April 2024 arXiv papers — page 31

Michael Lingzhi Li, Kosuke Imai

A century ago, Neyman showed how to evaluate the efficacy of treatment using a randomized experiment under a minimal set of assumptions. This classical repeated sampling framework serves as a basis of routine experimental analyses conducted by today's scientists across disciplines. In this paper, we demonstrate that Neyman's methodology can also be used to e

Thomas Marrinan, Pakeeza Akram, Oli Gurmessa, Anthony Shishkin

In video game design, audio (both environmental background music and object sound effects) play a critical role. Sounds are typically pre-created assets designed for specific locations or objects in a game. However, user-generated content is becoming increasingly popular in modern games (e.g. building custom environments or crafting unique objects). Since th

Jeremy Harper

The proliferation of large language models (LLMs) and their integration into multi-agent systems has paved the way for sophisticated automation in various domains. This paper introduces AutoGenesisAgent, a multi-agent system that autonomously designs and deploys other multi-agent systems tailored for specific tasks. AutoGenesisAgent comprises several special

Oluwamayokun Oshinowo, Priscila Delgado, Meredith Fay, C. Alessandra Luna

Social media platforms can quickly disseminate STEM content to diverse audiences, but their operation can be mysterious. We used open-source machine learning methods such as clustering, regression, and sentiment analysis to analyze over 1000 videos and metrics thereof from 6 social media STEM creators. Our data provide insights into how audiences generate in

Gereon Koßmann, René Schwonnek

Finding the minimal relative entropy of two quantum states under semidefinite constraints is a pivotal problem located at the mathematical core of various applications in quantum information theory. An efficient method for providing provable upper and lower bounds is the central result of this work. Our primordial motivation stems from the essential task of

Md Manjurul Ahsan, Shivakumar Raman, Zahed Siddique

Additive manufacturing (AM), particularly 3D printing, has revolutionized the production of complex structures across various industries. However, ensuring quality and detecting defects in 3D-printed objects remain significant challenges. This study focuses on improving defect detection in 3D-printed cylinders by integrating novel pre-processing techniques s

Norton Olivér Szabó, Antal Igaz, Márton Rózsahegyi, Krisztián Sárneczky

Here we present a continuation of the work that was based on video observations of the Tau Her 2022 outburst from the McDonald Observatory, Texas, US. On the night of the maximum in 2022 we detected 626 individual Tau Her meteors, for which we estimated photovisual magnitudes and analysed their distribution on the sky to determine the radiant position in an

Xin Li, Yan Zhong

Non-malleable extractors are generalizations and strengthening of standard randomness extractors, that are resilient to adversarial tampering. Such extractors have wide applications in cryptography and explicit construction of extractors. In the well-studied models of two-source and affine non-malleable extractors, the previous best constructions only work f

Dmitriy Kunisky, Xifan Yu

We introduce a new conjecture on the computational hardness of detecting random lifts of graphs: we claim that there is no polynomial-time algorithm that can distinguish between a large random $d$-regular graph and a large random lift of a Ramanujan $d$-regular base graph (provided that the lift is corrupted by a small amount of extra noise), and likewise fo

Bartłomiej Bosek, Grzegorz Gutowski, Michał Lasoń, Jakub Przybyło

We consider a graph coloring algorithm that processes vertices in order taken uniformly at random and assigns colors to them using First-Fit strategy. We show that this algorithm uses, in expectation, at most $(1 + o(1))\cdot \ln n \,/\, \ln\ln n$ different colors to color any forest with $n$ vertices. We also construct a family of forests that shows that th

A. I. Medvedeva, M. V. Kholod

The paper describes how various techniques for applying artificial intelligence to the study of human eyes are utilized. The first dataset was collected using computerized perimetry to investigate the visualization of the human visual field and the diagnosis of glaucoma. A method to analyze the image using software tools is proposed. The second dataset was o

Xuan Jiang, Raja Sengupta, James Demmel, Samuel Williams

Traffic propagation simulation is crucial for urban planning, enabling congestion analysis, travel time estimation, and route optimization. Traditional micro-simulation frameworks are limited to main roads due to the complexity of urban mobility and large-scale data. We introduce the Large Scale Multi-GPU Parallel Computing based Regional Scale Traffic Simul

Eren Dogan, M. Egemen Uzun, Atahan Uz, H. Emre Seyrek

The developments that language models have provided in fulfilling almost all kinds of tasks have attracted the attention of not only researchers but also the society and have enabled them to become products. There are commercially successful language models available. However, users may prefer open-source language models due to cost, data privacy, or regulat

