February 2024 arXiv papers — page 3

Yifei Zhou, Andrea Zanette, Jiayi Pan, Sergey Levine

A broad use case of large language models (LLMs) is in goal-directed decision-making tasks (or "agent" tasks), where an LLM needs to not just generate completions for a given prompt, but rather make intelligent decisions over a multi-turn interaction to accomplish a task (e.g., when interacting with the web, using tools, or providing customer support). Reinf

Arkabrata Ghosh

The main aim of this article is to find all solutions of the Diophantine equation $x^2 + p^k=y^n$ where $p \equiv 1 \pmod 4$, $\frac{p-1}{3}$ is a perfect square and the class number of $\mathbb{Z}[\sqrt{-p}]$ is $2$. In this article, I used a method involving prime factorization and class numbers which is different from using congruent number argument which

Gili Golan

Recall that a group $G$ is said to be $\frac{3}{2}$-generated if every non-trivial element $g\in G$ has a co-generator in $G$ (i.e., an element which together with $g$ generates $G$). Thompson's group $V$ was proved to be $\frac{3}{2}$-generated by Donoven and Harper in 2019. It was the first example of an infinite finitely presented non-cyclic $\frac{3}{2}$

Quentin Raymondaud, Mickael Rouvier, Richard Dufour

Deep learning architectures have made significant progress in terms of performance in many research areas. The automatic speech recognition (ASR) field has thus benefited from these scientific and technological advances, particularly for acoustic modeling, now integrating deep neural network architectures. However, these performance gains have translated int

Siyu Chen, Heejune Sheen, Tianhao Wang, Zhuoran Yang

We study the dynamics of gradient flow for training a multi-head softmax attention model for in-context learning of multi-task linear regression. We establish the global convergence of gradient flow under suitable choices of initialization. In addition, we prove that an interesting "task allocation" phenomenon emerges during the gradient flow dynamics, where

Xiangzhi Eric Wang, Zackary P. T. Sin

3D Gaussian Splatting has made a marked impact on neural rendering by achieving impressive fidelity and performance. Despite this achievement, however, it is not readily applicable to developing interactive applications. Real-time applications like XR apps and games require functions such as animation, UV-mapping, and model editing simultaneously manipulated

K. Azizi, Y. Sarac, H. Sundu

The continuous advancement of experimental techniques and investigations has led to observations of various exotic states in particle physics. Each addition to this family of states not only raises expectations for future discoveries but also focuses attention on such potential new states. Building upon this motivation and inspired by recent observations of

Aynur Bulut, Hongjie Dong

We study the global well-posedness of the supercritical dissipative surface quasi-geostrophic (SQG) equation, a key model in geophysical fluid dynamics. While local well-posedness is known, achieving global well-posedness for large initial data remains open. Motivated by enhanced decay in radial solutions, we aim to establish global well-posedness for small

Matthew Macauley

Group theory involves the study of symmetry, and its inherent beauty gives it the potential to be one of the most accessible and enjoyable areas of mathematics, for students and non-mathematicians alike. Unfortunately, many students never get a glimpse into the more alluring parts of this field because "traditional" algebra classes are often taught in a dry

Xinyu Zhou, Raef Bassily

We initiate a systematic study of worst-group risk minimization under $(\epsilon, \delta)$-differential privacy (DP). The goal is to privately find a model that approximately minimizes the maximal risk across $p$ sub-populations (groups) with different distributions, where each group distribution is accessed via a sample oracle. We first present a new algori

Takuya Okawa, Alexander Y. Chen

It was recently proposed that the electric field oscillation as a result of self-consistent $e^{\pm}$ pair production may be the source of coherent radio emission from pulsars. Direct Particle-in-Cell (PIC) simulations of this process have shown that the screening of the parallel electric field by this pair cascade manifests as a limit cycle, as the parallel

Ryan Kaufman, Chenxu Liu, Katarina Cicak, Boris Mesits

High-fidelity quantum non-demolition qubit measurement is critical to error correction and rapid qubit feedback in large-scale quantum computing. High-fidelity readout requires passing a short and strong pulse through the qubit's readout resonator, which is then processed by a sufficiently high bandwidth, high saturation power, and quantum-limited amplifier.

Arkabrata Ghosh

In this article, we consider primes $p \equiv 5 \pmod 8$ and are able to prove that $p \equiv 5 \pmod {16}$ if $2p$ is a congruent number.

