April 2024 arXiv papers — page 126

Edgar Mendoza, Samuel F. M. Costa, Miguel Carvajal, Sérgio Pilling

Among the silicon bearing species discovered in the interstellar medium, SiS and SiO stand out as key tracers due to their distinct chemistry and abundances in interstellar and circumstellar environments. Our objective is to enhance the network of Si- and S-bearing chemical reactions for a gas-grain model in molecular clouds, encompassing both low and high m

Jaemin Kang, Hoeseok Yang, Hyungshin Kim

Deep learning has been successfully applied to object detection from remotely sensed images. Images are typically processed on the ground rather than on-board due to the computation power of the ground system. Such offloaded processing causes delays in acquiring target mission information, which hinders its application to real-time use cases. For on-device o

Takanobu Amano, Miki Masuda, Mitsuo Oka, Naritoshi Kitamura

We statistically investigate high-frequency whistler waves (with frequencies higher than $\sim 10$ % of the local elect ron cyclotron frequency) at Earth's bow shock using Magnetospheric Multi-Scale (MMS) spacecraft observations. We focus specifically on the wave power within the shock transition layer, where we expect electron acceleration via stochastic sh

Mark Armstrong, Chi-Lan Yang, Kinga Skiers, Mengzhen Lim

The limited nonverbal cues and spatially distributed nature of remote communication make it challenging for unacquainted members to be expressive during social interactions over video conferencing. Though it enables seeing others' facial expressions, the visual feedback can instead lead to unexpected self-focus, resulting in users missing cues for others to

Asmaa Eldesoukey, Olga Movilla Miangolarra, Tryphon T. Georgiou

The purpose of the present work is to expand substantially the type of control and estimation problems that can be addressed following the paradigm of Schr\"odinger bridges, by incorporating termination (killing) of stochastic flows. Specifically, in the context of estimation, we seek the most likely evolution realizing measured spatio-temporal marginals of

Yoshinori Gongyo, Shigeharu Takayama

We give a twisted version of the Kawamata semi-positivity theorem by the $\mathbb{Q}$-line bundle with a vanishing Lelong number at every point. Moreover, we apply the result to the finite generation problem for canonical rings of Birkar's generalized pairs.

Amir Mardan, Martin Blouin, Gabriel Fabien-Ouellet, Bernard-Giroux

First-break picking is an essential step in seismic data processing. First arrivals should be picked by an expert. This is a time-consuming procedure and subjective to a certain degree, leading to different results for different operators. In this study, we used a U-Net architecture with residual blocks to perform automatic first-break picking based on deep

Zhuoqun Xue, Xiaojian Zhang, David O. Prevatt, Jennifer Bridge

Accurately assessing building damage is critical for disaster response and recovery. However, many existing models for detecting building damage have poor prediction accuracy due to their limited capabilities of identifying detailed, comprehensive structural and/or non-structural damage from the street-view image. Additionally, these models mainly rely on th

Kacper Nowak, Sergey Danilov, Vasco Müller, Caili Liu

Scale analysis based on coarse-graining has been proposed recently as an alternative to Fourier analysis. It is now broadly used to analyze energy spectra and energy transfers in eddy-resolving ocean simulations. However, for data from unstructured-mesh models it requires interpolation to a regular grid. We present a high-performance Python implementation of

Max Rubinstein, Maria Cuellar, Daniel Malinsky

We propose a set of causal estimands that we call the "mediated probabilities of causation." These estimands quantify the probabilities that an observed negative outcome was induced via a mediating pathway versus a direct pathway in a stylized setting involving a binary exposure or intervention, a single binary mediator, and a binary outcome. We outline a se

Van Pham, Scott Cunningham

This study investigates whether OpenAI's ChatGPT-3.5 and ChatGPT-4 can forecast future events. To evaluate the accuracy of the predictions, we take advantage of the fact that the training data at the time of our experiments (mid 2023) stopped at September 2021, and ask about events that happened in 2022. We employed two prompting strategies: direct predictio

Vikas Dwivedi

Given the destructive impacts of tropical cyclones, it is critical to have a reliable system for cyclone intensity detection. Various techniques are available for this purpose, each with differing levels of accuracy. In this paper, we introduce two ensemble-based models based on AlexNet architecture to estimate tropical cyclone intensity using visible satell

Tucker J. Ervin, Blake Jackson

To better understand mutation-invariant and hereditary properties of quivers (and more generally skew-symmetrizable matrices), we have constructed a topology on the set of all mutation classes of quivers which we call the mutation class topology. This topology is the Alexandrov topology induced by the poset structure on the set of mutation classes of quivers

