July 2023 arXiv papers — page 14

Sotiris Pelekis, Evangelos Karakolis, Theodosios Pountridis, George Kormpakis

This paper presents DeepTSF, a comprehensive machine learning operations (MLOps) framework aiming to innovate time series forecasting through workflow automation and codeless modeling. DeepTSF automates key aspects of the ML lifecycle, making it an ideal tool for data scientists and MLops engineers engaged in machine learning (ML) and deep learning (DL)-base

Kenny Chiu, Benjamin Bloem-Reddy

Symmetry plays a central role in the sciences, machine learning, and statistics. For situations in which data are known to obey a symmetry, a multitude of methods that exploit symmetry have been developed. Statistical tests for the presence or absence of general group symmetry, however, are largely non-existent. This work formulates non-parametric hypothesis

Wei Zhou, Xiangyu Peng, Mark Riedl

One major challenge in reinforcement learning (RL) is the large amount of steps for the RL agent needs to converge in the training process and learn the optimal policy, especially in text-based game environments where the action space is extensive. However, non-player characters (NPCs) sometimes hold some key information about the game, which can potentially

Dionysios Anninos, Tarek Anous, Ben Pethybridge, Gizem Şengör

We study quantum field theories placed on a two-dimensional de Sitter spacetime (dS$_2$) with an eye on the group-theoretic organisation of single and multi-particle states. We explore the distinguished role of the discrete series unitary irreducible representation (UIR) in the Hilbert space. By employing previous attempts to realise these states in free tac

Dooseok Escher Jung, Daniela Calzetti, Matteo Messa, Mark Heyer

We investigate the variation in the upper end of stellar initial mass function (uIMF) in 375 young and compact star clusters in five nearby galaxies within $\sim 5$ Mpc. All the young stellar clusters (YSCs) in the sample have ages $\lesssim 4$ Myr and masses above 500 $M_{\odot}$, according to standard stellar models. The YSC catalogs were produced from Hub

Christopher Salazar, Ashis G. Banerjee

Time series forecasting has received a lot of attention, with recurrent neural networks (RNNs) being one of the widely used models due to their ability to handle sequential data. Previous studies on RNN time series forecasting, however, show inconsistent outcomes and offer few explanations for performance variations among the datasets. In this paper, we prov

Rong Zou, Manasi Muglikar, Nico Messikommer, Davide Scaramuzza

Unwanted camera occlusions, such as debris, dust, rain-drops, and snow, can severely degrade the performance of computer-vision systems. Dynamic occlusions are particularly challenging because of the continuously changing pattern. Existing occlusion-removal methods currently use synthetic aperture imaging or image inpainting. However, they face issues with d

Shuyu Cheng, M. Nrisimhamurty, Tong Zhou, Nuria Bagues

Systems with flat bands are ideal for studying strongly correlated electronic states and related phenomena. Among them, kagome-structured metals such as CoSn have been recognized as promising candidates due to the proximity between the flat bands and the Fermi level. A key next step will be to realize epitaxial kagome thin films with flat bands to enable tun

Kimberly Golubeva, Minghao Pan, Omer Tamuz

We introduce asymptotic R\'enyi entropies as a parameterized family of invariants for random walks on groups. These invariants interpolate between various well-studied properties of the random walk, including the growth rate of the group, the Shannon entropy, and the spectral radius. They furthermore offer large deviation counterparts of the Shannon-McMillan

Eduard Suarez, Richard H. Benavides, Yithsbey Giraldo, William A. Ponce

We report the most general classification of 3-3-1 models with $\beta =\sqrt{3}$. We found several solutions where anomaly cancellation occurs among fermions of different families. These solutions are particularly interesting as they generate non-universal heavy neutral vector bosons. Non-universality in the SM fermion charges under an additional gauge group

Finn Bjarne Jost

By recent work of Afandi, it is known that tautological intersection numbers on the moduli space of stable $n$-pointed genus $g$ curves can be arranged into families of Ehrhart polynomials, $\{L_{\vec{d}}\}$, for partial polytopal complexes. In particular, the $f^*$-vector of $L_{\vec{d}}$ is known to be integral and non-negative. In this paper, we show that

Maya Fishbach, Lieke van Son

In their third observing run, the LIGO-Virgo-KAGRA gravitational-wave (GW) observatory was sensitive to binary black hole (BBH) mergers out to redshifts $z_\mathrm{merge}\approx1$. Because GWs are inefficient at shrinking the binary orbit, some of these BBH systems likely experienced long delay times $\tau$ between the formation of their progenitor stars at

