February 2024 arXiv papers — page 2

Per Bäck, Johan Richter

We introduce hom-associative versions of the higher order Weyl algebras, generalizing the construction of the first hom-associative Weyl algebras. We then show that the higher order hom-associative Weyl algebras are simple, and that all their one-sided ideals are principal.

Chester Holtz, Yucheng Wang, Chung-Kuan Cheng, Bill Lin

There is substantial interest in the use of machine learning (ML)-based techniques throughout the electronic computer-aided design (CAD) flow, particularly methods based on deep learning. However, while deep learning methods have achieved state-of-the-art performance in several applications, recent work has demonstrated that neural networks are generally vul

Vincent Dumont, Markus Bestler, Letizia Catalini, Gabriel Margiani

Many experimental techniques aim at determining the Hamiltonian of a given system. The Hamiltonian describes the system's evolution in the absence of dissipation, and is often central to control or interpret an experiment. Here, we theoretically propose and experimentally demonstrate a method for Hamiltonian reconstruction from measurements over a large area

D. A. Kann, N. E. White, G. Ghirlanda, S. R. Oates

Gamma-ray bursts (GRBs) are ideal probes of the Universe at high redshift (z > 5), pinpointing the locations of the earliest star-forming galaxies and providing bright backlights that can be used to spectrally fingerprint the intergalactic medium and host galaxy during the period of reionization. Future missions such as Gamow Explorer are being proposed to u

CMS Collaboration

A search for heavy neutral leptons (HNLs) of Majorana or Dirac type using proton-proton collision data at $\sqrt{s}$ = 13 TeV is presented. The data were collected by the CMS experiment at the CERN LHC and correspond to an integrated luminosity of 138 fb$^{-1}$. Events with three charged leptons (electrons, muons, and hadronically decaying tau leptons) are s

Waleed Abdeen, Xingru Chen, Michael Unterkalmsteiner

Model-based testing (MBT) is a method that supports the design and execution of test cases by models that specify the intended behaviors of a system under test. While systematic literature reviews on MBT in general exist, the state of the art on modeling and testing performance requirements has seen much less attention. Therefore, we conducted a systematic m

Gorav Jindal, Joël Ouaknine

The Skolem Problem asks, given an integer linear recurrence sequence (LRS), to determine whether the sequence contains a zero term or not. Its decidability is a longstanding open problem in theoretical computer science and automata theory. Currently, decidability is only known for LRS of order at most 4. On the other hand, the sole known complexity result is

Lvzhou Chen, Alexander J. Rasmussen

We study a skew product transformation associated to an irrational rotation of the circle [0,1]/~. This skew product keeps track of the number of times an orbit of the rotation lands in the two complementary intervals of {0,1/2} in the circle. We show that under certain conditions on the continued fraction expansion of the irrational number defining the rota

Raghavv Goel, Mukul Gagrani, Wonseok Jeon, Junyoung Park

Text generation with Large Language Models (LLMs) is known to be memory bound due to the combination of their auto-regressive nature, huge parameter counts, and limited memory bandwidths, often resulting in low token rates. Speculative decoding has been proposed as a solution for LLM inference acceleration. However, since draft models are often unavailable i

David Danks, Rada Mihalcea, Katie Siek, Mona Singh

This report summarizes the discussions and conclusions of a 2-day multidisciplinary workshop that brought together researchers and practitioners in healthcare, computer science, and social sciences to explore what lessons were learned and what actions, primarily in research, could be taken. One consistent observation was that there is significant merit in th

Neil Zhao, Diana Zheng

Skill mastery is a priority for success in all fields. We present a parallel between the development of skill mastery and the process of solving jigsaw puzzles. We show that iterative random sampling solves jigsaw puzzles in two phases: a lag phase that is characterized by little change and occupies the majority of the time, and a growth phase that marks rap

Luca Avena, Remco van der Hofstad, Frank den Hollander, Oliver Nagy

We analyse the mixing profile of a random walk on a dynamic random permutation, focusing on the regime where the walk evolves much faster than the permutation. Two types of dynamics generated by random transpositions are considered: one allows for coagulation of permutation cycles only, the other allows for both coagulation and fragmentation. We show that fo

Saptak Bhattacharya

We give a new elementary proof of existence and uniqueness of a solution to the Sylvester equation $AX-XB=Y$

Shruti P. Gadewar, Alyssa H. Zhu, Iyad Ba Gari, Sunanda Somu

Neuroimaging consortia can enhance reliability and generalizability of findings by pooling data across studies to achieve larger sample sizes. To adjust for site and MRI protocol effects, imaging datasets are often harmonized based on healthy controls. When data from a control group were not collected, statistical harmonization options are limited as patient

