July 2022 arXiv papers — page 119

Charles E. Thornton, R. Michael Buehrer, Anthony F. Martone

A key component of cognitive radar is the ability to generalize, or achieve consistent performance across a range of sensing environments, since aspects of the physical scene may vary over time. This presents a challenge for learning-based waveform selection approaches, since transmission policies which are effective in one scene may be highly suboptimal in

Jiyoun Randolph, Md Jobair Hossain Faruk, Hossain Shahriar, Maria Valero

In teleradiology, medical images are transmitted to offsite radiologists for interpretation and the dictation report is sent back to the original site to aid timely diagnosis and proper patient care. Although teleradiology offers great benefits including time and cost efficiency, after-hour coverages, and staffing shortage management, there are some technica

Mohammad Masum, Hossain Shahriar, Hisham Haddad, Md Jobair Hossain Faruk

Traditional network intrusion detection approaches encounter feasibility and sustainability issues to combat modern, sophisticated, and unpredictable security attacks. Deep neural networks (DNN) have been successfully applied for intrusion detection problems. The optimal use of DNN-based classifiers requires careful tuning of the hyper-parameters. Manually t

John R. Kender, Bishwaranjan Bhattacharjee, Parijat Dube, Brian Belgodere

Transfer learning is a deep-learning technique that ameliorates the problem of learning when human-annotated labels are expensive and limited. In place of such labels, it uses instead the previously trained weights from a well-chosen source model as the initial weights for the training of a base model for a new target dataset. We demonstrate a novel but gene

Glen Bigan Mbeng, Wolfgang Lechner

Approximate counterdiabatic (CD) protocols are a powerful tool to enhance quantum adiabatic processes that allow to reliably manipulate quantum systems on short time scales. However, implementing CD protocols entails the introduction of additional control fields in the Hamiltonian, often associated with highly non-local multi-body interactions. Here, we intr

Omer San, Suraj Pawar, Adil Rasheed

A central challenge in the computational modeling and simulation of a multitude of science applications is to achieve robust and accurate closures for their coarse-grained representations due to underlying highly nonlinear multiscale interactions. These closure models are common in many nonlinear spatiotemporal systems to account for losses due to reduced or

Suhong Moon, Domas Buracas, Seunghyun Park, Jinkyu Kim

A number of recent self-supervised learning methods have shown impressive performance on image classification and other tasks. A somewhat bewildering variety of techniques have been used, not always with a clear understanding of the reasons for their benefits, especially when used in combination. Here we treat the embeddings of images as point particles and

John C. Barentine

Ground-based optical astronomy necessarily involves sensing the light of astronomical objects along with the contributions of many natural sources ranging from the Earth's atmosphere to cosmological light. In addition, astronomers have long contended with artificial light pollution that further adds to the 'background' against which astronomical objects are

Zhiwei Peng, John F. Brady

In microrheology, the local rheological properties such as viscoelasticity of a complex fluid are inferred from the free or forced motion of embedded colloidal probe particles. Theoretical machinery developed for forced-probe microrheology of colloidal suspensions focused on either constant-force (CF) or constant-velocity (CV) probes while in experiments nei

Jyotirmoy Sau, S. R. Hassan, Nitesh Kumar, Manoranjan Kumar

Ferromagnetic (FM) semimetals Fe$_n$GeTe$_2$(n=3, 4, 5), exhibit several symmetry-protected band-crossing points or lines near the Fermi energy (E$_F$) and these topological properties of energy bands lead to interesting transport properties. We study these materials employing the first-principle calculations and the tight-binding Hamiltonian constructed by

Omer San, Suraj Pawar, Adil Rasheed

In this paper, we introduce a decentralized digital twin (DDT) framework for dynamical systems and discuss the prospects of the DDT modeling paradigm in computational science and engineering applications. The DDT approach is built on a federated learning concept, a branch of machine learning that encourages knowledge sharing without sharing the actual data.

Josh Meyer, David Ifeoluwa Adelani, Edresson Casanova, Alp Öktem

BibleTTS is a large, high-quality, open speech dataset for ten languages spoken in Sub-Saharan Africa. The corpus contains up to 86 hours of aligned, studio quality 48kHz single speaker recordings per language, enabling the development of high-quality text-to-speech models. The ten languages represented are: Akuapem Twi, Asante Twi, Chichewa, Ewe, Hausa, Kik

Deli Li, Yu Miao, Yongcheng Qi

Let $\{X, X_{n}; n \geq 1\}$ be a sequence of i.i.d. non-degenerate real-valued random variables with $\mathbb{E}X^{2} < \infty$. Let $S_{n} = \sum_{i=1}^{n} X_{i}$, $n \geq 1$. Let $g(\cdot): ~[0, \infty) \rightarrow [0, \infty)$ be a nondecreasing regularly varying function with index $\rho \geq 0$ and $\lim_{t \rightarrow \infty} g(t) = \infty$. Let $\mu