Fanqi Meng, Zhenling Tang, Petr Ourednik, Jahnabi Hazarika

Resonant tunneling diode (RTD) oscillators possess the highest oscillation frequency among all electronic THz emitters. However, the emitted power from RTDs remains limited. Here, we propose linear RTD-oscillator arrays capable of supporting coherent emission from both odd and even coupled modes. Both modes exhibit constructive interference in the far field,

Lisa Johnston, David Kenepp, Evuilynn Nguyen, Digjoy Paul

We introduce the immersion poset $(\mathcal{P}(n), \leqslant_I)$ on partitions, defined by $\lambda \leqslant_I \mu$ if and only if $s_\mu(x_1, \ldots, x_N) - s_\lambda(x_1, \ldots, x_N)$ is monomial-positive. Relations in the immersion poset determine when irreducible polynomial representations of $GL_N(\mathbb{C})$ form an immersion pair, as defined by Pra

Ioana Dutan, Kenichi Nishikawa, Athina Meli, Oleh Kobzar

The properties of relativistic jets, their interaction with the environment, and their emission of radiation can be self-consistently studied by using collisionless particle-in-cell (PIC) numerical simulations. Using three-dimensional (3D), relativistic PIC simulations, we present the first self-consistently calculated synthetic spectra of head-on and off-ax

Jinhee Lee, Inseok Song

Accurate age estimation of nearby young moving groups (NYMGs) is important as they serve as crucial testbeds in various fields of astrophysics, including formation and evolution of stars, planets, as well as loose stellar associations. The $\beta$-Pictoris moving group (BPMG), being one of the closest and youngest NYMGs, has been extensively investigated, an

Pedrom Zadeh, Brian A. Camley

The motility of eukaryotic cells is strongly influenced by their environment, with confined cells often developing qualitatively different motility patterns from those migrating on simple two-dimensional substrates. Recent experiments, coupled with data-driven methods to extract a cell's equation of motion, showed that cancerous MDA-MB-231 cells persistently

Yasi Zhang, Peiyu Yu, Ying Nian Wu

Text-to-image diffusion models have shown great success in generating high-quality text-guided images. Yet, these models may still fail to semantically align generated images with the provided text prompts, leading to problems like incorrect attribute binding and/or catastrophic object neglect. Given the pervasive object-oriented structure underlying text pr

Ryan Jackim, Jeremy Heyl, Harvey Richer

We present a catalogue of white dwarf candidates constructed from the GALEX and Gaia EDR3 catalogues. The catalogue contains 332,111 candidate binary white dwarf systems and 111,996 candidate single white dwarfs. Where available, the catalogue is augmented with photometry from Pan-STARRS DR1, SDSS DR12 and classifications from StarHorse. We fit photometric d

Ruijia Cheng, Titus Barik, Alan Leung, Fred Hohman

Programmers frequently engage with machine learning tutorials in computational notebooks and have been adopting code generation technologies based on large language models (LLMs). However, they encounter difficulties in understanding and working with code produced by LLMs. To mitigate these challenges, we introduce a novel workflow into computational noteboo

Brian Montambault, Gabriel Appleby, Jen Rogers, Camelia D. Brumar

Dimensionality reduction techniques are widely used for visualizing high-dimensional data. However, support for interpreting patterns of dimension reduction results in the context of the original data space is often insufficient. Consequently, users may struggle to extract insights from the projections. In this paper, we introduce DimBridge, a visual analyti

Omkar Sudhir Patil, Duc M. Le, Emily J. Griffis, Warren E. Dixon

Deep Neural Network (DNN)-based controllers have emerged as a tool to compensate for unstructured uncertainties in nonlinear dynamical systems. A recent breakthrough in the adaptive control literature provides a Lyapunov-based approach to derive weight adaptation laws for each layer of a fully-connected feedforward DNN-based adaptive controller. However, der

Petr Blaschke, Miroslav Engliš, El-Hassan Youssfi

We~describe a Dirichlet-type space of $H$-harmonic functions, i.e. functions annihilated by the hyperbolic Laplacian on~the unit ball of the real $n$-space, as~the analytic continuation (in~the spirit of Rossi and Vergne) of the corresponding weighted Bergman spaces. Characterizations in terms of derivatives are given, and the associated semi-inner product i

Shahin Atakishiyev, Mohammad Salameh, Randy Goebel

Autonomous vehicles often make complex decisions via machine learning-based predictive models applied to collected sensor data. While this combination of methods provides a foundation for real-time actions, self-driving behavior primarily remains opaque to end users. In this sense, explainability of real-time decisions is a crucial and natural requirement fo

Chenyang An, Zhibo Chen, Qihao Ye, Emily First

Recent advances in Automated Theorem Proving have shown the effectiveness of leveraging a (large) language model that generates tactics (i.e. proof steps) to search through proof states. The current model, while trained solely on successful proof paths, faces a discrepancy at the inference stage, as it must sample and try various tactics at each proof state