Pooja Srinivas, Fiza Husain, Anjaly Parayil, Ayush Choure

Cloud service owners need to continuously monitor their services to ensure high availability and reliability. Gaps in monitoring can lead to delay in incident detection and significant negative customer impact. Current process of monitor creation is ad-hoc and reactive in nature. Developers create monitors using their tribal knowledge and, primarily, a trial

Tianyi Zhang, Li Zhang, Zhaoyi Hou, Ziyu Wang

Planning in a text-based environment continues to be a major challenge for AI systems. Recent approaches have used language models to predict a planning domain definition (e.g., PDDL) but have only been evaluated in closed-domain simulated environments. To address this, we present Proc2PDDL , the first dataset containing open-domain procedural texts paired w

Ammar Ali, Hanjing Xu, William Bernoudy, Alberto Nocera

Geometric frustration in two-dimensional Ising models allows for a wealth of exotic universal behavior, both Ising and non-Ising, in the presence of quantum fluctuations. In particular, the triangular antiferromagnet and Villain model in a transverse field can be understood through distinct XY pseudospins, but have qualitatively similar phase diagrams includ

Pranay Mohta, Abhinandan Bhattacharjee, Anand K. Jha

Spatial coherence plays an important role in several real-world applications ranging from imaging to communication. As a result, its accurate characterization and measurement are extremely crucial for its optimal application. However, efficient measurement of an arbitrary complex spatial coherence function is still very challenging. In this letter, we propos

M. Eltohfa, Xinghan Wang, Colton M. Griffin, F. Robicheaux

One-dimensional systems, such as nanowires or electrons moving along strong magnetic field lines, have peculiar thermalization physics. The binary collision of point-like particles, typically the dominant process for reaching thermal equilibrium in higher dimensional systems, cannot thermalize a 1D system. We study how dilute classical 1D gases thermalize th

Deepika Badampudi, Michael Unterkalmsteiner, Ricardo Britto

Background: Modern Code Review (MCR) is a lightweight alternative to traditional code inspections. While secondary studies on MCR exist, it is unknown whether the research community has targeted themes that practitioners consider important. Objectives: The objectives are to provide an overview of MCR research, analyze the practitioners' opinions on the impor

Alessandro Cimatti, Alberto Griggio, Gianluca Redondi

Interlocking logics are at the core of critical systems controlling the traffic within stations. In this paper, we consider a generic interlocking logic, which can be instantiated to control a wide class of stations. We tackle the problem of parameterized verification, i.e. prove that the logic satisfies the required properties for all the relevant stations.

W. H. Blades, B. W. Y. Redemann, N. Smith, D. Sur

Single-phase multi-principal element alloys (MPEAs) hold promise for improved mechanical properties as a result of multiple operative deformation modes. However, the use of many of these alloys in structural applications is limited as a consequence of their poor aqueous corrosion resistance. Here we introduce a new approach for significantly improving the pa

Heather Prince, Erminia Calabrese, Jo Dunkley

The current limit on the tensor-to-scalar ratio from the BICEP/Keck Collaboration (with r<0.036 at 95% confidence) puts pressure on early universe models, with less than 10% of the error on r attributed to uncertainty in Galactic foregrounds. We use the BICEP/Keck BK18 public multi-frequency likelihood to test some further assumptions made in the foreground

Mateo Galdeano, Leander Stecker

We construct solutions to the heterotic G$_2$ system on almost contact metric manifolds with reduced characteristic holonomy. We focus on $3$-$(\alpha,\delta)$-Sasaki manifolds and $(\alpha,\delta)$-Sasaki manifolds, the latter being a convenient reformulation of spin $\eta$-Einstein $\alpha$-Sasaki manifolds. Investigating a $1$-parameter family of G$_2$-co

Md Shahin Alam, Alexandr Kazakov, Mujeeb Ahmad, Rajibul Islam

We report measurements of the electrical resistivity ($\rho$) and thermoelectric power (S) in a thin film of strained single-crystalline $\alpha$-Sn grown by molecular beam epitaxy on an insulating substrate. The temperature (T) dependence of the resistivity of $\alpha$-Sn can be divided into two regions:below T* $\approx$ 135 K $\rho$(T) shows a metallic-li

Kadijatou Diallo, Jonathan Smith, Chinasa T. Okolo, Dorcas Nyamwaya

Artificial Intelligence (AI) requires new ways of evaluating national technology use and strategy for African nations. We conduct a survey of existing 'readiness' assessments both for general digital adoption and for AI policy in particular. We conclude that existing global readiness assessments do not fully capture African states' progress in AI readiness a

