July 2022 arXiv papers — page 58

Shenyuan Gao, Chunluan Zhou, Chao Ma, Xinggang Wang

Transformer trackers have achieved impressive advancements recently, where the attention mechanism plays an important role. However, the independent correlation computation in the attention mechanism could result in noisy and ambiguous attention weights, which inhibits further performance improvement. To address this issue, we propose an attention in attenti

Kingman Cheung, Yi-Lun Chung, Shih-Chieh Hsu

Higgs boson pair production is well known to probe the structure of the electroweak symmetry breaking sector. We illustrate using the gluon-fusion process $pp \to H \to h h \to (b\bar b) (b\bar b)$ in the framework of two-Higgs-doublet models and how the machine learning approach (three-stream convolutional neural network) can substantially improve the signa

Yusong Bai, Yiliu Li, Song Liu, Yinjie Guo

Two-dimensional (2D) transition metal dichalcogenides (TMDC) and their moir\'e interfaces have been demonstrated for correlated electron states, including Mott insulators and electron/hole crystals commensurate with moir\'e superlattices. Here we present spectroscopic evidences for ordered bosons - interlayer exciton crystals in a WSe2/MoSe2/WSe2 trilayer, w

Kareem Hegazy, Varun Makhija, Phil Bucksbaum, Jeff Corbett

Currently, our general approach to retrieving molecular structures from ultrafast gas-phase diffraction heavily relies on complex ab initio electronic or vibrational excited state simulations to make conclusive interpretations. Without such simulations, inverting this measurement for the structural probability distribution is typically intractable. This crea

Noeloikeau Charlot, Daniel J. Gauthier, Daniel Canaday, Andrew Pomerance

We introduce a mathematical framework for simulating Hybrid Boolean Network (HBN) Physically Unclonable Functions (PUFs, HBN-PUFs). We verify that the model is able to reproduce the experimentally observed PUF statistics for uniqueness $\mu_{inter}$ and reliability $\mu_{intra}$ obtained from experiments of HBN-PUFs on Cyclone V FPGAs. Our results suggest th

Izak Oltman

This paper proves a probabilistic Weyl-law for the spectrum of randomly perturbed Berezin-Toeplitz operators, generalizing a result proven by Martin Vogel in 2020. This is done following Vogel's strategy using an exotic symbol calculus developed by the author in a recent paper.

Andrew Akerson

The complex physics and numerous failure modes of structural impact creates challenges when designing for impact resistance. While simple geometries of layered material are conventional, advances in 3D printing and additive manufacturing techniques have now made tailored geometries or integrated multi-material structures achievable. Here, we apply gradient-b

Niraj Gupta, Eric J. Roberts, Song Pang, C. Shan Xu

Three-dimensional volumetric imaging of cells allows for in situ visualization, thus preserving contextual insights into cellular processes. Despite recent advances in machine learning methods, morphological analysis of sub-nuclear structures have proven challenging due to both the shallow contrast profile and the technical limitation in feature detection. H

JB Lanier, Stephen McAleer, Pierre Baldi, Roy Fox

Robust reinforcement learning (RL) considers the problem of learning policies that perform well in the worst case among a set of possible environment parameter values. In real-world environments, choosing the set of possible values for robust RL can be a difficult task. When that set is specified too narrowly, the agent will be left vulnerable to reasonable

Izak Oltman

We develop a calculus of Berezin-Toeplitz operators quantizing exotic classes of smooth functions on compact K\"ahler manifolds and acting on holomorphic sections of powers of positive line bundles. These functions (classical observables) are exotic in the sense that their derivatives are allowed to grow in ways controlled by local geometry and the power of

Andreij C. Gadelha, Rafael Nadas, Tiago C. Barbosa, Kenji Watanabe

Due to its ultra-thin nature, the study of graphene quantum optoelectronics, like gate-dependent graphene Raman properties, is obscured by interactions with substrates and surroundings. For instance, the use of doped silicon with a capping thermal oxide layer limited the observation to low temperatures of a well-defined Kohn-anomaly behavior, related to the

Honggui Li, Maria Trocan, Dimitri Galayko, Mohamad Sawan

Closed-loop architecture is widely utilized in automatic control systems and attain distinguished performance. However, classical compressive sensing systems employ open-loop architecture with separated sampling and reconstruction units. Therefore, a method of iterative compensation recovery for image compressive sensing (ICRICS) is proposed by introducing c