Shuaifeng Jiang, Ahmed Alkhateeb

Deep learning (DL) approaches have demonstrated high performance in compressing and reconstructing the channel state information (CSI) and reducing the CSI feedback overhead in massive MIMO systems. One key challenge, however, with the DL approaches is the demand for extensive training data. Collecting this real-world CSI data incurs significant overhead tha

Federico Garcia-Gaitan, Ali Kefayati, John Q. Xiao, Branislav K. Nikolic

The energy-momentum dispersion of magnons, as collective low-energy excitations of magnetic material, is computed from an effective quantum spin Hamiltonian but simplified via linearized Holstein-Primakoff transformations to describe noninteracting magnons. The dispersion produced by such linear spin wave theory (LSWT) is then plotted as ``sharp bands'' of i

Lauren Stumpf, Balasundaram Kadirvelu, Sigourney Waibel, A. Aldo Faisal

Dysarthria, a condition resulting from impaired control of the speech muscles due to neurological disorders, significantly impacts the communication and quality of life of patients. The condition's complexity, human scoring and varied presentations make its assessment and management challenging. This study presents a transformer-based framework for automatic

Jonathan Yang, Catherine Glossop, Arjun Bhorkar, Dhruv Shah

Recent years in robotics and imitation learning have shown remarkable progress in training large-scale foundation models by leveraging data across a multitude of embodiments. The success of such policies might lead us to wonder: just how diverse can the robots in the training set be while still facilitating positive transfer? In this work, we study this ques

Ryan Cavanagh, Jelena Trajkovic, Wenlu Zhang, I-Hung Khoo

Human gait has been commonly used for the diagnosis and evaluation of medical conditions and for monitoring the progress during treatment and rehabilitation. The use of wearable sensors that capture pressure or motion has yielded techniques that analyze the gait data to aid recovery, identify activity performed, or identify individuals. Deep learning, usuall

Zexiong Ma, Shengnan An, Bing Xie, Zeqi Lin

Large language models (LLMs) have achieved exceptional performance in code generation. However, the performance remains unsatisfactory in generating library-oriented code, especially for the libraries not present in the training data of LLMs. Previous work utilizes API recommendation technology to help LLMs use libraries: it retrieves APIs related to the use

Lucia Garozzo, Alfredo Guevara

We describe a method to extract an effective Lagrangian description for open bosonic strings, at zero transcendentality. The method relies on a particular formulation of its scattering amplitudes derived from color-kinematics duality. More precisely, starting from a $(DF)^2 + \text{YM}$ quantum field theory, we integrate out all the massive degrees of freedo

Chengyi Luo, Haoqing Zhang, Anjun Chu, Chitose Maruko

Quantum simulation using synthetic quantum systems offers unique opportunities to explore open questions in many-body physics and a path for the generation of useful entangled states. Nevertheless, so far many quantum simulators have been fundamentally limited in the models they can mimic. Here, we are able to realize an all-to-all interaction with arbitrary

Donald C. Boone

This computational research study analyzes the increase of the specific charge capacity that comes with the reduction of the anisotropic volume expansion during lithium ion insertion within silicon nanowires. This research paper is a continuation from previous work that studied the expansion rate and volume increase. It has been determined that when the lith

Soham De, Samuel L. Smith, Anushan Fernando, Aleksandar Botev

Recurrent neural networks (RNNs) have fast inference and scale efficiently on long sequences, but they are difficult to train and hard to scale. We propose Hawk, an RNN with gated linear recurrences, and Griffin, a hybrid model that mixes gated linear recurrences with local attention. Hawk exceeds the reported performance of Mamba on downstream tasks, while

Ivan Korneev, Anna Zakharova, Vladimir V. Semenov

Using the FitzHugh-Nagumo system in the excitable regime, we investigate the influence of the L{\'e}vy noise properties on the effect of coherence resonance. In particular, we demonstrate that the L{\'e}vy noise can be a constructive or destructive factor providing for enhancement or suppression of noise-induced coherence. We show that the positive or negati

Sukjin Han, Hiroaki Kaido, Lorenzo Magnolfi

Specifying the information structure in strategic environments is difficult for empirical researchers. We develop a test of information ordering that examines whether the true information structure is at least as informative as a proposed baseline. Using Bayes Correlated Equilibrium (BCE), we translate the ordering of information structures into testable mom

J. Chilufya, M. J. Hardcastle, J. C. S. Pierce, J. H. Croston

We investigate the nature of low-luminosity radio-loud active galactic nuclei (RLAGN) selected from the LOFAR Two-metre Sky Survey (LoTSS) first data release (DR1). Using optical, mid-infrared, and radio data, we have conservatively selected 55 radiative AGN candidates from DR1 within the redshift range $0.03<z<0.1$. We show using high-frequency {\it Karl G.

