallucinations. Unlike previo

Ye He, Kevin Rojas, Molei Tao

This paper considers the problem of sampling from non-logconcave distribution, based on queries of its unnormalized density. It first describes a framework, Denoising Diffusion Monte Carlo (DDMC), based on the simulation of a denoising diffusion process with its score function approximated by a generic Monte Carlo estimator. DDMC is an oracle-based meta-algo

Philip Jordan, Anas Barakat, Niao He

Constrained Markov games offer a formal mathematical framework for modeling multi-agent reinforcement learning problems where the behavior of the agents is subject to constraints. In this work, we focus on the recently introduced class of constrained Markov Potential Games. While centralized algorithms have been proposed for solving such constrained games, t

Luis Chiner Carrillo

This paper generalizes the notion of geometric curves such as hyperbolas and ellipses to more general vector spaces with an associated inner product. This is done by generalizing the definition in terms of loci and foci of said curves in Euclidean geometry to a general vector space with a real inner product, through which a norm can be induced. Through this

Hung P. Tong-Viet

Thompson's theorem stated that a finite group $G$ is solvable if and only if every $2$-generated subgroup of $G$ is solvable. In this paper, we prove some new criteria for both solvability and nilpotency of a finite group using certain condition on $2$-generated subgroups. We show that a finite group $G$ is solvable if and only if for every pair of two eleme

Parker Glenn, Parag Pravin Dakle, Liang Wang, Preethi Raghavan

Many existing end-to-end systems for hybrid question answering tasks can often be boiled down to a "prompt-and-pray" paradigm, where the user has limited control and insight into the intermediate reasoning steps used to achieve the final result. Additionally, due to the context size limitation of many transformer-based LLMs, it is often not reasonable to exp

A. Kafuri, F. H. Maldonado-Villamizar, A. Moroz, B. M. Rodríguez-Lara

We revisit the Jaynes-Cummings and anti-Jaynes-Cummings model through the lens of Lie theory, aiming to highlight the efficacy of an operator-based approach for diagonalization. We focus on explicitly delineating the steps from an underlying abstract supersymmetry, provided by the $u(1 \vert 1)$ superalgebra, into concrete proper states and energies in the l

Chau Tran, Kejsi Take, Kaylea Champion, Benjamin Mako Hill

Content moderation practices and technologies need to change over time as requirements and community expectations shift. However, attempts to restructure existing moderation practices can be difficult, especially for platforms that rely on their communities to conduct moderation activities, because changes can transform the workflow and workload of moderator

Michael Y. Li, Emily B. Fox, Noah D. Goodman

Statistical model discovery is a challenging search over a vast space of models subject to domain-specific constraints. Efficiently searching over this space requires expertise in modeling and the problem domain. Motivated by the domain knowledge and programming capabilities of large language models (LMs), we introduce a method for language model driven auto

Laura Stegner, David Porfirio, Laura M. Hiatt, Séverin Lemaignan

End-user development (EUD) represents a key step towards making robotics accessible for experts and nonexperts alike. Within academia, researchers investigate novel ways that EUD tools can capture, represent, visualize, analyze, and test developer intent. At the same time, industry researchers increasingly build and ship programming tools that enable custome

Preethi Chandrasekaran, Chong Chen, Yingmin Liu, Syed Murtaza Arshad

Background: Cardiovascular magnetic resonance imaging (CMR) is a well established imaging tool for diagnosing and managing cardiac conditions. The integration of exercise stress with CMR (ExCMR) can enhance its diagnostic capacity. Despite recent advances in CMR technology, quantitative ExCMR during exercise remains technically challenging due to motion arti

Adam Britel, Giulia Tomagra, Pietro Aprà, Veronica Varzi

Droplet-based microfluidics systems have become widely used in recent years thanks to their advantages, varying from the possibility of handling small fluid volumes to directly synthesizing and encapsulating various living forms for biological-related applications. The effectiveness of such systems mainly depends on the ability to control some of these syste

