January 2022 arXiv papers — page 118

Yasufumi Kojima, Shota Kisaka, Kotaro Fujisawa

We investigate the magneto--elastic equilibrium of a neutron star crust and magnetic energy stored by the elastic force. The solenoidal motion driven by the Lorentz force can be controlled by the magnetic elastic force, so that conditions for the magnetic field strength and geometry are less restrictive. For equilibrium models, the minor solenoidal part of t

Xiangci Li, Jessica Ouyang

Academic research is an exploration activity to solve problems that have never been resolved before. By this nature, each academic research work is required to perform a literature review to distinguish its novelties that have not been addressed by prior works. In natural language processing, this literature review is usually conducted under the "Related

Huanfei Zheng, Jonathon M. Smereka, Dariusz Mikluski, Yue Wang

In multi-robot system (MRS) bounding overwatch, it is crucial to determine which point to choose for overwatch at each step and whether the robots' positions are trustworthy so that the overwatch can be performed effectively. In this paper, we develop a Bayesian optimization based computational trustworthiness model (CTM) for the MRS to select overwatch

Liuxian Zhao, Timothy Horiuchi, Miao Yu

This paper investigates the acoustic Luneburg Lens (ALL) as a design framework for guiding acoustic wave propagation. In this study, we propose to develop an acoustic waveguide based on the characteristics of both acoustic wave focusing and collimation of cascaded ALLs. The continuous variation of refractive index of the ALL is achieved by using lattice unit

Igor Halperin, Jiayu Liu, Xiao Zhang

We suggest a simple practical method to combine the human and artificial intelligence to both learn best investment practices of fund managers, and provide recommendations to improve them. Our approach is based on a combination of Inverse Reinforcement Learning (IRL) and RL. First, the IRL component learns the intent of fund managers as suggested by their tr

Meitar Shechter, Rana Hanocka, Gal Metzer, Raja Giryes

We introduce NeuralMLS, a space-based deformation technique, guided by a set of displaced control points. We leverage the power of neural networks to inject the underlying shape geometry into the deformation parameters. The goal of our technique is to enable a realistic and intuitive shape deformation. Our method is built upon moving least-squares (MLS), sin

Zhe Shen, Takeshi Tsuchiya

Conventional Feedback-Linearization-based controller, applied to the tilt-rotor (eight inputs), results in the extensive changes in the tilting angles, which are not expected in practice. To solve this problem, we introduce the novel concept UAV gait to restrict the tilting angles. The gait plan was initially to solve the control problems for quadruped (four

Seyf Eddine Ghenimi, Abdelmouhcene Sengouga

We study the small vibrations of axially moving strings described by a wave equation in an interval with two endpoints moving in the same direction with a constant speed. The solution is expressed by a series formula where the coefficients are explicitly computed in function of the initial data. We also define an energy expression for the solution that is co

Shvetank Prakash, Tim Callahan, Joseph Bushagour, Colby Banbury

Need for the efficient processing of neural networks has given rise to the development of hardware accelerators. The increased adoption of specialized hardware has highlighted the need for more agile design flows for hardware-software co-design and domain-specific optimizations. In this paper, we present CFU Playground: a full-stack open-source framework tha

Xiao-Yong Jin

We propose a generic construction of Lie group agnostic and gauge covariant neural networks, and introduce constraints to make the neural networks continuous differentiable and invertible. We combine such neural networks and build gauge field transformations that is suitable for Hybrid Monte Carlo (HMC). We use HMC to sample lattice gauge configurations in t

Dale R. Harshman, Anthony T. Fiory

This article updates version 1 by restricting consideration to only the resistive data and excluding the questioned 287.7-K datum reported for carbonaceous sulfur hydride in Snider et al., Nature $\textbf{585}$, 373 (2020). The superconducting transitions are considered in terms of the theoretically-discovered compressed $I$$\overline{\textrm{4}}$3$m$ CSH$_7

Konrad Altenmüller, Juan F. Castel, Susana Cebrián, Theopisti Dafni

Surface contamination of $^{222}$Rn progeny from the $^{238}$U natural decay chain is one of the most difficult background contributions to measure in rare event searches experiments. In this work we propose AlphaCAMM, a gaseous chamber read with a segmented Micromegas, for the direct measurement of $^{210}$Pb surface contamination of flat samples. The detec