Utkarsh Pratiush, Kevin M. Roccapriore, Yongtao Liu, Gerd Duscher

Exploring the structural, chemical, and physical properties of matter on the nano- and atomic scales has become possible with the recent advances in aberration-corrected electron energy-loss spectroscopy (EELS) in scanning transmission electron microscopy (STEM). However, the current paradigm of STEM-EELS relies on the classical rectangular grid sampling, in

Michael Jaber, Shachar Lovett, Anthony Ostuni

Motivated by applications to matrix multiplication algorithms, Pratt asked (ITCS'24) how large a subset of $[n] \times [n]$ could be without containing a skew-corner: three points $(x,y), (x,y+h),(x+h,y')$ with $h \ne 0$. We prove any skew corner-free set has size at most $\exp(-\Omega(\log^{1/12} n))\cdot n^2$, nearly matching the best known lower bound of

Stephen P. Humphries

We study commutative Schur rings over the symplectic groups Sp$(n,2)$ containing the class $\mathcal C$ of symplectic transvections. We find the possible partitions of $\mathcal C$ determined by the Schur ring. We show how this restricts the possibilities for multiplicity one subgroups of Sp$(n,2)$.

Dirk van Dam, Matthew Kenworthy

Context. Time-series photometry has given astronomers the tools to study time-dependent astrophysical phenomena, from stellar activity to fast radio bursts and exoplanet transits. Transit events in particular are focused primarily on planetary transits, and eclipsing binaries with eclipse geometries that are parameterised with a few variables, while more com

Rajarshi Haldar, Julia Hockenmaier

Large language models (LLMs) such as Llama 2 perform very well on tasks that involve both natural language and source code, particularly code summarization and code generation. We show that for the task of code summarization, the performance of these models on individual examples often depends on the amount of (subword) token overlap between the code and the

Sahil Garg, Anderson Schneider, Anant Raj, Kashif Rasul

Building on the remarkable achievements in generative sampling of natural images, we propose an innovative challenge, potentially overly ambitious, which involves generating samples of entire multivariate time series that resemble images. However, the statistical challenge lies in the small sample size, sometimes consisting of a few hundred subjects. This is

Masoud Monajatipoor, Jiaxin Yang, Joel Stremmel, Melika Emami

Large Language Models (LLMs) demonstrate remarkable versatility in various NLP tasks but encounter distinct challenges in biomedical due to the complexities of language and data scarcity. This paper investigates LLMs application in the biomedical domain by exploring strategies to enhance their performance for the NER task. Our study reveals the importance of

Miquel Saucedo, Sergey Tikhonov

It is well known that if a function $f$ satisfies $$\|f(x) e^{\pi \alpha |x|^2}\|_p + \| \widehat{f}(\xi) e^{\pi \alpha |\xi|^2} \|_q<\infty \qquad\qquad\qquad(*)$$ with $\alpha=1$ and $1\le p,q<\infty$, then $f\equiv 0.$ We prove that if $f$ satisfies $(*)$ with some $0<\alpha<1$ and $1\le p,q\leq \infty$, then $$ |f(y)|\le C (1+|y|)^{\frac{d}{p}} e^{- \pi

Pranav Kulkarni, Adway Kanhere, Harshita Kukreja, Vivian Zhang

Generative Adversarial Network (GAN)-based synthesis of fat suppressed (FS) MRIs from non-FS proton density sequences has the potential to accelerate acquisition of knee MRIs. However, GANs trained on single-site data have poor generalizability to external data. We show that federated learning can improve multi-center generalizability of GANs for synthesizin

Andrew Douglas, Joe Repka

Let $\mathfrak{s}$ $\ltimes$ $\mathfrak{r}$ be a Levi decomposable Lie algebra, with Levi factor $\mathfrak{s}$, and radical $\mathfrak{r}$. A module $V$ of $\mathfrak{s}$ $\ltimes$ $\mathfrak{r}$ is cyclic indecomposable if it is indecomposable and the quotient module $V /\mathfrak{r}\cdot V$ is a simple $\mathfrak{s}$-module. A Levi decomposable subalgebra

Lukas Johannes Splitthoff, Miguel Carrera Belo, Guliuxin Jin, Yu Li

Metamaterials engineered to host topological states of matter in controllable quantum systems hold promise for the advancement of quantum simulations and quantum computing technologies. In this context, the Su-Schrieffer-Heeger (SSH) model has gained prominence due to its simplicity and practical applications. Here, we present the implementation of a gate-tu