Nyteisha Bookert, Mohd Anwar

The Internet of Medical Things (IoMT) is a frequent target of attacks -- compromising both patient data and healthcare infra-structure. While privacy-enhanced technologies and services (PETS) are developed to mitigate traditional privacy concerns, they cannot be applied without identifying specific threat models. Therefore, our position is that the new threa

Nyteisha Bookert, May Almousa, Mohd Anwar

Ambient assisted living (AAL) environments support independence and quality of life of older adults However, in an AAL environment, privacy-related issues (e.g., unawareness, information disclosure, and lack of support) directly impact older adults and bystanders (e.g., caregivers, service providers, etc.). We explore the privacy challenges that both older a

Houssam Yassin

Quasigeostrophic flows are induced by spatial variations in interior potential vorticity and boundary buoyancy. We begin by developing the geostrophic turbulence theory of boundary buoyancy anomalies in a fluid with vanishing potential vorticity. We find that the vertical stratification controls both the interaction range of boundary buoyancy anomalies and t

Alessandro Mastrototaro, Jimmy Olsson

We present a new approach-the ALVar estimator-to estimation of asymptotic variance in sequential Monte Carlo methods, or, particle filters. The method, which adjusts adaptively the lag of the estimator proposed in [Olsson, J. and Douc, R. (2019). Numerically stable online estimation of variance in particle filters. Bernoulli, 25(2), pp. 1504-1535] applies to

Joaquin Chung, Ely M. Eastman, Gregory S. Kanter, Keshav Kapoor

The Illinois Express Quantum Network (IEQNET) is a program to realize metropolitan scale quantum networking over deployed optical fiber using currently available technology. IEQNET consists of multiple sites that are geographically dispersed in the Chicago metropolitan area. Each site has one or more quantum nodes (Q-nodes) representing the communication par

Dimitri Bertsekas

We consider some classical optimization problems in path planning and network transport, and we introduce new auction-based algorithms for their optimal and suboptimal solution. The algorithms are based on mathematical ideas that are related to competitive bidding by persons for objects and the attendant market equilibrium, which underlie auction processes.

Chin-Yao Chang, Andrey Bernstein

This paper presents a robust data-driven controller design based on the noisy input-output data without assumptions on the statistical properties of the noises. We start with the direct data-representation of system models that take elements from behavioral system theory, followed by analyses of the upper bound of the "modeling" error with the data represent

Othmane Aouane, Marcello Sega, Bastian Bäuerlein, Kerstin Avila

The dynamics of rigid particle suspensions in a wall-bounded laminar flow present several non-trivial and intriguing features, including particle ordering, lateral transport, and the appearance of stable, preferential locations like the Segr\'e-Silberberg annulus. The formation of more than one annulus is a particularly puzzling phenomenon that is still not

Vladimir Dragović, Andrey E. Mironov

We introduce a method to find differential equations for functions which define tables, such that associated billiard systems admit a local first integral. We illustrate this method in three situations: the case of (locally) integrable wire billiards, for finding surfaces in ${\mathbb R}^3$ with a first integral of degree one in velocities, and for finding a

Mohammad-Amin Charusaie, Hussein Mozannar, David Sontag, Samira Samadi

One of the goals of learning algorithms is to complement and reduce the burden on human decision makers. The expert deferral setting wherein an algorithm can either predict on its own or defer the decision to a downstream expert helps accomplish this goal. A fundamental aspect of this setting is the need to learn complementary predictors that improve on the

Paulo C. Lima, Riccardo Mariani, Aldo Procacci, Benedetto Scoppola

We analyse the Blume-Emery-Griffiths (BEG) model on the lattice $\Zd$ at the ferromagnetic-antiquadrupolar-disordered (FAD) and antiquadrupolar-disordered (AD) interfaces of parameters. In our analysis of the FAD interface we introduce a Gibbs sampler of the ground states at zero temperature, and we exploit it in two different ways: first, we perform via per

Omar Boudraa

3D image segmentation is a recent and crucial step in many medical analysis and recognition schemes. In fact, it represents a relevant research subject and a fundamental challenge due to its importance and influence. This paper provides a multi-phase Deep Learning-based system that hybridizes various efficient methods in order to get the best 3D segmentation

Sebastian Schulz

We investigate $\mathbb{C}^\times$-families of flat connections whose leading term is a nilpotent Higgs field. Examples of such families include real twistor lines and families arising from the conformal limit. We show that these families have the same monodromy as families whose leading term is a regular Higgs bundle and use this to deduce that traces of ho