Cono Di Paola, Evgeny Plekhanov, Michal Krompiec, Chandan Kumar

Hydrogen has emerged as a promising energy source, holding the key to achieve low-carbon and sustainable mobility. However, its applications are still limited by modest conversion efficiency in the electrocatalytic oxygen reduction reaction (ORR) within fuel cells. Consequently, the development of novel catalysts and a profound understanding of the underlyin

Doug Hardin, Nathaniel Tenpas

We develop lower bounds for the energy of configurations in $\mathbb{R}^d$ periodic with respect to a lattice. In certain cases, the construction of sharp bounds can be formulated as a finite dimensional, multivariate polynomial interpolation problem. We use this framework to show a scaling of the equitriangular lattice $A_2$ is universally optimal among all

Dmitry N. Kim, Or Hen, Gerald A. Miller, E. Piasetzky

The relationship between medium modifications of nuclear quark structure functions and medium modifications of elastic electromagnetic form factors is shown to be model dependent.

Glenn Bruns

Model checking has found a role in the engineering of reactive systems. However, model checkers are still strongly limited by the size of the system description they can check. Here we present a technique in which a system is simplified prior to model checking by the application of abstraction rules. The rules can greatly reduce the state space of a system d

Alessandro Duca, Eugenio Pozzoli

We address the small-time controllability problem for a nonlinear Schr\"odinger equation (NLS) on $\mathbb{R}^N$ in the presence of magnetic and electric external fields. We choose a particular framework where the equation becomes $i\partial_t \psi = [-\Delta+u_0(t)h_{\vec{0}}+\langle u(t), P\rangle +\kappa|\psi|^{2p}]\psi$. Here, the control operators are d

Anthony Brohan, Noah Brown, Justice Carbajal, Yevgen Chebotar

We study how vision-language models trained on Internet-scale data can be incorporated directly into end-to-end robotic control to boost generalization and enable emergent semantic reasoning. Our goal is to enable a single end-to-end trained model to both learn to map robot observations to actions and enjoy the benefits of large-scale pretraining on language

Lizhao Zhang

For any $n$-dimensional simplex in the Euclidean space $\mathbb{R}^n$ with $n\ge 4$, it is asked that if a continuous deformation preserves the volumes of all the codimension 2 faces, then is it necessarily a \emph{rigid} motion. While the question remains open and the general belief is that the answer is affirmative, for all $n\ge 4$, we provide counterexam

Guy RY Coleman, Matthew Kutugata, Michael J Walsh, Muthukumar Bagavathiannan

Many advanced, image-based precision agricultural technologies for plant breeding, field crop research, and site-specific crop management hinge on the reliable detection and phenotyping of plants across highly variable morphological growth stages. Convolutional neural networks (CNNs) have shown promise for image-based plant phenotyping and weed recognition,

T. de Oliveira, D. Harnett, R. Kleiv, A. Palameta

QCD Laplace sum-rules are used to examine the constituent mass spectrum of $J^P\in\{0^+,1^+\}$ heavy-light [Qq] diquarks with $Q\in\{c,b\}$ and $q\in\{u,d,s\}$. As in previous sum-rule studies, the negative parity $J^P\in\{0^-, 1^-\}$ [Qq] diquark mass predictions do not stabilize, so the sum-rule analysis focuses on positive parity [Qq] diquarks. Doubly-str

Eryk Kopczynski

In this paper we discuss computer simulations of de Sitter and anti de Sitter spacetimes, which are maximally symmetric, relativistic analogs of non-Euclidean geometries. We present prototype games played in these spacetimes; such games and visualizations can help the players gain intuition about these spacetimes. We discuss the technical challenges in creat

A. Antipov, W. Cole, K. Kalashnikov, F. Karimi

In this comment, we show that the model introduced in Hess et al. Phys. Rev. Lett. {\bf 130}, 207001 (2023) fails the topological gap protocol (TGP) (Pikulin et al., arXiv:2103.12217 and M. Aghaee et al., Phys. Rev. B 107, 245424 (2023)). In addition, we discuss this model in the broader context of how the TGP has been benchmarked.

T. Banks

We review ideas relating the breaking of Supersymmetry in de Sitter (dS) space-time to amplitudes in which gravitinos are reflected from the dS horizon. A self consistent evaluation of such amplitudes leads to the estimate $m_{3/2} = K \Lambda^{1/4}$, with a constant $K$ that is not easily calculable. LHC bounds on superpartner masses, plus the structure of

Teresa D'Aprile, Juncheng Wei, Lei Zhang

We are concerned with the existence of blowing-up solutions to the following boundary value problem $$-\Delta u= \lambda V(x) e^u-4\pi N \delta_0\;\mbox{ in } B_1,\quad u=0 \;\mbox{ on }\partial B_1,$$ where $B_1$ is the unit ball in $\mathbb R^2$ centered at the origin, $V(x)$ is a positive smooth potential, $N$ is a positive integer ($N\geq 1$). Here $\del