Manuel González-Navarrete, Rodrigo Lambert, Victor Hugo Vázquez Guevara

We present a complete characterization of the asymptotic behaviour of a correlated Bernoulli sequence { which depends on the parameter $\theta \in [0,1]$. A martingale theory based approach will allow} us to prove versions of the law of large numbers, quadratic strong law, law of iterated logarithm, almost sure central limit theorem and functional central li

Matthew L. Freeman, P. T. Madathil, L. N. Pfeiffer, K. W. Baldwin

At low Landau level filling factors ($\nu$), Wigner solid phases of two-dimensional electron systems in GaAs are pinned by disorder, and exhibit a pinning mode, whose frequency is a measure of the disorder that pins the Wigner solid. Despite numerous studies spanning the last three decades, the origin of the disorder that causes the pinning and determines th

Anna Kamińska, Hyung-Joon Tag

In this article, we study a number of properties of the K\"othe duals $\mathcal{M}_{\varphi,w}$ of Orlicz-Lorentz spaces. An explicit description of the order-continuous subspace of $\mathcal{M}_{\varphi,w}$ is provided. Moreover, the separability of these spaces is characterized by the growth condition $\Delta_2$. Consequently, the K\"othe dual space $\math

Karolina Wamsler, Louise C. Head, Tyler N. Shendruk

Liquid crystalline media mediate interactions between suspended particles and confining geometries, which not only has potential to guide patterning and bottom-up colloidal assembly, but can also control colloidal migration in microfluidic devices. However, simulating such dynamics is challenging because nemato-elasticity, diffusivity and hydrodynamic intera

Vahideh Moghtadaiee, Mina Alishahi, Milad Rabiei

The advent of location-based services has led to the widespread adoption of indoor localization systems, which enable location tracking of individuals within enclosed spaces such as buildings. While these systems provide numerous benefits such as improved security and personalized services, they also raise concerns regarding privacy violations. As such, ther

Samuel Pérez-Ayala, Aaron J. Tyrrell

We derive a sharp upper bound for the first eigenvalue $\lambda_{1,p}$ of the $p$-Laplacian on asymptotically hyperbolic manifolds for $1<p<\infty$. We then prove that a particular class of conformally compact submanifolds within asymptotically hyperbolic manifolds are themselves asymptotically hyperbolic. As a corollary, we show that for any minimal conform

Ruhan Yang, Krithik Ranjan, Ellen Yi-Luen Do

This paper introduces a new method of paper circuit fabrication that overcomes design barriers and increases flexibility in circuit design. Conventional circuit boards rely on thin traces, which limits the complexity and accuracy when applied to paper circuits. To address this issue, we propose a method that uses large conductive zones in paper circuits and

R. H. Álvarez-Gutiérrez, A. M. Stutz, N. Sandoval-Garrido, F. Louvet

The ALMA-IMF Large Program provides multi-tracer observations of 15 Galactic massive protoclusters at matched sensitivity and spatial resolution. We focus on the dense gas kinematics of the G353.41 protocluster traced by N$_2$H$^+$ (1$-$0), with an spatial resolution $\sim$0.02 pc. G353.41, at a distance of $\sim$2 kpc, has a mass of $\sim$2500 M$_{\odot}$ w

Michael Xieyang Liu, Frederick Liu, Alexander J. Fiannaca, Terry Koo

Large language models can produce creative and diverse responses. However, to integrate them into current developer workflows, it is essential to constrain their outputs to follow specific formats or standards. In this work, we surveyed 51 experienced industry professionals to understand the range of scenarios and motivations driving the need for output cons

Shreyas Chaudhari, Srinivasa Pranav, José M. F. Moura

Directly parameterizing and learning gradients of functions has widespread significance, with specific applications in inverse problems, generative modeling, and optimal transport. This paper introduces gradient networks (GradNets): novel neural network architectures that parameterize gradients of various function classes. GradNets exhibit specialized archit

Ruhan Yang, Ellen Yi-Luen Do

This paper explores the implementation of embedded magnets to enhance paper-based interactions. The integration of magnets in paper-based interactions simplifies the fabrication process, making it more accessible for building soft robotics systems. We discuss various interaction patterns achievable through this approach and highlight their potential applicat

Karol Kozioł, I. Agustín Aucar, Konstantin Gaul, Robert Berger

Results of relativistic calculations of nuclear magnetic resonance shielding tensors ($\sigma$) for the thallium monocation (Tl$^+$), thallium hydride (TlH) and thallium halides (TlF, TlCl, TlBr, TlI, and TlAt) are presented as obtained within a four-component polarization propagator formalism and a two-component linear response approach within the zeroth-or

