August 2022 arXiv papers — page 73

Timothy D. Loose, Patrick G. Sahrmann, Gregory A. Voth

For nearly the past 30 years, Centroid Molecular Dynamics (CMD) has proven to be a viable classical-like phase space formulation for the calculation of quantum dynamical properties. However, calculation of the centroid effective force remains a significant computational cost and limits the ability of CMD to be an efficient approach to study condensed phase q

George Boateng, Xiangyu Zhao, Malgorzata Speichert, Elgar Fleisch

Couples generally manage chronic diseases together and the management takes an emotional toll on both patients and their romantic partners. Consequently, recognizing the emotions of each partner in daily life could provide an insight into their emotional well-being in chronic disease management. Currently, the process of assessing each partner's emotions is

S. D. Odintsov, V. K. Oikonomou

The black hole observations obtained so far indicate one thing: similar "donuts" exist in the sky. But what if some of the observed black hole shadows that will obtained in the future are different from the others? In this work the aim is to show that a difference in the shadow of some observed black holes in the future, might explain the $H_0$-tension probl

Arunima Singh, Preeti Bhumla, Manjari Jain, Saswata Bhattacharya

Molecular hydrogen (H$_2$) production by electrochemical hydrogen evolution reaction (HER) is being actively explored for non-precious-metal based electrocatalysts that are earth-abundant and low cost like MoS$_2$. Although it is acid-stable, its applicability is limited by catalytically inactive basal plane, poor electrical transport and inefficient charge

Yuhki Hosoya

We investigate Gale's important paper published in 1960. This paper contains an example of a candidate of the demand function that satisfies the weak axiom of revealed preference and that is doubtful that it is a demand function of some weak order. We examine this paper and first scrutinize what Gale proved. Then we identify a gap in Gale's proof and show th

Yuqin Jiang, Andrey A. Popov, Zhenlong Li, Michael E. Hodgson

Human movements in urban areas are essential to understand human-environment interactions. However, activities and associated movements are full of uncertainties due to the complexity of a city. In this paper, we propose a novel sensor-based approach for spatiotemporal event detection based on the Discrete Empirical Interpolation Method. Specifically, we fir

Jonggi Hong, Jaina Gandhi, Ernest Essuah Mensah, Farnaz Zamiri Zeraati

Iteration of training and evaluating a machine learning model is an important process to improve its performance. However, while teachable interfaces enable blind users to train and test an object recognizer with photos taken in their distinctive environment, accessibility of training iteration and evaluation steps has received little attention. Iteration as

Micheline Fakhoury

We show that if $K$ is a compact metrizable space with finitely many accumulation points, then the closed unit ball of $C(K)$ is a plastic metric space, which means that any non-expansive bijection from $B_{C(K)}$ onto itself is in fact an isometry. We also show that if $K$ is a zero-dimensional compact Hausdorff space with a dense set of isolated points, th

Hammad A. Faizi, Rony Granek, Petia M. Vlahovska

The biological function of membranes is closely related to their softness, which is often studied through the membranes' thermally-driven fluctuations. The analysis commonly assumes that the relaxation rate of a pure bending deformation is determined by the competition between membrane bending rigidity and viscous dissipation in the surrounding medium. Here,

Uchenna D Ani, Jeremy D McK Watson, Nilufer Tuptuk, Steve Hailes

The UK Critical National Infrastructure is critically dependent on digital technologies that provide communications, monitoring, control, and decision-support functionalities. Digital technologies are progressively enhancing efficiency, reliability, and availability of infrastructure, and enabling new benefits not previously available. These benefits can int

Yun-Peng Huang, Panagiotis Kotetes

We propose an alternative route to stabilize magnetic skyrmion textures which does not require Dzyaloshinkii-Moriya interaction, magnetic anisotropy, or an external Zeeman field. Instead, it solely relies on the emergence of flux in the system's ground state. We discuss scenarios that lead to a nonzero flux, and identify the magnetic skyrmion ground states w

Michele Grossi, Noelle Ibrahim, Voica Radescu, Robert Loredo

This paper presents a first end-to-end application of a Quantum Support Vector Machine (QSVM) algorithm for a classification problem in the financial payment industry using the IBM Safer Payments and IBM Quantum Computers via the Qiskit software stack. Based on real card payment data, a thorough comparison is performed to assess the complementary impact brou

Mohsen Ghassemi, Niccolò Dalmasso, Simran Lamba, Vamsi K. Potluru

Online learning of Hawkes processes has received increasing attention in the last couple of years especially for modeling a network of actors. However, these works typically either model the rich interaction between the events or the latent cluster of the actors or the network structure between the actors. We propose to model the latent structure of the netw