Zilin Ma, Yiyang Mei, Zhaoyuan Su

Conversational agents powered by large language models (LLM) have increasingly been utilized in the realm of mental well-being support. However, the implications and outcomes associated with their usage in such a critical field remain somewhat ambiguous and unexplored. We conducted a qualitative analysis of 120 posts, encompassing 2917 user comments, drawn f

Paul Kiefer, Riccardo Zuffetti

We study the injectivity of the Kudla-Millson lift of genus 2 Siegel cusp forms, vector-valued with respect to the Weil representation associated to an even lattice L. We prove that if L splits off two hyperbolic planes and is of sufficiently large rank, then the lift is injective. As an application, we deduce that the image of the lift in the degree 4 cohom

Khaled Jawhar, Evangelos Kranakis

Two autonomous mobile robots and a non-autonomous one, also called bike, are placed at the origin of an infinite line. The autonomous robots can travel with maximum speed $1$. When a robot rides the bike its speed increases to $v>1$, however only exactly one robot at a time can ride the bike and the bike is non-autonomous in that it cannot move on its own. A

Sérgio F. Chevtchenko, Elisson da Silva Rocha, Monalisa Cristina Moura Dos Santos, Ricardo Lins Mota

Anomaly detection is critical in the smart industry for preventing equipment failure, reducing downtime, and improving safety. Internet of Things (IoT) has enabled the collection of large volumes of data from industrial machinery, providing a rich source of information for Anomaly Detection. However, the volume and complexity of data generated by the Interne

Adam G. Riess, Gagandeep S. Anand, Wenlong Yuan, Stefano Casertano

High-resolution JWST observations can test confusion-limited HST observations for a photometric bias that could affect extragalactic Cepheids and the determination of the Hubble constant. We present JWST NIRCAM observations in two epochs and three filters of >330 Cepheids in NGC4258 (which has a 1.5% maser-based geometric distance) and in NGC5584 (host of SN

Joffrey Derchu, Dimitrios Kavvathas, Thibaut Mastrolia, Mathieu Rosenbaum

We study a toy two-player game for periodic double auction markets to generate liquidity. The game has imperfect information, which allows us to link market spreads with signal strength. We characterize Nash equilibria in cases with or without incentives from the exchange. This enables us to derive new insights about price formation and incentives design. We

Joan Bruna, Loucas Pillaud-Vivien, Aaron Zweig

Sparse high-dimensional functions have arisen as a rich framework to study the behavior of gradient-descent methods using shallow neural networks, showcasing their ability to perform feature learning beyond linear models. Amongst those functions, the simplest are single-index models $f(x) = \phi( x \cdot \theta^*)$, where the labels are generated by an arbit

Eryk Kopczynski

We prove the conjecture of Grosse-Kunstleve et al. that coordination sequences of periodic structures in n-dimensional Euclidean space are rational. This has been recently proven by Nakamura et al.; however, our proof is a straightforward application of classic techniques from automata theory.

Kopo M. Ramokapane, Lizzie Coles-Kemp, Nikhil Patnaik, Rui Huan

Ensuring equitable privacy experiences remains a challenge, especially for marginalised and vulnerable populations (MVPs) who often hesitate to participate or use digital services due to concerns about the privacy of their sensitive information. In response, security research has emphasised the importance of inclusive security and privacy practices to facili

Kaitlin Rasmussen, Jocelyne Chen, Rebecca L. Colquhoun, Sophia Frentz

Gender inequity is one of the biggest challenges facing the STEM workforce. While there are many studies that look into gender disparities within STEM and academia, the majority of these have been designed and executed by those unfamiliar with research in sociology and gender studies. They adopt a normative view of gender as a binary choice of 'male' or 'fem

Ayano Hiranaka, Minjune Hwang, Sharon Lee, Chen Wang

Reinforcement learning (RL) algorithms face significant challenges when dealing with long-horizon robot manipulation tasks in real-world environments due to sample inefficiency and safety issues. To overcome these challenges, we propose a novel framework, SEED, which leverages two approaches: reinforcement learning from human feedback (RLHF) and primitive sk

Fanglin Bao, Shubhankar Jape, Andrew Schramka, Junjie Wang

The resolution of optical imaging is limited by diffraction as well as detector noise. However, thermal imaging exhibits an additional unique phenomenon of ghosting which results in blurry and low-texture images. Here, we provide a detailed view of thermal physics-driven texture and explain why it vanishes in thermal images capturing heat radiation. We show