Aser Abbas, Joseph P. Vantassel, Brady R. Cox, Krishna Kumar

This paper presents a frequency-velocity convolutional neural network (CNN) for rapid, non-invasive 2D shear wave velocity (Vs) imaging of near-surface geo-materials. Operating in the frequency-velocity domain allows for significant flexibility in the linear-array, active-source experimental testing configurations used for generating the CNN input, which are

Logan A. Pearce, Jared R. Males, Alycia J. Weinberger, Joseph D. Long

Improving direct detection capability close to the star through improved star-subtraction and post-processing techniques is vital for discovering new low-mass companions and characterizing known ones at longer wavelengths. We present results of 17 binary star systems observed with the Magellan Adaptive Optics system (MagAO) and the Clio infrared camera on th

Joe Alexandersen

This article presents a detailed introduction to density-based topology optimisation of fluid flow problems. The goal is to allow new students and researchers to quickly get started in the research area and to skip many of the initial steps, often consuming unnecessarily long time from the scientific advancement of the field. This is achieved by providing a

Jiuzu Hong, Shrawan Kumar

Let $\Gamma$ be a finite group acting on a simple Lie algebra $\mathfrak{g}$ and acting on a $s$-pointed projective curve $(\Sigma, \vec{p}=\{p_1, \dots, p_s\})$ faithfully (for $s\geq 1$). Also, let an integrable highest weight module $\mathscr{H}_c(\lambda_i)$ of an appropriate twisted affine Lie algebra determined by the ramification at $p_i$ with a fixed

Mo Collaboration, C. Augier, A. S. Barabash, F. Bellini

The CUPID-Mo experiment, located at Laboratoire Souterrain de Modane (France), was a demonstrator experiment for CUPID. It consisted of an array of 20 Li$_2^{100}$MoO$_4$ (LMO) calorimeters each equipped with a Ge light detector (LD) for particle identification. In this work, we present the result of a search for two-neutrino and neutrinoless double beta dec

Jihao Liu, Lingyao Xie

We prove some basic properties of the relative Nakayama-Zariski decomposition. We apply them to the study of lc generalized pairs. We prove the existence of log minimal models or Mori fiber spaces for (relative) lc generalized pairs polarized by an ample divisor. This extends a result of Hashizume-Hu to generalized pairs. We also show that, for any lc genera

Hao Xu, Kai-Kit Wong, Giuseppe Caire

In this note, we show how difficult the brute-force Fourier-Motzkin elimination is, even in a simple case with three eliminating variables. Specifically, we first give a theorem, which plays quite an important role in the study of information-theoretic security for a multiple access wiretap (MAC-WT) channel, and then prove it for the case with three users by

BABAR Collaboration

This article presents a model independent search for an additional, mostly sterile, Heavy Neutral Lepton (HNL), that is capable of mixing with the Standard Model $\tau$ neutrino with a mixing strength of $|U_{\tau 4}|^{2}$, corresponding to the absolute square of the extended Pontecorvo-Maki-Nakagawa-Sakata (PMNS) matrix element. Data from the \babar~ experi

Nikolai V. Ivanov

The paper is devoted to an analogue of Atiyah-Bott-Singer index theorem for families of self-adjoint elliptic (i.e. satisfying the Shapiro-Lopatinskii condition) local boundary problems of order 1. The proofs are based on classical topological and pseudo-differential methods, but in the self-adjoint case one encounters some new phenomena. The topological ind

Agustin G. Nogales

Strong consistency of the Bayes estimator of a regression curve for the $L^1$-squared loss function is proved. It is also shown the convergence to 0 of the Bayes risk of this estimator both for the $L^1$ and $L^1$-squared loss functions. The Bayes estimator of a regression curve is the regression curve with respect to the posterior predictive distribution.

Asael Fabian Martínez, Somnath Chaudhuri, Carlos Díaz-Avalos, Pablo Juan

An unsupervised classification method for point events occurring on a network of lines is proposed. The idea relies on the distributional flexibility and practicality of random partition models to discover the clustering structure featuring observations from a particular phenomenon taking place on a given set of edges. By incorporating the spatial effect in

Linbo Liu, Youngsuk Park, Trong Nghia Hoang, Hilaf Hasson

This work studies the threats of adversarial attack on multivariate probabilistic forecasting models and viable defense mechanisms. Our studies discover a new attack pattern that negatively impact the forecasting of a target time series via making strategic, sparse (imperceptible) modifications to the past observations of a small number of other time series.