Kori Inkpen, Shreya Chappidi, Keri Mallari, Besmira Nushi

Human-AI collaboration for decision-making strives to achieve team performance that exceeds the performance of humans or AI alone. However, many factors can impact success of Human-AI teams, including a user's domain expertise, mental models of an AI system, trust in recommendations, and more. This work examines users' interaction with three simulated algori

Zilong Xie, Yunxiao Chen, Matthias von Davier, Haolei Weng

International large-scale assessments (ILSAs) play an important role in educational research and policy making. They collect valuable data on education quality and performance development across many education systems, giving countries the opportunity to share techniques, organizational structures, and policies that have proven efficient and successful. To g

Maria Yliruka, Stefano Moret, Nilay Shah

Energy systems modellers often resort to simplified system representations and deterministic model formulations (i.e., not considering uncertainty) to preserve computational tractability. However, reduced levels of detail and neglected uncertainties can both lead to sub-optimal system designs. In this paper, we present a novel method that quantitatively comp

Yonah Borns-Weil, Di Fang

Known as no fast-forwarding theorem in quantum computing, the simulation time for the Hamiltonian evolution needs to be $O(\|H\| t)$ in the worst case, which essentially states that one can not go across the multiple scales as the simulation time for the Hamiltonian evolution needs to be strictly greater than the physical time. We demonstrated in the context

Stephen L. Skinner, Marc Audard

We summarize Hubble Space Telescope (HST) UV observations of the weak-lined T Tauri star (wTTS) PDS 70 obtained with the Space Telescope Imaging Spectrograph (STIS). These observations provide the first far-UV (FUV) and near-UV (NUV) spectra of PDS 70. Ground-based observations have so far revealed two formative giant planets orbiting in a wide gap in its ci

Jiayan Gu, Ashiq Anjum, Yan Wu, Lu Liu

As the number of devices connected to the Internet of Things (IoT) increases significantly, it leads to an exponential growth in the number of services that need to be processed and stored in the large-scale Cloud-based service repositories. An efficient service indexing model is critical for service retrieval and management of large-scale Cloud-based servic

Philip Chrostoski, Pauli Kehayias, D. H. Santamore

Noise is a detrimental issue for nitrogen-vacancy (NV) centers in diamond, causing line broadening and decreasing the coherence time (T2). Following our previous electric and magnetic field noise work, we investigate noise caused by the diamond surface roughness, which is a source for charge density fluctuations and incoherent photon scattering. We find that

Matt Bellis, Brian Shuve, Anna Barth, Andres Cook

Over the last 20+ years, experimentalists have presented tantalizing hints of physics beyond the standard model, but nothing definitive. With the wealth of data from experiments, in particular the collider experiments, it is imperative that the community leave no reasonable model untested and no search unsought. Open datasets from particle physics experiment

Hadi Keramati, Feridun Hamdullahpur

Generative design has been growing across the design community as a viable method for design space exploration. Thermal design is more complex than mechanical or aerodynamic design because of the additional convection-diffusion equation and its pertinent boundary interaction. We present a generative thermal design using cooperative multi-agent deep reinforce

Nisha Chandramoorthy, Andreas Loukas, Khashayar Gatmiry, Stefanie Jegelka

Generalization analyses of deep learning typically assume that the training converges to a fixed point. But, recent results indicate that in practice, the weights of deep neural networks optimized with stochastic gradient descent often oscillate indefinitely. To reduce this discrepancy between theory and practice, this paper focuses on the generalization of

R. Ehlers, A. Angerami, R. Arora, S. A. Bass

The JETSCAPE Collaboration reports a new determination of jet transport coefficients in the Quark-Gluon Plasma, using both reconstructed jet and hadron data measured at RHIC and the LHC. The JETSCAPE framework incorporates detailed modeling of the dynamical evolution of the QGP; a multi-stage theoretical approach to in-medium jet evolution and medium respons

Chin-Wei Huang, Milad Aghajohari, Avishek Joey Bose, Prakash Panangaden

Diffusion models are recent state-of-the-art methods for image generation and likelihood estimation. In this work, we generalize continuous-time diffusion models to arbitrary Riemannian manifolds and derive a variational framework for likelihood estimation. Computationally, we propose new methods for computing the Riemannian divergence which is needed in the