Hans Christiansen, Bence Takács, Steen H. Hansen

The accelerated expansion of the Universe is impressively well described by a cosmological constant. However, the observed value of the cosmological constant is much smaller than expected based on quantum field theories. Recent efforts to achieve consistency in these theories have proposed a relationship between Dark Energy and the most compact objects, such

Michael Neumann, Klaus Schmid, Lars Baumann

Context: Cultural aspects are of high importance as they guide people's behaviour and thus, influence how people apply methods and act in projects. In recent years, software engineering research emphasized the need to analyze the challenges of specific cultural characteristics. Investigating the influence of cultural characteristics is challenging due to the

Arno Botha, Tanja Verster, Roelinde Bester

A novel procedure is presented for finding the true but latent endpoints within the repayment histories of individual loans. The monthly observations beyond these true endpoints are false, largely due to operational failures that delay account closure, thereby corrupting some loans. Detecting these false observations is difficult at scale since each affected

Norton Olivér Szabó, Antal Igaz, László L. Kiss, Márton Rózsahegyi

As part of an intensive effort to observe the predicted 2022 Tau Herculids outburst, we recorded almost 800 individual meteor streaks on May 30th and 31st, 2022, using a high-sensitivity Sony~$\alpha$7 camera. The video recordings were obtained under perfect conditions at the McDonald Observatory, Texas, USA. The meteor sample is dominated by the predicted T

Timothy Bennett

We investigate the complexities of the McKean-Vlasov optimal control problem, exploring its various formulations such as the strong and weak formulations, as well as both Markovian and non-Markovian setups within financial markets. Furthermore, we examine scenarios where the law governing the control process impacts the dynamics of options. By conceptualizin

Dingding Dong, Anqi Li, Yufei Zhao

A system of linear equations $L$ is common over $\mathbb{F}_p$ if, as $n\to\infty$, any 2-coloring of $\mathbb{F}_p^n$ gives asymptotically at least as many monochromatic solutions to $L$ as a random 2-coloring. The notion of common linear systems is analogous to that of common graphs, i.e., graphs whose monochromatic density in 2-edge-coloring of cliques is

Ephim Golbraikh, Yuri M. Shtemler

Generated under hurricane conditions, a slip layer composed of foam, bubble emulsion, and spray determines the behavior of the surface drag with wind speed. This study enables us to estimate foam's contribution to this behavior. A logarithmic parametrization of surface drag is introduced, wherein the effective roughness length of the underlying surface is de

M. J. Taranchuk, R. J. Braun

One of the main roles of the lipid layer (LL) of the tear film (TF) is to help prevent evaporation of the aqueous layer (AL). The LL thickness, composition, and structure all contribute to its barrier function. It is believed that the lipid layer is primarily nonpolar with a layer of polar lipids at the LL/AL interface. There is evidence that the nonpolar re

Sean Thompson

Motivated by the problem of classifying quantum symmetries of non-semisimple, finite-dimensional associative algebras, we define a notion of connection between bounded quivers and build a bicategory of bounded quivers and quiver connections. We prove this bicategory is equivalent to a bicategory of basic algebras, bimodules, and intertwiners with some additi

Kristian Tyn Kai Chung, Rafael Flores-Calderón, Rafael C. Torres, Pedro Ribeiro

Motivated by recent work connecting Higgs phases to symmetry protected topological (SPT) phases, we investigate the interplay of gauge redundancy and global symmetry in lattice gauge theories with Higgs fields in the presence of a boundary. The core conceptual point is that a global symmetry associated to a Higgs field, which is pure-gauge in a closed system

Bradley P. Allen, Paul T. Groth

A backbone of knowledge graphs are their class membership relations, which assign entities to a given class. As part of the knowledge engineering process, we propose a new method for evaluating the quality of these relations by processing descriptions of a given entity and class using a zero-shot chain-of-thought classifier that uses a natural language inten

Amreen Bano, Dan T Major

Van der Waals (vdW) heterostructures have attracted intense interest worldwide as they offer several routes to design materials with novel features and wide-ranging applications. Unfortunately, at present, vdW heterostructures are restricted to a small number of stackable layers, due to the weak vdW forces holding adjacent layers together. In this work, we r

T. Liu, M. Smith, A. V. Andreev, B. Z. Spivak

In this article we study microwave absorption in superconductors in the presence of a vortex lattice. We show that in addition to the conventional absorption mechanism associated with the vortex core motion, there is another mechanism of microwave absorption, which is caused by the time-dependence of the quasiparticle density of states outside the vortex cor