Jose L. Ocana-Pujol, Lea Forster, Ralph Spolenak, Henning Galinski

Hyperbolic metamaterials show exceptional optical properties, such as near-perfect broadband absorption, due to their geometrically-engineered optical anisotropy. Many of their proposed applications, such as thermophotovoltaics or radiative cooling, require high-temperature stability. In this work we examine Ag/a-Si multilayers as a model system for the ther

Nicolaos Petropoulos, Ali Mashayek, Colm-cille P. Caulfield

Formation of step-like 'density staircase' distributions induced by stratification and turbulence has been widely studied and can be explained by the 'instability' of a sufficiently strongly stably stratified turbulent flow due to the decrease of the turbulent density flux with increasing stratification via the 'Phillips mechanism'. However, such density sta

Jiban Kangsabanik, Mark Kamper Svendsen, Alireza Taghizadeh, Andrea Crovetto

Discovery of high-performance materials remains one of the most active areas in photovoltaics (PV) research. Indirect band gap materials form the largest part of the semiconductor chemical space, but predicting their suitability for PV applications from first principles calculations remains challenging. Here we propose a computationally efficient method to a

Amit Kumar Kundu, Joseph Jaja

Federated learning (FL) is a recently developed area of machine learning, in which the private data of a large number of distributed clients is used to develop a global model under the coordination of a central server without explicitly exposing the data. The standard FL strategy has a number of significant bottlenecks including large communication requireme

Chams Gharib Ali Barura, Philippe Ben-Abdallah, Riccardo Messina

We analyze the coupling between conduction and radiative heat transfer in near-field regime between two coaxial cylinders separated by a vacuum gap. By solving the heat transport equation in the steady-state regime between metals or polar materials we highlight a flux saturation mechanism for the radiative transfer even without non-local effect. In the case

Harsha Kokel, Mayukh Das, Rakibul Islam, Julia Bonn

We consider the problem of human-machine collaborative problem solving as a planning task coupled with natural language communication. Our framework consists of three components -- a natural language engine that parses the language utterances to a formal representation and vice-versa, a concept learner that induces generalized concepts for plans based on lim

Xuan Chen, Fei Ji, Miaowen Wen, Yu Huang

In this paper, we propose a novel inter-symbol interference (ISI) mitigation scheme for molecular communication via diffusion (MCvD) systems with the optimal detection interval. Its rationale is to exploit the discarded duration (i.e., the symbol duration outside this optimal interval) to relieve ISI in the target system. Following this idea, we formulate an

Thomas G. Kelly, Mohammad Divband Soorati, Klaus-Peter Zauner, Sarvapali D. Ramchurn

One of the main tasks for autonomous robot swarms is to collectively decide on the best available option. Achieving that requires a high quality communication between the agents that may not be always available in a real world environment. In this paper we introduce the communication-constrained collective decision-making problem where some areas of the envi

R. Rama-Eiroa, R. M. Otxoa, U. Atxitia

The discovery of current-induced spin-orbit torque (SOT) orthogonal reorientation, also known as orthogonal switching, of metallic Mn$_2$Au and CuMnAs has opened the door for ultrafast writing of an antiferromagnet (AFM). Phenomenological theory predicts that the minimum field necessary for SOT switching -- critical field -- for ultrashort pulses increases i

Tin Kuculo, Simon Gottschalk, Elena Demidova

Quotes of public figures can mark turning points in history. A quote can explain its originator's actions, foreshadowing political or personal decisions and revealing character traits. Impactful quotes cross language barriers and influence the general population's reaction to specific stances, always facing the risk of being misattributed or taken out of con

Joaquin Garcia-Suarez, Tobias Brink, Jean-François Molinari

Building on an analogy to ductile fracture mechanics, we quantify the size of debris particles created during adhesive wear. Earlier work suggested a linear relation between tangential work and wear debris volume, assuming that the debris size is proportional to the micro contact size multiplied by the junction shear strength. However, the present study reve

Amine Bennouna, Bart Van Parys, Ryan Lucas

The design of data-driven formulations for machine learning and decision-making with good out-of-sample performance is a key challenge. The observation that good in-sample performance does not guarantee good out-of-sample performance is generally known as overfitting. Practical overfitting can typically not be attributed to a single cause but is caused by se

David Hasler, Oliver Siebert

We consider a translation-invariant Pauli-Fierz model describing a non-relativistic charged quantum mechanical particle interacting with the quantized electromagnetic field. The charged particle may be spinless or have spin one half. We decompose the Hamiltonian with respect to the total momentum into a direct integral of so called fiber Hamiltonians. We per