J. J. A. Houwman, D. Baillie, P. B. Blakie, G. Natale

The excitation spectrum of a cigar-shaped strongly dipolar quantum gas at the crossover from a Bose-Einstein condensate to a trapped macrodroplet is predicted to exhibit peculiar features - a strong upward shift of low momentum excitation energies together with a strong multi-band response for high momenta. By performing Bragg spectroscopy over a wide range

Slava Smartsev, Aaron Liberman, Igor A. Andriyash, Antoine Cavagna

We present a novel and straightforward approach for the spatio-spectral characterization of ultrashort pulses. This minimally intrusive method relies on placing a mask with specially arranged pinholes in the beam path before the focusing optic and retrieving the spectrally-resolved laser wavefront from the speckle pattern produced at focus. We test the effic

Durgakant Pushp, Junhong Xu, Lantao Liu

Biological agents, such as humans and animals, are capable of making decisions out of a very large number of choices in a limited time. They can do so because they use their prior knowledge to find a solution that is not necessarily optimal but good enough for the given task. In this work, we study the motion coordination of multiple drones under the above-m

Yu Liu, Zhixiang Hu, Xiao Tong, David Graf

We report a study of selenospinel Cu$_{6-x}$Fe$_{4+x}$Sn$_{12}$Se$_{32}$ ($x$ = 0, 1, 2) single crystals, which crystalize in a cubic structure with the $Fd\overline{3}m$ space group, and show typical semiconducting behavior. The large discrepancy between the activation energy for electrical conductivity $E_\rho$ (32.3 $\sim$ 69.8 meV), and for thermopower $

Zhongwei Zhang, David Bolin, Sebastian Engelke, Raphaël Huser

Moving average processes driven by exponential-tailed L\'evy noise are important extensions of their Gaussian counterparts in order to capture deviations from Gaussianity, more flexible dependence structures, and sample paths with jumps. Popular examples include non-Gaussian Ornstein--Uhlenbeck processes and type G Mat\'ern stochastic partial differential eq

Roger Proksch, Ryan Wagner, Joel Lefever

Accurate measurements of the nanoscale electromechanical coupling in materials, including piezo and ferroelectrics, twisted 2D layers, and biological systems is of both fundamental scientific and applied importance. Piezoresponse Force Microscopy (PFM) is capable of detecting strains in these materials, down to the picometer range. Following the emergence of

Md Abdul Aziz, Brittany Burdette, John Mayer

Laminations are a combinatorial and topological way to study Julia sets. Laminations give information about the structure of parameter space of degree $d$ polynomials with connected Julia sets. We first study fixed point portraits in laminations and their respective global count. Then, we investigate the correspondence between locally unicritical laminations

Sumit Asthana, Sagih Hilleli, Pengcheng He, Aaron Halfaker

Meetings play a critical infrastructural role in coordinating work. The recent surge of hybrid and remote meetings in computer-mediated spaces has led to new problems (e.g., more time spent in less engaging meetings) and new opportunities (e.g., automated transcription/captioning and recap support). Advances in dialogue summarization offer the potential for

Xin Li, Mohamed Al Begaowe, Shu Zhang, Benedetta Flebus

The non-Hermitian skin effect (NHSE) has emerged as a hallmark of non-Hermitian physics, with far-reaching implications for transport, topology, and sensing. While recent works have uncovered the NHSE in magnetic systems, these analyses rely on effective non-Hermitian Hamiltonians, thereby leaving open critical questions regarding their applicability and pre

Fatma Terzioglu, Emil Y. Sidky, Jp Phillips, Ingrid Reiser

Purpose: This study proposes a systematic method for determining the optimal x-ray tube settings/energy windows and fluence for minimal noise and maximum CNR in material density images obtained from DECT scans by fixing the subject size and the total radiation dose. Methods: The noise propagation in the process of sinogram and image reconstruction from DECT

A. Allahyari, E. Ebrahimian, R. Mondol, M. M. Sheikh-Jabbari

We continue the study of dipole cosmology framework put forward in \cite{Krishnan:2022qbv}, a beyond FLRW setting that has a preferred direction in the metric which may be associated with a cosmological tilt, a cosmic dipole. In this setup the shear and the tilt can be positive or negative given the dipole direction. We thoroughly analyze evolution of the un

JS Tan, Natalia Luka, Emily Mazo

Tech workers -- professional workers in the technology industry including software engineers, product managers, UX designers, etc. -- are not normally associated with labor activism. Yet, since 2017, we have seen a significant rise in labor actions among this group. Using an original dataset, we demonstrate how, in the case of tech workers, periods of intens