Joris Hermans, Rony Keppens

Flows are omnipresent and govern the dynamics of plasma. Solar tornadoes are a class of apparently rotating prominences, that might be formed by thermal instability. In spectroscopic studies on thermal instability background flow is commonly neglected. We here determine the effect of background flow on thermal instability in cylindrical magnetic field config

Joshua Z. Tan, Max Langenkamp, Anna Weichselbraun, Ann Brody

The governance of online communities has been a critical issue since the first USENET groups, and a number of serious constitutions -- declarations of goals, values, and rights -- have emerged since the mid-1990s. More recently, decentralized autonomous organizations (DAOs) have begun to publish their own constitutions, manifestos, and other governance docum

Jorge Castillo-Mateo, Alan E. Gelfand, Zeus Gracia-Tabuenca, Jesús Asín

Record-breaking temperature events are now very frequently in the news, viewed as evidence of climate change. With this as motivation, we undertake the first substantial spatial modeling investigation of temperature record-breaking across years for any given day within the year. We work with a dataset consisting of over sixty years (1960-2021) of daily maxim

Daniel Bissinger, Rolf Farnsteiner

Let $\mathbb{k}$ be an algebraically closed field. Connections between representations of the generalized Kronecker quivers $K_r$ and vector bundles on $\mathbb{P}^{r-1}$ have been known for quite some time. This article is concerned with a particular aspect of this correspondence, involving more generally Steiner bundles on Grassmannians $\mathrm{Gr}_d(\mat

Shi-Ju Kang, Bing Lyu, Qingwen Wu, Yong-Gang Zheng

Changing-look active galactic nuclei (AGNs) are a special class of AGNs that change their spectral type from type 1 to type 2 or vice versa. In recent years, a number of changing-look blazars (CLBs) were also reported, which transition between flat-spectrum radio quasars and BL Lacs. The physical properties of CLBs are still unclear. Using the $mclust$ R pac

Jacob S. Nelson, Andrew D. Baczewski

We compare several quantum phase estimation (QPE) protocols intended for early fault-tolerant quantum computers (EFTQCs) in the context of models of their implementations on a surface code architecture. We estimate the logical and physical resources required to use these protocols to calculate the ground state energy of molecular hydrogen in a minimal basis

Mitchell Cohen, James Richard Forbes

This paper presents a solution for the state estimation and control problems for a class of unconventional vertical takeoff and landing (VTOL) UAVs operating in forward-flight conditions. A tightly-coupled state estimation approach is used to estimate the aircraft navigation states, sensor biases, and the wind velocity. State estimation is done within a matr

Niels van der Laan, Mitchell Cohen, Jonathan Arsenault, James Richard Forbes

This paper presents an invariant Rauch-Tung- Striebel (IRTS) smoother applicable to systems with states that are an element of a matrix Lie group. In particular, the extended Rauch-Tung-Striebel (RTS) smoother is adapted to work within a matrix Lie group framework. The main advantage of the invariant RTS (IRTS) smoother is that the linearization of the proce

Junyao Li, John D. Silverman, Yue Shen, Marta Volonteri

JWST is revealing a new remarkable population of high-redshift ($z\gtrsim4$), low-luminosity Active Galactic Nuclei (AGNs) in deep surveys and detecting the host galaxy stellar light in the most luminous and massive quasars at $z\sim 6$ for the first time. Latest results claim supermassive black holes (SMBHs) in these systems to be significantly more massive

Ankit Aggarwal, Florian Ecker, Daniel Grumiller, Dmitri Vassilevich

Carroll black holes with an associated Carroll temperature were introduced recently. So far, it is unclear if they exhibit a Hawking-like effect. To solve this, we study scalar fields on Carroll black hole backgrounds. Inspired by anomaly methods, we derive a Hawking-like energy-momentum tensor compatible with the Carroll temperature and the Stefan-Boltzmann

Seigo Kikura, Rui Asaoka, Masato Koashi, Yuuki Tokunaga

We propose a scheme for generating a high-purity single photon on the basis of cavity quantum electrodynamics (QED). This scheme employs a four-level system including two excited states, two ground states, and two driving lasers; this structure allows the suppression of the re-excitation process due to the atomic decay, which is known to significantly degrad

Suyuchen Wang, Ivan Kobyzev, Peng Lu, Mehdi Rezagholizadeh

This paper addresses the challenge of train-short-test-long (TSTL) scenarios in Large Language Models (LLMs) equipped with Rotary Position Embedding (RoPE), where models pre-trained on shorter sequences face difficulty with out-of-distribution (OOD) token positions in longer sequences. We introduce Resonance RoPE, a novel approach designed to narrow the gene