Salvatore D. Pace, Xiao-Gang Wen

We consider compact $U^\kappa(1)$ gauge theory in 3+1D with the $2\pi$-quantized topological term ${\sum_{I, J =1}^\kappa\frac{K_{IJ}}{4\pi}\int_{M^4}F^I\wedge F^J}$. At energies below the gauge charges' gaps but above the monopoles' gaps, this field theory has an emergent ${\mathbb{Z}_{k_1}^{(1)}\times\mathbb{Z}_{k_2}^{(1)}\times\cdots}$ 1-symmetry, where $

Moein Shakeri, Hong Zhang

This paper is concerned with specular reflection removal based on tensor low-rank decomposition framework with the help of polarization information. Our method is motivated by the observation that the specular highlight of an image is sparsely distributed while the remaining diffuse reflection can be well approximated by a linear combination of several disti

Jan Haskovec, Peter Markowich, Simone Portaro

We study self-regulating processes modeling biological transportation networks. Firstly, we write the formal $L^2$-gradient flow for the symmetric tensor valued diffusivity $D$ of a broad class of entropy dissipations associated with a purely diffusive model. The introduction of a prescribed electric potential leads to the Fokker-Planck equation, for whose e

Ivan Oreshnikov, Oliver Melchert, Stephanie Willms, Surajit Bose

For waveguides with two separate regions of anomalous dispersion, it is possible to create a quasi-stable two-color solitary wave. In this paper we consider how those waves interact with dispersive radiation, both generation of Cherenkov radiation and scattering of incident dispersive waves. We derive the analytic resonance conditions and verify them through

Alexis Rapin, Maroun Bou Sleiman, Johan Auwerx

Human life expectancy has dramatically improved over the course of the last century. Although this reflects a global improvement in sanitation and medical care, this also implies that more people suffer from diseases that typically manifest later in life, like Alzheimer and atherosclerosis. Increasing healthspan by delaying or reverting the development of th

Qihao Peng, Zhiyu Xiang, YuanGang Fan, Tengqi Zhao

As a fundamental task for intelligent robots, visual SLAM has made great progress over the past decades. However, robust SLAM under highly weak-textured environments still remains very challenging. In this paper, we propose a novel visual SLAM system named RWT-SLAM to tackle this problem. We modify LoFTR network which is able to produce dense point matching

Rodrigo Leal Martir, María José Sánchez, Myriam Aguirre, Walter Quiñonez

Memristors are expected to be one of the key building blocks for the development of new bio-inspired nanoelectronics. Memristive effects in transition metal oxides are usually linked to the electromigration at the nanoscale of charged oxygen vacancies (OV). In this paper we address, for Pt/TiOx/TaOy/Pt devices, the exchange of OV between the device and the e

N. Brouillet, D. Despois, J. Molet, T. Nony

W43-MM1 is a young region, very rich in terms of high-mass star formation. We aim to systematically identify the massive cores which contain a hot core and compare their molecular composition. We used ALMA high-spatial resolution (2500 au) data of W43-MM1 to identify line-rich protostellar cores and make a comparative study of their temperature and molecular

Md Jobair Hossain Faruk, Sharaban Tahora, Masrura Tasnim, Hossain Shahriar

The promise of quantum computing is not speeding up conventional computing rather delivering an exponential advantage for certain classes of problems, with profound implications for cybersecurity for instance. With the advent and development of quantum computers, cyberspace security can surely become the most critical problem for the Internet in near future.

Sebastian Casalaina-Martin, Samuel Grushevsky, Klaus Hulek, Radu Laza

The moduli space of complex cubic surfaces has three different, but isomorphic, compact realizations: as a GIT quotient, as a Baily--Borel compactification of a ball quotient, and as a compactified $K$-moduli space. From all three perspectives, there is a unique boundary point corresponding to non-stable surfaces. From the GIT point of view, to deal with thi

Brian Welch, Dan Coe, Adi Zitrin, Jose M. Diego

Detailed observations of star forming galaxies at high redshift are critical to understand the formation and evolution of the earliest galaxies. Gravitational lensing provides an important boost, allowing observations at physical scales unreachable in unlensed galaxies. We present three lensed galaxies from the RELICS survey at $z_{phot} = 6 - 10$, including

Pierfrancesco Dionigi, Diego Garlaschelli, Rajat Subhra Hazra, Frank den Hollander