Dibyendu Das, Soumyajit Dey

Advancement of chip technology will make future computer chips faster. Power consumption of such chips shall also decrease. But this speed gain shall not come free of cost, there is going to be a trade-off between speed and efficiency, i.e accuracy of the computation. In order to achieve this extra speed we will simply have to let our computers make more mis

Avraham Moriel, Edan Lerner, Eran Bouchbinder

It is now established that glasses feature low-frequency, nonphononic excitations, in addition to phonons that follow Debye's vibrational density of state (VDoS). Extensive computer studies demonstrated that these nonphononic, glassy excitations follow a universal non-Debye VDoS ${\cal D}_{\rm G}(\omega)\!\sim\!\omega^4$, at low frequencies $\omega$. Yet, du

Dana I. Casetti-Dinescu, Roberto Baena-Galle, Terrence M. Girard, Alejandro Cervantes-Rovira

We present an expanded and improved deep-learning (DL) methodology for determining centers of star images on HST/WFPC2 exposures. Previously, we demonstrated that our DL model can eliminate the pixel-phase bias otherwise present in these undersampled images; however that analysis was limited to the central portion of each detector. In the current work we int

Lin Xu, Yilin Zhao, Daquan Zhou, Zhijie Lin

Vision-language pre-training has significantly elevated performance across a wide range of image-language applications. Yet, the pre-training process for video-related tasks demands exceptionally large computational and data resources, which hinders the progress of video-language models. This paper investigates a straight-forward, highly efficient, and resou

Hao Zhang, Linshan Sun, Jack Hirschman, Mirali Seyed Shariatdoust

Four-wave mixing (FWM) in gas-filled hollow-core capillaries, a nonlinear optical process that mixes signal and pump photon frequencies to generate idler frequency photons, offers a method for precise spectral phase transfer from signal to idler at ultrashort timescales and extreme powers. However, this regime is challenged by competing linear and nonlinear

Manoel Aranda, Naelson Oliveira, Elvys Soares, Márcio Ribeiro

Test smells can pose difficulties during testing activities, such as poor maintainability, non-deterministic behavior, and incomplete verification. Existing research has extensively addressed test smells in automated software tests but little attention has been given to smells in natural language tests. While some research has identified and catalogued such

Abeynaya Gnanasekaran, Amit Surana

We develop a novel approach for efficiently applying variational quantum linear solver (VQLS) in context of structured sparse matrices. Such matrices frequently arise during numerical solution of partial differential equations which are ubiquitous in science and engineering. Conventionally, Pauli basis is used for linear combination of unitary (LCU) decompos

Dirk Van Essendelft, Hayl Almolyki, Wei Shi, Terry Jordan

The versatility and wide-ranging applicability of the Ising model, originally introduced to study phase transitions in magnetic materials, have made it a cornerstone in statistical physics and a valuable tool for evaluating the performance of emerging computer hardware. Here, we present a novel implementation of the two-dimensional Ising model on a Cerebras

Sangwon Seo, Vaibhav Unhelkar

When faced with accomplishing a task, human experts exhibit intentional behavior. Their unique intents shape their plans and decisions, resulting in experts demonstrating diverse behaviors to accomplish the same task. Due to the uncertainties encountered in the real world and their bounded rationality, experts sometimes adjust their intents, which in turn in

F. Kahraman Aliçavuş, G. Handler, S. Chowdhury, E. Niemczura

There are different classes of pulsating stars in the H-R diagram. While many of those classes are undisputed, some remain a mystery such as the objects historically called "Maia variables". Whereas the presence of such a class was suggested seven decades ago, no pulsational driving mechanism is known that could excite short-period oscillations in these late

Philip F. Hopkins

In galaxy formation simulations, it is increasingly common to represent supernovae (SNe) at finite resolution (when the Sedov-Taylor phase is unresolved) via hybrid energy-momentum coupling with some 'terminal momentum' $p_{\rm term}$ (depending weakly on ambient density and metallicity) that represents unresolved work from an energy-conserving phase. Numeri

Rayan Mazouz, Frederik Baymler Mathiesen, Luca Laurenti, Morteza Lahijanian

This paper presents a novel stochastic barrier function (SBF) framework for safety analysis of stochastic systems based on piecewise (PW) functions. We first outline a general formulation of PW-SBFs. Then, we focus on PW-Constant (PWC) SBFs and show how their simplicity yields computational advantages for general stochastic systems. Specifically, we prove th