Fletcher Waller, Kim Venn, Federico Sestito, Jaclyn Jensen

Gaia EDR3 data was used to identify potential members in the outskirts of three ultra faint dwarf (UFD) galaxies; Coma Berenices (> 2Rh), Ursa Major I ($\sim$ 4Rh), and Bo\"otes I ($\sim$ 4Rh), as well as a new member in the central region of Ursa Major I. These targets were observed with the Gemini GRACES spectrograph, which was used to determine precision

Nisreen Mohammed Mahdi, Arzu Kurt, Ferdi Altintas

We investigate the coherence and non-Markovianity of a quantum tunneling system whose barrier is fluctuated by a telegraph noise, and its energy gap is modulated by Gaussian noise. With the help of averaging method, the system dynamics are analytically derived, and the analytical expression for coherence measure and non-Markovianity for the very limited para

Parvez Rasul

Let $k$ be an algebraically closed field of characteristic $p > 3$. Let $A$ be an abelian surface over $k$. Fix an integer $n \geq 1$ such that $p \nmid n$ and let $K^{[n]}$ be the $n$-th Generalized Kummer Variety associated to $A$. In this article we aim to find the $S$-fundamental group scheme and Nori's fundamental group scheme of $K^{[n]}$.

W. C. Haxton, Evan Rule, Ken McElvain, Michael J. Ramsey-Musolf

New mu-to-e conversion searches aim to advance limits on charged lepton flavor violation (CLFV) by four orders of magnitude. By considering P and CP selection rules and the structure of possible charge and current densities, we show that rates are governed by six nuclear responses. To generate a microscopic formulation of these responses, we construct in non

Halie M. Rando, Ronan Lordan, Alexandra J. Lee, Amruta Naik

Over the past 150 years, vaccines have revolutionized the relationship between people and disease. During the COVID-19 pandemic, technologies such as mRNA vaccines have received attention due to their novelty and successes. However, more traditional vaccine development platforms have also yielded important tools in the worldwide fight against the SARS-CoV-2

Shubham Dokania, Anbumani Subramanian, Manmohan Chandraker, C. V. Jawahar

High-quality structured data with rich annotations are critical components in intelligent vehicle systems dealing with road scenes. However, data curation and annotation require intensive investments and yield low-diversity scenarios. The recently growing interest in synthetic data raises questions about the scope of improvement in such systems and the amoun

R. Nikandish, M. J. Nikmehr, A. Yassine

A famous result due to I. M. Isaacs states that if a commutative ring $R$ has the property that every prime ideal is principal, then every ideal of $R$ is principal. This motivates ring theorists to study commutative rings for which every ideal is a direct sum of cyclically presented modules. In this paper, we study commutative rings whose ideals are direct

Robert R. Bruner, Daniel C. Isaksen

In 2006, Jeff Smith proposed a theory of ideals for rings in a triangulated symmetric monoidal category such as ring spectra or DGAs. We show that his definition is equivalent to a `central' $R$-$R$-bimodule map $ I \to R$.

R. Nikandish, M. J. Nikmehr, A. Yassine

An $R$-module $M$ is called virtually uniserial if for every finitely generated submodule $0 \neq K \subseteq M$, $K/$Rad$(K)$ is virtually simple. In this paper, we generalize virtually uniserial modules by dropping the virtually simple condition and replacing it by the cyclic uniform condition. An $R$-module $M$ is called cyclic-uniform uniserial if $K/$Ra

Gang Chen

Exotic state of matter could coexist with conventional orders such that the gauge fields and fractionalized excitations could prevail in a seemingly ordered state. We explore the Coulombic antiferromagnet in the spin-1/2 pyrochlores with dipole-octupole doublets. This fractionalized antiferromagnetic state carries both antiferromagnetic order and emergent qu

Maren Cosens, Shelley A. Wright, Aaron Brown, Michael Fitzgerald

Liger is a next-generation near-infrared imager and integral field spectrograph (IFS) planned for the W.M. Keck Observatory. Liger is designed to take advantage of improved adaptive optics (AO) from the Keck All-Sky Precision Adaptive Optics (KAPA) upgrade currently underway. Liger operates at 0.84-2.45 $\mu$m with spectral resolving powers of R$\sim$4,000-1

Nils Rundquist, Andrea Zonca, Arun Surya, Shelley A. Wright

Liger is a second generation near-infrared imager and integral field spectrograph (IFS) for the W. M. Keck Observatory that will utilize the capabilities of the Keck All-sky Precision Adaptive-optics (KAPA) system. Liger operates at a wavelength range of 0.81 {\mu}m - 2.45 {\mu}m and utilizes a slicer and a lenslet array IFS with varying spatial plate scales