A Chung-Lu random graph is an inhomogeneous Erd\H{o}s-R\'enyi random graph in which vertices are assigned average degrees, and pairs of vertices are connected by an edge with a probability that is proportional to the product of their average degrees, independently for different edges. We derive a central limit theorem for the principal eigenvalue and the com

Matteo Bettini, Ryan Kortvelesy, Jan Blumenkamp, Amanda Prorok

While many multi-robot coordination problems can be solved optimally by exact algorithms, solutions are often not scalable in the number of robots. Multi-Agent Reinforcement Learning (MARL) is gaining increasing attention in the robotics community as a promising solution to tackle such problems. Nevertheless, we still lack the tools that allow us to quickly

Md Jobair Hossain Faruk, Shashank Trivedi, Mohammad Masum, Maria Valero

People's personal hygiene habits speak volumes about the condition of taking care of their bodies and health in daily lifestyle. Maintaining good hygiene practices not only reduces the chances of contracting a disease but could also reduce the risk of spreading illness within the community. Given the current pandemic, daily habits such as washing hands or ta

Marco Farinati

In \cite{F} there is a statement generalizing the results in \cite{FG}. Unfortunately there is a mistake in a computation that affects the main result. I don't know if the main result in \cite{F} is true or not, but I propose an alternative statement (Theorem 3.7) that was actually the main motivation in \cite{FG}. This statement answers in an affirmative wa

Oscar Fuentes-Muñoz, Alex J. Meyer, Daniel J. Scheeres

The propagation of small bodies in the Solar system is driven by the combination of planetary encounters that cause abrupt changes in their orbits and secular long-term perturbations. We propose a propagation strategy that combines both of these effects into a single framework for long-term, rapid propagation of small bodies in the inner Solar System. The an

Yi Zhang, Robert W. Heath

In this paper, we develop algorithms for joint user scheduling and three types of mmWave link configuration: relay selection, codebook optimization, and beam tracking in millimeter wave (mmWave) networks. Our goal is to design an online controller that dynamically schedules users and configures their links to minimize the system delay. To solve this complex

Ryan Shivers, Mohammad Ashiqur Rahman, Md Jobair Hossain Faruk, Hossain Shahriar

Ride-hailing and ride-sharing applications have recently gained popularity as a convenient alternative to traditional modes of travel. Current research into autonomous vehicles is accelerating rapidly and will soon become a critical component of a ride-hailing platforms architecture. Implementing an autonomous vehicle ride-hailing platform proves a difficult

Ezra Tal, Gilhyun Ryou, Sertac Karaman

This paper proposes a novel algorithm for aerobatic trajectory generation for a vertical take-off and landing (VTOL) tailsitter flying wing aircraft. The algorithm differs from existing approaches for fixed-wing trajectory generation, as it considers a realistic six-degree-of-freedom (6DOF) flight dynamics model, including aerodynamics equations. Using a glo

Mikail Khona, Sarthak Chandra, Joy J. Ma, Ila Fiete

Recurrent neural networks (RNNs) are often used to model circuits in the brain, and can solve a variety of difficult computational problems requiring memory, error-correction, or selection [Hopfield, 1982, Maass et al., 2002, Maass, 2011]. However, fully-connected RNNs contrast structurally with their biological counterparts, which are extremely sparse (~0.1

Oleksandr Ferludin, Arno Eigenwillig, Martin Blais, Dustin Zelle

TensorFlow-GNN (TF-GNN) is a scalable library for Graph Neural Networks in TensorFlow. It is designed from the bottom up to support the kinds of rich heterogeneous graph data that occurs in today's information ecosystems. In addition to enabling machine learning researchers and advanced developers, TF-GNN offers low-code solutions to empower the broader deve

Abhishek Jha, Carlo Sanna

Let $\mathcal{A}$ be the set of all integers of the form $\gcd(n, F_n)$, where $n$ is a positive integer and $F_n$ denotes the $n$th Fibonacci number. Leonetti and Sanna proved that $\mathcal{A}$ has natural density equal to zero, and asked for a more precise upper bound. We prove that \begin{equation*} \#\big(\mathcal{A} \cap [1, x]\big) \ll \frac{x \log \l

Yunsheng Li, Yinpeng Chen, Xiyang Dai, Dongdong Chen

The complexity-precision trade-off of an object detector is a critical problem for resource constrained vision tasks. Previous works have emphasized detectors implemented with efficient backbones. The impact on this trade-off of proposal processing by the detection head is investigated in this work. It is hypothesized that improved detection efficiency requi

Thomas M Bendall, Golo A Wimmer

Within finite element models of fluids, vector-valued fields such as velocity or momentum variables are commonly discretised using the Raviart-Thomas elements. However, when using the lowest-order quadrilateral Raviart-Thomas elements, standard finite element discretisations of the vector transport equation typically have a low order of spatial accuracy. Thi