Solomon Negussie Tesema, El-Bay Bourennane

Modern leading object detectors are either two-stage or one-stage networks repurposed from a deep CNN-based backbone classifier network. YOLOv3 is one such very-well known state-of-the-art one-shot detector that takes in an input image and divides it into an equal-sized grid matrix. The grid cell having the center of an object is the one responsible for dete

Olivia Zahn, Jorge Bustamante, Callin Switzer, Thomas Daniel

Insect flight is a strongly nonlinear and actuated dynamical system. As such, strategies for understanding its control have typically relied on either model-based methods or linearizations thereof. Here we develop a framework that combines model predictive control on an established flight dynamics model and deep neural networks (DNN) to create an efficient m

Giulio Rossolini, Federico Nesti, Gianluca D'Amico, Saasha Nair

The existence of real-world adversarial examples (commonly in the form of patches) poses a serious threat for the use of deep learning models in safety-critical computer vision tasks such as visual perception in autonomous driving. This paper presents an extensive evaluation of the robustness of semantic segmentation models when attacked with different types

Sariel Har-Peled, Everett Yang

We present a $(1- \varepsilon)$-approximation algorithms for maximum cardinality matchings in disk intersection graphs -- all with near linear running time. We also present estimation algorithm that returns $(1\pm \varepsilon)$-approximation to the size of such matchings -- this algorithms run in linear time for unit disks, and $O(n \log n)$ for general disk

Charles Collot, Thomas Duyckaerts, Carlos Kenig, Frank Merle

We consider the quadratic semilinear wave equation in six dimensions. This energy critical problem admits a ground state solution, which is the unique (up to scaling) positive stationary solution. We prove that any spherically symmetric solution, that remains bounded in the energy norm, evolves asymptotically to a sum of decoupled modulated ground states, pl

Zoey Liu, Emily Prud'hommeaux

Common designs of model evaluation typically focus on monolingual settings, where different models are compared according to their performance on a single data set that is assumed to be representative of all possible data for the task at hand. While this may be reasonable for a large data set, this assumption is difficult to maintain in low-resource scenario

Makan Zamanipour

\textit{When an adversary gets access to the data sample in the adversarial robustness models and can make data-dependent changes, how has the decision maker consequently, relying deeply upon the adversarially-modified data, to make statistical inference? How can the resilience and elasticity of the network be literally justified $-$ if there exists a tool t

Makan Zamanipour

This paper technically explores the secrecy rate $\Lambda$ and a maximisation problem over the concave version of the secrecy outage probability (SOP) as $\mathop{{\rm \mathbb{M}ax}}\limits_{\Delta } {\rm \; } \mathbb{P}\mathscr{r} \big( \Lambda \ge \lambda \big) $. We do this from a generic viewpoint even though we use a traditional Wyner's wiretap channel

Makan Zamanipour

We in this paper theoretically go over a rate-distortion based sparse dictionary learning problem. We show that the Degrees-of-Freedom (DoF) interested to be calculated $-$ satnding for the minimal set that guarantees our rate-distortion trade-off $-$ are basically accessible through a \textit{Langevin} equation. We indeed explore that the relative time evol

Aaron S. Meyer, André Walker-Loud, Callum Wilkinson

Calculations of neutrino-nucleus cross sections begin with the neutrino-nucleon interaction, making the latter critically important to flagship neutrino oscillation experiments, despite limited measurements with poor statistics. Alternatively, lattice QCD (LQCD) can be used to determine these interactions from the Standard Model with quantifiable theoretical

Fakai Wang, Kang Zheng, Le Lu, Jing Xiao

Osteoporosis is a common chronic metabolic bone disease often under-diagnosed and under-treated due to the limited access to bone mineral density (BMD) examinations, e.g. via Dual-energy X-ray Absorptiometry (DXA). This paper proposes a method to predict BMD from Chest X-ray (CXR), one of the most commonly accessible and low-cost medical imaging examinations

Alfredo Jaramillo, Vinícius Pessoa Mapelli, Luben Cabezas-Gómez

Boiling is a complex phenomenon where different non-linear physical interactions take place and for which the quantitative modeling of the mechanism involved is not fully developed yet. In the last years, many works have been published focusing on the numerical analysis of this problem. However, a lack of numerical works assessing quantitatively the sensitiv