Tiezheng Zhang, Xiaoxi Chen, Chongyu Qu, Alan Yuille

Interactive segmentation, an integration of AI algorithms and human expertise, premises to improve the accuracy and efficiency of curating large-scale, detailed-annotated datasets in healthcare. Human experts revise the annotations predicted by AI, and in turn, AI improves its predictions by learning from these revised annotations. This interactive process c

Niccolò Cavagnero, Gabriele Rosi, Claudia Cuttano, Francesca Pistilli

Recent transformer-based architectures have shown impressive results in the field of image segmentation. Thanks to their flexibility, they obtain outstanding performance in multiple segmentation tasks, such as semantic and panoptic, under a single unified framework. To achieve such impressive performance, these architectures employ intensive operations and r

Lijia Ma, Xingchen Xu, Yong Tan

In the domain of digital information dissemination, search engines act as pivotal conduits linking information seekers with providers. The advent of chat-based search engines utilizing Large Language Models (LLMs) and Retrieval Augmented Generation (RAG), exemplified by Bing Chat, marks an evolutionary leap in the search ecosystem. They demonstrate metacogni

Greg d'Eon, Neil Newman, Kevin Leyton-Brown

Iterative combinatorial auctions are widely used in high stakes settings such as spectrum auctions. Such auctions can be hard to analyze, making it difficult for bidders to determine how to behave and for designers to optimize auction rules to ensure desirable outcomes such as high revenue or welfare. In this paper, we investigate whether multi-agent reinfor

Mark A. Mathis, Chris A. Marianetti

Computing the temperature and stress dependence of the full elastic constant tensor from first-principles in non-cubic materials remains a challenging problem. Here we circumvent the aforementioned challenge via the generalized quasiharmonic approximation in conjunction with the irreducible derivative approach for computing strain dependent phonons using fin

Gergő Thiering, Adam Gali

Optically accessible solid state defect spins serve as a primary platform for quantum information processing, where precise control of the electron spin and ancillary nuclear spins is essential for operation. Using the nitrogen-vacancy (NV) color center in diamond as an example, we employ a combined group theory and density functional theory study to demonst

Minoru Eto, Yu Hamada, Ryusuke Jinno, Muneto Nitta

We examine neutrino zeromode solutions on the electroweak $Z$-string and their effect on the stability of the string in the standard model and its extensions. We propose using topological invariants constructed from the momentum (and real) space topology of Green's functions, often used for investigating edge modes in condensed matter physics. We analyze the

Filipe B. Teixeira, Manuel Ricardo, André Coelho, Hélder P. Oliveira

Telecommunications and computer vision have evolved separately so far. Yet, with the shift to sub-terahertz (sub-THz) and terahertz (THz) radio communications, there is an opportunity to explore computer vision technologies together with radio communications, considering the dependency of both technologies on Line of Sight. The combination of radio sensing a

Ruth Britto, Claude Duhr, Holmfridur S. Hannesdottir, Sebastian Mizera

We review different notions of cuts appearing throughout the literature on scattering amplitudes. Despite similar names, such as unitarity cuts or generalized cuts, they often represent distinct computations and distinct physics. We consolidate this knowledge, summarize how cuts are used in various computational strategies, and explain their relations to oth

Hao Tian, Reza Zafarani

Network data has become widespread, larger, and more complex over the years. Traditional network data is dyadic, capturing the relations among pairs of entities. With the need to model interactions among more than two entities, significant research has focused on higher-order networks and ways to represent, analyze, and learn from them. There are two main di

Cai-Ping Jia, Yu Jia, Junliang Lu, Zhewen Mo

The conventional wisdom in dealing with electromagnetic transition between heavy quarkonia is the multipole expansion, when the emitted photon has a typical energy of order quarkonium binding energy. Nevertheless, in the case when the energy carried by the photon is of order typical heavy quark momentum, the multipole expansion doctrine is expected to break

Christian Carisch, Oded Zilberberg, Alessandro Romito

Monitored quantum systems evolve along stochastic trajectories correlated with the observer's knowledge of the system's state. Under such dynamics, certain quantum resources like entanglement may depend on the observer's state of knowledge. Here, we quantify the entanglement for a particle on a 1d quantum random walk under inefficient monitoring using a mixe

Mainak Ghosh, Michael E. Rose, Sebastian Erhardt, Erik Buunk

PaECTER is an open-source document-level encoder specific for patents. We fine-tune BERT for Patents with examiner-added citation information to generate numerical representations for patent documents. PaECTER performs better in similarity tasks than current state-of-the-art models used in the patent domain. More specifically, our model outperforms the paten