Mariam Campbell, Sante Carloni, Peter K. S. Dunsby, Nolene F. Naidu

We present a covariant description of non-vacuum static spherically symmetric spacetimes in $f(R)$ gravity applying the (1+1+2) covariant formalism. The propagation equations are then used to derive a covariant and dimensionless form of the Tolman-Oppenheimer-Volkoff (TOV) equations. We then give a solution strategy to these equations and obtain some new exa

Arjun Mirani, Patrick Hayden

Efficiently learning an unknown Hamiltonian given access to its dynamics is a problem of interest for quantum metrology, many-body physics and machine learning. A fundamental question is whether learning can be performed at the Heisenberg limit, where the Hamiltonian evolution time scales inversely with the error, $\varepsilon$, in the reconstructed paramete

Kazuki Hayashi, Yusuke Sakai, Hidetaka Kamigaito, Katsuhiko Hayashi

Large-scale Vision-Language Models (LVLMs) output text from images and instructions, demonstrating capabilities in text generation and comprehension. However, it has not been clarified to what extent LVLMs possess the ability to understand the knowledge necessary for explaining images, the complex relationships between various pieces of knowledge, and how th

Md Tahmid Rahman Laskar, Elena Khasanova, Xue-Yong Fu, Cheng Chen

This work focuses on the task of query-based meeting summarization in which the summary of a context (meeting transcript) is generated in response to a specific query. When using Large Language Models (LLMs) for this task, usually a new call to the LLM inference endpoint/API is triggered for each new query, even if the context stays the same. However, repeat

Nathan Steinle, Davide Gerosa, Martin G. H. Krause

The precession of astrophysical jets produced by active-galactic nuclei is likely related to the dynamics of the accretion disks surrounding the central supermassive black holes (BHs) from which jets are launched. The two main mechanisms that can drive jet precession arise from Lense-Thirring precession and tidal torquing. These can explain direct and indire

Ana Ines Ennis, Juan Pablo Caso, Lilia Patricia Bassino

We present a wide-field study of the globular cluster systems (GCS) of the elliptical galaxy NGC 3640 and its companion NGC 3641, based on observations from Gemini Multi-Object Spectrograph/Gemini using the g'r'i' filters. NGC 3640 is a shell galaxy which presents a complex morphology, which previous studies have indicated as the sign of a recent `dry' merge

Marco Golla, Marco Marengon

For every $n \ge 3$, we construct 2-component links in $S^{n+1}$ that are a split by an integer homology $n$-sphere, but not by $S^n$. In the special case $n=3$, i.e. that of 2-links in $S^4$, we produce an infinite family of links $L_\ell$ and of integer homology spheres $Y_\ell$ such that the link $L_\ell$ is (topologically or smoothly) split by $Y_\ell$ a

Jonathan Cabrera Garcia, Charli M. Sakari, Ian U. Roederer, Donavon W. Evans

M15 is a globular cluster with a known spread in neutron-capture elements. This paper presents abundances of neutron-capture elements for 62 stars in M15. Spectra were obtained with the Michigan/Magellan Fiber System (M2FS) spectrograph, covering a wavelength range from ~4430-4630 A. Spectral lines from Fe I, Fe II, Sr I, Zr II, Ba II, La II, Ce II, Nd II, S

Serhii Kryhin, Subir Sachdev, Pavel A. Volkov

We show that nonlinear transport responses in strange metals are strong, larger by a factor of $E_F/T$ than in Fermi liquids. Within the two-dimensional Yukawa-Sachdev-Ye-Kitaev model of a Fermi surface with a spatially random coupling to a critical scalar, the third order conductivity is found to diverge as $1/T$ at low $T$, indicating the existence of a vo

Shiyu Zhang, Yang Su, Xuepeng Chen, Min Fang

We study the physical properties and 3D distribution of molecular clouds (MCs) toward the Cygnus region using the MWISP CO survey and Gaia DR3 data. Based on Gaussian decomposition and clustering for $\rm ^{13}CO$ lines, over 70% of the fluxes are recovered. With the identification result of $\rm ^{13}CO$ structures, two models are designed to measure the di

Daria Gangardt, Alessandro Alberto Trani, Clément Bonnerot, Davide Gerosa

Models of accretion discs surrounding active galactic nuclei (AGNs) find vast applications in high-energy astrophysics. The broad strategy is to parametrize some of the key disc properties such as gas density and temperature as a function of the radial coordinate from a given set of assumptions on the underlying physics. Two of the most popular approaches in

Charlie Nation, Valentina Notararigo, Hallmann Oskar Gestsson, Luca Sapienza

Identifying signatures of quantum coherent behaviour in photoactive systems that are maintained in stationary states away from thermal equilibrium is an open problem of wide interest in a variety of physical scenarios, including single photosynthetic complexes subjected to continuous incoherent illumination. Here we consider a prototype light-harvesting hete