Paige L. Reiter, Talia Y. Moore

How should zoomorphic, or bio-inspired, robots indicate to humans that interactions will be safe and fun? Here, a survey is used to measure how human willingness to interact with a simulated butterfly robot is affected by different flight patterns. Flapping frequency, flap to glide ratio, and flapping pattern were independently varied based on a literature r

Rebecca C. Levy, Alexander Tielens, Justin Spilker, Daniel P. Marrone

This paper presents an overview of the Milky Way and nearby galaxies science case for the \textit{Single Aperture Large Telescope for Universe Studies} (SALTUS) far-infrared NASA probe-class mission concept. SALTUS offers enormous gains in spatial resolution and spectral sensitivity over previous far-IR missions, thanks to its cold ($<$40~K) 14-m primary mir

Justin Spilker, Rebecca C. Levy, Daniel Marrone, Stacey Alberts

This paper presents an overview of the high-redshift extragalactic science case for the Single Aperture Large Telescope for Universe Studies (SALTUS) far-infrared NASA probe-class mission concept. Enabled by its 14m primary reflector, SALTUS offers enormous gains in spatial resolution and spectral sensitivity over previous far-IR missions. SALTUS would be a

Josef Küstner

In this article we generalize the $q$-difference operator due to Carlitz in order to derive explicit sum formulae for several extensions of Stirling numbers of the second kind, including complete homogeneous symmetric functions, complementary symmetric functions, $r$-Whitney numbers and elliptic analogues of rook, Stirling and Lah numbers. Furthermore, we ge

Giulio Neri, Stefano Liberati

This work introduces a novel prescription for the expression of the thermodynamic potentials associated with the couplings of a Lanczos-Lovelock theory. These potentials emerge in theories with multiple couplings, where the ratio between them provide intrinsic length scales that break scale invariance. Our prescription, derived from the covariant phase space

Ulrich Römer, Stefan Hartmann, Jendrik-Alexander Tröger, David Anton

In the framework of solid mechanics, the task of deriving material parameters from experimental data has recently re-emerged with the progress in full-field measurement capabilities and the renewed advances of machine learning. In this context, new methods such as the virtual fields method and physics-informed neural networks have been developed as alternati

Mark Mandelkern

The classical theory of plane projective geometry is examined constructively, using both synthetic and analytic methods. The topics include Desargues's Theorem, harmonic conjugates, projectivities, involutions, conics, Pascal's Theorem, poles and polars. The axioms used for the synthetic treatment are constructive versions of the traditional axioms. The anal

Chen Shao, Elias Giacoumidis, Shi Li, Jialei Li

A frequency-calibrated SCINet (FC-SCINet) equalizer is proposed for down-stream 100G PON with 28.7 dB path loss. At 5 km, FC-SCINet improves the BER by 88.87% compared to FFE and a 3-layer DNN with 10.57% lower complexity.

David P. Huenemoerder, Pragati Pradhan, Claude R. Canizares, Sean Gunderson

High-resolution X-ray spectra of $\pi\,$Aqr, a $\gamma\,$Cas-type star, obtained with the Chandra/HETG grating spectrometer, revealed emission lines of H-like ions of Mg, Si, S, and Fe, a strong, hard continuum, and a lack of He-like ions, indicating the presence of very hot thermal plasma. The X-ray light curve showed significant fluctuations, with coherent

Alkisti Vaitsi, Vivien Sleziona, Luis E. Parra López, Yannic Behovits

Spintronic terahertz emitters (STEs) are powerful sources of ultra-broadband single-cycle terahertz (THz) field transients. They work with any pump wavelength, and their polarity and polarization direction are easily adjustable. However, at high pump powers and high repetition rates, STE operation is hampered by a significant increase in the local temperatur

Martin Bourhis, O. R. H. Buxton

This study aims to evaluate the effect of freestream turbulence (FST) on wakes produced by discs with different porosity. The wakes are exposed to various freestream turbulence "flavours", where turbulence intensity and integral length scale are independently varied. The turbulent wakes are interrogated through hot-wire anemometry from 3 to 15 diameters down

Vasileios Dimitropoulos, Andreas D. Syrmakesis, Nikos Hatziargyriou

Power grids heavily rely on Automatic Generation Control (AGC) systems to maintain grid stability by balancing generation and demand. However, the increasing digitization and interconnection of power grid infrastructure expose AGC systems to new vulnerabilities, particularly from cyberattacks such as false data injection attacks (FDIAs). These attacks aim at