F. Gomez, S. Lepe, V. C. Orozco, P. Salgado

We consider the five-dimensional Einstein-Gauss-Bonnet gravity, which can be obtained by means of an apropriate choice of coeficients in the five-dimensional Lanczos-Lovelock gravity theory. The Einstein-Gauss-Bonnet field equations for the Friedmann-Lema\^itre-Robertson-Walker metric are found as well as some of their solutions. A four-dimensional gravity a

Aiusha Sangadiev, Alvaro Gonzalez-Castellanos, David Pozo

Worldwide commitments to net zero greenhouse emissions have accelerated investments in renewable energy resources. The requirements for operating and planning power systems are becoming stringent because of the need to take into account the uncertainty associated with renewable generation. Several modeling frameworks that consider the inherent uncertainty in

Drew Duncan, David B. Leep

We prove that an additive form of degree $d=2m$, $m$ odd, $m\ge3$, over the unramified quadratic extension $\mathbb{Q}_2(\sqrt{5})$ has a nontrivial zero if the number of variables $s$ satisifies $s \ge 4d+1$. If $3 \nmid d$, then there exists a nontrivial zero if $s \ge \frac{3}{2}d + 1$, this bound being optimal. We give examples of forms in $3d$ variables

Soroush Bateni, Marten Lohstroh, Hou Seng Wong, Rohan Tabish

Asynchronous frameworks for distributed embedded systems, like ROS and MQTT, are increasingly used in safety-critical applications such as autonomous driving, where the cost of unintended behavior is high. The coordination mechanism between the components in these frameworks, however, gives rise to nondeterminism, where factors such as communication timing c

Hung-Jui Guo, Balakrishnan Prabhakaran

Mixed Reality (MR) is an evolving technology lying in the continuum spanned by related technologies such as Virtual Reality (VR) and Augmented Reality (AR), and creates an exciting way of interacting with people and the environment. This technology is fast becoming a tool used by many people, potentially improving living environments and work efficiency. Mic

Ivan Cisneros, Peng Yin, Ji Zhang, Howie Choset

We present the ALTO dataset, a vision-focused dataset for the development and benchmarking of Visual Place Recognition and Localization methods for Unmanned Aerial Vehicles. The dataset is composed of two long (approximately 150km and 260km) trajectories flown by a helicopter over Ohio and Pennsylvania, and it includes high precision GPS-INS ground truth loc

A. Atteya, S. K. EL-Labany, P. K. Karmakar, M. S. Afify

Motivated by the recent Magnetospheric Multiscale (MMS) observations of oblique electron acoustic waves, we addressed the generation mechanism of the observed waves by utilizing the reductive perturbation technique. The nonlinear Zakharov-Kuznetsov (ZK) equation is derived for collisionless, magnetised plasma composed of cool inertial background electrons, t

Elliot Dang, Zheyuan Hu, Tong Li

Collaborative Filtering(CF) recommender is a crucial application in the online market and ecommerce. However, CF recommender has been proven to suffer from persistent problems related to sparsity of the user rating that will further lead to a cold-start issue. Existing methods address the data sparsity issue by applying token-level sentiment analysis that tr

Arkadiy Aliev

Let $K$ be a convex body in $\mathbb{R}^{n}$. Let $ d_{n,n-1}(K)$ be the smallest possible density of a non-separable lattice of translates of $K$. In this paper we prove the estimate $d_{2,1}(K)\leq \frac{\pi\sqrt{3}}{8}$ for $K\subset \mathbb{R}^{2}$, with equality if and only if $K$ is an ellipse, which was conjectured by E. Makai. Also we prove the estim

Julian Heidecke, Jan Fuhrmann, Maria Vittoria Barbarossa

Diagnostic testing followed by isolation of identified cases with subsequent tracing and quarantine of close contacts - often referred to as test-trace-isolate-and-quarantine (TTIQ) strategy - is one of the cornerstone measures of infectious disease control. The COVID-19 pandemic has highlighted that an appropriate response to outbreaks requires us to be awa

Dong-min Kim, Sinwoo Choi, Jungwan Cho, Mikyung Lim

We experimentally demonstrate a boosted in-plane thermal conduction by surface plasmon polaritons (SPPs) propagating along a thin Ti film on a glass substrate. Owing to a lossy nature of metal, SPPs can propagate over centimeter-scale distance even with a supported metal film, and resulting ballistic heat conduction can be quantitatively validated. Further,

Po-Wei Lo, Michael J. Lawler

Topological frustration (or topological mechanics) is the existence of classical zero modes that are robust to many but not all distortions of the Hamiltonian. It arises naturally from locality in systems whose interactions form a set of constraints such as in geometrically frustrated magnets and balls and springs metamaterials. For a magnet whose classical