C. Giménez-Arteaga, S. Fujimoto, F. Valentino, G. B. Brammer

We present JWST/NIRCam observations of a strongly-lensed, multiply-imaged galaxy at $z=6.072$, with magnification factors >~20 across the galaxy. We perform a spatially-resolved analysis of the physical properties at scales of ~200 pc, inferred from SED modelling of 5 NIRCam imaging bands on a pixel-by-pixel basis. We find young stars surrounded by extended

Mel Krusniak, Forrest Laine

When modeling robot interactions as Nash equilibrium problems, it is desirable to place coupled constraints which restrict these interactions to be safe and acceptable (for instance, to avoid collisions). Such games are continuous with potential mixed strategy equilibria, and this combination of characteristics means special care must be given to setting cou

Anastasia Kireeva, Joel A. Tropp

This short course offers a new perspective on randomized algorithms for matrix computations. It explores the distinct ways in which probability can be used to design algorithms for numerical linear algebra. Each design template is illustrated by its application to several computational problems. This treatment establishes conceptual foundations for randomize

Tahani Makki, Mounib El Eid, Grant Mathews

To constrain the universe before recombination (380000 years after the Big Bang), we mostly rely on the measurements of the primordial abundances that indicate the first insight into the thermal history of the universe. The first production of the light elements is obtained by the Big Bang Nucleosynthesis (BBN). The production of the elements deuterium, heli

Samuel Gruffaz, Kyurae Kim, Alain Oliviero Durmus, Jacob R. Gardner

The expectation maximization (EM) algorithm is a widespread method for empirical Bayesian inference, but its expectation step (E-step) is often intractable. Employing a stochastic approximation scheme with Markov chain Monte Carlo (MCMC) can circumvent this issue, resulting in an algorithm known as MCMC-SAEM. While theoretical guarantees for MCMC-SAEM have p

Pavle Midodashvili

In the article, we investigate localization problem for spinor fields within the 6D standing wave braneworld with the bulk real scalar field, introduced earlier in [30], and explicitly show that there is no normalizable fermion field zero mode trapped on the brane.

Alan McGibney, Tharindu Ranathunga, Roman Pospisil

Recent developments in Distributed Ledger Technology (DLT), including Blockchain offer new opportunities in the manufacturing domain, by providing mechanisms to automate trust services (digital identity, trusted interactions, and auditable transactions) and when combined with other advanced digital technologies (e.g. machine learning) can provide a secure ba

Yongxin Zeng, Daniele Guerci, Valentin Crépel, Andrew J. Millis

The prediction and realization of the quantum anomalous Hall effect are often intimately connected to honeycomb lattices in which the sublattice degree of freedom plays a central role in the nontrivial topology. Two-dimensional Wigner crystals, on the other hand, form triangular lattices without sublattice degrees of freedom, resulting in a topologically tri

Júlio Borges, Altieris M. Peixoto, Thiago H. Silva, Anelise Munaretto

This study aims to propose an approach for spatiotemporal integration of bus transit, which enables users to change bus lines by paying a single fare. This could increase bus transit efficiency and, consequently, help to make this mode of transportation more attractive. Usually, this strategy is allowed for a few hours in a non-restricted area; thus, certain

Maico Freitas, Evgeny Mukhin

The polynomial ideals studied by A. Garsia and C. Procesi play an important role in the theory of Kostka polynomials. We give multiparameter flat deformations of these ideals and define an action of the extended affine symmetric group on the corresponding quotient algebras multiplied by the sign representation. We show that the images of these modules under

César D. Fosco, Fernando C. Lombardo, Francisco D. Mazzitelli

We review the derivative expansion (DE) method in Casimir physics, an approach which extends the proximity force approximation (PFA). After introducing and motivating the DE in contexts other than the Casimir effect, we present different examples which correspond to that realm. We focus on different particular geometries, boundary conditions, types of fields