Aidan P. Reddy, Nisarga Paul, Ahmed Abouelkomsan, Liang Fu

Motivated by the recent discovery of fractional quantum anomalous Hall states in moir\'e systems, we consider the possibility of realizing non-Abelian phases in topological minibands. We study a family of moir\'e systems, skyrmion Chern band models, which can be realized in two-dimensional semiconductor-magnet heterostructures and also capture the essence of

Jonah S. Peter, Raphael Holzinger, Stefan Ostermann, Susanne F. Yelin

Light-harvesting via the transport and trapping of optically-induced electronic excitations is of fundamental interest to the design of new energy efficient quantum technologies. Using a paradigmatic quantum optical model, we study the influence of coherence, entanglement, and cooperative dissipation on the transport and capture of excitation energy. In part

Marco Marengon, Clayton McDonald

We show that there exists a link with 2 components which is not smoothly slice in $\mathbb{CP}^2 \# \overline{\mathbb{CP}^2}$. By contrast, it is well-known that every knot (i.e., link with 1 component) is smoothly slice therein. Our proof uses classical topological and smooth obstructions, as well as constructive arguments to exploit the symmetries of the p

Manato Fujimoto, Daniel E. Parker, Junkai Dong, Eslam Khalaf

The rise of moir\'{e} materials has led to experimental realizations of integer and fractional Chern insulators in small or vanishing magnetic fields. At the same time, a set of minimal conditions sufficient to guarantee a Abelian fractional state in a flat band were identified, namely "ideal" or "vortexable" quantum geometry. Such vortexable bands share ess

David Benisty, Supriya Pan, Denitsa Staicova, Eleonora Di Valentino

We investigated a possible interaction between cold dark matter and dark energy, corresponding to a well-known interacting dark energy model discussed in the literature within the context of resolving the Hubble tension. We put constraints on it in a novel way, by creating new likelihoods with an analytical marginalization over the Hubble parameter $H_0$, th

Nathan W. Galliher, Thomas Procter, Nicholas M. Law, Hank Corbett

ArgusSpec is a prototype autonomous spectroscopic follow-up instrument designed to characterize flares detected by the Argus Pathfinder telescope array by taking short exposure (30 s) broadband spectra (370 - 750 nm) at low resolutions (R~150 at 500 nm). The instrument is built from consumer off-the-shelf astronomical equipment, assembled inside a shipping c

Julian May-Mann, Mark R. Hirsbrunner, Lei Gioia, Taylor L. Hughes

Three-dimensional Dirac semimetals can be driven into an insulating state by coupling to a charge density wave (CDW) order. Here, we consider the quantized crystalline responses of such charge-ordered Dirac semimetals, which we dub Dirac-CDW insulators, in which charge is bound to disclination defects of the lattice. Using analytic and numeric methods we sho

Xingrui Song, Flavio Salvati, Chandrashekhar Gaikwad, Nicole Yunger Halpern

The goal of quantum metrology is to improve measurements' sensitivities by harnessing quantum resources. Metrologists often aim to maximize the quantum Fisher information, which bounds the measurement setup's sensitivity. In studies of fundamental limits on metrology, a paradigmatic setup features a qubit (spin-half system) subject to an unknown rotation. On

Luca Griguolo, Rodolfo Panerai, Jacopo Papalini, Domenico Seminara

We compute the exact all-orders perturbative expansion for the partition function of 2d $\mathrm{SU}(2)$ Yang-Mills theory on closed surfaces around higher critical points. We demonstrate that the expansion can be derived from the lattice partition function for all genera using a distributional generalization of the Poisson summation formula. We then recompu

Ming Xie, Mohammad Hafezi, Sankar Das Sarma

Moir\'e superlattices based on two-dimensional transition metal dichalcogenides (TMDs) have emerged as a highly versatile and fruitful platform for exploring correlated topological electronic phases. One of the most remarkable examples is the recently discovered fractional quantum anomalous Hall effect (FQAHE) under zero magnetic field. Here we propose a min

Gary T. Horowitz, Maciej Kolanowski, Grant N. Remmen, Jorge E. Santos

It was recently shown that (near-)extremal Kerr black holes are sensitive probes of small higher-derivative corrections to general relativity. In particular, these corrections produce diverging tidal forces on the horizon in the extremal limit. We show that adding a black hole charge makes this effect qualitatively stronger. Higher-derivative corrections to

Christian Kragh Jespersen, Charles L. Steinhardt, Rachel S. Somerville, Christopher C. Lovell

The discovery of extremely luminous galaxies at ultra-high redshifts ($z\gtrsim 8$) has challenged galaxy formation models. Most analyses of this tension have not accounted for the variance due to field-to-field clustering, which causes the number counts of galaxies to vary greatly in excess of Poisson noise. This super-Poissonian variance is often referred