Zexin Li, Soroush Bateni, Cong Liu

Despite the promising future of autonomous robots, several key issues currently remain that can lead to compromised performance and safety. One such issue is latency, where we find that even the latest embedded platforms from NVIDIA fail to execute intelligence tasks (e.g., object detection) of autonomous vehicles in a real-time fashion. One remedy to this p

L. Quaglia, M. Abbrescia, G. Aielli, R. Aly

ALICE (A Large Ion Collider Experiment) studies the Quark-Gluon Plasma (QGP): a deconfined state of matter obtained in ultra-relativistic heavy-ion collisions. One of the probes for QGP study are quarkonia and open heavy flavour, of which ALICE exploits the muonic decay. A set of Resistive Plate Chambers (RPCs), placed in the forward rapidity region of the A

Jinfeng Xu, Zheyu Chen, Shuo Yang, Jinze Li

With the increasing multimedia information, multimodal recommendation has received extensive attention. It utilizes multimodal information to alleviate the data sparsity problem in recommendation systems, thus improving recommendation accuracy. However, the reliance on labeled data severely limits the performance of multimodal recommendation models. Recently

Nathan Godey, Éric de la Clergerie, Benoît Sagot

Language models have long been shown to embed geographical information in their hidden representations. This line of work has recently been revisited by extending this result to Large Language Models (LLMs). In this paper, we propose to fill the gap between well-established and recent literature by observing how geographical knowledge evolves when scaling la

Shresth Grover, Vibhav Vineet, Yogesh S Rawat

In this work we present a novel task of understanding unintentional human activities in videos. We formalize this problem as a reasoning task under zero-shot scenario, where given a video of an unintentional activity we want to know why it transitioned from intentional to unintentional. We first evaluate the effectiveness of current state-of-the-art Large Mu

Ali Beikmohammadi, Sarit Khirirat, Sindri Magnússon

Parallel stochastic gradient methods are gaining prominence in solving large-scale machine learning problems that involve data distributed across multiple nodes. However, obtaining unbiased stochastic gradients, which have been the focus of most theoretical research, is challenging in many distributed machine learning applications. The gradient estimations e

Junzhe Zhang, Huixuan Zhang, Xunjian Yin, Xiaojun Wan

News image captioning requires model to generate an informative caption rich in entities, with the news image and the associated news article. Current MLLMs still bear limitations in handling entity information in news image captioning tasks. Besides, generating high-quality news image captions requires a trade-off between sufficiency and conciseness of text

P. Arévalo, E. López-Navas, M. L. Martínez-Aldama, P. Lira

We report on the finding of a newborn AGN, i.e. current AGN activity in a galaxy previously classified as non-active, and characterize its evolution. Black hole ignition event candidates were selected from a parent sample of spectrally classified non-active galaxies (2.394.312 objects), that currently show optical flux variability indicative of a type I AGN,

Young-Jin Park, Donghyun Kim, Frédéric Odermatt, Juho Lee

Time series forecasting is one of the most essential and ubiquitous tasks in many business problems, including demand forecasting and logistics optimization. Traditional time series forecasting methods, however, have resulted in small models with limited expressive power because they have difficulty in scaling their model size up while maintaining high accur

Huakun Shen, Boyue Caroline Hu, Krzysztof Czarnecki, Lina Marsso

While Neural Networks (NNs) have surpassed human accuracy in image classification on ImageNet, they often lack robustness against image corruption, i.e., corruption robustness. Yet such robustness is seemingly effortless for human perception. In this paper, we propose visually-continuous corruption robustness (VCR) -- an extension of corruption robustness to

Yin Tang, Han Ma, Qicheng Tang, Yin-Chen He

Conformal symmetry, emerging at critical points, can be lost when renormalization group fixed points collide. Recently, it was proposed that after collisions, real fixed points transition into the complex plane, becoming complex fixed points described by complex conformal field theories (CFTs). Although this idea is compelling, directly demonstrating such co

Shahen Hacyan

In the 17th and 18th centuries, several natural philosophers studied the phenomenon of refraction and attempted to obtain the Snell law from various assumptions. Lacking experimental data, it was generally believed that light travels faster in a refracting medium than in air. In the present article, I review the contributions to the problem of light refracti

Vahidin Jeleskovic

This article presents an empirical investigation into the determinants of total revenue generated by counterfeit tokens on Uniswap. It offers a detailed overview of the counterfeit token fraud process, along with a systematic summary of characteristics associated with such fraudulent activities observed in Uniswap. The study primarily examines the relationsh