James Wiley, Aaron Brown, Renate Kupke, Maren Cosens

Liger is an adaptive optics (AO) fed imager and integral field spectrograph (IFS) designed to take advantage of the Keck All-sky Precision Adaptive-optics (KAPA) upgrade for the W.M. Keck Observatory. We present the design and analysis of the imager optical assembly including the spectrograph Re-Imaging Optics (RIO) which transfers the beam path from the ima

Kizito Salako, Xingyu Zhao

This paper presents Bayesian techniques for conservative claims about software reliability, particularly when evidence suggests the software's executions are not statistically independent. We formalise informal notions of "doubting" that the executions are independent, and incorporate such doubts into reliability assessments. We develop techniques that revea

Povilas Daniušis, Shubham Juneja, Lukas Kuzma, Virginijus Marcinkevičius

In this paper, we focus on the problem of statistical dependence estimation using characteristic functions. We propose a statistical dependence measure, based on the maximum-norm of the difference between joint and product-marginal characteristic functions. The proposed measure can detect arbitrary statistical dependence between two random vectors of possibl

Eduard Feireisl, Arnab Roy, Arghir Zarnescu

We consider the motion of a small rigid object immersed in a viscous compressible fluid in the 3-dimensional Eucleidean space. Assuming the object is a ball of a small radius $\varepsilon$ we show that the behavior of the fluid is not influenced by the object in the asymptotic limit $\varepsilon \to 0$. The result holds for the isentropic pressure law $p(\va

S. D. Bale, J. F. Drake, M. D. McManus, M. I. Desai

The fast solar wind that fills the heliosphere originates from deep within regions of open magnetic field on the Sun called coronal holes. The energy source responsible for accelerating the plasma to high speeds is widely debated, however there is evidence that it is ultimately magnetic in nature with candidate mechanisms including wave heating^(1,2) and int

Srinath Mahankali, Yunan Yang

This work analyzes the forward and inverse scattering series for scalar waves based on the Helmholtz equation and the diffuse waves from the time-independent diffusion equation, which are important PDEs in various applications. Different from previous works, which study the radius of convergence for the forward and inverse scattering series, the stability, a

Carolyn Abbott, Jason Behrstock, Jacob Russell

We prove several topological and dynamical properties of the boundary of a hierarchically hyperbolic group are independent of the specific hierarchically hyperbolic structure. This is accomplished by proving that the boundary is invariant under a "maximization" procedure introduced by the first two authors and Durham.

James Wensel, Hayat Ullah, Arslan Munir

Human activity recognition is an emerging and important area in computer vision which seeks to determine the activity an individual or group of individuals are performing. The applications of this field ranges from generating highlight videos in sports, to intelligent surveillance and gesture recognition. Most activity recognition systems rely on a combinati

Orlenys Lopez-Pintado, Marlon Dumas

Business process simulation is a versatile technique to predict the impact of one or more changes on the performance of a process. Mainstream approaches in this space suffer from various limitations, some stemming from the fact that they treat resources as undifferentiated entities grouped into resource pools. These approaches assume that all resources in a

Linshanshan Wang, Xuan Wang, Katherine P. Liao, Tianxi Cai

In modern machine learning applications, frequent encounters of covariate shift and label scarcity have posed challenges to robust model training and evaluation. Numerous transfer learning methods have been developed to robustly adapt the model itself to some unlabeled target populations using existing labeled data in a source population. However, there is a

R. Maria del Rio-Chanona, Alejandro Hermida-Carrillo, Melody Sepahpour-Fard, Luning Sun

To study the causes of the 2021 Great Resignation, we use text analysis to investigate the changes in work- and quit-related posts between 2018 and 2021 on Reddit. We find that the Reddit discourse evolution resembles the dynamics of the U.S. quit and layoff rates. Furthermore, when the COVID-19 pandemic started, conversations related to working from home, s

Fabrizio Canfora, Diego Hidalgo, Marcela Lagos, Enzo Meneses

The present manuscript discusses a remarkable phenomenon concerning non-linear and non-integrable field theories in $(3+1)$-dimensions, living at finite density and possessing non-trivial topological charges and non-Abelian internal symmetries (both local and global). With suitable types of ans\"atze, one can construct infinite-dimensional families of analyt

Salar Abbasi Aghda, Ali Naji

We report on experimentally measured drag force experienced by a solid cylinder penetrating a granular bed of glass beads including, specifically, a highly polydisperse sample with grain sizes in the range 1-100 {\mu}m. We consider both cases of lateral and axial intrusion in which the long axis of the cylinder is held horizontally and vertically, respective