Bin Yang, Yuming Qin, Alain Miranville, Ke Wang

In this paper, we consider the asymptotic behavior of weak solutions for non-autonomous diffusion equations with delay in time-dependent spaces when the nonlinear function $f$ is critical growth, the delay term $g(t, u_t)$ contains some hereditary characteristics and the external force $h \in L_{l o c}^{2}\left(\mathbb{R} ; L^{2}(\Omega)\right)$. Firstly, we

Christoph Böhm, Timothy Buttsworth, Brian Clarke

Let $M$ be a smooth, compact manifold and let $\mathcal{N}_{\mu}$ denote the set of Riemannian metrics on $M$ with smooth volume density $\mu$. For a given $g_0\in \mathcal{N}_{\mu}$, we show that if $\dim(M)\ge 5$, then there exists an open and dense subset $\mathcal{Y}_{g_0} \subset T_{g_0} \mathcal{N}_{\mu}$ (in the $C^{\infty}$ topology) so that for each

Amir Samadi, Amir Shirian, Konstantinos Koufos, Kurt Debattista

A CF explainer identifies the minimum modifications in the input that would alter the model's output to its complement. In other words, a CF explainer computes the minimum modifications required to cross the model's decision boundary. Current deep generative CF models often work with user-selected features rather than focusing on the discriminative features

Spencer Hutchinson, Berkay Turan, Mahnoosh Alizadeh

In societal-scale infrastructures, such as electric grids or transportation networks, pricing mechanisms are often used as a way to shape users' demand in order to lower operating costs and improve reliability. Existing approaches to pricing design for safety-critical networks often require that users are queried beforehand to negotiate prices, which has pro

Katsuki Kinjo, Hiroki Fujibayashi, Hiroki Matsumura, Fumiya Hori

Superconducting (SC) state has spin and orbital degrees of freedom, and spin-triplet superconductivity shows multiple SC phases due to the presence of these degrees of freedom. However, the observation of spin-direction rotation occurring inside the SC state (SC spin rotation) has hardly been reported. UTe2, a recently discovered topological superconductor,

Paloma R. Casale, J. E. Amaro, M. B. Barbaro

We present a model that incorporates the effect of two-body currents in quasielastic electron-nucleus scattering within the framework of a consistent superscaling formalism. This is achieved by defining an averaged single-nucleon hadronic tensor based on the 1p1h matrix element of the one-body current plus meson-exchange currents (MEC). The consistent treatm

Xiuping Wang, Huangxin Chen, Jisheng Kou, Shuyu Sun

We propose an unconditionally energy-stable, orthonormality-preserving, component-wise splitting iterative scheme for the Kohn-Sham gradient flow based model in the electronic structure calculation. We first study the scheme discretized in time but still continuous in space. The component-wise splitting iterative scheme changes one wave function at a time, s

Jessica S. Li, Carlos J. Vargas, Donal O'Sullivan, Erika Hamden

The recent discovery of enormous Ly$\alpha$ nebulae (ELANe), characterized by physical extents $>200$ kpc and Ly$\alpha$ luminosities $>10^{44}$ erg s$^{-1}$, provide a unique opportunity to study the intergalactic and circumgalactic medium (IGM/CGM) in distant galaxies. Many existing ELANe detections are associated with local overdensities of active galacti

Vasiliy Usatyuk, Sergey Egorov, Denis Sapozhnikov

The paper introduces the application of information geometry to describe the ground states of Ising models by utilizing parity-check matrices of cyclic and quasi-cyclic codes on toric and spherical topologies. The approach establishes a connection between machine learning and error-correcting coding. This proposed approach has implications for the developmen

Colin S. Gordon, Chaewon Yun

We describe a new concrete approach to giving predictable error locations for sequential (flow-sensitive) effect systems. Prior implementations of sequential effect systems rely on either computing a bottom-up effect and comparing it to a declaration (e.g., method annotation) or leaning on constraint-based type inference. These approaches do not necessarily

Micheal Abaho, Yousef H. Alfaifi

Injecting textual information into knowledge graph (KG) entity representations has been a worthwhile expedition in terms of improving performance in KG oriented tasks within the NLP community. External knowledge often adopted to enhance KG embeddings ranges from semantically rich lexical dependency parsed features to a set of relevant key words to entire tex

Corrado Coppola, Giampaolo Liuzzi, Laura Palagi

The supervised training of a deep neural network on a given dataset consists in the unconstrained minimization of the finite sum of continuously differentiable functions, commonly referred to as loss with respect to the samples. These functions depend on the network parameters and most of the times are non-convex. We develop CMA Light, a globally convergent

David E. Tyler, Mengxi Yi, Klaus Nordhausen

We introduce a class of regularized M-estimators of multivariate scatter and show, analogous to the popular spatial sign covariance matrix (SSCM), that they possess high breakdown points. We also show that the SSCM can be viewed as an extreme member of this class. Unlike the SSCM, this class of estimators takes into account the shape of the contours of the d