Łukasz Janeczko, Piotr Faliszewski

Over the last few years, researchers have put significant effort into understanding of the notion of proportional representation in committee election. In particular, recently they have proposed the notion of proportionality degree. We study the complexity of computing committees with a given proportionality degree and of testing if a given committee provide

Kin G. Olivares, Azul Garza, David Luo, Cristian Challú

Large collections of time series data are commonly organized into structures with different levels of aggregation; examples include product and geographical groupings. It is often important to ensure that the forecasts are coherent so that the predicted values at disaggregate levels add up to the aggregate forecast. The growing interest of the Machine Learni

Haochuan Li, Lawrence Widrow

We simultaneously model the gravitational potential and phase space distribution function (DF) of giant stars near the Sun using the {\it Gaia} DR2 radial velocity catalog. We assume that the Galaxy is in equilibrium and is symmetric about both the spin axis of the disk and the Galactic midplane. The potential is taken as a sum of terms that nominally repres

Oliver Franke, Dumitru Călugăru, Andreas Nunnenkamp, Johannes Knolle

The honeycomb magnet $\alpha-$RuCl$_3$ is a prime candidate material for realizing the Kitaev quantum spin liquid (QSL), but it shows long-range magnetic order at low temperature. Nevertheless, its broad inelastic neutron scattering (INS) response at finite frequency has been interpreted as that of a 'proximate QSL'. A moderate in-plane magnetic field indeed

Enrique Moreno Méndez, Fabio De Colle, Diego López Cámara, Alejandro Vigna-Gómez

Hydrodynamic studies of stellar-mass compact objects (COs) in a common envelope (CE)have shown that the accretion rate onto the CO is a few orders of magnitude below the Bondi-Hoyle-Lyttleton (BHL) estimate. This is several orders of magnitude above the Eddington limit and above the limit for neutrino-cooled accretion (i.e., hypercritical accretion, or HCA).

Kira Maag, Matthias Rottmann

State-of-the-art deep neural networks demonstrate outstanding performance in semantic segmentation. However, their performance is tied to the domain represented by the training data. Open world scenarios cause inaccurate predictions which is hazardous in safety relevant applications like automated driving. In this work, we enhance semantic segmentation predi

Eitan Levin, Joe Kileel, Nicolas Boumal

We develop new tools to study landscapes in nonconvex optimization. Given one optimization problem, we pair it with another by smoothly parametrizing the domain. This is either for practical purposes (e.g., to use smooth optimization algorithms with good guarantees) or for theoretical purposes (e.g., to reveal that the landscape satisfies a strict saddle pro

Lorenzo Ricci, Marc Riembau

Energy correlators are field-theoretically clean and phenomenologically valuable probes of QCD dynamics. We explore the possibility of using the information encoded in the energy correlators of a hadronically decaying electroweak vector boson in order to extract its full decay density matrix. The kinematics of the one- and two-point energy correlators can in

Pierre Auclair, Simone Blasi, Vedran Brdar, Kai Schmitz

Cosmic strings are predicted by many Standard Model extensions involving the cosmological breaking of a symmetry with nontrivial first homotopy group and represent a potential source of primordial gravitational waves (GWs). Present efforts to model the GW signal from cosmic strings are often based on minimal models, such as, eg, the Nambu--Goto action that d

Zejiang Hou, Julian Salazar, George Polovets

Large pretrained language models (PLMs) are often domain- or task-adapted via fine-tuning or prompting. Finetuning requires modifying all of the parameters and having enough data to avoid overfitting while prompting requires no training and few examples but limits performance. Instead, we prepare PLMs for data- and parameter-efficient adaptation by learning

Javier Roulet, Seth Olsen, Jonathan Mushkin, Tousif Islam

Quasicircular binary black hole mergers are described by 15 parameters, of which gravitational wave observations can typically constrain only $\sim 10$ independent combinations to varying degree. In this work, we devise coordinates that remove correlations, and disentangle well- and poorly-measured quantities. Additionally, we identify approximate discrete s

Brayden R. Hull, Robert B. Mann

We show that asymptotically de Sitter black holes of negative mass can exist in Lovelock gravity. Such black holes have horizon geometries with non-constant curvature and are known as Exotic Black Holes. We explicitly examine the case of Gauss-Bonnet gravity. We briefly discuss the positive mass case where we show how the transverse space geometry affects wh