Muyang Li, Tianle Cai, Jiaxin Cao, Qinsheng Zhang

Diffusion models have achieved great success in synthesizing high-quality images. However, generating high-resolution images with diffusion models is still challenging due to the enormous computational costs, resulting in a prohibitive latency for interactive applications. In this paper, we propose DistriFusion to tackle this problem by leveraging parallelis

Jarosław Pawłowski, Pankaj Kumar, Kenji Watanabe, Takashi Taniguchi

Spin-valley properties in two-dimensional (2D) semiconducting transition metal dichalcogenides (TMDC) has attracted significant interest due to the possible applications in quantum computing. Spin-valley properties can be exploited in TMDC quantum dot (QD) with well-resolved energy levels. This requires smaller QDs, especially in material systems with heavy

Sangwoon Kim, Antonia Bronars, Parag Patre, Alberto Rodriguez

We introduce a novel approach that combines tactile estimation and control for in-hand object manipulation. By integrating measurements from robot kinematics and an image-based tactile sensor, our framework estimates and tracks object pose while simultaneously generating motion plans in a receding horizon fashion to control the pose of a grasped object. This

Tsai-Shien Chen, Aliaksandr Siarohin, Willi Menapace, Ekaterina Deyneka

The quality of the data and annotation upper-bounds the quality of a downstream model. While there exist large text corpora and image-text pairs, high-quality video-text data is much harder to collect. First of all, manual labeling is more time-consuming, as it requires an annotator to watch an entire video. Second, videos have a temporal dimension, consisti

Yang-Zhi Chou, Yuting Tan, Fengcheng Wu, Sankar Das Sarma

We study theoretically the magic-angle twisted bilayer graphene with proximity-induced Ising and Rashba spin-orbit couplings on the top layer. Topological flat bands (with three distinct phases) are generically realized by the spin-orbit couplings. Using a mean field analysis, we find that (partial) valley polarization prevails for a wide range of doping, su

Lingchen Yang, Gaspard Zoss, Prashanth Chandran, Markus Gross

Physically-based simulation is a powerful approach for 3D facial animation as the resulting deformations are governed by physical constraints, allowing to easily resolve self-collisions, respond to external forces and perform realistic anatomy edits. Today's methods are data-driven, where the actuations for finite elements are inferred from captured skin geo

Charlie T. Mpetha, Giuseppe Congedo, Andy Taylor, Martin A. Hendry

Gravitational waves from binary mergers at cosmological distances will experience weak lensing by large scale structure. This causes a (de-)magnification, $\mu$, of the wave amplitude, and a degenerate modification to the inferred luminosity distance $d_L$. To address this the uncertainty on $d_L$ is increased according to the dispersion of the magnification

Alex Gu, Wen-Ding Li, Naman Jain, Theo X. Olausson

While language models are increasingly more proficient at code generation, they still frequently generate incorrect programs. Many of these programs are obviously wrong, but others are more subtle and pass weaker correctness checks such as being able to compile. In this work, we focus on these counterfeit samples: programs sampled from a language model that

Weiyun Wang, Yiming Ren, Haowen Luo, Tiantong Li

We present the All-Seeing Project V2: a new model and dataset designed for understanding object relations in images. Specifically, we propose the All-Seeing Model V2 (ASMv2) that integrates the formulation of text generation, object localization, and relation comprehension into a relation conversation (ReC) task. Leveraging this unified task, our model excel

Penghao Zhao, Hailin Zhang, Qinhan Yu, Zhengren Wang

Advancements in model algorithms, the growth of foundational models, and access to high-quality datasets have propelled the evolution of Artificial Intelligence Generated Content (AIGC). Despite its notable successes, AIGC still faces hurdles such as updating knowledge, handling long-tail data, mitigating data leakage, and managing high training and inferenc

Cai Dieball, Aljaž Godec

We prove that the transport of any differentiable scalar observable in $d$-dimensional non-equilibrium systems is bounded from above by the total entropy production scaled by the amount the observation "stretches" microscopic coordinates. The result--a time-integrated generalized speed limit--reflects the thermodynamic cost of transport of observables, and p

Gaspare Galati, Gabriele Pavan

Both Noise Radar and Quantum Radar, with some alleged common features, exploit the randomness of the transmitted signal to enhance radar covertness and to reduce mutual interference. While Noise Radar has been prototypically developed and successfully tested in many environments by different organizations, the significant investments on Quantum Radar seem no

Ameya Prabhu, Vishaal Udandarao, Philip Torr, Matthias Bethge

Standardized benchmarks drive progress in machine learning. However, with repeated testing, the risk of overfitting grows as algorithms over-exploit benchmark idiosyncrasies. In our work, we seek to mitigate this challenge by compiling ever-expanding large-scale benchmarks called Lifelong Benchmarks. These benchmarks introduce a major challenge: the high cos