Young Kyung Kim, J. Matías Di Martino, Guillermo Sapiro

Tokens or patches within Vision Transformers (ViT) lack essential semantic information, unlike their counterparts in natural language processing (NLP). Typically, ViT tokens are associated with rectangular image patches that lack specific semantic context, making interpretation difficult and failing to effectively encapsulate information. We introduce a nove

Mincheol Park, Dongjin Kim, Cheonjun Park, Yuna Park

Channel pruning is widely accepted to accelerate modern convolutional neural networks (CNNs). The resulting pruned model benefits from its immediate deployment on general-purpose software and hardware resources. However, its large pruning granularity, specifically at the unit of a convolution filter, often leads to undesirable accuracy drops due to the infle

Victor Ojewale, Ryan Steed, Briana Vecchione, Abeba Birhane

Audits are critical mechanisms for identifying the risks and limitations of deployed artificial intelligence (AI) systems. However, the effective execution of AI audits remains incredibly difficult, and practitioners often need to make use of various tools to support their efforts. Drawing on interviews with 35 AI audit practitioners and a landscape analysis

Johan du Buisson, David A. Sivak, John Bechhoefer

We review recent studies of a colloidal information engine that consists of a bead in water and held by an optical trap. The bead is ratcheted upward without any apparent external work, by taking advantage of favorable thermal fluctuations. Much of the previous work on such engines aimed to show that accounting for information-processing costs can reconcile

Howard Baer, Vernon Barger, Dakotah Martinez, Shadman Salam

Superstring flux compactifications can stabilize all moduli while leading to an enormous number of vacua solutions, each leading to different $4-d$ laws of physics. While the string landscape provides at present the only plausible explanation for the size of the cosmological constant, it may also predict the form of weak scale supersymmetry which is expected

Michelle Delcourt, Tom Kelly, Luke Postle

We prove that if $p \geq n^{-(q-6)/2}$, then asymptotically almost surely the binomial random $q$-uniform hypergraph $G^{(q)}(n,p)$ contains an $(n,q,2)$-Steiner system, provided $n$ satisfies the necessary divisibility conditions.

Michelle Delcourt, Tom Kelly, Luke Postle

We prove that if $p\ge n^{-\frac{1}{3}+\beta}$ for some $\beta > 0$, then asymptotically almost surely the binomial random graph $G(n,p)$ has a $K_3$-packing containing all but at most $n + O(1)$ edges. Similarly, we prove that if $d \ge n^{\frac{2}{3}+\beta}$ for some $\beta > 0$ and $d$ is even, then asymptotically almost surely the random $d$-regular grap

Michelle Delcourt, Luke Postle

We prove the High Girth Existence Conjecture - the common generalization of the Existence Conjecture for Combinatorial Designs originating from the 1800s and Erd\H{o}s' Conjecture from 1973 on the Existence of High Girth Steiner Triple Systems.

Michelle Delcourt, Luke Postle

The study of combinatorial designs has a rich history spanning nearly two centuries. In a recent breakthrough, the notorious Existence Conjecture for Combinatorial Designs dating back to the 1800s was proved in full by Keevash via the method of randomized algebraic constructions. Subsequently Glock, K\"{u}hn, Lo, and Osthus provided an alternate purely combi

S. Shefali, Frank G. Schroeder

The surface array of IceCube, IceTop, operates primarily as a cosmic-ray detector, as well as a veto for astrophysical neutrino searches for the IceCube in-ice instrumentation. However, the snow accumulation on top of the IceTop detectors increases the detection threshold and attenuates the measured IceTop signals. Enhancing IceTop by a hybrid array of scint

Zijie Li, Saurabh Patil, Francis Ogoke, Dule Shu

Neural networks have shown promising potential in accelerating the numerical simulation of systems governed by partial differential equations (PDEs). Different from many existing neural network surrogates operating on high-dimensional discretized fields, we propose to learn the dynamics of the system in the latent space with much coarser discretizations. In