L. M. Janssen, G. Butseraen, J. Krause, A. Coissard

We investigate the effect of magnetic field on a photonic-crystal Josephson traveling-wave parametric amplifier (TWPA). We show that the observed change in photonic bandgap and plasma frequency of the TWPA can be modeled by considering the suppression of the critical current in the Josephson junctions (JJs) of the TWPA due to the Fraunhofer effect and closin

Fabio D'Ambrosio, Francesco Gozzini, Lavinia Heisenberg, Henri Inchauspé

We perform a comprehensive analysis of state-of-the-art waveform models, focusing on their predictions concerning kick velocity and inferred gravitational wave memory. In our investigation we assess the accuracy of waveform models using energy-momentum balance laws, which were derived in the framework of full, non-linear General Relativity. The numerical acc

Andreas Kofler, Felix Frederik Zimmermann, Kostas Papafitsoros

In the last years, the design of image reconstruction methods in the field of quantitative Magnetic Resonance Imaging (qMRI) has experienced a paradigm shift. Often, when dealing with (quantitative) MR image reconstruction problems, one is concerned with solving one or a couple of ill-posed inverse problems which require the use of advanced regularization me

The RPC ECOGas@GIF++ collaboration, :, L. Quaglia, M. Abbrescia

Resistive Plate Chambers (RPCs) are gaseous detectors widely used in high energy physics experiments, operating with a gas mixture primarily containing Tetrafluoroethane (C$_{2}$H$_{2}$F$_{4}$), commonly known as R-134a, which has a global warming potential (GWP) of 1430. To comply with European regulations and explore environmentally friendly alternatives,

Julia Zotova, Alexander Semenov, Rui Wang, Yu Zhou

We develop a compact four-port superconducting switch with a tunable operating frequency in the range of 4.8 GHz -- 7.3 GHz. Isolation between channel exceeds 20~dB over a bandwidth of several hundred megahertz, exceeding 40 dB at some frequencies. The footprint of the device is $80\times420~\mu$m. The tunability requires only a global flux bias without eith

Ibrahim Safa

Astrophysical neutrinos allow us to access energies and baselines that cannot be reached by human-made accelerators, offering unique probes of new physics phenomena. This thesis aims to address the challenges currently facing searches for Beyond Standard Model (BSM) physics in the high-energy universe using astrophysical neutrinos, particularly in the contex

Maicol A. Ochoa, Keyi Liu, Michał Zieliński, Garnett W. Bryant

We characterize the single-electron energies and the wavefunction structure of arrays with two, three, and four phosphorus atoms in silicon by implementing atomistic tight-binding calculations and analyzing wavefunction overlaps to identify the single-dopant states that hybridize to make the array states. The energy spectrum and wavefunction overlap variatio

Jack Lawless, Andrew L. Hazel, Anne Juel

The displacement of a viscous liquid by air in the narrow gap between two parallel plates - a Hele-Shaw channel - is an exemplar of complex pattern formation. Typically, bubbles or fingers of air propagate steadily at low values of the driving parameter. However, as the driving parameter increases, they can exhibit disordered pattern-forming dynamics. In thi

Patrik Penc, Cătălin Paşcu Moca, Örs Legeza, Tomaž Prosen

Information propagation in the one-dimensional infinite temperature Hubbard model with a dissipative particle sink at the end of a semi-infinite chain is studied. In the strongly interacting limit, the two-site mutual information and the operator entanglement entropy exhibit a rich structure with two propagating information fronts and superimposed interferen

Pranav Maheshwari, Ankur Raina

We present a fault-tolerant [[8, 1, 3]] non-CSS quantum error correcting code and study its logical error rates. We choose the unitary encoding procedure for stabilizer codes given by Gottesman and modify it to suit the setting of a class of non- CSS codes. Considering two types of noise models for this study, namely the depolarising noise and anisotropic no

Wenping Cui, Jemma M. Fendley, Sriram Srikant, Boris Shraiman

Bacteria and phages have been in an ongoing arms race for billions of years. To resist phages bacteria have evolved numerous defense systems, which nevertheless are still overcome by counter-defense mechanisms of specific phages. These defense/counter-defense systems are a major element of microbial genetic diversity and have been demonstrated to propagate b

Bingchen Li, Xin Li, Hanxin Zhu, Yeying Jin

Generative Adversarial Networks (GANs) have been widely used to recover vivid textures in image super-resolution (SR) tasks. In particular, one discriminator is utilized to enable the SR network to learn the distribution of real-world high-quality images in an adversarial training manner. However, the distribution learning is overly coarse-grained, which is