Gabriel Grand, Valerio Pepe, Jacob Andreas, Joshua B. Tenenbaum

Questions combine our mastery of language with our remarkable facility for reasoning about uncertainty. How do people navigate vast hypothesis spaces to pose informative questions given limited cognitive resources? We study these tradeoffs in a classic grounded question-asking task based on the board game Battleship. Our language-informed program sampling (L

Qi Chen, Xiaoxi Chen, Haorui Song, Zhiwei Xiong

Tumor synthesis enables the creation of artificial tumors in medical images, facilitating the training of AI models for tumor detection and segmentation. However, success in tumor synthesis hinges on creating visually realistic tumors that are generalizable across multiple organs and, furthermore, the resulting AI models being capable of detecting real tumor

Ilija Radosavovic, Bike Zhang, Baifeng Shi, Jathushan Rajasegaran

We cast real-world humanoid control as a next token prediction problem, akin to predicting the next word in language. Our model is a causal transformer trained via autoregressive prediction of sensorimotor trajectories. To account for the multi-modal nature of the data, we perform prediction in a modality-aligned way, and for each input token predict the nex

Andrew L. Miller, Nancy Aggarwal, Sébastien Clesse, Federico De Lillo

Gravitational waves from sub-solar mass inspiraling compact objects would provide almost smoking-gun evidence for primordial black holes (PBHs). We perform the first search for inspiraling planetary-mass compact objects in equal-mass and highly asymmetric mass-ratio binaries using data from the first half of the LIGO-Virgo-KAGRA third observing run. Though w

Kate Sanders, Nathaniel Weir, Benjamin Van Durme

It is challenging for models to understand complex, multimodal content such as television clips, and this is in part because video-language models often rely on single-modality reasoning and lack interpretability. To combat these issues we propose TV-TREES, the first multimodal entailment tree generator. TV-TREES serves as an approach to video understanding

Anna Julia Poser, Ronald Redmer

We are interested in the influence of cloudy atmospheres on the thermal radius evolution of warm exoplanets from an interior modelling perspective. By applying a physically motivated but simple parameterized cloud model, we obtain the atmospheric $P$-$T$ structure that is connected to the adiabatic interior at the self-consistently calculated radiative-conve

Chen Qian, Jie Zhang, Wei Yao, Dongrui Liu

Ensuring the trustworthiness of large language models (LLMs) is crucial. Most studies concentrate on fully pre-trained LLMs to better understand and improve LLMs' trustworthiness. In this paper, to reveal the untapped potential of pre-training, we pioneer the exploration of LLMs' trustworthiness during this period, focusing on five key dimensions: reliabilit

Zhang-Wei Hong, Idan Shenfeld, Tsun-Hsuan Wang, Yung-Sung Chuang

Large language models (LLMs) hold great potential for many natural language applications but risk generating incorrect or toxic content. To probe when an LLM generates unwanted content, the current paradigm is to recruit a \textit{red team} of human testers to design input prompts (i.e., test cases) that elicit undesirable responses from LLMs. However, relyi

Jenny Seidenschwarz, Aljoša Ošep, Francesco Ferroni, Simon Lucey

We tackle semi-supervised object detection based on motion cues. Recent results suggest that heuristic-based clustering methods in conjunction with object trackers can be used to pseudo-label instances of moving objects and use these as supervisory signals to train 3D object detectors in Lidar data without manual supervision. We re-think this approach and su

Pranav Shetty, Aishat Adeboye, Sonakshi Gupta, Chao Zhang

We present a simulation of various active learning strategies for the discovery of polymer solar cell donor/acceptor pairs using data extracted from the literature spanning $\sim$20 years by a natural language processing pipeline. While data-driven methods have been well established to discover novel materials faster than Edisonian trial-and-error approaches

Ionut Chifan, Adrian Ioana, Denis Osin, Bin Sun

For a class of wreath-like product groups with property (T), we describe explicitly all the embeddings between their von Neumann algebras. This allows us to provide a continuum of ICC groups with property (T) whose von Neumann algebras are pairwise non (stably) embeddable. We also give a construction of groups in this class only having inner injective homomo

Bálint Mucsányi, Michael Kirchhof, Seong Joon Oh

Uncertainty quantification, once a singular task, has evolved into a spectrum of tasks, including abstained prediction, out-of-distribution detection, and aleatoric uncertainty quantification. The latest goal is disentanglement: the construction of multiple estimators that are each tailored to one and only one source of uncertainty. This paper presents the f