Dongryul Kim

We prove a descent result for finite projective modules, motivated by a question in perfectoid geometry. Given a commutative ring $A$, we formulate a descent problem for descending a finite projective module over the Novikov ring with coefficients in $A$ to a finite projective module over $A$. The main theorem of this paper is that all such descent data are

I. Montoya Arroyave, C. Cicone, P. Andreani, A. Weiss

Local ULIRGs host ubiquitous molecular outflows, including the most massive and powerful ever detected. These sources have also exceptionally excited global, galaxy-integrated CO ladders. A connection between outflows and molecular gas excitation has however never been established, since previous multi-J CO surveys were limited in spectral resolution and sen

Krasimir Kanchev, Ognian Kassabov, Velichka Milousheva

In this paper we give Weierstrass-type representation formulas for the null curves and for the minimal Lorentz surfaces in the Minkowski 3-space $\mathbb R^3_1$ using real-valued functions. Applying the Weierstrass-type representations for the null curves, we find a correspondence between the null curves in $\mathbb R^4_2$ and the pairs of null curves in $\m

Manosij Ghosh Dastidar, Michael Wallner

We prove new bijections between different variants of Dyck paths and integer compositions, which give combinatorial explanations of their simple counting formula $4^{n-1}$. These give relations between different statistics, such as the number of crossings of the $x$-axis in classes of Dyck bridges or the distribution of peaks in classes of Dyck paths, and fu

Vassilis Papadopoulos, Guilhem Doat, Arthur Renard, Clément Hongler

One key challenge in Artificial Life is designing systems that display an emergence of complex behaviors. Many such systems depend on a high-dimensional parameter space, only a small subset of which displays interesting dynamics. Focusing on the case of continuous systems, we introduce the 'Phase Transition Finder'(PTF) algorithm, which can be used to effici

Nouran Soliman, Hyeonsu B Kang, Matthew Latzke, Jonathan Bragg

In communities with social hierarchies, fear of judgment can discourage communication. While anonymity may alleviate some social pressure, fully anonymous spaces enable toxic behavior and hide the social context that motivates people to participate and helps them tailor their communication. We explore a design space of meronymous communication, where people

Iyad Kanj, Salman Parsa

We study computationally-hard fundamental motion planning problems where the goal is to translate $k$ axis-aligned rectangular robots from their initial positions to their final positions without collision, and with the minimum number of translation moves. Our aim is to understand the interplay between the number of robots and the geometric complexity of the

F. Valentino, S. Fujimoto, C. Giménez-Arteaga, G. Brammer

We present the results of a ~60-hr observational campaign with ALMA targeting a spectroscopically confirmed and lensed sub-$L^\star$ galaxy at z=6.07, identified during the ALMA Lensing Cluster Survey (ALCS). We sample the dust continuum emission from rest frame 90 to 370 $\mu$m at six different frequencies and set constraining upper limits on the molecular

Andrzej Grudka, Tim R. Morris, Jonathan Oppenheim, Andrea Russo

One of the obstacles to reconciling quantum theory with general relativity, is constructing a theory which is both consistent with observation, and and gives finite answers at high energy, so that the theory holds at arbitrarily short distances. Quantum field theory achieves this through the process of renormalisation, but famously, perturbative quantum grav

Y. Ohno, A. Del Maestro, T. I. Lakoba

We develop convergence acceleration procedures that enable a gradient descent-type iteration method to efficiently simulate Hartree--Fock equations for atoms interacting both with each other and with an external potential. Our development focuses on three aspects: (i) optimization of a parameter in the preconditioning operator; (ii) adoption of a technique t

Bushra Alhijawi, Rawan Jarrar, Aseel AbuAlRub, Arwa Bader

Large Language Models (LLMs), such as GPT-3 and BERT, reshape how textual content is written and communicated. These models have the potential to generate scientific content that is indistinguishable from that written by humans. Hence, LLMs carry severe consequences for the scientific community, which relies on the integrity and reliability of publications.