E. R. Zinatullin, S. B. Korolev, A. D. Manukhova, T. Yu. Golubeva

In this paper, we propose two strategies for decreasing the error of arbitrary single-mode Gaussian transformations implemented using one-way quantum computation on a four-node linear cluster state. We show that it is possible to minimize the error of the arbitrary single-mode Gaussian transformation by a proper choice of the weight coefficients of the clust

Hui Yu, Sudip Chakravarty

In this paper we promote the idea of quantum critical lines ({\em inter alia} surfaces) as opposed to points. A quantum critical line obtains when criticality at zero temperature is extended over a continuum in a one-dimensional line. We base our ideas on a simple but exactly solved model introduced by one of the authors involving a one-dimensional quantum t

Shezad Mohamed

We prove that there exists a version of Weil descent, or Weil restriction, in the category of $\mathcal{D}$-algebras. The objects of this category are $k$-algebras $R$ equipped with a homomorphism $e \colon R \to R \otimes_k \mathcal{D}$ for some fixed field $k$ and finite-dimensional $k$-algebra $\mathcal{D}$. We do this under a mild assumption on the so-ca

Hu Fu, Jiawei Li, Daogao Liu

Weitzman (1979) introduced the Pandora Box problem as a model for sequential search with inspection costs, and gave an elegant index-based policy that attains provably optimal expected payoff. In various scenarios, the searching agent may select an option without making a costly inspection. The variant of the Pandora box problem with non-obligatory inspectio

A. A. Titov, S. S. Ablaev, M. S. Alkousa, F. S. Stonyakin

In this paper, we introduce some adaptive methods for solving variational inequalities with relatively strongly monotone operators. Firstly, we focus on the modification of the recently proposed, in smooth case [1], adaptive numerical method for generalized smooth (with H\"older condition) saddle point problem, which has convergence rate estimates similar to

Jediah R. Clark, Mohammad Naiseh, Joel Fischer, Marise Galvez Trigo

In the domain of unmanned vehicles, autonomous robotic swarms promise to deliver increased efficiency and collective autonomy. How these swarms will operate in the future, and what communication requirements and operational boundaries will arise are yet to be sufficiently defined. A workshop was conducted with 11 professional unmanned-vehicle operators and d

Shiyu Wang, Yuanqi Du, Xiaojie Guo, Bo Pan

Designing and generating new data under targeted properties has been attracting various critical applications such as molecule design, image editing and speech synthesis. Traditional hand-crafted approaches heavily rely on expertise experience and intensive human efforts, yet still suffer from the insufficiency of scientific knowledge and low throughput to s

Sheik Murad Hassan Anik, Xinghua Gao, Na Meng

The user persona is a communication tool for designers to generate a mental model that describes the archetype of users. Developing building occupant personas is proven to be an effective method for human-centered smart building design, which considers occupant comfort, behavior, and energy consumption. Optimization of building energy consumption also requir

Jialin Zhang, Zhiyi Zhang

Testing hypothesis of independence between two random elements on a joint alphabet is a fundamental exercise in statistics. Pearson's chi-squared test is an effective test for such a situation when the contingency table is relatively small. General statistical tools are lacking when the contingency data tables are large or sparse. A test based on generalized

Syeda S. Nasim, Gaia Fabj, Freddy Caban, Amy Secunda

Stars and stellar remnants orbiting a supermassive black hole (SMBH) can interact with an active galactic nucleus (AGN) disc. Over time, prograde orbiters (inclination $i<90^{\circ}$) decrease inclination, as well as semi-major axis $(a)$ and eccentricity $(e)$ until orbital alignment with the gas disc ('disc capture'). Captured stellar-origin black holes (s

Mujahid Al Rafi, Yuan Feng, Hyeran Jeon

With the growing burden of training deep learning models with large data sets, transfer-learning has been widely adopted in many emerging deep learning algorithms. Transformer models such as BERT are the main player in natural language processing and use transfer-learning as a de facto standard training method. A few big data companies release pre-trained mo

Peter R. Young, Nicholeen M. Viall

Observations from the 2012 transit of Venus are used to derive empirical formulae for long and short-range scattered light at locations on the solar disk observed by the Hinode Extreme ultraviolet Imaging Spectrometer (EIS) and the Solar Dynamics Observatory Atmospheric Imaging Assembly (AIA) instruments. Long-range scattered light comes from the entire sola