Marcel Nonnenmacher, Maneesh Sahani

The von Mises-Fisher distribution as an exponential family can be expressed in terms of either its natural or its mean parameters. Unfortunately, however, the normalization function for the distribution in terms of its mean parameters is not available in closed form, limiting the practicality of the mean parametrization and complicating maximum-likelihood es

Francesco Di Filippo

Non-singular horizonless ultracompact objects provide a simple resolution to the black holes singularity problem. It has been shown that, if these objects are compact enough to exhibit the presence of the light-ring required to mimic the phenomenology of general relativity black holes, they must have at least one additional light-ring. The stability of the i

Daniel Platnick, Sourena Khanzadeh, Alireza Sadeghian, Richard Anthony Valenzano

Microplastic particle ingestion or inhalation by humans is a problem of growing concern. Unfortunately, current research methods that use machine learning to understand their potential harms are obstructed by a lack of available data. Deep learning techniques in particular are challenged by such domains where only small or imbalanced data sets are available.

William J. Cramer, A. G. Noble, G. Rudnick, A. Pigarelli

The changes in colors across a galaxy are intimately connected to the galaxy's formation, growth, quenching history, and dust content. A particularly important epoch in the growth of galaxies is near $z \sim 2$ often referred to as `cosmic noon', where galaxies on average reach the peak of their star formation. We study a population of 125 cluster galaxies a

Nima Shahbazi, Mahdi Erfanian, Abolfazl Asudeh, Fatemeh Nargesian

Entity matching is one the earliest tasks that occur in the big data pipeline and is alarmingly exposed to unintentional biases that affect the quality of data. Identifying and mitigating the biases that exist in the data or are introduced by the matcher at this stage can contribute to promoting fairness in downstream tasks. This demonstration showcases Fair

Michael Hodel

This work presents code to procedurally generate examples for the ARC training tasks. For each of the 400 tasks, an example generator following the transformation logic of the original examples was created. In effect, the assumed underlying distribution of examples for any given task was reverse engineered by implementing a means to sample from it. An attemp

A. Krzyzewska, A. Dyrdal

The linear and nonlinear Hall effects in 2D systems are considered theoretically within the isotropic k-cubed Rashba model. We show that the presence of an out-of-plane external magnetic field or net magnetization is a necessary condition to induce a nonzero Berry curvature in the system, whereas an in-plane magnetic field tunes the Berry curvature leading t

Suleyman Ozdel, Yao Rong, Berat Mert Albaba, Yen-Ling Kuo

Eye-tracking applications that utilize the human gaze in video understanding tasks have become increasingly important. To effectively automate the process of video analysis based on eye-tracking data, it is important to accurately replicate human gaze behavior. However, this task presents significant challenges due to the inherent complexity and ambiguity of

Ian Charlesworth, Rolando de Santiago, Ben Hayes, David Jekel

Graph independence (also known as $\epsilon$-independence or $\lambda$-independence) is a mixture of classical independence and free independence corresponding to graph products or groups and operator algebras. Using conjugation by certain random permutation matrices, we construct random matrix models for graph independence with amalgamation over the diagona

Nicolas T. Kurtovic, Paola Pinilla

The composition and distribution of the gas in a protoplanetary disk plays a key role in shaping the outcome of the planet formation process. Observationally, the recovery of information such as the emission height and brightness temperature from interferometric data is often limited by the imaging processes. To overcome the limitations of image-reconstructi

Mariza Dima, Damon Daylamani-Zad, Vangelis Lympouridis

In this paper we introduce two world-first Mixed Reality (MR) experiences that fuse smart AR glasses and live theatre and take place in a heritage site with the purpose to reveal the site's hidden and difficult histories about slavery. We term these unique general audience experiences Mixed Reality Heritage Performances (MRHP). Along with the development of

Suleyman Ozdel, Yao Rong, Berat Mert Albaba, Yen-Ling Kuo

Humans utilize their gaze to concentrate on essential information while perceiving and interpreting intentions in videos. Incorporating human gaze into computational algorithms can significantly enhance model performance in video understanding tasks. In this work, we address a challenging and innovative task in video understanding: predicting the actions of

Nima Noii, Mehran Ghasabeh, Peter Wriggers

Electro-active materials are classified as electrostrictive and piezoelectric materials. They deform under the action of an external electric field. Piezoelectric material, as a special class of active materials, can produce an internal electric field when subjected to mechanical stress or strain. In return, there is the converse piezoelectric response, whic

Amir Fathalizadeh, Vahideh Moghtadaiee, Mina Alishahi

The pervasive integration of Indoor Positioning Systems (IPS) arises from the limitations of Global Navigation Satellite Systems (GNSS) in indoor environments, leading to the widespread adoption of Location-Based Services (LBS) in places such as shopping malls, airports, hospitals, museums, corporate campuses, and smart buildings. Specifically, indoor locati