Stan Gudder

We first show that every operation possesses an unique dual operation and measures an unique effect. If $a$ and $b$ are effects and $J$ is an operation that measures $a$, we define the sequential product of $a$ then $b$ relative to $J$. Properties of the sequential product are derived and are illustrated in terms of L\"uders and Holevo operations. We next ex

Hamid Mozaffari, Virendra J. Marathe, Dave Dice

Federated Learning (FL) is a distributed learning paradigm that enables mutually untrusting clients to collaboratively train a common machine learning model. Client data privacy is paramount in FL. At the same time, the model must be protected from poisoning attacks from adversarial clients. Existing solutions address these two problems in isolation. We pres

Cosimo Flavi

We determine the border rank of each power of any quadratic form in three variables. Since the problem for rank $1$ and rank $2$ quadratic forms can be reduced to determining the rank of powers of binary forms, we primarily focus on non-degenerate quadratic forms. We begin by considering the quadratic form $q_{n}=x_1^{2}+\dots+x_n^{2}$ in an arbitrary number

Kevin Hughes

Using the Girard--Newton formulae, I give a simple proof of isotropic square function estimates for extension operators along the moment curve in generic local fields. Using Bezout's Theorem and the Implicit Function Theorem, I give an alternate, sharper proof for real or complex non-degenerate, polynomial curves.

Theo Diamandis, Alex Evans, Tarun Chitra, Guillermo Angeris

Public blockchains implement a fee mechanism to allocate scarce computational resources across competing transactions. Most existing fee market designs utilize a joint, fungible unit of account (e.g., gas in Ethereum) to price otherwise non-fungible resources such as bandwidth, computation, and storage, by hardcoding their relative prices. Fixing the relativ

Jonathan Vasquez, Xavier Gitiaux, Huzefa Rangwala

Data owners face increasing liability for how the use of their data could harm under-priviliged communities. Stakeholders would like to identify the characteristics of data that lead to algorithms being biased against any particular demographic groups, for example, defined by their race, gender, age, and/or religion. Specifically, we are interested in identi

Mingzhen Lu, Chuanbin Zhou, Chenghao Wang, Robert B. Jackson

The production of waste as a consequence of human activities is one of the most fundamental challenges facing our society and global ecological systems. Waste generation is rapidly increasing, with corresponding shifts in the structure of our societies where almost all nations are moving from rural agrarian societies to urban and technological ones. However,

Gleb Smirnov

Let $\omega$ be a Kaehler form on the real $4$-torus $T^4$. Suppose that $\omega$ satisfies an irrationality condition which can be achieved by an arbitrarily small perturbation of $\omega$. This note shows that the smoothly trivial symplectic mapping class group of the one-point symplectic blowup of $(T^4,\omega)$ is infinitely generated.

Chen Xie, Elodie Choquet, Arthur Vigan, Faustine Cantalloube

Reference-star differential imaging (RDI) is a promising technique in high-contrast imaging that is thought to be more sensitive to exoplanets and disks than angular differential imaging (ADI) at short angular separations (i.e., <0.3"). However, it is unknown whether the performance of RDI on ground-based instruments can be improved by using all the archival

Toygun Basaklar, Suat Gumussoy, Umit Y. Ogras

Multi-objective reinforcement learning (MORL) approaches have emerged to tackle many real-world problems with multiple conflicting objectives by maximizing a joint objective function weighted by a preference vector. These approaches find fixed customized policies corresponding to preference vectors specified during training. However, the design constraints a

Stuart Wayland

Gerrymandering is the perversion of an election based on manipulation of voting district boundaries, and has been a historically important yet difficult task to analytically prove. We propose a Markov Chain Monte Carlo with Simulated Annealing as a solution for measuring the extent to which a districting plan is unfair. We put forth promising results in the

David J. Benson

Thanks to the work of Karin Erdmann, we know a great deal about the representation theory of blocks of finite groups with tame representation type. Our purpose here is to examine the $p$-completed classifying spaces of these blocks and their loop spaces. We pay special attention to the $A_\infty$ algebra structures, and singularity and cosingularity categori

M. Koussour, K. El Bourakadi, S. H. Shekh, S. K. J. Pacif

This paper is devoted to investigate the anisotropic locally rotationally symmetric (LRS) Bianchi type-I space-time in the context of the recently proposed $f(Q)$ gravity in which $Q$ is the non-metricity scalar. For this purpose, we consider a linear form of $f\left( Q\right) $ gravity model, specifically, $f\left( Q\right) =\alpha Q+\beta $, where $\alpha

Huaduo Wang, Gopal Gupta

We present FOLD-SE, an efficient, explainable machine learning algorithm for classification tasks given tabular data containing numerical and categorical values. FOLD-SE generates a set of default rules-essentially a stratified normal logic program-as an (explainable) trained model. Explainability provided by FOLD-SE is scalable, meaning that regardless of t

Jacky J. Chong, Laurent Lafleche, Chiara Saffirio

We study the regularity properties of fermionic equilibrium states at finite positive temperature and show that they satisfy certain semiclassical bounds. As a corollary, we identify explicitly a class of positive temperature states satisfying the regularity assumptions of [J.J. Chong, L. Lafleche, C. Saffirio: arXiv:2103.10946 (2021)].