Sut-Ieng Tam, Keiichi Umetsu, Andrew Robertson, Ian G. McCarthy

The radial acceleration relation (RAR) represents a tight empirical relation between the inferred total and baryonic centripetal accelerations, $g_{\rm{tot}}=GM_{\rm{tot}}(<r)/r^2$ and $g_{\rm{bar}}=GM_{\rm{bar}}(<r)/r^2$, observed in galaxies and galaxy clusters. The tight correlation between these two quantities can provide insight into the nature of dark

Masoumeh Tavakoli, Jerry Wu, Robert B. Mann

We present the first examples in black hole thermodynamics of multicritical phase transitions, in which more than three distinct black hole phases merge at a critical point. Working in the context of non-linear electrodynamics, we explicitly present examples of black hole quadruple and quintuple points, and demonstrate how $n$-tuple critical points can be ob

Claire S. Ye, Giacomo Fragione

The number of millisecond pulsars (MSPs) observed in Milky Way globular clusters has increased explosively in recent years, but the underlying population is still uncertain due to observational biases. We use state-of-the-art $N$-body simulations to study the evolution of MSP populations in dense star clusters. These cluster models span a wide range in initi

Fabrizio Caola, Amlan Chakraborty, Giulio Gambuti, Andreas von Manteuffel

We compute the three-loop helicity amplitudes for $q\bar{q} \to gg$ and its crossed partonic channels, in massless QCD. Our analytical results provide a non-trivial check of the color quadrupole contribution to the infrared poles for external states in different color representations. At high energies, the $qg \to qg$ amplitude shows the predicted factorized

Gopal Yadav, Aalok Misra

Obtaining the Page curve in the context of eternal black holes associated with top-down non-conformal holographic thermal duals at intermediate coupling, has been entirely unexplored in the literature. We fill this gap in the context of a doubly holographic setup relevant to the M-theory dual of thermal QCD-like theories at $T>T_c$ at intermediate coupling.

Jean-Paul Breuer, Gábor Galgóczi, Valentina Fioretti, Jakub Zlámal

The last generation of X-ray focusing telescopes operating outside the Earth's radiation belt discovered that optics were able to focus not only astrophysical X-ray photons, but also low-energy heliophysical protons entering the Field of View (FOV). This "soft proton" contamination affects around 40\% of the observation time of XMM-Newton. The ATHENA Charged

Maxim Trushin

Excitonic insulators conduct neither electrons nor holes but bound electron-hole pairs, excitons. Unfortunately, it is not possible to inject and detect the electron and hole currents independently within a single semiconducting layer. However, interlayer excitonic insulators provide a spatial separation of electrons and holes enabling exciton current measur

Melissa Joseph, Daniel Aloni, Martin Schmaltz, Eashwar N. Sivarajan

Models of dark sectors with a mass threshold can have important cosmological signatures. If, in the era prior to recombination, a relativistic species becomes nonrelativistic and is then depopulated in equilibrium, there can be measurable impacts on the cosmic microwave background as the entropy is transferred to lighter relativistic particles. In particular

Alexander P. Ji, Joshua D. Simon, Ian U. Roederer, Ekaterina Magg

The ultra-faint dwarf galaxy Reticulum~II was enriched by a single rare and prolific r-process event. The r-process content of Reticulum~II thus provides a unique opportunity to study metal mixing in a relic first galaxy. Using multi-object high-resolution spectroscopy with VLT/GIRAFFE and Magellan/M2FS, we identify 32 clear spectroscopic member stars and me

Craig S. Anderson, Christopher L. Carilli, Paolo Tozzi, G. K. Miley

We present deep broadband radio polarization observations of the Spiderweb radio galaxy (J1140-2629) in a galaxy proto-cluster at $z=2.16$. These yield the most detailed polarimetric maps yet made of a high redshift radio galaxy. The intrinsic polarization angles and Faraday Rotation Measures (RMs) reveal coherent magnetic fields spanning the $\sim60$ kpc le

Christopher Henderson, Stanley Snelson, Andrei Tarfulea

This article considers the spatially inhomogeneous, non-cutoff Boltzmann equation. We construct a large-data classical solution given bounded, measurable initial data with uniform polynomial decay of mild order in the velocity variable. Our result requires no assumption of strict positivity for the initial data, except locally in some small ball in phase spa

Li-kun Shi, Oles Matsyshyn, Justin C. W. Song, Inti Sodemann Villadiego

We dismantle the previously held misconception that it is impossible for bulk rectification mechanisms to induce a net DC electric current when the frequency of the impinging radiation lies within the optical gap of a metal in the limit of small carrier relaxation rates. We argue that generically such in-gap rectification mechanisms are irreversible and acco