Keshav Ramji, Young-Suk Lee, Ramón Fernandez Astudillo, Md Arafat Sultan

It is often desirable for Large Language Models (LLMs) to capture multiple objectives when providing a response. In document-grounded response generation, for example, agent responses are expected to be relevant to a user's query while also being grounded in a given document. In this paper, we introduce Proxy Metric-based Self-Refinement (ProMiSe), which ena

Christo Morison, Małgorzata Fic, Thomas Marcou, Javad Mohamadichamgavi

Cooperation arises in nature at every scale, from within cells to entire ecosystems. In the framework of evolutionary game theory, public goods games (PGGs) are used to analyse scenarios where individuals can cooperate or defect, and can predict when and how these behaviours emerge. However, too few examples motivate the transferal of knowledge from one appl

Jeremy Quail, Puck Rombach

Positroids are matroids realizable by real matrices with all nonnegative maximal minors. They partition the ordered matroids into equivalence classes, called positroid envelope classes, by their Grassmann necklaces. We give an explicit graph construction that shows that every positroid envelope class contains a graphic matroid. We prove that a graphic positr

Zhenting Qi, Hanlin Zhang, Eric Xing, Sham Kakade

Retrieval-Augmented Generation (RAG) improves pre-trained models by incorporating external knowledge at test time to enable customized adaptation. We study the risk of datastore leakage in Retrieval-In-Context RAG Language Models (LMs). We show that an adversary can exploit LMs' instruction-following capabilities to easily extract text data verbatim from the

Ada Boralevi, Enrico Carlini, Mateusz Michałek, Emanuele Ventura

In this article, we study permanental varieties, i.e. varieties defined by the vanishing of permanents of fixed size of a generic matrix. Permanents and their varieties play an important, and sometimes poorly understood, role in combinatorics. However, there are essentially no geometric results about them in the literature, in very sharp contrast to the well

A. Zanella, E. Iani, M. Dessauges-Zavadsky, J. Richard

Observations at UV and optical wavelengths have revealed that galaxies at z~1-4 host star-forming regions, dubbed "clumps", which are believed to form due to the fragmentation of gravitationally unstable, gas-rich disks. However, the detection of the parent molecular clouds that give birth to such clumps is still possible only in a minority of galaxies, most

Laura Stegner, David Porfirio, Mark Roberts, Laura M. Hiatt

As service robots become more capable of autonomous behaviors, it becomes increasingly important to consider how people communicate with a robot what task it should perform and how to do the task. Accordingly, there has been a rise in attention to end-user development (EUD) interfaces, which enable non-roboticist end users to specify tasks for autonomous rob

Kieran Wood, Paul M. Saffin, Anastasios Avgoustidis

We construct a wide class of black hole solutions to the general theory of ghost free multi-metric gravity in arbitrary spacetime dimension, extending and generalising the known results in 4-dimensional dRGT massive gravity and bigravity. The solutions are split into three generic classes based on whether the metrics can be simultaneously diagonalised - one

Marco Bellagente, Jonathan Tow, Dakota Mahan, Duy Phung

We introduce StableLM 2 1.6B, the first in a new generation of our language model series. In this technical report, we present in detail the data and training procedure leading to the base and instruction-tuned versions of StableLM 2 1.6B. The weights for both models are available via Hugging Face for anyone to download and use. The report contains thorough

Almudena Carrera Vazquez, Caroline Tornow, Diego Riste, Stefan Woerner

Quantum computers process information with the laws of quantum mechanics. Current quantum hardware is noisy, can only store information for a short time, and is limited to a few quantum bits, i.e., qubits, typically arranged in a planar connectivity. However, many applications of quantum computing require more connectivity than the planar lattice offered by

D. N. Sheng, Aidan P. Reddy, Ahmed Abouelkomsan, Emil J. Bergholtz

We predict the emergence a state of matter with intertwined ferromagnetism, charge order and topology in fractionally filled moir\'e superlattice bands. Remarkably, these quantum anomalous Hall crystals exhibit a quantized integer Hall conductance that is different than expected from the filling and Chern number of the band. Microscopic calculations show tha