Yanfang Liu, Guohao Dai, Wei W. Xing

Being able to efficiently obtain an accurate estimate of the failure probability of SRAM components has become a central issue as model circuits shrink their scale to submicrometer with advanced technology nodes. In this work, we revisit the classic norm minimization method. We then generalize it with infinite components and derive the novel optimal manifold

Ronald DeVore, Robert D. Nowak, Rahul Parhi, Jonathan W. Siegel

We investigate the approximation of functions $f$ on a bounded domain $\Omega\subset \mathbb{R}^d$ by the outputs of single-hidden-layer ReLU neural networks of width $n$. This form of nonlinear $n$-term dictionary approximation has been intensely studied since it is the simplest case of neural network approximation (NNA). There are several celebrated approx

Thomas McGrath, Matthew Rahtz, Janos Kramar, Vladimir Mikulik

We investigate the internal structure of language model computations using causal analysis and demonstrate two motifs: (1) a form of adaptive computation where ablations of one attention layer of a language model cause another layer to compensate (which we term the Hydra effect) and (2) a counterbalancing function of late MLP layers that act to downregulate

Jingwei Ni, Julia Bingler, Chiara Colesanti-Senni, Mathias Kraus

In the face of climate change, are companies really taking substantial steps toward more sustainable operations? A comprehensive answer lies in the dense, information-rich landscape of corporate sustainability reports. However, the sheer volume and complexity of these reports make human analysis very costly. Therefore, only a few entities worldwide have the

Kai Huang, Edward Schwartz, Ding-Fu Shao, Alexey A. Kovalev

Magnetic skyrmions and antiskyrmions are topologically protected quasiparticles exhibiting a whirling spin texture in real space. Antiskyrmions offer some advantages over skyrmions as they are expected to have higher stability and can be electrically driven with no transverse motion. However, unlike the widely investigated skyrmions, antiskyrmions are rarely

Sulyab Thottungal Valapu, Tamoghna Sarkar, Jared Coleman, Anusha Avyukt

We introduce DARSAN, a decentralized review system designed for Non-Fungible Token (NFT) marketplaces, to address the challenge of verifying the quality of highly resalable products with few verified buyers by incentivizing unbiased reviews. DARSAN works by iteratively selecting a group of reviewers (called ``experts'') who are likely to both accurately pred

Kenneth M. Rudinger, Corey I. Ostrove, Stefan K. Seritan, Matthew D. Grace

Gate set tomography (GST) is a self-consistent and highly accurate method for the tomographic reconstruction of a quantum information processor's quantum logic operations, including gates, state preparations, and measurements. However, GST's experimental cost grows exponentially with qubit number. For characterizing even just two qubits, a standard GST exper

Sunil Subedi, Bidur Poudel, Pooja Aslami, Robert Fourney

This research focuses on the evolving dynamics of the power grid, where traditional synchronous generators are being replaced by non-synchronous power electronic converter (PEC)-interfaced renewable energy sources. The non-linear dynamics must be accurately modeled to ensure the stability of future converter-dominated power systems (CDPS). However, obtaining

Anuj Chaudhri

This study focuses on trying to understand the flow of argon inside carbon nanotubes. The methodology of molecular dynamics and its implementation as a tool to effectively model fluid flows inside nanocomponents is established, followed by an understanding of the intermolecular potentials which effectively model the interactions between the argon and carbon

Pablo Robles-Granda, Katherine Tsai, Oluwasanmi Koyejo

Probabilistic generative models of graphs are important tools that enable representation and sampling. Many recent works have created probabilistic models of graphs that are capable of representing not only entity interactions but also their attributes. However, given a generative model of random attributed graph(s), the general conditions that establish goo

Yunus Emre Demirci, Serdar Yüksel

We present a reachability based approach to establish unique ergodicity of non-linear filter processes where state space of a hidden Markov model is a compact Polish metric space and the observation space is a Polish metric space. We also establish a weak convergence result on occupation measures under such a reachability condition. Our conditions, which are

Denton S. Ebel, Conel M. O'D. Alexander

The origin of Mercury's anomalous core and low FeO surface mineralogy are outstanding questions in planetary science. Mercury's composition may result from cosmochemical controls on the precursor solids that accreted to form Mercury. High temperatures and enrichment in solid condensates are likely conditions near the midplane of the inner solar protoplanetar

J. Martin Laming, Elena Provornikova, Yuan-Kuen Ko

We model the observed charge states of the elements C, O, Mg, Si, and Fe in the coronal mass ejections (CMEs) ejecta. We concentrate on "halo" CMEs observed in situ by ACE/SWICS to measure ion charge states, and also remotely by STEREO when in near quadrature with Earth, so that the CME expansion can be accurately specified. Within this observed expansion, w