R. Citro, T. Giamarchi, E. Orignac

We use bosonization, retaining band curvature terms, to analyze the Hall response of interacting bosonic and fermionic two-leg ladders threaded by a flux. We derive an explicit expression of the Hall imbalance in a perturbative expansion in the band curvature, retaining fully the interactions. We show that the flux dependence of the Hall imbalance allows to

Samia Shafique, Shu Kong, Charless Fowlkes

Shoeprints are a common type of evidence found at crime scenes and are used regularly in forensic investigations. However, existing methods cannot effectively employ deep learning techniques to match noisy and occluded crime-scene shoeprints to a shoe database due to a lack of training data. Moreover, all existing methods match crime-scene shoeprints to clea

Sarmad N. Mohammed, Semra Gündüç

One of the prime problems of computer science and machine learning is to extract information efficiently from large-scale, heterogeneous data. Text data, with its syntax, semantics, and even hidden information content, possesses an exceptional place among the data types in concern. The processing of the text data requires embedding, a method of translating t

Arturo Rodriguez Fanlo, Ori Segel

We study type spaces and saturation for local positive logic.

Jeffrey Uhlmann, Simon Julier

One of the most common misconceptions made about the Kalman filter when applied to linear systems is that it requires an assumption that all error and noise processes are Gaussian. This misconception has frequently led to the Kalman filter being dismissed in favor of complicated and/or purely heuristic approaches that are supposedly "more general" in that th

Hongyu Ke, Wanxin Jin, Haoxin Wang

This paper presents a solution to address carbon emission mitigation for end-to-end edge computing systems, including the computing at battery-powered edge devices and servers, as well as the communications between them. We design and implement, CarbonCP, a context-adaptive, carbon-aware, and uncertainty-aware AI inference framework built upon conformal pred

Ruben Ciranni, Giorgio Mariani, Michele Mancusi, Emilian Postolache

We present COCOLA (Coherence-Oriented Contrastive Learning for Audio), a contrastive learning method for musical audio representations that captures the harmonic and rhythmic coherence between samples. Our method operates at the level of the stems composing music tracks and can input features obtained via Harmonic-Percussive Separation (HPS). COCOLA allows t

Dmitry Kerner, Rodrigo Mendes

Let X be a reduced complex-analytic germ of pure dimension n\ge2, with arbitrary singularities (not necessarily normal or complete intersection). Various homology cycles on Link_\ep[X] vanish at different speeds when \ep\to0. We give a condition ensuring fast vanishing loops on X. The condition is in terms of the discriminant and the covering data for "conve

Melissa Ailem, Katerina Marazopoulou, Charlotte Siska, James Bono

Benchmarks have emerged as the central approach for evaluating Large Language Models (LLMs). The research community often relies on a model's average performance across the test prompts of a benchmark to evaluate the model's performance. This is consistent with the assumption that the test prompts within a benchmark represent a random sample from a real-worl

Sukhwan Chung, Madison Smith, Andrew Jin, Luke Hogewood

Emergency services play a crucial role in safeguarding human life and property within society. In this paper, we propose a network-based methodology for calculating transportation access between emergency services and the broader community. Using New York City as a case study, this study identifies 'emergency service deserts' based on the National Fire Prote

Salvador Curiel, Gisela N. Ortiz-Leon, Amy J. Mioduszewski, Anthony B. Arenas-Martinez

LP~349$-$25 is a well studied close stellar binary system comprised of two late M dwarf stars, both stars close to the limit between star and brown dwarf. This system was previously identified as a source of GHz radio emission. We observed LP~349$-$25AB in 11 epochs in 2020$-$2022, detecting both components in this nearby binary system using the Very Long Ba

Yi Xu, Masami Ouchi, Hidenobu Yajima, Hajime Fukushima

We investigate the dynamics of GN-z11, a luminous galaxy at $z=10.60$, carefully analyzing the public deep integral field spectroscopy (IFS) data taken with JWST NIRSpec IFU. While the observations of the IFS data originally targeted a He II clump near GN-z11, we find that CIII]$\lambda\lambda$1907,1909 emission from ionized gas at GN-z11 is bright and spati

Amirreza Kachabi, Mitchel J. Colebank, Sofia Altieri Correa, Naomi C. Chesler

Microvascular disease is a contributor to persistent pulmonary hypertension in those with chronic thromboembolic pulmonary hypertension (CTEPH). The heterogenous nature of the micro and macrovascular defects motivates the use of personalized computational models, which can predict flow dynamics within multiple generations of the arterial tree and into the mi