Alice Pagano, Daniel Jaschke, Werner Weiss, Simone Montangero

The transport of neutral atoms in Rydberg quantum computers is a crucial step of the initial arrangement of the grid as well as to the dynamic connectivity, recently successfully demonstrated. We study the application of optimal control and the quantum speed limit for the transport of neutral atoms in optical tweezers at finite temperatures and analyze how l

Bronwyn Reichardt Chu, Deanne B. Fisher, John Chisholm, Danielle Berg

We measure resolved (kiloparsec-scale) outflow properties in a sample of 10 starburst galaxies from the DUVET (Deep near-UV observations of Entrained gas in Turbulent galaxies) sample, using Keck/KCWI observations of H$\beta$ and [OIII]~$\lambda$5007. We measure $\sim460$ lines-of-sight that contain outflows, and use these to study scaling relationships of o

A. Calabrò, L. Pentericci, P. Santini, A. Ferrara

The galaxy integrated star-formation rate (SFR) surface density ($\Sigma_{\rm SFR}$) has been proposed as a valuable diagnostic of the mass accumulation in galaxies as being more tightly related to the physics of star-formation (SF) and stellar feedback than other SF indicators. In this paper, we assemble a statistical sample of 230 galaxies observed with JW

Zihao Zuo, Shifu Zhu, W. N. Brandt, Gordon P. Garmire

Highly radio-loud quasars (HRLQs; $\log R>2.5$) at $z\gtrsim 4$ show apparent enhanced X-ray emission compared to matched HRLQs at lower redshifts, perhaps due to a redshift-dependent fractional contribution to the X-ray luminosity from inverse-Compton scattering of cosmic microwave background photons (IC/CMB). Using new {\it Chandra} observations and archiv

Zenan Dai, Xiao Yan Xu

Residual entropy, which reflects the degrees of freedom in a system at absolute zero temperature, is crucial for understanding quantum and classical ground states. Despite its key role in explaining low-temperature phenomena and ground state degeneracy, accurately measuring residual entropy remains a difficult task owing to computational limitations. In this

Ivi Chatzi, Eleni Straitouri, Suhas Thejaswi, Manuel Gomez Rodriguez

Large language models are often ranked according to their level of alignment with human preferences -- a model is better than other models if its outputs are more frequently preferred by humans. One of the popular ways to elicit human preferences utilizes pairwise comparisons between the outputs provided by different models to the same inputs. However, since

Ana Alonso-Serrano, Erickson Tjoa, Luis J. Garay, Eduardo Martín-Martínez

We analyze how the presence of closed timelike curves (CTCs) characterizing a time machine can be discerned by placing a local particle detector in a region of spacetime which is causally disconnected from the CTCs. Our study shows that not only can the detector tell if there are CTCs, but also that the detector can separate topological from geometrical info

Subir Sachdev

A brief survey of some random quantum models with infinite-range couplings is presented, ranging from the quantum Ising model to the Sachdev-Ye-Kitaev model. The Sachdev-Ye-Kitaev model was the first to realize an extensive zero temperature entropy without requiring an exponentially large ground state degeneracy. This phenomenon is closely linked to the abse

Valentin Thoss, Andreas Burkert, Kazunori Kohri

The energy injection through Hawking evaporation has been used to put strong constraints on primordial black holes as a dark matter candidate at masses below $10^{17}\,\rm{g}$. However, Hawking's semiclassical approximation breaks down at latest after half-decay. Beyond this point, the evaporation could be significantly suppressed, as was shown in recent wor

Gideon Ilani, Kuan-Chou Hou, Gil Nadler, Uri Keshet

Following the recent identification of discrete ROSAT and radio sources associated with the virial shocks of MCXC clusters and groups, we examine if the early eROSITA-DE data release (EDR) shows virial-shock X-ray sources within its $140$ deg$^2$ field. EDR catalog sources are stacked and radially binned around EDR catalog clusters and groups. The properties