Alexandre Boulch, Renaud Marlet

Implicit neural networks have been successfully used for surface reconstruction from point clouds. However, many of them face scalability issues as they encode the isosurface function of a whole object or scene into a single latent vector. To overcome this limitation, a few approaches infer latent vectors on a coarse regular 3D grid or on 3D patches, and int

Mattia Radice

We consider the dynamical evolution of a Brownian particle undergoing stochastic resetting, meaning that after random periods of time it is forced to return to the starting position. The intervals after which the random motion is stopped are drawn from a Gamma distribution of shape parameter $\alpha$ and scale parameter $r$, while the return motion is perfor

Harry Pei, Maren Vairo

A buyer and a seller bargain over the price of an object. Both players can build reputations for being obstinate by offering the same price over time. Before players bargain, the seller decides whether to adopt a new technology that can lower his cost of production. We show that even when the buyer cannot observe the seller's adoption decision, players' repu

Jacopo Rizzo, Francesco Libbi, Francesco Tacchino, Pauline J. Ollitrault

Many-body Green's functions encode all the properties and excitations of interacting electrons. While these are challenging to be evaluated accurately on a classical computer, recent efforts have been directed towards finding quantum algorithms that may provide a quantum advantage for this task, exploiting architectures that will become available in the near

Itay Levinas, Yoram Louzoun

Multiple methods of finding the vertices belonging to a planted dense subgraph in a random dense $G(n, p)$ graph have been proposed, with an emphasis on planted cliques. Such methods can identify the planted subgraph in polynomial time, but are all limited to several subgraph structures. Here, we present PYGON, a graph neural network-based algorithm, which i

Celina Hanouti, Hervé Le Borgne

Zero-shot learning (ZSL) aims at recognizing classes for which no visual sample is available at training time. To address this issue, one can rely on a semantic description of each class. A typical ZSL model learns a mapping between the visual samples of seen classes and the corresponding semantic descriptions, in order to do the same on unseen classes at te

Davis Arthur, Prasanna Date

Deep learning is one of the most successful and far-reaching strategies used in machine learning today. However, the scale and utility of neural networks is still greatly limited by the current hardware used to train them. These concerns have become increasingly pressing as conventional computers quickly approach physical limitations that will slow performan

Joseph Gais, Ken Ng, Eungwang Seo, Kaze W. K. Wong

The population properties of intermediate mass black holes remain largely unknown, and understanding their distribution could provide a missing link in the formation of supermassive black holes and galaxies. Gravitational wave observations can help fill in the gap from stellar mass black holes to supermassive black holes. In our work, we propose a new method

Fernando Benjamín Pérez Maurera, Maurizio Ferrari Dacrema, Paolo Cremonesi

This work explores the reproducibility of CFGAN. CFGAN and its family of models (TagRec, MTPR, and CRGAN) learn to generate personalized and fake-but-realistic rankings of preferences for top-N recommendations by using previous interactions. This work successfully replicates the results published in the original paper and discusses the impact of certain diff

Farzad Pourbabaee

I introduce a dynamic model of learning and random meetings between a long-lived agent with unknown ability and heterogeneous projects with observable qualities. The outcomes of the agent's matches with the projects determine her posterior belief about her ability (i.e., her reputation). In a self-type learning framework with endogenous outside option, I fin

Alfredo M. Ozorio de Almeida

Phase space reflection operators lie at the core of the Wigner-Weyl representation of density operators and observables. The role of the corresponding classical reflections is known in the construction of semiclassical approximations to Wigner functions of pure eigenstates and their coarsegrained microcanonical superpositions, which are not restricted to cla

Abdullah Alomar, Pouya Hamadanian, Arash Nasr-Esfahany, Anish Agarwal

We present CausalSim, a causal framework for unbiased trace-driven simulation. Current trace-driven simulators assume that the interventions being simulated (e.g., a new algorithm) would not affect the validity of the traces. However, real-world traces are often biased by the choices algorithms make during trace collection, and hence replaying traces under a

Kamil Erdayandi, Amrit Paudel, Lucas Cordeiro, Mustafa A. Mustafa

In this paper, we propose a decentralized, privacy-friendly energy trading platform (PFET) based on game theoretical approach - specifically Stackelberg competition. Unlike existing trading schemes, PFET provides a competitive market in which prices and demands are determined based on competition, and computations are performed in a decentralized manner whic