A. L. Aguayo-Alvarado, F. Domínguez-Serna, W. De La Cruz, K. Garay-Palmett

This work presents a feasible design of an integrated photonic circuit performing as a device for single-qubit preparation and rotations through the third-order nonlinear process of difference frequency generation (DFG) and defined in the temporal mode basis. The first stage of our circuit includes the generation of heralded single photons by spontaneous fou

Xue Lyu, Irina Subotić, Dominic Groß

In this work we present a novel dual-port grid-forming control strategy, for permanent magnet synchronous generator wind turbines with back-to-back voltage source converters, that unifies the entire range of functions from maximum power point tracking (MPPT) to providing inertia and fast frequency response without explicit mode switching between grid-followi

Sachit Menon, David Blei, Carl Vondrick

Variational autoencoders (VAEs) suffer from posterior collapse, where the powerful neural networks used for modeling and inference optimize the objective without meaningfully using the latent representation. We introduce inference critics that detect and incentivize against posterior collapse by requiring correspondence between latent variables and the obser

Ryan Birchfield, Maddison Caten, Errica Cheng, Madyson Kelly

Graphical perception studies are a key element of visualization research, forming the basis of design recommendations and contributing to our understanding of how people make sense of visualizations. However, graphical perception studies typically include only brief training sessions, and the impact of longer and more in-depth feedback remains unclear. In th

Ana Cadena, Bea Botka, Áron Pekker, Cla Duri Tschannen

Growing graphene nanoribbons from small organic molecules encapsulated in carbon nanotubes can result in products with uniform width and chirality. We propose a method based on encapsulation of 1,2,4-trichlorobenzene from the liquid phase and subsequent annealing. This procedure results in graphene nanoribbons several tens of nanometers long. The presence of

Ralph Howard, Ognian Trifonov

We prove explicit bounds on the number of lattice points on or near a convex curve in terms of geometric invariants such as length, curvature, and affine arclength. In several of our results we obtain the best possible constants. Our estimates hold for lattices more general than the usual lattice of integral points in the plane.

Ashkan Ganj, Mohsen Ebadpour, Mahdi Darvish, Hamid Bahador

The success of CNN-based architecture on image classification in learning and extracting features made them so popular these days, but the task of image classification becomes more challenging when we apply state of art models to classify noisy and low-quality images. It is still difficult for models to extract meaningful features from this type of image due

Nastaran Naghshineh, W. Cade Reinberger, Nathaniel S. Barlow, Mohamed A. Samaha

We examine the classical problem of the height of a static liquid interface that forms on the outside of a solid vertical cylinder in an unbounded stagnant pool exposed to air. Gravitational and surface tension effects compete to affect the interface shape as characterized by the Bond number, $B = \rho g R^{2}/\sigma$, where $\rho$ is fluid density, $g$ is t

Pedro E. Chavarrias-Solanon, Mansoor Ali-Teevno, Gilberto Ochoa-Ruiz, Sharib Ali

Prevalence of gastrointestinal (GI) cancer is growing alarmingly every year leading to a substantial increase in the mortality rate. Endoscopic detection is providing crucial diagnostic support, however, subtle lesions in upper and lower GI are quite hard to detect and cause considerable missed detection. In this work, we leverage deep learning to develop a

Idil Aytekin, Onat Dalmaz, Kaan Gonc, Haydar Ankishan

Monitoring of prevalent airborne diseases such as COVID-19 characteristically involves respiratory assessments. While auscultation is a mainstream method for preliminary screening of disease symptoms, its utility is hampered by the need for dedicated hospital visits. Remote monitoring based on recordings of respiratory sounds on portable devices is a promisi

Terrence George, Giovanni Inchiostro

Associated to a convex integral polygon $N$ in the plane are two integrable systems: the cluster integrable system of Goncharov and Kenyon, constructed from the dimer model on bipartite torus graphs, and the Beauville integrable system associated with the toric surface of $N$. These two systems are related by a birational map called the spectral transform. I

Junehyoung Jeon, Volker Bromm, Steven L. Finkelstein

X-ray feedback in the pre-reionization Universe provided one of the major energy sources for reionization and the thermal evolution of the early intergalactic medium. However, X-ray sources at high redshift have remained largely inaccessible to observations. One alternative approach to study the overall effect of X-ray feedback in the early Universe is a ful

Valerio Bertone

The operator definition of generalised transverse-momentum-dependent (GTMD) distributions is exploited to compute for the first time the full set of one-loop corrections to the off-forward matching functions. These functions allow one to obtain GTMDs in the perturbative regime in terms of generalised parton distributions (GPDs). In the unpolarised case, non-