Andrej Kruzliak, Jiri Hartvich, Shubhan P. Patni, Lukas Rustler

This work presents a framework for automatically extracting physical object properties, such as material composition, mass, volume, and stiffness, through robot manipulation and a database of object measurements. The framework involves exploratory action selection to maximize learning about objects on a table. A Bayesian network models conditional dependenci

T. E. Zastrocky, Michael S. Brotherton, Pu Du, Jacob N. McLane

We report first-time reverberation mapping results for 14 AGNs from the ongoing Monitoring AGNs with H$\beta$ Asymmetry campaign (MAHA). These results utilize optical spectra obtained with the Long Slit Spectrograph on the Wyoming Infrared 2.3m Telescope between 2017 November-2023 May. MAHA combines long-duration monitoring with high cadence. We report resul

Paul Boisseau, Weixiao Lu, Hang Xue

This is the first of a series of three papers where we prove the Gan--Gross--Prasad conjecture for Fourier--Jacobi periods on unitary groups and an Ichino--Ikeda type refinement. Our strategy is based on the comparison of relative trace formulae formulated by Liu. The goal of this first paper is to introduce the relative trace formulae and establish the coar

Kevin Zhang, Luka Chkhetiani, Francis McCann Ramirez, Yash Khare

This paper presents Conformer-1, an end-to-end Automatic Speech Recognition (ASR) model trained on an extensive dataset of 570k hours of speech audio data, 91% of which was acquired from publicly available sources. To achieve this, we perform Noisy Student Training after generating pseudo-labels for the unlabeled public data using a strong Conformer RNN-T ba

Ryan Murtfeldt, Sejin Paik, Naomi Alterman, Ihsan Kahveci

Since 2006, Twitter's APIs have been rich sources of data for researchers studying social phenomena such as misinformation, public communication, crisis response, and political behavior. However, in 2023, Twitter began heavily restricting data access, dismantling its academic access program, and setting the Enterprise API price at $42,000 per month. Lacking

Elisabeth R. Adams, Brian Jackson, Amanda A. Sickafoose, Jeffrey P. Morgenthaler

Ultra-hot Jupiters are likely doomed by tidal forces to undergo orbital decay and eventual disruption by their stars, but the timescale over which this process unfolds is unknown. We present results from a long-term project to monitor ultra-hot Jupiters transits. We recovered WASP-12 b's orbital decay rate of dP/dt = -29.8 +/- 1.6 ms yr-1, in agreement with

Kelsey Sikes, Sarah Keren, Sarath Sreedharan

One of the most difficult challenges in creating successful human-AI collaborations is aligning a robot's behavior with a human user's expectations. When this fails to occur, a robot may misinterpret their specified goals, prompting it to perform actions with unanticipated, potentially dangerous side effects. To avoid this, we propose a new metric we call Go

Isaac Dobes, Naihuan Jing

In this paper we present a modified version of the proof given Jing-Yang-Zhao's paper titled "Local Unitary Equivalence of Quantum States and Simultaneous Orthogonal Equivalence," which established the correspondance between local unitary equivalence and simultaneous orthogonal equivalence of $2$-qubits. Our modified proof utilizes a hypermatrix algebra fram

So Hirata

The diameter of the Cayley graph of the Rubik's Cube group is the fewest number of turns needed to solve the Cube from the hardest initial configuration. For the 2$\times$2$\times$2 Cube, the diameter is 11 in the half-turn metric, 14 in the quarter-turn metric, 19 in the semi-quarter-turn metric, and 10 in the bi-quarter-turn metric. For the 3$\times$3$\tim

Lucas Goncalves, Prashant Mathur, Chandrashekhar Lavania, Metehan Cekic

Recent advancements in audio-visual generative modeling have been propelled by progress in deep learning and the availability of data-rich benchmarks. However, the growth is not attributed solely to models and benchmarks. Universally accepted evaluation metrics also play an important role in advancing the field. While there are many metrics available to eval

I. Y. Park

Finite-temperature one-loop renormalization of the Standard Model, coupled with dynamic metric, is conducted in this study. The entire analysis is coherently carried out by using the refined background field method, applied in the spirit of the Coleman-Weinberg technique. The general form of the propagator, introduced in our previous work to facilitate Feynm

Maryam Soleymaninia, Hadi Hashamipour, Maral Salajegheh, Hamzeh Khanpour

In this study, we revisit the extraction of parton-to-$K^0_S$ hadron fragmentation functions, named FF24-$K^0_S$, focusing on both next-to-leading-order and next-to-next-to-leading-order accuracy in perturbative QCD. Our approach involves the analysis of single inclusive electron-positron annihilation (SIA) data. The two key improvements are, on the one hand