Gilberto Colangelo, Martin Hoferichter, Joachim Monnard, Jacobo Ruiz de Elvira

We present a calculation of the $C$-odd radiative corrections to $e^+e^-\to \pi^+\pi^-$ in a dispersive formalism, concentrating on the leading pion-pole contribution in the virtual box diagrams. In particular, we show how the effect of a general pion vector form factor in the loop integral can be incorporated in a model-independent way and how the cancellat

Kurt Hinterbichler

Massive fields on (anti) de Sitter space realize extended shift symmetries at particular values of their masses. We find these symmetries for all bosonic p-forms and mixed symmetry fields, in arbitrary spacetime dimension. These shift symmetric fields correspond to the missing longitudinal modes of mixed symmetry partially massless fields where the top row o

Jindra Gensior, Robert Feldmann, Lucio Mayer, Andrew Wetzel

Accurately reproducing the thin cold gas discs observed in nearby spiral galaxies has been a long standing issue in cosmological simulations. Here, we present measurements of the radially resolved HI scale height in 22 non-interacting Milky Way-mass galaxies from the FIREbox cosmological volume. We measure the HI scale heights using five different approaches

Axel Widmark, Lawrence M. Widrow, Aneesh Naik

We have mapped the number density and mean vertical velocity of the Milky Way's stellar disk out to roughly two kiloparsecs from the Sun using Gaia Data Release 3 (DR3) and complementary photo-astrometric distance information from StarHorse. For the number counts, we carefully masked spatial regions that are compromised by open clusters, great distances, or

Mariana Carrillo Gonzalez, Claudia de Rham, Victor Pozsgay, Andrew J. Tolley

Physical principles such as unitarity, causality, and locality can constrain the space of consistent effective field theories (EFTs) by imposing two-sided bounds on the allowed values of Wilson coefficients. In this paper, we consider the bounds that arise from the requirement of low-energy causality alone, without appealing to any assumptions about UV physi

Chuang Gan, Yi Gu, Siyuan Zhou, Jeremy Schwartz

The way an object looks and sounds provide complementary reflections of its physical properties. In many settings cues from vision and audition arrive asynchronously but must be integrated, as when we hear an object dropped on the floor and then must find it. In this paper, we introduce a setting in which to study multi-modal object localization in 3D virtua

Hanoona Rasheed, Muhammad Maaz, Muhammad Uzair Khattak, Salman Khan

Existing open-vocabulary object detectors typically enlarge their vocabulary sizes by leveraging different forms of weak supervision. This helps generalize to novel objects at inference. Two popular forms of weak-supervision used in open-vocabulary detection (OVD) include pretrained CLIP model and image-level supervision. We note that both these modes of sup

Alexander Borzunov, Max Ryabinin, Tim Dettmers, Quentin Lhoest

The infrastructure necessary for training state-of-the-art models is becoming overly expensive, which makes training such models affordable only to large corporations and institutions. Recent work proposes several methods for training such models collaboratively, i.e., by pooling together hardware from many independent parties and training a shared model ove

Ruo Cheng Huang, Paul M. Riechers, Mile Gu, Varun Narasimhachar

Quantum information-processing techniques enable work extraction from a system's inherently quantum features, in addition to the classical free energy it contains. Meanwhile, the science of computational mechanics affords tools for the predictive modeling of non-Markovian classical and quantum stochastic processes. We combine tools from these two sciences to

Chima D. McGruder, Mercedes López-Morales, James Kirk, Néstor Espinoza

One of the strongest ${\rm Na~I}$ features was observed in WASP-96b. To confirm this novel detection, we provide a new 475-825nm transmission spectrum obtained with Magellan/IMACS, which indeed confirms the presence of a broad sodium absorption feature. We find the same result when reanalyzing the 400-825nm VLT/FORS2 data. We also utilize synthetic data to t

Niv Cohen, Jonathan Kahana, Yedid Hoshen

Anomaly detection methods strive to discover patterns that differ from the norm in a semantic way. This goal is ambiguous as a data point differing from the norm by an attribute e.g., age, race or gender, may be considered anomalous by some operators while others may consider this attribute irrelevant. Breaking from previous research, we present a new anomal

Andrei Manolache, Florin Brad, Antonio Barbalau, Radu Tudor Ionescu

The DarkWeb represents a hotbed for illicit activity, where users communicate on different market forums in order to exchange goods and services. Law enforcement agencies benefit from forensic tools that perform authorship analysis, in order to identify and profile users based on their textual content. However, authorship analysis has been traditionally stud

Konstantinos Dareiotis, Máté Gerencsér

Differential equations perturbed by multiplicative fractional Brownian motions are considered. Depending on the value of the Hurst parameter $H$, the resulting equation is pathwise viewed as an ODE, YDE, or RDE. In all three regimes we show regularisation by noise phenomena by proving the strongest kind of well-posedness with irregular drift: strong existenc