Neel Haldolaarachchige

Student performance of virtual introductory physics class (calculus-based mechanics) is analyzed. A fully web-enhanced class was done synchronously. The analysis is done in two categories, averaging all mid-exams (or chapter exams) and cumulative final exams. It shows that students perform well with shorter timed mid-semester assessments (or chapter exams) t

Imen Bouabdallah, Hakima Mellah

Cloud computing is an opened and distributed network that guarantees access to a large amount of data and IT infrastructure at several levels (software, hardware...). With the increase demand, handling clients' needs is getting increasingly challenging. Responding to all requesting clients could lead to security breaches, and since it is the provider's respo

Mikhail Khovanov, Maithreya Sitaraman, Daniel Tubbenhauer

The linear decomposition attack provides a serious obstacle to direct applications of noncommutative groups and monoids (or semigroups) in cryptography. To overcome this issue we propose to look at monoids with only big representations, in the sense made precise in the paper, and undertake a systematic study of such monoids. One of our main tools is Green's

Pierfrancesco Siena, Michele Girfoglio, Gianluigi Rozza

In this work a machine learning-based Reduced Order Model (ROM) is developed to investigate in a rapid and reliable way the hemodynamic patterns in a patient-specific configuration of Coronary Artery Bypass Graft (CABG). The computational domain is composed by the left branches of coronary arteries when a stenosis of the Left Main Coronary Artery (LMCA) occu

Weiqiang Wang, Weinan Zhang

We initiate a general approach to the relative braid group symmetries on (universal) $\imath$quantum groups, arising from quantum symmetric pairs of arbitrary finite types, and their modules. Our approach is built on new intertwining properties of quasi $K$-matrices which we develop and braid group symmetries on (Drinfeld double) quantum groups. Explicit for

Huijie Zheng, Jaroslav Hruby, Emilie Bourgeois, Josef Soucek

While nitrogen-vacancy (NV-) centers have been extensively investigated in the context of spin-based quantum technologies, the spin-state readout is conventionally performed optically, which may limit miniaturization and scalability. Here, we report photoelectric readout of ground-state cross-relaxation features, which serves as a method for measuring electr

Amin Ebrahimi, Mohammad Sattari, Scholte J. L. Bremer, Martin Luckabauer

The absorptivity of a material is a major uncertainty in numerical simulations of laser welding and additive manufacturing, and its value is often calibrated through trial-and-error exercises. This adversely affects the capability of numerical simulations when predicting the process behaviour and can eventually hinder the exploitation of fully digitised manu

Long Chen, Michał Czakon

We provide the $\bar{\mathrm{MS}}$ factor of the renormalization constant of the singlet axial-current operator in dimensional regularization at $\mathcal{O}(\alpha_s^5)$ in perturbative Quantum Chromodynamics (QCD). The result is obtained from a formula derived using the Adler-Bell-Jackiw equation in terms of renormalized operators. The required input consi

Patrick Tamburo, Philip S. Muirhead, Allison M. McCarthy, Murdock Hart

We describe the Perkins INfrared Exosatellite Survey (PINES), a near-infrared photometric search for short-period transiting planets and moons around a sample of 393 spectroscopically confirmed L- and T-type dwarfs. PINES is performed with Boston University's 1.8 m Perkins Telescope Observatory, located on Anderson Mesa, Arizona. We discuss the observational

Lu Yu, Jiaying Gu, Stanislav Volgushev

Consider a panel data setting where repeated observations on individuals are available. Often it is reasonable to assume that there exist groups of individuals that share similar effects of observed characteristics, but the grouping is typically unknown in advance. We first conduct a local analysis which reveals that the variances of the individual coefficie

Yizhuang Liu, Maciej A. Nowak, Ismail Zahed

We revisit the holographic description of strange baryons in the context of the Sakai-Sugimoto construction, by considering the strange quark mass as heavy. Hyperons are described by a massive $(K,K^*)$ multiplet, bound to a light-flavor instanton in bulk, much in the spirit of the Callan-Klebanov construction. The modular Hamiltonian maps onto the Landau pr

Martin van Beek

We describe several exotic fusion systems related to the Sporadic simple groups at odd primes. More generally, we classify saturated fusion systems supported on Sylow $3$-subgroups of the Conway group $\mathrm{Co}_1$ and the Thompson group $\mathrm{F}_3$, and a Sylow $5$-subgroup of the Monster $\mathrm{M}$, as well as a particular maximal subgroup of the la