Peter H. C. Pang

This article considers the variational wave equation with viscosity and transport noise as a system of three coupled nonlinear stochastic partial differential equations. We prove pathwise global existence, uniqueness, and temporal continuity of solutions to this system in $L^2_x$. Martingale solutions are extracted from a two-level Galerkin approximation via

Ali Ebnenasir

This paper presents an algorithmic method that, given a positive integer $j$, generates the $j$-th convergence stair containing all natural numbers from where the Collatz conjecture holds by exactly $j$ applications of the Collatz function. To this end, we present a novel formulation of the Collatz conjecture as a concurrent program, and provide the general

Wenbo Shao, Jiahui Xu, Wenhao Yu, Jun Li

In the rapidly evolving field of autonomous driving, reliable prediction is pivotal for vehicular safety. However, trajectory predictions often deviate from actual paths, particularly in complex and challenging environments, leading to significant errors. To address this issue, our study introduces a novel method for Dynamic Occupancy Set (DOS) prediction, i

E. F. Talantsev, V. V. Chistyakov

For seven decades by A-15 superconductors we meant metallic $A_3B$ alloys (where A is a transition metal, and B is groups IIIB and IVB element) discovered by Hardy and Hulm (Phys. Rev. 89, 884 (1953)). Nb3Ge exhibited the highest superconducting transition temperature, $T_c = 23 K$, among these alloys. One of these alloys, $Nb_3Sn$, is primary material in mo

Ching-Yi Lai, Kao-Yueh Kuo

This article explores the application of coding techniques for fault-tolerant quantum computation and extends their usage to fault-tolerant quantum communication. We review repeater-based quantum networks, emphasizing the roles of coding theory and fault-tolerant quantum operations, particularly in the context of quantum teleportation. We highlight that faul

Alberto Bordin, Chun-Xiao Liu, Tom Dvir, Francesco Zatelli

Majorana zero modes (MZMs) are non-Abelian excitations predicted to emerge at the edges of topological superconductors. One proposal for realizing a topological superconductor in one dimension involves a chain of spinless fermions, coupled through $p$-wave superconducting pairing and electron hopping. This concept is also known as the Kitaev chain. A minimal

Kabir Bakhshaei, Umberto Emil Morelli, Giovanni Stabile, Gianluigi Rozza

A stochastic inverse heat transfer problem is formulated to infer the transient heat flux, treated as an unknown Neumann boundary condition. Therefore, an Ensemble-based Simultaneous Input and State Filtering as a Data Assimilation technique is utilized for simultaneous temperature distribution prediction and heat flux estimation. This approach is incorporat

Adeline Guéret, Wolf-Peter Schill, Carlos Gaete-Morales

Electrifying the car fleet is a major strategy for mitigating emissions in the transport sector. As electrification cannot solve all negative externalities associated with cars, reducing the size of the car fleet would be beneficial. Electric carsharing could allow to reconcile current car usage habits with a smaller fleet, but this may reduce the potential

Philipp Schoenegger, Indre Tuminauskaite, Peter S. Park, Philip E. Tetlock

Human forecasting accuracy in practice relies on the 'wisdom of the crowd' effect, in which predictions about future events are significantly improved by aggregating across a crowd of individual forecasters. Past work on the forecasting ability of large language models (LLMs) suggests that frontier LLMs, as individual forecasters, underperform compared to th

Rachel Woods-Robinson, Monica Morales-Masis, Geoffroy Hautier, Andrea Crovetto

A high-performance p-type transparent conductor (TC) does not yet exist, but could lead to advances in a wide range of optoelectronic applications and enable new architectures for, e.g., next-generation photovoltaic (PV) devices. High-throughput computational material screenings have been a promising approach to filter databases and identify new p-type TC ca

A. Gokus, J. Wilms, M. Kadler, D. Dorner

By studying the variability of blazars across the electromagnetic spectrum, it is possible to resolve the underlying processes responsible for rapid flux increases, so-called flares. We report on an extremely bright X-ray flare in the high-peaked BL Lacertae object Mrk 421 that occurred simultaneously with enhanced $\gamma$-ray activity detected at very high

Harideep Nair, Prabhu Vellaisamy, Tsung-Han Lin, Perry Wang

General Matrix Multiply (GEMM) units, consisting of multiply-accumulate (MAC) arrays, perform bulk of the computation in deep learning (DL). Recent work has proposed a novel MAC design, Bit-Pragmatic (PRA), capable of dynamically exploiting bit sparsity. This work presents OzMAC (Omit-zero-MAC), a modified re-implementation of PRA, but extends beyond earlier