Sanket Chirame, Fiona J. Burnell, Sarang Gopalakrishnan, Abhinav Prem

We present a family of local quantum channels whose steady-states exhibit stable mixed-state symmetry-protected topological (SPT) order. Motivated by recent experimental progress on "erasure conversion" techniques that allow one to identify ($\textit{herald}$) decoherence processes, we consider open systems with biased erasure noise, which leads to strongly

Cliff B. Abbott, Dmytro A. Bozhko

Magnonic systems have been a major area of research interest due to their potential benefits in speed and lower power consumption compared to traditional computing. One particular area that they may be of advantage is as Physical Reservoir Computers in machine learning models. In this work, we build on an established design for using an Auto-Oscillation Ring

Martin Huber, Eva-Maria Oeß

This paper introduces an overidentification test of two alternative assumptions to identify the average treatment effect on the treated in a two-period panel data setting: unconfoundedness and common trends. Under the unconfoundedness assumption, treatment assignment and post-treatment outcomes are independent, conditional on control variables and pre-treatm

Hannah Varner, Tal Cohen

Accuracy in the measurement of mechanical properties is essential for precision engineering and for the interrogation of composition-property relationships. Conventional methods of mechanical testing, such as uniaxial tension, compression, and nanoindentation, provide highly repeatable and reliable results for stiff materials, for which they were originally

Nicolas Dupuis

We study the superfluid--Bose-glass transition in a one-dimensional lattice boson model with power-law decaying hopping amplitude $t_{i-j}\sim 1/|i-j|^\alpha$, using bosonization and the nonperturbative functional renormalization group (FRG). When $\alpha$ is smaller than a critical value $\alpha_c<3$, the U(1) symmetry is spontaneously broken, which leads t

Juri Opitz

Classification systems are evaluated in a countless number of papers. However, we find that evaluation practice is often nebulous. Frequently, metrics are selected without arguments, and blurry terminology invites misconceptions. For instance, many works use so-called 'macro' metrics to rank systems (e.g., 'macro F1') but do not clearly specify what they wou

Yunfei Ge, Ya-Ting Yang, Quanyan Zhu

The pervasive integration of Artificial Intelligence (AI) has introduced complex challenges in the responsibility and accountability in the event of incidents involving AI-enabled systems. The interconnectivity of these systems, ethical concerns of AI-induced incidents, coupled with uncertainties in AI technology and the absence of corresponding regulations,

Natalie S. Frank

We propose a new notion of uniqueness for the adversarial Bayes classifier in the setting of binary classification. Analyzing this concept produces a simple procedure for computing all adversarial Bayes classifiers for a well-motivated family of one dimensional data distributions. This characterization is then leveraged to show that as the perturbation radiu

Matteo Paoluzzi, Andrea Puglisi, Luca Angelani

We analyze the entropy production in run-and-tumble models. After presenting the general formalism in the framework of the Fokker-Planck equations in one space dimension, we derive some known exact results in simple physical situations (free run-and-tumble particles and harmonic confinement). We then extend the calculation to the case of anisotropic motion (

Harit Vishwakarma, Heguang Lin, Ramya Korlakai Vinayak

Robustness to out-of-distribution (OOD) samples is crucial for safely deploying machine learning models in the open world. Recent works have focused on designing scoring functions to quantify OOD uncertainty. Setting appropriate thresholds for these scoring functions for OOD detection is challenging as OOD samples are often unavailable up front. Typically, t

Remi Delaunay, Yipeng Hu, Tom Vercauteren

Shear wave elastography involves applying a non-invasive acoustic radiation force to the tissue and imaging the induced deformation to infer its mechanical properties. This work investigates the use of convolutional neural networks to improve displacement estimation accuracy in shear wave imaging. Our training approach is completely unsupervised, which allow

Yiang Lu, Bin Li, Wei Chen, Junyan Yan

Recently, fiber optic sensors such as fiber Bragg gratings (FBGs) have been widely investigated for shape reconstruction and force estimation of flexible surgical robots. However, most existing approaches need precise model parameters of FBGs inside the fiber and their alignments with the flexible robots for accurate sensing results. Another challenge lies i

Mihails Birjukovs, Klaas Bente, Damien Faivre, Guntars Kitenbergs

Magnetotactic bacteria (MTB) are of significant fundamental and practical interest, especially for applications such as drug delivery and general-purpose object manipulators and payload carriers. While magnetic and other modes of control for individual MTB have been demonstrated, formation, motion and control of MTB swarms are much less studied and understoo