Ana Luisa Foguel, Peter Reimitz, Renata Zukanovich Funchal

Abelian U(1) gauge group extensions of the Standard Model represent one of the most minimal approaches to solve some of the most urgent particle physics questions and provide a rich phenomenology in various experimental searches. In this work, we focus on baryophilic vector mediator models in the MeV-to-GeV mass range and, in particular, present, for the fir

Nicolas Gontier, Siva Reddy, Christopher Pal

We study the utility of incorporating entity type abstractions into pre-trained Transformers and test these methods on four NLP tasks requiring different forms of logical reasoning: (1) compositional language understanding with text-based relational reasoning (CLUTRR), (2) abductive reasoning (ProofWriter), (3) multi-hop question answering (HotpotQA), and (4

Alberto Guijosa, Yaithd D. Olivas, Juan F. Pedraza

There is some tension between two well-known ideas in holography. On the one hand, subregion duality asserts that the reduced density matrix associated with a limited region of the boundary theory is dual to a correspondingly limited region in the bulk, known as the entanglement wedge. On the other hand, correlators that in the boundary theory can be compute

V. Montenegro, M. G. Genoni, A. Bayat, M. G. A. Paris

Hybrid optomechanical systems are emerging as a fruitful architecture for quantum technologies. Hence, determining the relevant atom-light and light-mechanics couplings is an essential task in such systems. The fingerprint of these couplings is left in the global state of the system during non-equilibrium dynamics. However, in practice, performing measuremen

Jorge Miguel-Ramiro, Ferran Riera-Sàbat, Wolfgang Dür

Maximally entangled states are a key resource in many quantum communication and computation tasks, and their certification is a crucial element to guarantee the desired functionality. We introduce collective strategies for the efficient, local verification of ensembles of Bell pairs that make use of an initial information and noise transfer to few copies pri

Dávid Guszejnov, Carleen Markey, Stella S. R. Offner, Michael Y. Grudić

Stars form in dense, clustered environments, where feedback from newly formed stars eventually ejects the gas, terminating star formation and leaving behind one or more star clusters. Using the STARFORGE simulations, it is possible to simulate this process in its entirety within a molecular cloud, while explicitly evolving the gas radiation and magnetic fiel

Stephen Ebert, Eliot Hijano, Per Kraus, Ruben Monten

Pure three-dimensional gravity is a renormalizable theory with two free parameters labelled by $G$ and $\Lambda$. As a consequence, correlation functions of the boundary stress tensor in AdS$_3$ are uniquely fixed in terms of one dimensionless parameter, which is the central charge of the Virasoro algebra. The same argument implies that AdS$_3$ gravity at a

Mohammad Alidoust, Klaus Halterman

Starting from a low-energy effective Hamiltonian model, we theoretically calculate the dynamical optical conductivity and permittivity tensor of a magnetized graphene layer with Rashba spin orbit coupling (SOC). Our results reveal a transverse Hall conductivity correlated with the usual nonreciprocal longitudinal conductivity. Further analysis illustrates th

Zidu Liu, Pei-Xin Shen, Weikang Li, L. -M. Duan

Capsule networks, which incorporate the paradigms of connectionism and symbolism, have brought fresh insights into artificial intelligence. The capsule, as the building block of capsule networks, is a group of neurons represented by a vector to encode different features of an entity. The information is extracted hierarchically through capsule layers via rout

Dong Yuan, Shun-Yao Zhang, Yu Wang, L. -M. Duan

Quantum many-body scarred systems host special non-thermal eigenstates that support periodic revival dynamics and weakly break the ergodicity. Here, we study the quantum information scrambling dynamics in quantum many-body scarred systems, with a focus on the "PXP" model. We use the out-of-time-ordered correlator (OTOC) and Holevo information as measures of

K. Zheng, D. Kowsari, N. J. Thobaben, X. Du

Microwave loss in niobium metallic structures used for superconducting quantum circuits is limited by a native surface oxide layer formed over a timescale of minutes when exposed to an ambient environment. In this work, we show that nitrogen plasma treatment forms a niobium nitride layer at the metal-air interface which prevents such oxidation. X-ray photoel