Benjamin Nachman

This is a personal perspective on data sharing in the context of public data releases suitable for generic analysis. These open data can be a powerful tool for expanding the science of high energy physics, but care must be taken in when, where, and how they are utilized. I argue that data preservation even within collaborations needs additional support in or

Orizon P. Ferreira, Guilherme. A. Franca, Max V. Lemes

In this work, we introduce Modern Portfolio Theory using basic concepts from linear algebra, differential calculus, statistics, and optimization. This theory allows us to measure the return and risk of an investment portfolio, serving as a basis for decision-making in the financial market. As an application, we will present four very simple investment strate

Ken K. W. Ma, Michael R. Peterson, V. W. Scarola, Kun Yang

The fractional quantum Hall (FQH) effect at the filling factor $\nu=5/2$ was discovered in GaAs heterostructures more than 35 years ago. Various topological orders have been proposed as possible candidates to describe this FQH state. Some of them possess non-Abelian anyon excitations, an entirely new type of quasiparticle with fascinating properties. If obse

M. Jamil Aslam, Wen Chen, Andrzej Czarnecki, Muhammad Mubasher

Decay rates of the positronium hydride PsH, a bound state of a proton, a positron, and two electrons, are determined for two rare channels, PsH $\to p^+ e^- \gamma$ and PsH $\to p^+ e^-$. Previous studies overestimated these rates by factors of about 2 and 700, respectively. We explain the physics underlying these wrong predictions. We confirm a range of sta

D. R. Wilkins, S. W. Allen, E. D. Miller, M. Bautz

The sensitivity of astronomical X-ray detectors is limited by the instrumental background. The background is especially important when observing low surface brightness sources that are critical for many of the science cases targeted by future X-ray observatories, including Athena and future US-led flagship or probe-class X-ray missions. Above 2keV, the backg

Jonathan Bader, Fabian Lehmann, Alexander Groth, Lauritz Thamsen

Scientific workflows typically comprise a multitude of different processing steps which often are executed in parallel on different partitions of the input data. These executions, in turn, must be scheduled on the compute nodes of the computational infrastructure at hand. This assignment is complicated by the facts that (a) tasks typically have highly hetero

Philippe Pébay, J. Maurice Rojas, David C. Thompson

Sturm's Theorem is a fundamental 19th century result relating the number of real roots of a polynomial $f$ in an interval to the number of sign alternations in a sequence of polynomial division-like calculations. We provide a short direct proof of Sturm's Theorem, including the numerically vexing case (ignored in many published accounts) where an interval en

Pulkit Gera, Mohammad Reza Karimi Dastjerdi, Charles Renaud, P. J. Narayanan

We present PanoHDR-NeRF, a neural representation of the full HDR radiance field of an indoor scene, and a pipeline to capture it casually, without elaborate setups or complex capture protocols. First, a user captures a low dynamic range (LDR) omnidirectional video of the scene by freely waving an off-the-shelf camera around the scene. Then, an LDR2HDR networ

Jingang Li, Di Zhang, Zhongyuan Guo, Xi Jiang

C-H bond activation enables the facile synthesis of new chemicals. While C-H activation in short-chain alkanes has been widely investigated, it remains largely unexplored for long-chain organic molecules. Here, we report light-driven C-H activation in complex organic materials mediated by 2D transition metal dichalcogenides (TMDCs) and the resultant solid-st

Kiril Datchev, Jeremy L. Marzuola, Jared Wunsch

We prove explicit asymptotics for the location of semiclassical scattering resonances in the setting of $h$-dependent delta-function potentials on $\mathbb{R}$. In the cases of two or three delta poles, we are able to show that resonances occur along specific lines of the form $\Im z \sim -\gamma h \log(1/h).$ More generally, we use the method of Newton poly

Lucas da Cunha Godoy, Marcos Oliveira Prates, Jun Yan

Accurate modeling of spatial dependence is pivotal in analyzing spatial data, influencing parameter estimation and predictions. The spatial structure of the data significantly impacts valid statistical inference. Existing models for areal data often rely on adjacency matrices, struggling to differentiate between polygons of varying sizes and shapes. Converse