Samiya A Alkhairy

Cochlear wavenumber and impedance are mechanistic variables that encode information regarding how the cochlea works - specifically wave propagation and Organ of Corti dynamics. These mechanistic variables underlie interesting features of cochlear signal processing such as its place-based wavelet analyzers, dispersivity and high-gain. Consequently, it is of i

A. Bartkiewicz, A. Sanna, M. Szymczak, L. Moscadelli

Methanol masers at 6.7~GHz are well-known signposts of high-mass star-forming regions. [...] We aim to understand the origin of the ring-like structures outlined by methanol maser emission in a number of sources. This emission could be, a priori, spatially associated with an outflow and/or disc around a high-mass protostar. [...] Using sensitive, three-epoch

J. L. G. Sobrinho, P. Augusto

Some of the Intermediate Mass Black Hole (IMBH) candidates observed at the center of galaxies or in globular clusters and some of the Supermassive Black Holes (SMBHs) seen at the center of many galaxies might be of primordial origin. Indeed, Primordial Black Holes (PBHs) of such mass could have formed when the Universe was $\sim$1-10$^3$ s old, due to the co

Victor Cardenas

The document provides an overview of financial climate risks. It delves into how climate change impacts the global financial system, distinguishing between physical risks (such as extreme weather events) and transition risks (stemming from policy changes and economic transitions towards low carbon technologies). The paper underlines the complexity of accurat

Bikram Khanal, Pablo Rivas

Quantum Computing in the Noisy Intermediate-Scale Quantum (NISQ) era has shown promising applications in machine learning, optimization, and cryptography. Despite the progress, challenges persist due to system noise, errors, and decoherence that complicate the simulation of quantum systems. The depolarization channel is a standard tool for simulating a quant

Meet Patel, Juan Sebastian Rubio, David Shekhtman, Nick Parziale

Experiments and numerical simulations of inertial particles in underexpanded jets are performed. The structure of the jet is controlled by varying the nozzle pressure ratio, while the influence of particles on emerging shocks and rarefaction patterns is controlled by varying the particle size and mass loading. Ultra-high-speed schlieren and Lagrangian partic

Nicolas Guay, Peggy Jankovic, Mamoru Ueda

We extend to the super Yangian of the special linear Lie superalgebra $\mathfrak{sl}_{m|n}$ and its affine version certain results related to Schur-Weyl duality. We do the same for the deformed double current superalgebra of $\mathfrak{sl}_{m|n}$, which is introduced here for the first time.

Ø. H. Færder, D. Nóbrega-Siverio, M. Carlsson, J. Martínez-Sykora

Understanding the role of magnetic reconnection in the heating and dynamics of the solar atmosphere requires detailed observational data of any observable aspect of the reconnection process, including small-scale features such as plasmoids. Here, we examine the capability of active and upcoming instruments to detect plasmoids generated by reconnection in the

Aernout C. D. van Enter, Roberto Fernández, Mirmukhsin Makhmudov, Evgeny Verbitskiy

Ruelle's transfer operator plays an important role in understanding thermodynamic and probabilistic properties of dynamical systems. In this work, we develop a method of finding eigenfunctions of transfer operators based on comparing Gibbs measures on the half-line $\mathbb Z_+$ and the whole line $\Z$. For a rather broad class of potentials, including both

Chloe Herman, Bridget M. Barker, Thais F. Bartelli, Vidhi Chandra

Fecal Microbiota Transplant (FMT) is an FDA approved treatment for recurrent Clostridium difficile infections, and is being explored for other clinical applications, from alleviating digestive and neurological disorders, to priming the microbiome for cancer treatment, and restoring microbiomes impacted by cancer treatment. Quantifying the extent of engraftme

Brian Nevins, Luke F. Roberts

Recent studies of the neutrino-driven wind from proto-neutron stars have indicated that the wind is likely proton-rich for much of its lifetime, and the high flux of neutrinos can induce $\nu$p-process nucleosynthesis allowing for the formation of heavy elements. It has also been shown that gravito-acoustic waves, generated by convection within the proto-neu

Maijia Su, Ziqi Wang, Oreste Salvatore Bursi, Marco Broccardo

The active learning (AL) technique, one of the state-of-the-art methods for constructing surrogate models, has shown high accuracy and efficiency in forward uncertainty quantification (UQ) analysis. This paper provides a comprehensive study on AL-based global surrogates for computing the full distribution function, i.e., the cumulative distribution function

Federico G. Iza, Sebastián E. Nuza, Cecilia Scannapieco, Robert J. J. Grand

We investigate the growth of stellar discs in Milky Way-mass galaxies using the magnetohydrodynamical simulations of the Auriga Project in a full cosmological context. We focus on the gas accretion process along the discs, calculating the net, infall and outflow rates as a function of galactocentric distance, and investigate the relation between them and the