Yarone M. Tokayer, Isaque Dutra, Priyamvada Natarajan, Guillaume Mahler

Strong gravitational lensing offers a powerful probe of the detailed distribution of matter in lenses, while magnifying and bringing faint background sources into view. Observed strong lensing by massive galaxy clusters, which are often in complex dynamical states, has also been used to map their dark matter substructures on smaller scales. Deep high resolut

Enrique Rozas Garcia, Alfred Weddig Karlsson, Johannes Hofmann

In reaction-diffusion models of annihilation reactions in low dimensions, single-particle dynamics provides a bottleneck for reactions, leading to an anomalously slow approach to the empty state. Here, we construct a reaction model with a reciprocal bottleneck on particle dynamics where single-particle motion conserves the center of mass. We show that such a

Mattia Emma, Tiago Fernandes de Nobrega, Gregory Ashton

The expansion and upgrade of the global network of ground-based gravitational wave detectors promises to improve our capacity to infer the sky-localization of transient sources, enabling more effective multi-messenger follow-ups. At the same time, the increase in the signal-to-noise ratio of detected events allows for more precise estimates of the source par

A. V. Glushkov, A. V. Saburov, L. T. Ksenofontov, K. G. Lebedev

An analysis of calibrations of extensive air showers with zenith angles $\theta \le 50^{\circ}$ and energies $E_{\text{SD}} \ge 10^{18.5}$ eV was carried out in experiments at the Yakutsk array and Telescope Array. The values of $E_{\text{SD}}$ were determined from particle densities measured with ground-based scintillation detectors at a distance $r = 800$

Yi Ding, Yong Li, Hao Sun, Rui Liu

Effectively learning the temporal dynamics in electroencephalogram (EEG) signals is challenging yet essential for decoding brain activities using brain-computer interfaces (BCIs). Although Transformers are popular for their long-term sequential learning ability in the BCI field, most methods combining Transformers with convolutional neural networks (CNNs) fa

Ben Limpanukorn, Jiyuan Wang, Hong Jin Kang, Eric Zitong Zhou

Compiler technologies in deep learning and domain-specific hardware acceleration are increasingly adopting extensible compiler frameworks such as Multi-Level Intermediate Representation (MLIR) to facilitate more efficient development. With MLIR, compiler developers can easily define their own custom IRs in the form of MLIR dialects. However, the diversity an

Avik Banerjee, Pratik Roy

Motivated by the existence of complex spectrum in $T\bar T$-deformed CFTs, in this paper we revisit the broadly studied topic of (holographic) entanglement entropy in the deformed theory to investigate its complex behaviour. As a concrete example, we show that in case of a 1+1 dimensional holographic CFT at finite temperature $\beta^{-1}$ and chemical potent

A. L. Cherchiglia, A. G. Dias, J. Leite, C. C. Nishi

We investigate how the solution to the strong CP problem and the explanation for the observed fermion mass hierarchies can be intrinsically related. Specifically, we explore the Nelson-Barr mechanism and identify its "seesaw limit", where light quark masses are suppressed by large CP-violating terms. Upon adding three (two) vector-like quarks that mix with t

Mehmet Kerem Turkcan, Sanjeev Narasimhan, Chengbo Zang, Gyung Hyun Je

We introduce Constellation, a dataset of 13K images suitable for research on detection of objects in dense urban streetscapes observed from high-elevation cameras, collected for a variety of temporal conditions. The dataset addresses the need for curated data to explore problems in small object detection exemplified by the limited pixel footprint of pedestri

Alexander F. Jercher, José Diogo Simão, Sebastian Steinhaus

We study the semi-classical limit of the recently proposed coherent spin foam model for (2+1) Lorentzian quantum gravity. Specifically, we analyze the gluing equations derived from the stationary phase approximation of the vertex amplitude. Typically these exhibit two solutions yielding a cosine of the Regge action. However, by inspection of the algebraic eq

Danish Khan, Maximilian L. Ach, O. Anatole von Lilienfeld

Atomic basis sets are widely employed within quantum mechanics based simulations of matter. We introduce a machine learning model that adapts the basis set to the local chemical environment of each atom, prior to the start of self consistent field (SCF) calculations. In particular, as a proof of principle and because of their historic popularity, we have stu

Sam Hadden

We describe a method for calculating action-angle variables in axisymmetric galactic potentials using Birkhoff normalization, a technique from Hamiltonian perturbation theory. An advantageous feature of this method is that it yields explicit series expressions for both the forward and inverse transformations between the action-angle variables and position-ve