Joshua Levett, Vassilios Vassilakis, Poonam Yadav

Heightened interest from nation states to perform content censorship make it evermore critical to identify the impact of censorship efforts on the Internet. We undertake a study of Internet architecture, capturing the state of Internet topology with greater completeness than existing state-of-the-art. We describe our methodology for this, including the tooli

Grigore Călugăreanu, Tsiu-Kwen Lee, Jerzy Matczuk

For a nonempty subset $X$ of a ring $R$, the ring $R$ is called $X$-semiprime if, given $a\in R$, $aXa=0$ implies $a=0$. This provides a proper class of semiprime rings. First, we clarify the relationship between idempotent semiprime and unit-semiprime rings. Secondly, given a Lie ideal $L$ of a ring $R$, we offer a criterion for $R$ to be $L$-semiprime. For

Theodoros Papanikolaou, Charalampos Tzerefos, Spyros Basilakos, Emmanuel N. Saridakis

Light primordial black holes (PBHs) with masses $M_\mathrm{PBH}<10^9\mathrm{g}$ can interestingly dominate the Universe's energy budget and give rise to early matter-dominated (eMD) eras before Big Bang Nucleosyntesis (BBN). During this eMD era, one is met with an abundant production of induced gravitational waves (GWs) serving as a portal to constrain the u

Stefan Johansson, Dennis Lönard, Isabel Cardoso Barbosa, Jonas Gutsche

The nitrogen-vacancy (NV) center in diamond is a prime candidate for quantum sensing technologies. Here, we present a fully integrated and mechanically robust fiber-based endoscopic sensor with a tip diameter of $1.25 \mathrm{mm}$. On its tip, a direct laser writing process is used to fixate a diamond containing NV centers above the fiber's core inside a pol

Jenish Maharjan, Anurag Garikipati, Navan Preet Singh, Leo Cyrus

LLMs have become increasingly capable at accomplishing a range of specialized-tasks and can be utilized to expand equitable access to medical knowledge. Most medical LLMs have involved extensive fine-tuning, leveraging specialized medical data and significant, thus costly, amounts of computational power. Many of the top performing LLMs are proprietary and th

Tobias Kramer, Daniel Waltner, Eric J. Heller, Dan R. Stinebring

The dynamic spectra of pulsars frequently exhibit diverse interference patterns, often associated with parabolic arcs in the Fourier-transformed (secondary) spectra. Our approach differs from previous ones in two ways: first, we extend beyond the traditional Fresnel-Kirchhoff method by using the Green's function of the Helmholtz equation, i.e.\ we consider s

Haoye Lu, Spencer Szabados, Yaoliang Yu

In recent years, diffusion models have become the leading approach for distribution learning. This paper focuses on structure-preserving diffusion models (SPDM), a specific subset of diffusion processes tailored for distributions with inherent structures, such as group symmetries. We complement existing sufficient conditions for constructing SPDMs by proving

Sofia Wood

We calculate the orbifold Euler characteristics of all the degree d fine universal compactified Jacobians (defined by Pagani and Tommasi) over the moduli space of stable curves of genus g with n marked points. We show that this orbifold Euler characteristic agrees with the Euler characteristic of the moduli space of stable, genus 0 curves with 2g+n markings

Andrea Bracco, Marco Padovani, Daniele Galli

Low-frequency radio observations of diffuse synchrotron radiation offer a unique vantage point for investigating the intricate relationship between gas and magnetic fields in the formation of structures within the Galaxy, spanning from the diffuse interstellar medium (ISM) to star-forming regions. Achieving this pivotal objective hinges on a comprehensive un

Akila Wickramasekara, Frank Breitinger, Mark Scanlon

The ever-increasing workload of digital forensic labs raises concerns about law enforcement's ability to conduct both cyber-related and non-cyber-related investigations promptly. Consequently, this article explores the potential and usefulness of integrating Large Language Models (LLMs) into digital forensic investigations to address challenges such as bias,

Kunal Relia

Consider a committee election consisting of (i) a set of candidates who are divided into arbitrary groups each of size ${at~most}$ two and a diversity constraint that stipulates the selection of ${at~least}$ one candidate from each group and (ii) a set of voters who are divided into arbitrary populations each approving ${at~most}$ two candidates and a repres

Lukas Gianinazzi, Alexandros Nikolaos Ziogas, Langwen Huang, Piotr Luczynski

We propose a novel approach to iterated sparse matrix dense matrix multiplication, a fundamental computational kernel in scientific computing and graph neural network training. In cases where matrix sizes exceed the memory of a single compute node, data transfer becomes a bottleneck. An approach based on dense matrix multiplication algorithms leads to subopt