Lindsey Dietz, Sakshi Arya, Vishal Subedi, Auroop R. Ganguly

Bayesian hierarchical models are proposed for modeling tropical cyclone characteristics and their damage potential in the Atlantic basin. We model the joint probability distribution of tropical cyclone characteristics and their damage potential at two different temporal scales, while taking several climate indices into account. First, a predictive model for

Yuji Kawamata, Ryoki Motai, Yukihiko Okada, Akira Imakura

In recent years, the development of technologies for causal inference with privacy preservation of distributed data has gained considerable attention. Many existing methods for distributed data focus on resolving the lack of subjects (samples) and can only reduce random errors in estimating treatment effects. In this study, we propose a data collaboration qu

Pedro D. Alvarez, Juan Ortiz

We present analytical solutions for homogenous and isotropic spaces of the supersymmetric Chern-Simons model with matter in the adjoint representation. The configurations that we found correspond to a gravitating spinor content and torsion is also present. The spinor behaves like dark energy in the sense that drives an exponential expansion. The solution fou

Yakine Bahri, Hichem Hajaiej

In this paper, we study the transverse instability of generalized Zakharov-Kuznetsov equation for the line soliton with critical speed. We derive and justify a normal form reduction for a bifurcation problem of the stationary nonlinear KdV equation on the product space R ? T.

Horacio Olivares-Pilón, Alexander V. Turbiner

The analytic Born-Oppenheimer (B-O) potential curve for the ground state $X^1\Sigma^+$ of the molecule (H,D,T)Cl is constructed for the whole range of internuclear distances $R \in [0,\infty)$ with an accuracy of 3-5 figures in comparison with the RKR-style potential curve derived from available experimental data on vibrational energies. With an accuracy of

Gheorghe Nenciu, Evelyn Richman, Christof Sparber

We study the large field limit in Schr\"odinger equations with magnetic vector potentials describing translationally invariant $B$-fields with respect to the $z$-axis. In a first step, using regular perturbation theory, we derive an approximate description of the solution, provided the initial data is compactly supported in the Fourier-variable dual to $z\in

Zhe Qu, Xingyu Li, Jie Xu, Bo Tang

Multi-server Federated learning (FL) has been considered as a promising solution to address the limited communication resource problem of single-server FL. We consider a typical multi-server FL architecture, where the coverage areas of regional servers may overlap. The key point of this architecture is that the clients located in the overlapping areas update

Eun Jung Chung, Chang Won Lee, Woojin Kwon, Hyunju Yoo

We present the results of 850 $\mu$m polarization and C$^{18}$O (3-2) line observations toward the western hub-filament structure (W-HFS) of the dark Streamer in IC 5146 using the James Clerk Maxwell Telescope (JCMT) SCUBA-2/POL-2 and HARP instruments. We aim to investigate how the relative importance of the magnetic field, gravity, and turbulence affects co

Stefano Boccelli, James G. McDonald

This work introduces a limitation on the minimum value that can be assumed by the energy of a relativistic gas in the presence of a non-zero heat flux. Such a limitation arises from the non-negativity of the particle distribution function, and is found by solving the Hamburger moment problem. The resulting limitation is seen to recover the Taub inequality in

Metin Aktaş

The present paper engages in a particular attempt to acquire exact analytical eigensolutions of the position-dependent effective mass (PDEM) Schr\"odinger equation for a variety of squared style trigonometric potentials. The algebraic process entitled as the point canonical transformation (PCT) approach is implemented in the course of study. Certain spatiall

Robert Wissing, Sijing Shen

Understanding the numerical dependencies that act on the galactic dynamo is a crucial step in determining what resolution and what conditions are required to properly capture the magnetic fields observed in galaxies. Here, we present an extensive study on the numerical dependencies of the galactic dynamo in isolated spiral galaxies using smoothed particle ma

Jacob Hammond

Random number generation is a key technology that is useful in a variety of ways. Random numbers are often used to generate keys for data encryption. Random numbers generated at a sufficiently long length can encrypt sensitive data and make it difficult for another computer or person to decrypt the data. Other uses for random numbers include statistical samp

Eirik Holm Fyhn, Arne Brataas, Alireza Qaiumzadeh, Jacob Linder

Unlike ferromagnetism, antiferromagnetism cannot readily be included in the quasiclassical Keldysh theory because of the rapid spatial variation in the directions of the magnetic moments. The quasiclassical framework is useful because it separates the quantum effects occurring at length scales comparable to the Fermi wavelength from other length scales, and

Jef Pauwels, Stefano Pironio, Erik Woodhead, Armin Tavakoli

Quantum communication is often investigated in scenarios where only the dimension of Hilbert space is known. However, assigning a precise dimension is often an approximation of what is actually a higher-dimensional process. Here, we introduce and investigate quantum information encoded in carriers that nearly, but not entirely, correspond to standard qudits.