Yasemin Kara, Diana Mocanu, Ekin Özman

In this paper, we use the modular method over totally real fields together with some standard conjectures (the Weak Frey--Mazur Conjecture and the Eichler--Shimura Conjecture) to prove that infinitely many equations of the type $x^r+y^r=Dz^p$ do not have any non-trivial primitive integer solutions, where $r \geq 5$ is a fixed prime, whenever $p$ is large eno

Nicholas Konz, Yuwen Chen, Hanxue Gu, Haoyu Dong

Modern medical image translation methods use generative models for tasks such as the conversion of CT images to MRI. Evaluating these methods typically relies on some chosen downstream task in the target domain, such as segmentation. On the other hand, task-agnostic metrics are attractive, such as the network feature-based perceptual metrics (e.g., FID) that

Hsuan-Hao Lu, Joseph M. Lukens, Muneer Alshowkan, Brian T. Kirby

By harnessing multiple degrees of freedom (DoFs) within a single photon, controlled quantum unitaries, such as the two-qubit controlled-NOT (CNOT) gate, play a pivotal role in advancing quantum communication protocols like dense coding and entanglement distillation. In this work, we devise and realize a CNOT operation between polarization and frequency DoFs

Alexander Laroche, Joshua S. Speagle

Data-driven models for stellar spectra which depend on stellar labels suffer from label systematics which decrease model performance: the "stellar labels gap". To close the stellar labels gap, we present a stellar label independent model for Gaia BP/RP spectra. We develop a novel implementation of a variational auto-encoder, which learns to generate an XP sp

Archana Bura, Sarat Chandra Bobbili, Shreyas Rameshkumar, Desik Rengarajan

Media streaming is the dominant application over wireless edge (access) networks. The increasing softwarization of such networks has led to efforts at intelligent control, wherein application-specific actions may be dynamically taken to enhance the user experience. The goal of this work is to develop and demonstrate learning-based policies for optimal decisi

Rui Xiong, Kirill Zainoulline

We show that the Grothendieck-Chow motive of a smooth hyperplane section $Y$ of an inner twisted form $X$ of a Milnor hypersurface splits as a direct sum of shifted copies of the motive of the Severi-Brauer variety of the associated cyclic algebra $A$ and the motive of its maximal commutative subfield $L\subset A$. The proof is based on the non-triviality of

Francesco Pace, Orlando Luongo, Antonino Del Popolo

We explore the impact of dynamical friction on scales where the linear growth factor and the spherical collapse model can be applied and show its influence on the evolution of perturbations. In particular, considering smooth and clustering dark energy models, we describe the role played by friction by selecting two main hierarchical models, i.e., the first w

M. Maus, S. Chen, M. White, J. Aguilar

In anticipation of forthcoming data releases of current and future spectroscopic surveys, we present the validation tests and analysis of systematic effects within \texttt{velocileptors} modeling pipeline when fitting mock data from the \texttt{AbacusSummit} N-body simulations. We compare the constraints obtained from parameter compression methods to the dir

Basheer Joudeh, Boris Škorić

We calculate the average differential entropy of a $q$-component Gaussian mixture in $\mathbb R^n$. For simplicity, all components have covariance matrix $\sigma^2 {\mathbf 1}$, while the means $\{\mathbf{W}_i\}_{i=1}^{q}$ are i.i.d. Gaussian vectors with zero mean and covariance $s^2 {\mathbf 1}$. We obtain a series expansion in $\mu=s^2/\sigma^2$ for the a

Rohan Reddy Mekala, Elias Garratt, Matthias Muehle, Arjun Srinivasan

Process refinement to consistently produce high-quality material over a large area of the grown crystal, enabling various applications from optics crystals to quantum detectors, has long been a goal for diamond growth. Machine learning offers a promising path toward this goal, but faces challenges such as the complexity of features within datasets, their tim

M. Ostilli

Small-world networks provide an interesting framework for studying the interplay between regular and random graphs, where links are located in a regular and random way, respectively. On one hand, the random links make the model to obey some kind of mean-field behavior. On the other hand, the links of the regular lattice make the system to retain some related

Jakob Holstein, Nicholas K. North, Michael D. Horbury, Sanchit Kondawar

Monolithically integrated, antenna-coupled field-effect transistors (TeraFETs) are rapid and sensitive detectors for the terahertz range (0.3-10~THz) that can operate at room temperature. We conducted experimental characterizations of a single patch-antenna coupled TeraFET optimized for 3.4~THz operation and its integration into an 8x8 multi-element detector