Lucio Galeati, Máté Gerencsér

We consider stochastic differential equations (SDEs) driven by a fractional Brownian motion with a drift coefficient that is allowed to be arbitrarily close to criticality in a scaling sense. We develop a comprehensive solution theory that includes strong existence, path-by-path uniqueness, existence of a solution flow of diffeomorphisms, Malliavin different

Boris Kruglikov, Wijnand Steneker

The Koutras-McIntosh family of metrics include conformally flat pp-waves and the Wils metric. It appeared in a paper of 1996 by Koutras-McIntosh as an example of a pure radiation spacetime without scalar curvature invariants or infinitesimal symmetries. Here we demonstrate that these metrics have no "hidden symmetries", by which we mean Killing tensors of lo

Yasar Y. Atas, Jan F. Haase, Jinglei Zhang, Victor Wei

Quantum chromodynamics - the theory of quarks and gluons - has been known for decades, but it is yet to be fully understood. A recent example is the prediction and experimental discovery of tetraquarks, that opened a new research field. Crucially, numerous unsolved questions of the standard model can exclusively be addressed by nonperturbative calculations.

Mladen Kezunovic, Rashid Baembitov, Mohammad Khoshjahan

An approach for reaching the net-zero carbon electricity grid is to intensify the deployment of distributed renewable generation resources such as photovoltaic (PV) solar and wind generation, complemented with stationary and mobile (electric vehicle) battery energy storage systems (BESS). This paper assumes a scenario where the PV renewable generation and BE

Dimitrios Tanoglidis, Aleksandra Ćiprijanović, Alex Drlica-Wagner

Measuring the structural parameters (size, total brightness, light concentration, etc.) of galaxies is a significant first step towards a quantitative description of different galaxy populations. In this work, we demonstrate that a Bayesian Neural Network (BNN) can be used for the inference, with uncertainty quantification, of such morphological parameters f

Scott Emmons, Caspar Oesterheld, Andrew Critch, Vincent Conitzer

Although it has been known since the 1970s that a globally optimal strategy profile in a common-payoff game is a Nash equilibrium, global optimality is a strict requirement that limits the result's applicability. In this work, we show that any locally optimal symmetric strategy profile is also a (global) Nash equilibrium. Furthermore, we show that this resul

Anton V. Vykhodtsev, Darren Jang, Qianpu Wang, William Rosehart

This paper proposes the linearized physics-based model of a lithium-ion battery that can be incorporated into the optimization framework for power system economic studies. The proposed model is a linear approximation of the single particle model and it allows to characterize dynamics of the physical processes inside the battery that impact the battery operat

Stefano Baiguera, Gerben Oling, Watse Sybesma, Benjamin T. Søgaard

We construct two distinct actions for scalar fields that are invariant under local Carroll boosts and Weyl transformations. Conformal Carroll field theories were recently argued to be related to the celestial holography description of asymptotically flat spacetimes. However, only few explicit examples of such theories are known, and they lack local Carroll b

Pengzi Miao

We study connections among the ADM mass, positive harmonic functions tending to zero at infinity, and the capacity of the boundary of asymptotically flat $3$-manifolds with nonnegative scalar curvature. First we give new formulae that detect the ADM mass via harmonic functions. Then we derive a family of monotone quantities and geometric inequalities if the

Pei-Chun Su, Hau-Tieng Wu

We develop a data-driven optimal shrinkage algorithm for matrix denoising in the presence of high-dimensional noise with a separable covariance structure; that is, the noise is colored and dependent across samples. The algorithm, coined {\em extended OptShrink} (eOptShrink) depends on the asymptotic behavior of singular values and singular vectors of the ran

Thomas G. Kiely, Erich J. Mueller

We explore matrix product state approximations to wavefunctions which have spontaneously broken symmetries or are critical. We are motivated by the fact that symmetries, and their associated conservation laws, lead to block-sparse matrix product states. Numerical calculations which take advantage of these symmetries run faster and require less memory. Howeve

B. Chauhan

We discuss both the off-shell nilpotent Becchi-Rouet-Stora-Tyutin (BRST) and anti-BRST symmetry transformations for the cosmological Friedmann-Robertson-Walker (FRW) model with a differential gauge condition in the extended phase space. In this discussion, the presence of anti-BRST symmetry provides the complete geometrical description of BRST within the amb

Kannan Soundararajan

We give a brief account of some of the most spectacular results established by James Maynard for which he has been awarded the Fields Medal.