CMS Collaboration

A search for new physics in top quark production with additional final-state leptons is performed using data collected by the CMS experiment in proton-proton collisions at $\sqrt{s}$ = 13 TeV at the LHC during 2016-2018. The data set corresponds to an integrated luminosity of 138 fb$^{-1}$. Using the framework of effective field theory (EFT), potential new p

Johannes Herms, Sudip Jana, Vishnu P. K., Shaikh Saad

We present a minimal sub-GeV thermal Dark Matter (DM) model where the DM primarily interacts with neutrinos and participates in neutrino mass generation through quantum loop corrections at one-loop level. We discuss the challenges in achieving this in the scotogenic framework and identify a viable variant. Due to minimality and the interplay between obtainin

Xiangyun Lei, Edward Kim, Viktoriia Baibakova, Shijing Sun

Natural Language Processing (NLP), a cornerstone field within artificial intelligence, has been increasingly utilized in the field of materials science literature. Our study conducts a reproducibility analysis of two pioneering works within this domain: "Machine-learned and codified synthesis parameters of oxide materials" by Kim et al., and "Unsupervised wo

G. Yu. Prokhorov, O. V. Teryaev, V. I. Zakharov

By chiral effects one understands manifestations of chiral gauge anomaly and of gravitational chiral anomaly in hydrodynamics. In recent two-three years our understanding of the chiral effects has considerably changed. Here we present mini-review of two topics. First, shift in understanding symmetry which underlies the chiral magnetic effect and, second, int

Boris Kunyavskii, Eugene Plotkin, Nikolai Vavilov

In this paper we establish a definitive result which almost completely closes the problem of bounded elementary generation for Chevalley groups of rank $\ge 2$ over arbitrary Dedekind rings $R$ of arithmetic type, with uniform bounds. Namely, we show that for every reduced irreducible root system $\Phi$ of rank $\ge 2$ there exists a universal bound $L=L(\Ph

Hector Carmenate, Paul Bosch, Juan E. Nápoles, José M. Sigarreta

In this paper we propose and solve a generalization of the Bernoulli Differential Equation, by means of a generalized fractional derivative. First we prove a generalization of Gronwall's inequality, which is useful for studying the stability of systems of fractional differential equations and we state results about the qualitative behavior of the trivial sol

Abinand Gopal, Vladimir Rokhlin

We introduce an efficient scheme for the construction of quadrature rules for bandlimited functions. While the scheme is predominantly based on well-known facts about prolate spheroidal wave functions of order zero, it has the asymptotic CPU time estimate $O(n log n)$ to construct an n-point quadrature rule. Moreover, the size of the ``$n log n$'' term in th

The LZ Collaboration, J. Aalbers, D. S. Akerib, A. K. Al Musalhi

The LUX-ZEPLIN (LZ) experiment is a dark matter detector centered on a dual-phase xenon time projection chamber. We report searches for new physics appearing through few-keV-scale electron recoils, using the experiment's first exposure of 60 live days and a fiducial mass of 5.5t. The data are found to be consistent with a background-only hypothesis, and limi

Vidhita Jagwani, Smit Meghani, Krishna Pai, Sudhir Dhage

In this paper, we propose a method for resume rating using Latent Dirichlet Allocation (LDA) and entity detection with SpaCy. The proposed method first extracts relevant entities such as education, experience, and skills from the resume using SpaCy's Named Entity Recognition (NER). The LDA model then uses these entities to rate the resume by assigning topic

Yisu Remy Wang

Since the inception of SQL, nulls have frustrated database users and builders alike. Those writing SQL must painstakingly guard their queries against surprising results caused by nulls, while those building database engines constantly struggle to implement the subtle semantics of 3-valued logic. Given that the relational model already provides a way to repre

Alfonso Di Bartolo, Gianmarco La Rosa

The authors of this article intend to present some results obtained in the study of biderivations of complete Lie algebras. Firstly they present a matricial approach to do this, which was a useful and explanatory tool not only in the study of biderivations but also in the synthesis of these results. Then they study all biderivations of a Lie algebra $L$ with

Julian Ebelt, Sven Krippendorf, Andreas Schachner

In this note we explore the distribution of vacuum expectation values of the superpotential $W_0$ in explicit Type IIB flux compactifications. We show that the distribution can be approximated, universally across geometries, by a two-dimensional Gaussian with a model dependent standard deviation. We identify this behaviour in 20 Calabi-Yau orientifold compac