Kevin N. Ortiz Ceballos, Yvette Cendes, Edo Berger, Peter K. G. Williams

We present results from a search for radio emission in 77 stellar systems hosting 140 exoplanets, predominantly within 17.5 pc using the Very Large Array (VLA) at $4-8$ GHz. This is the largest and most sensitive search to date for radio emission in exoplanetary systems in the GHz frequency range. We obtained new observations of 58 systems, and analyzed arch

Danny Horta, Ricardo P. Schiavon

Stellar halos of galaxies retain crucial clues to their mass assembly history. It is in these galactic components that the remains of cannibalised galactic building blocks are deposited. For the case of the Milky Way, the opportunity to analyse the stellar halo's structure on a star-by-star basis in a multi-faceted approach provides a basis from which to inf

I. E. López, G. Yang, G. Mountrichas, M. Brusa

The spectral energy distribution (SED) of low-luminosity active galactic nuclei (LLAGN) presents challenges due to their faint emissions and the complexity of their accretion processes. This study introduces a new CIGALE module tailored for LLAGN, combining the empirical $L_X$-$L_{12\mu m}$ relationship with physical models like advection-dominated accretion

Feng Liu, A. Daria Dumitriu-I., Alessandro Principi

We calculate the energy current flowing in the bulk of a (2+1)-dimensional system of massive Dirac fermions and along a (1+1)-dimensional domain wall generated by flipping the sign of the particle mass. We show that, at low temperatures and in the long-wavelenghth limit, the system does not support a bulk thermal Hall current proportional to the temperature

Luca Razzoli, Matteo Carrega, Fabio Cavaliere, Giuliano Benenti

Fluctuations affect the functionality of nanodevices. Thermodynamic uncertainty relations (TURs), derived within the framework of stochastic thermodynamics, show that a minimal amount of dissipation is required to obtain a given relative energy current dispersion, that is, current precision has a thermodynamic cost. It is therefore of great interest to explo

Emily Z. Zhang, Ciarán Hickey, Yong Baek Kim

Inelastic neutron scattering (INS) has traditionally been one of the primary methods for investigating quantum magnets, particularly in identifying a continuum of excitations as a hallmark of spin fractionalization in quantum spin liquids (QSLs). However, INS faces severe limitations due to its inability to distinguish between such QSL signatures and similar

Tomáš Blažek, Julian Heeck, Jan Heisig, Peter Maták

Leptogenesis typically requires the introduction of heavy particles whose out-of-equilibrium decays are essential for generating a matter-antimatter asymmetry, according to one of Sakharov's conditions. We demonstrate that in Dirac leptogenesis, scatterings between the light degrees of freedom -- Standard Model particles plus Dirac neutrinos - are sufficient

Hans Peter Nilles, Saul Ramos-Sanchez

Discrete flavor symmetries provide a promising approach to understand the flavor sector of the standard model of particle physics. Top-down (TD) explanations from string theory reveal two different types of such flavor symmetries: traditional and modular flavor symmetries that combine to the eclectic flavor group. There have been many bottom-up (BU) construc

Marcos A. G. Garcia, Mathias Pierre

After cosmic inflation, coherent oscillations of the inflaton field about a monomial potential $V(\phi)\sim \phi^k$ result in an expansion phase characterized by a stiff equation-of-state $w\simeq(k-2)/(k+2)$. Sourced by the oscillating inflaton condensate, parametric (self)resonant effects can induce the exponential growth of inhomogeneities eventually back

Bowen Fu, Anish Ghoshal, Stephen F. King, Moinul Hossain Rahat

The spontaneous breaking of a $U(1)$ symmetry via an intermediate discrete symmetry may yield a hybrid topological defect of \emph{domain walls bounded by cosmic strings}. The decay of this defect network leads to a unique gravitational wave signal spanning many orders in observable frequencies, that can be distinguished from signals generated by other sourc

Davide Gerosa, Malvina Bellotti

Accurate modeling of selection effects is a key ingredient to the success of gravitational-wave astronomy. The detection probability plays a crucial role in both statistical population studies, where it enters the hierarchical Bayesian likelihood, and astrophysical modeling, where it is used to convert predictions from population-synthesis codes into observa

Henrique Rubira, Fabian Schmidt

The renormalization group equations for large-scale structure (RG-LSS) describe how the bias and stochastic (noise) parameters -- both of matter and biased tracers such as galaxies -- evolve as a function of the cutoff $\Lambda$ of the effective field theory. In previous work, we derived the RG-LSS equations for the bias parameters using the Wilson-Polchinsk