Miguel Gonçalves, Bruno Amorim, Eduardo V. Castro, Pedro Ribeiro

We propose a solvable class of 1D quasiperiodic tight-binding models encompassing extended, localized, and critical phases, separated by nontrivial mobility edges. Limiting cases include the Aubry-Andr\'e model and the models of PRL 114, 146601 and PRL 104, 070601. The analytical treatment follows from recognizing these models as a novel type of fixed-points

S. Shahina, J. Gorres, D. Robertson, M. Couder

The $^{22}\rm{Ne}(\alpha,\gamma)^{26}\rm{Mg}$ is an important reaction in stellar helium burning environments as it competes directly with one of the main neutron sources for the s-process, the $^{22}\rm{Ne}(\alpha,n)^{25}\rm{Mg}$ reaction. The reaction rate of the $^{22}\rm{Ne}(\alpha,\gamma)^{26}\rm{Mg}$ is dominated by the low energy resonances at $E_{\al

Shani Meynet, Robert Moscrop

When a quantum field theory in $d$-spacetime dimensions possesses a global $(d-1)$-form symmetry, it can decompose into disjoint unions of other theories. This is reflected in the physical quantities of the theory and can be used to study properties of the constituent theories. In this note we highlight the equivalence between the decomposition of orbifold $

Romy Rodríguez Martínez, B. Scott Gaudi, Joseph G. Schulze, Lorena Acuña

We present a reanalysis of the K2-106 transiting planetary system, with a focus on the composition of K2-106b, an ultra-short period, super-Mercury candidate. We globally model existing photometric and radial velocity data and derive a planetary mass and radius for K2-106b of $M_{p} = 8.53\pm1.02~M_{\oplus}$ and $R_{p} = 1.71^{+0.069}_{-0.057}~R_{\oplus}$, w

Csaba Csáki, Andrew Gomes, Yonit Hochberg, Eric Kuflik

We introduce Super-Resonant Dark Matter, a model of self-interacting dark matter based on the low energy effective theory of supersymmetric QCD. The structure of the theory ensures a resonant enhancement of the self-interactions of the low energy mesons, since their mass ratio is set by the number of colors and flavors. The velocity dependence of the resonan

Elena González Prieto, Kyle Kremer, Giacomo Fragione, Miguel A. S. Martinez

The existence of black holes (BHs) with masses in the range between stellar remnants and supermassive BHs has only recently become unambiguously established. GW190521, a gravitational wave signal detected by the LIGO/Virgo Collaboration, provides the first direct evidence for the existence of such intermediate-mass BHs (IMBHs). This event sparked and continu

Ilias Cholis, Iason Krommydas

The inner galaxy has hosted cosmic-ray burst events including those responsible for the gamma-ray Fermi bubbles and the eROSITA bubbles in X-rays. In this work, we study the AMS-02 positron fraction and find three features around 12, 21 and 48 GeV of which the lowest energy has a 1.4 to 4.9-$\sigma$ significance, depending on astrophysical background assumpt

Charles L. Steinhardt, Vasily Kokorev, Vadim Rusakov, Ethan Garcia

Recent data from the James Webb Space Telescope allow a first glimpse of galaxies at $z \gtrsim 11$. The most successful tool for identifying ultra-high-redshift candidates and inferring their properties is photometric template fitting. However, current methods rely on templates derived from much lower-redshift conditions, including stellar populations older

Patrick Barnes, Raymond T. Co, Keisuke Harigaya, Aaron Pierce

If the Peccei-Quinn field containing the QCD axion undergoes rotations in the early universe, the dimension-five operator responsible for neutrino masses can generate a lepton asymmetry that ultimately gives rise to the observed baryon asymmetry of the Universe. This lepto-axiogenesis scenario requires a flat potential for the radial direction of the Peccei-

Samuel M. Factor, Adam L. Kraus

Filling out the dearth of detections between direct imaging and radial velocity surveys will test theories of planet formation and (sub)stellar binarity across the full range of semi-major axes, connecting formation of close to wide separation gas giants and substellar companions. Direct detection of close-in companions is notoriously difficult: coronagraphs