S. Berta, F. Stanley, D. Ismail, P. Cox

The z-GAL survey observed 137 bright Herschel-selected targets with the IRAM NOrthern Extended Millimeter Array, with the aim to measure their redshift and study their properties. Several of them have been resolved into multiple sources. Consequently, robust spectroscopic redshifts have been measured for 165 individual galaxies in the range 0.8<z<6.5. In thi

D. Ismail, A. Beelen, V. Buat, S. Berta

(Abridged) We present the dust properties of 125 bright Herschel galaxies selected from the z-GAL survey. The large instantaneous bandwidth of NOEMA provides an exquisite sampling of the underlying dust continuum emission at 2 and 3 mm in the observed frame, with flux densities in at least four side bands for each source. Together with the available Herschel

Wenqian Sun, Cody Rasmussen, Roman Vetter, Jayson Paulose

Orthotropic shell structures are ubiquitous in biology and engineering, from bacterial cell walls to reinforced domes. We present a rescaling transformation that maps an orthotropic shallow shell to an isotropic one with a different local geometry. The mapping is applicable to any shell section for which the material orthotropy directions match the principal

Nandita Naik, Christopher Potts, Elisa Kreiss

Visual question answering (VQA) has the potential to make the Internet more accessible in an interactive way, allowing people who cannot see images to ask questions about them. However, multiple studies have shown that people who are blind or have low-vision prefer image explanations that incorporate the context in which an image appears, yet current VQA dat

Nathaniel Bottman, Y. Cooper, Antonio Lerario

What neural networks learn depends fundamentally on the geometry of the underlying loss function. We study how different regularizers affect the geometry of this function. One of the most basic geometric properties of a smooth function is whether it is Morse or not. For nonlinear deep neural networks, the unregularized loss function $L$ is typically not Mors

Martine Schut, Andrew Geraci, Sougato Bose, Anupam Mazumdar

The quantum gravity-induced entanglement of masses (QGEM) protocol for testing quantum gravity using entanglement witnessing utilizes the creation of spatial quantum superpositions of two neutral, massive matter-wave interferometers kept adjacent to each other, separated by a distance d. The mass and the spatial superposition should be such that the two quan

Nathaniel Craig, Yu-Tse Lee

We develop a generalized field space geometry for higher-derivative scalar field theories, expressing scattering amplitudes in terms of a covariant geometry on the all-order jet bundle. The incorporation of spacetime and field derivative coordinates solves complications due to higher-order derivatives faced by existing approaches to field space geometry. We

Danny Horta, Emily C. Cunningham, Robyn Sanderson, Kathryn V. Johnston

Observational studies are finding stars believed to be relics of the earliest stages of hierarchical mass assembly of the Milky Way (i.e., proto-Galaxy). In this work, we contextualize these findings by studying the masses, ages, spatial distributions, morphology, kinematics, and chemical compositions of proto-galaxy populations from the 13 Milky Way (MW)-ma

Claire S. Ye, Kyle Kremer, Scott M. Ransom, Frederic A. Rasio

Globular clusters (GCs) are particularly efficient at forming millisecond pulsars. Among these pulsars, about half lack a companion star, a significantly higher fraction than in the Galactic field. This fraction increases further in some of the densest GCs, especially those that have undergone core collapse, suggesting that dynamical interaction processes pl

Max Jaarsma, Yibei Li, Ian Moult, Wouter J. Waalewijn

Energy correlators measured inside high-energy jets at hadron colliders have recently been demonstrated to provide a new window into both perturbative and non-perturbative Quantum Chromodynamics. A number of the most interesting features of these correlators, namely their universal scaling behavior and the ability to image the confinement transition, require

P. Rosenberg, D. Sénéchal, A. -M. S. Tremblay, M. Charlebois

Two of the primary sources of error in the Cluster dynamical mean-field theory (CDMFT) technique arise from the use of finite size clusters and finite size baths, which makes the development of impurity solvers that can treat larger systems an essential goal. In this work we introduce an impurity solver based on the recently developed dynamical variational M

Andrzej J. Buras

We summarize the status of the Kaon Theory 50 years after the seminal paper of Kobayashi and Maskawa who pointed out that six quarks are necessary to have CP violation in the Standard Model (SM) and presented a parametrization of a $3\times 3$ unitary matrix that after the discovery of the charm quark in 1974 and the $b$ quark in 1977 dominated the field of

Thomas Schwemberger, Volodymyr Takhistov, Tien-Tien Yu

Next generation direct dark matter (DM) detection experiments will have unprecedented capabilities to explore coherent neutrino-nucleus scattering (CE$\nu$NS) complementary to dedicated neutrino experiments. We demonstrate that future DM experiments can effectively probe nonstandard neutrino interactions (NSI) mediated by scalar fields in the scattering of s