Jonathan Oppenheim, Andrea Russo

We consider a proposed alternative to quantum gravity, in which the spacetime metric is treated as classical, even while matter fields remain quantum. Consistency of the theory necessarily requires that the metric evolve stochastically. Here, we show that this stochastic behaviour leads to a modification of general relativity at low accelerations. In the low

Jay Armas, Giorgos Batzios, Akash Jain

Higher-group symmetries are combinations of higher-form symmetries which appear in various field theories. In this paper, we explain how higher-group symmetries arise in 10d and 11d supergravities when the latter are coupled to brane sources. Motivated by this observation, we study field theories at zero and finite temperature invariant under a class of cont

Maxime Darrin, Philippe Formont, Jackie Chi Kit Cheung, Pablo Piantanida

Assessing the quality of summarizers poses significant challenges. In response, we propose a novel task-oriented evaluation approach that assesses summarizers based on their capacity to produce summaries that are useful for downstream tasks, while preserving task outcomes. We theoretically establish a direct relationship between the resulting error probabili

Leo Zhou, Joao Basso, Song Mei

The quantum approximate optimization algorithm (QAOA) is a general-purpose algorithm for combinatorial optimization. In this paper, we analyze the performance of the QAOA on a statistical estimation problem, namely, the spiked tensor model, which exhibits a statistical-computational gap classically. We prove that the weak recovery threshold of $1$-step QAOA

David Heurtel-Depeiges, Charles C. Margossian, Ruben Ohana, Bruno Régaldo-Saint Blancard

In recent years, denoising problems have become intertwined with the development of deep generative models. In particular, diffusion models are trained like denoisers, and the distribution they model coincide with denoising priors in the Bayesian picture. However, denoising through diffusion-based posterior sampling requires the noise level and covariance to

Jacob P. Ruf, Hilary M. L. Noad, Romain Grasset, Ludi Miao

In bulk Sr$_{2}$RuO$_{4}$, the strong sensitivity of the superconducting transition temperature $T_{\text{c}}$ to nonmagnetic impurities provides robust evidence for a superconducting order parameter that changes sign around the Fermi surface. In superconducting epitaxial thin-film Sr$_{2}$RuO$_{4}$, the relationship between $T_{\text{c}}$ and the residual r

Shiyuan Gao, Jin-Jian Zhou, Yao Luo, Marco Bernardi

Twisted bilayer graphene (tBLG) has emerged as an exciting platform for novel condensed matter physics. However, electron-phonon ($e$-ph) interactions in tBLG and their effects on electronic transport are not completely understood. Here we show first-principles calculations of $e$-ph interactions and resistivity in commensurate tBLG with large twist angles o

Evan Deddo, James T. Liu, Leopoldo A. Pando Zayas, Robert J. Saskowski

The superconformal index of half-BPS states in ${\cal N}=4$ supersymmetric Yang-Mills with gauge group $U(N)$ admits an expansion in terms of giant gravitons, ${\cal I}_N(q)={\cal I}_\infty(q) \sum\limits_{m=0}^\infty q^{mN}\hat{\mathcal I}_m(q)$, where $m$ is the number of giant gravitons. We derive this expansion directly in supergravity from the class of

Horst-Holger Boltz, Thomas Ihle

We highlight the importance of long-range correlations in active matter systems of self-propelling particles even in the absence of global order or steric interactions by demonstrating that long-range density fluctuations are reduced. We show this analytically for a one-dimensional lattice process employing a Poisson representation. Within this framework, we

Saurabh Srivastava, Annarose M B, Anto P, Shashank Menon

We propose a framework for robust evaluation of reasoning capabilities of language models, using functional variants of benchmarks. Models that solve a reasoning test should exhibit no difference in performance over the static version of a problem compared to a snapshot of the functional variant. We have rewritten the relevant fragment of the MATH benchmark

Frederik Kunstner, Robin Yadav, Alan Milligan, Mark Schmidt

Adam has been shown to outperform gradient descent on large language models by a larger margin than on other tasks, but it is unclear why. We show that a key factor in this performance gap is the heavy-tailed class imbalance found in language tasks. When trained with gradient descent, the loss of infrequent words decreases more slowly than the loss of freque

Yang Yu, Philip Goyal

In classical physics, a single measurement can in principle reveal the state of a system. However, quantum theory permits numerous non-equivalent measurements on a physical system, each providing only limited information about the state. This set of various measurements on a quantum system indicates a rich internal structure. We illuminate this structure for

Yungang Lu

Motivated by the study of certain combinatorial properties of $(q,2)$-Fock space, we compute explicitly a sequence driven by the Catalan's convolution and parameterized by $1+q$. As an application of this explicit form, we calculate the number of pair partitions involved in the determination of the vacuum--moments of the field operator defined on the $(q,2)$