Julia Barnett, Nicholas Diakopoulos

With the increasing pervasiveness of algorithms across industry and government, a growing body of work has grappled with how to understand their societal impact and ethical implications. Various methods have been used at different stages of algorithm development to encourage researchers and designers to consider the potential societal impact of their researc

Matthew R. DeVerna, Rachith Aiyappa, Diogo Pacheco, John Bryden

The world's digital information ecosystem continues to struggle with the spread of misinformation. Prior work has suggested that users who consistently disseminate a disproportionate amount of low-credibility content -- so-called superspreaders -- are at the center of this problem. We quantitatively confirm this hypothesis and introduce simple metrics to pre

Mikhail Tokman, Alex Behne, Brandon Torres, Maria Erukhimova

We study quantum dynamics of many-qubit systems strongly coupled to a quantized electromagnetic cavity field in the presence of decoherence and dissipation for both fermions and cavity photons, and taking into account the varying coupling strength of different qubits to the cavity field and the spread of their transition frequencies. Compact analytic solutio

J. Lorca Espiro

In the literature, abelian higher gauge symmetry models are shown to be valid in all finite dimensions and exhibit the characteristic behavior of SPT phases models. While the ground state degeneracy and the entanglement entropy were thoroughly studied, the classification of the ground state space still remained obscure. Based on differentio-geometric approac

Sofie Tilborghs, Jeroen Bertels, David Robben, Dirk Vandermeulen

Albeit the Dice loss is one of the dominant loss functions in medical image segmentation, most research omits a closer look at its derivative, i.e. the real motor of the optimization when using gradient descent. In this paper, we highlight the peculiar action of the Dice loss in the presence of missing or empty labels. First, we formulate a theoretical basis

Vahid Ashrafimoghari

Working with big data using data mining tools is rapidly becoming a trend in education industry. The combination of the current capacity to collect, store, manage and process data in a timely manner, and data from online educational platforms represents an unprecedented opportunity for educational institutes, learners, educators, and researchers. In this pos

Kshitij Girigoudar, Ashley M. Hou, Line A. Roald

The growing penetration of distributed energy resources (DERs) is leading to continually changing operating conditions, which need to be managed efficiently by distribution grid operators. The intermittent nature of DERs such as solar photovoltaic (PV) systems as well as load forecasting errors not only increase uncertainty in the grid, but also pose signifi

Renrui Zhang, Zhang Wei, Rongyao Fang, Peng Gao

Contrastive Vision-Language Pre-training, known as CLIP, has provided a new paradigm for learning visual representations using large-scale image-text pairs. It shows impressive performance on downstream tasks by zero-shot knowledge transfer. To further enhance CLIP's adaption capability, existing methods proposed to fine-tune additional learnable modules, wh

Marina A. Ferreira, Jani Lukkarinen, Alessia Nota, Juan J. L. Velázquez

It is well known that for a large class of coagulation kernels, Smoluchowski coagulation equations have particular power law solutions which yield a constant flux of mass along all scales of the system. In this paper, we prove that for some choices of the coagulation kernels there are solutions with a constant flux of mass along all scales which are not powe

Idan Meirzada, Assaf Kalinski, Dov Furman, Tsafrir Armon

The increasing complexity of required computational tasks alongside the inherent limitations in conventional computing calls for disruptive innovation. LightSolver devised a new quantum-inspired computing paradigm, which utilizes an all-optical platform for solving hard optimization problems. In this work, LightSolver introduces its digital simulator and joi

Gerard McCaul, Denys I. Bondar

It has long been known that there exists a coordinate transformation which exactly maps the quantum free particle to the quantum harmonic oscillator. Here we extend this result by reformulating it as a unitary operation followed by a time coordinate transformation. We demonstrate that an equivalent transformation can be performed for classical systems in the

Yen-Ju Lu, Xuankai Chang, Chenda Li, Wangyou Zhang

This paper presents recent progress on integrating speech separation and enhancement (SSE) into the ESPnet toolkit. Compared with the previous ESPnet-SE work, numerous features have been added, including recent state-of-the-art speech enhancement models with their respective training and evaluation recipes. Importantly, a new interface has been designed to f

Patrick Daniels

We prove the Pappas-Rapoport conjecture on the existence of canonical integral models of Shimura varieties with parahoric level structure in the case where the Shimura variety is defined by a torus. As an important ingredient, we show, using the Bhatt-Scholze theory of prismatic $F$-crystals, that there is a fully faithful functor from $\mathcal{G}$-valued c