Sagar Gautam, Manil T. Mohan

In this article, the following controlled convective Brinkman-Forchheimer extended Darcy (CBFeD) system is considered in a $d$-dimensional torus $\mathbb{T}^d$: \begin{align*} \frac{\partial\boldsymbol{y}}{\partial t}-\mu \Delta\boldsymbol{y}+(\boldsymbol{y}\cdot\nabla)\boldsymbol{y}+\alpha\boldsymbol{y}+\beta\vert \boldsymbol{y}\vert^{r-1}\boldsymbol{y}+\ga

Laurenţiu Bubuianu, Sergiu I. Vacaru, Elşen Veli Veliev, Assel Zhamysheva

We extend the anholonomic frame and connection deformation method, AFCDM, for constructing exact and parametric solutions in general relativity, GR, to geometric flow models and modified gravity theories, MGTs, with nontrivial torsion and nonmetricity fields. Following abstract geometric or variational methods, we can derive corresponding systems of nonmetri

Nikola Jovanović, Robin Staab, Martin Vechev

LLM watermarking has attracted attention as a promising way to detect AI-generated content, with some works suggesting that current schemes may already be fit for deployment. In this work we dispute this claim, identifying watermark stealing (WS) as a fundamental vulnerability of these schemes. We show that querying the API of the watermarked LLM to approxim

Niklas Schmid, Marta Fochesato, Tobias Sutter, John Lygeros

We establish a linear programming formulation for the solution of joint chance constrained optimal control problems over finite time horizons. The joint chance constraint may represent an invariance, reachability or reach-avoid specification that the trajectory must satisfy with a predefined probability. For finite state and action spaces, the solution is ex

David C. Williams, Neil Inala

We present a diffusion-based, generative model for conformer generation. Our model is focused on the reproduction of bonded structure and is constructed from the associated terms traditionally found in classical force fields to ensure a physically relevant representation. Techniques in deep learning are used to infer atom typing and geometric parameters from

Hao Wang, Ranadeep G. Dastidar, Dimitrios Giannios, Paul C. Duffell

Gamma-ray burst (GRB) afterglows are emissions from ultrarelativistic blast waves produced by a narrow jet interacting with surrounding matter. Since the first multimessenger observation of a neutron star merger, hydrodynamic modeling of GRB afterglows for structured jets with smoothly varying angular energy distributions has gained increased interest. While

Francesca Fassioli, Jerome Faist, Martin Eckstein, Daniele Fausti

Cavity electrodynamics is emerging as a promising tool to control chemical processes and quantum material properties. In this work we develop a formalism to describe the cavity mediated energy exchange between a material and its electromagnetic environment. We show that coplanar cavities can significantly affect the heat load on the sample if the cavity reso

Eric Perlmutter

We give an elementary proof of the following property of unitary, interacting four-dimensional $\mathcal{N}=2$ superconformal field theories: at large central charge $c$, there exist at least $\sqrt{c}$ single-trace, scalar superconformal primary operators with dimensions $\Delta \lesssim \sqrt{c}$ (suppressing multiplicative logarithmic corrections). This f

Nabil Ramlawi, Mohammad Tanver Hossain, Abhishek Shetty, Randy H. Ewoldt

We report the first-ever complete measurement of MAOStress material functions, which reveal that stress can be more fundamental than strain or strain rate for understanding linearity limits as a function of Deborah number. The material used is a canonical viscoelastic liquid with a single dominant relaxation time: Polyvinyl alcohol (PVA) polymer solution cro

Marcos Marino, Ramon Miravitllas

The Shifman-Vainshtein-Zakharov (SVZ) sum rules provide a method to obtain trans-series expansions in many quantum field theories, in which exponentially small corrections are calculated by combining the operator product expansion with the assumption of vacuum condensates. In some solvable models, exact expressions for trans-series can be obtained from non-p

Sonal Joshi, Thomas Thebaud, Jesús Villalba, Najim Dehak

Adversarial examples have proven to threaten speaker identification systems, and several countermeasures against them have been proposed. In this paper, we propose a method to detect the presence of adversarial examples, i.e., a binary classifier distinguishing between benign and adversarial examples. We build upon and extend previous work on attack type cla

Matteo Ruggeri, Victor C. B. Sousa, Carlo Scalo

A new combined sub-filter scale turbulence and shock-capturing model is developed for high-order finite volume numerics, extending previous work to unstructured solvers. Block Spectral Stresses (BSS) method relies on the spectra of the velocity gradients to estimate the subfilter scale stresses, heat-flux, and pressure-work based on the resolved field. The m