Javier Aguilar, Beatriz Arregui García, Raúl Toral, Sandro Meloni

In the recent COVID-19 pandemic we assisted at a sequence of epidemic waves intertwined by anomalous fade-outs with periods of low but persistent epidemic prevalence. These long-living epidemic states complicate epidemic control and challenge current modeling approaches as classical epidemic models fail to explain their emergence. Inspired by this phenomenon

Mingjie Bi, Gongyu Chen, Dawn M. Tilbury, Siqian Shen

Due to the COVID-19 pandemic, the global supply chain is disrupted at an unprecedented scale under uncertain and unknown trends of labor shortage, high material prices, and changing travel or trade regulations. To stay competitive, enterprises desire agile and dynamic response strategies to quickly react to disruptions and recover supply-chain functions. Alt

Yue Sun, Tao Shi, Zhiyong Liu, Zhidong Zhang

Exploring non-Hermitian phenomenology is an exciting frontier of modern physics. However, the demonstration of a non-Hermitian phenomenon that is quantum in nature has remained elusive. Here, we predict quantum non-Hermitian phenomena: the fractional quantum Zeno (FQZ) effect and FQZ-induced photon antibunching. We consider a quantum optics platform with res

Krishnamurthi Ravishankar, Kumarjit Saha

In this paper we study the convergence of dynamical discrete web (DyDW) to the dynamical Brownian web (DyBW) in the path space topology. We show that almost surely the DyBW has RCLL paths taking values in an appropriate metric space and as a sequence of RCLL paths, the scaled dynamical discrete web converges to the DyBW. This proves weak convergence of the D

Ming Yi, Meng Wang

The rapid deployment of renewable generations such as photovoltaic (PV) generations brings great challenges to the resiliency of existing power systems. Because PV generations are volatile and typically invisible to the power system operator, estimating the generation and characterizing the uncertainty are in urgent need for operators to make insightful deci

David Espinoza-Galeas, Michael Francis Corcoran, Kenji Hamaguchi, Christopher M. P. Russell

We report high-precision X-ray monitoring observations in the 0.4-10 keV band of the luminous, long-period colliding-wind binary Eta Carinae up to and through its most recent X-ray minimum/periastron passage in February 2020. Eta Carinae reached its observed maximum X-ray flux on 7 January 2020, at a flux level of $3.30 \times 10^{-10}$ ergs s$^{-1}$ cm$^{-2

Atish Dixit, Ahmed H. ElSheikh

We present a case study of model-free reinforcement learning (RL) framework to solve stochastic optimal control for a predefined parameter uncertainty distribution and partially observable system. We focus on robust optimal well control problem which is a subject of intensive research activities in the field of subsurface reservoir management. For this probl

Adrián González Casanova, András Tóbiás, Daniel Valesin

We introduce and study an interacting particle system evolving on the $d$-dimensional torus $(\mathbb Z/N\mathbb Z)^d$. Each vertex of the torus can be either empty or occupied by an individual of type $\lambda \in (0,\infty)$. An individual of type $\lambda$ dies with rate one and gives birth at each neighboring empty position with rate $\lambda$; moreover,

Shohei Saga, Teppei Okumura, Atsushi Taruya, Takuya Inoue

We study relativistic effects, arising from the light propagation in an inhomogeneous universe. We particularly investigate the effects imprinted in a cross-correlation function between galaxy positions and intrinsic galaxy shapes (GI correlation). Considering the Doppler and gravitational redshift effects as major relativistic effects, we present an analyti

F. R. Klinkhamer

A 4D-brane realization of $q$-theory has been proposed a few years ago. The present paper studies the corresponding late-time cosmology and establishes the dynamic cancellation of an initial cosmological constant and an attractor behavior towards Minkowski spacetime.

Leonardo de la Cruz

We extend a previously developed approach to relate thermal currents in the high temperature regime and classical limits of amplitudes. We consider the bi-adjoint scalar theory, which has the basic structure of a cubic theory and which is related to QCD and gravity through the double copy. In addition, we consider a generalization of scalar QED to model clas

Alexis Ralli, Tim Weaving, Andrew Tranter, William M. Kirby

The contextual subspace variational quantum eigensolver (CS-VQE) is a hybrid quantum-classical algorithm that approximates the ground-state energy of a given qubit Hamiltonian. It achieves this by separating the Hamiltonian into contextual and noncontextual parts. The ground-state energy is approximated by classically solving the noncontextual problem, follo

Zihan Li, Dihan Li, Cangbai Xu, Weice Wang

Medical image segmentation is one of the most fundamental tasks concerning medical information analysis. Various solutions have been proposed so far, including many deep learning-based techniques, such as U-Net, FC-DenseNet, etc. However, high-precision medical image segmentation remains a highly challenging task due to the existence of inherent magnificatio