Hooman Davoudiasl, Roman Marcarelli, Ethan T. Neil

We revisit the possibility that light axion-like particles (ALPs) with lepton flavor violating couplings could give significant contributions to the electron's anomalous magnetic moment $g_e-2$. Unlike flavor diagonal lepton-ALP couplings, which are exclusively axial, lepton flavor violating couplings can have arbitrary chirality. Focusing on the $e$-$\tau$

Mariia Khelashvili, Mariangela Lisanti, Anirudh Prabhu, Benjamin R. Safdi

Electromagnetic fields surrounding pulsars may source coherent ultralight axion signals at the known rotational frequencies of the neutron stars, which can be detected by laboratory experiments (e.g., pulsarscopes). As a promising case study, we model axion emission from the well-studied Crab pulsar, which would yield a prominent signal at $f \approx 29.6$ H

Seunghwan Lim, Sandro Tacchella, Joop Schaye, Matthieu Schaller

Motivated by the recent JWST discovery of galaxy overdensities during the Epoch of Reionzation, we examine the physical properties of high-$z$ protoclusters and their evolution using the FLAMINGO simulation suite. We investigate the impact of the apertures used to define protoclusters, because the heterogeneous apertures used in the literature have limited o

Chris Byrohl, Dylan Nelson

scida is a Python package for reading and analyzing large scientific data sets with support for various cosmological and galaxy formation simulations out-of-the-box. Data access is provided through a hierarchical dictionary-like data structure after a simple load() function. Using the dask library for scalable, parallel and out-of-core computation, all compu

William H. Pannell, Andreas Stergiou

The gradient property of the renormalisation group (RG) flow of multiscalar theories is examined perturbatively in $d=4$ and $d=4-\varepsilon$ dimensions. Such theories undergo RG flows in the space of quartic couplings $\lambda^I$. Starting at five loops, the relevant vector field that determines the physical RG flow is not the beta function traditionally c

Sébastien Picard

This is a survey on the Strominger system and a geometric flow known as the anomaly flow. We will discuss various aspects of non-K\"ahler geometry on Calabi-Yau threefolds. Along the way, we discuss balanced metrics and balanced classes, the Aeppli cohomology class associated to a solution to the Strominger system, the equations of motion of heterotic superg

Laura Stegner, Emmanuel Senft, Bilge Mutlu

We introduce a taxonomy of important factors to consider when designing interactions with an assistive robot in a senior living facility. These factors are derived from our reflection on two field studies and are grouped into the following high-level categories: primary user (residents), care partners, robot, facility and external circumstances. We outline h

Xiaoyu Zhang, Matthew Chang, Pranav Kumar, Saurabh Gupta

A common failure mode for policies trained with imitation is compounding execution errors at test time. When the learned policy encounters states that are not present in the expert demonstrations, the policy fails, leading to degenerate behavior. The Dataset Aggregation, or DAgger approach to this problem simply collects more data to cover these failure stat

Arjun Gupta, Michelle Zhang, Rishik Sathua, Saurabh Gupta

What does it take to build mobile manipulation systems that can competently operate on previously unseen objects in previously unseen environments? This work answers this question using opening of articulated structures as a mobile manipulation testbed. Specifically, our focus is on the end-to-end performance on this task without any privileged information,

Zekun Qi, Runpei Dong, Shaochen Zhang, Haoran Geng

This paper presents ShapeLLM, the first 3D Multimodal Large Language Model (LLM) designed for embodied interaction, exploring a universal 3D object understanding with 3D point clouds and languages. ShapeLLM is built upon an improved 3D encoder by extending ReCon to ReCon++ that benefits from multi-view image distillation for enhanced geometry understanding.

Balázs Bárány, Gábor Domokos, Ágoston Szesztay

In this paper, we consider a fractal model motivated by the abrasion of convex polyhedra, where the abrasion is realised by chipping small neighbourhoods of vertices. After providing a formal description of the successive chippings, we show that the net of edges converge to a compact limit set under mild assumptions. Furthermore, we study the upper box-count