Baoxing Zhai, Bohao Li, Yao Wen, Fengcheng Wu

A noncentrosymmetric superconductor can have a superconducting diode effect, where the critical current in opposite directions is different when time-reversal symmetry is also broken. We theoretically propose that a ferroelectric superconductor with coexisting ferroelectricity and superconductivity can support a ferroelectric reversible superconducting diode

Justin C. Feng, Filip Hejda, Sante Carloni

In this article, we describe and numerically implement a method for relativistic location in slightly curved but otherwise generic spacetimes. For terrestrial positioning in the context of Global Navigation Satellite Systems, our algorithm incorporates gravitational as well as tropospheric and ionospheric effects modeled by the Gordon metric. The algorithm i

Tristan Martin, Ivar Martin, Kartiek Agarwal

Symmetries (and their spontaneous rupturing) can be used to protect and engender novel quantum phases and lead to interesting collective phenomena. In Ref. 1, the authors described a general dynamical decoupling (polyfractal) protocol that can be used to engineer multiple discrete symmetries in many-body systems. The present work expands on the former by stu

Jesse Thorner

We show that Landau-Siegel zeros for Dirichlet $L$-functions do not exist or quantum unique ergodicity for $\mathrm{GL}_2$ Hecke-Maass newforms holds with an effective rate of convergence. This follows from a more general result: Landau-Siegel zeros of Dirichlet $L$-functions repel the zeros of all other automorphic $L$-functions from the line $\mathrm{Re}(s

Samarjeet Singh, Ankit Kumar Dutta, Jayesh M. Dhadphale, Amitesh Roy

Open-loop control is known to be an effective strategy for controlling self-excited thermoacoustic oscillations in turbulent combustors. In this study, we investigate the suppression of thermoacoustic instability in a lean premixed, laboratory-scale combustor using experiments and analysis. Starting with a self-excited thermoacoustic instability in the combu

Bowen Shi, Wei-Ning Hsu, Abdelrahman Mohamed

Audio-based automatic speech recognition (ASR) degrades significantly in noisy environments and is particularly vulnerable to interfering speech, as the model cannot determine which speaker to transcribe. Audio-visual speech recognition (AVSR) systems improve robustness by complementing the audio stream with the visual information that is invariant to noise

Yang Zhou, Jiuhong Xiao, Yue Zhou, Giuseppe Loianno

Multi-robot systems such as swarms of aerial robots are naturally suited to offer additional flexibility, resilience, and robustness in several tasks compared to a single robot by enabling cooperation among the agents. To enhance the autonomous robot decision-making process and situational awareness, multi-robot systems have to coordinate their perception ca

Benedict Guttman-Kenney, Christopher Firth, John Gathergood

We provide the first economic research on `buy now, pay later' (BNPL): an unregulated FinTech credit product enabling consumers to defer payments into interest-free instalments. We study BNPL using UK credit card transaction data. We document consumers charging BNPL transactions to their credit card. Charging of BNPL to credit cards is most prevalent among y

Eitan Frachtenberg, Rhody D. Kaner

The gender gap in computer science (CS) research is a well-studied problem, with an estimated ratio of 15%--30% women researchers. However, far less is known about gender representation in specific fields within CS. Here, we investigate the gender gap in one large field, computer systems. To this end, we combined data from 53 leading systems conferences with

Shriya Soma, Lingxiao Wang, Shuzhe Shi, Horst Stöcker

The Equation of State (EoS) of strongly interacting cold and hot ultra-dense QCD matter remains a major challenge in the field of nuclear astrophysics. With the advancements in measurements of neutron star masses, radii, and tidal deformabilities, from electromagnetic and gravitational wave observations, neutron stars play an important role in constraining t

Tommaso Armadillo, Roberto Bonciani, Simone Devoto, Narayan Rana

We present the two-loop mixed strong-electroweak virtual corrections to the neutral current Drell-Yan process and we provide, in ancillary files, the explicit formulae of the infrared-subtracted finite remainder. The final state collinear singularities are regularised by the lepton mass. The evaluation of all the relevant Feynman integrals, including those w

Maria F. Gamal'

The notion of isometric and unitary asymptotes was introduced for power bounded operators in 1989 and was generalized in 2016--2019 by K\'erchy. In particular, it was shown that there exist operators without unitary asymptote. In this paper operators are constructed which are quasisimilar to isometries and do not have isometric asymptotes. Also a contraction

Mateo Uldemolins, Andrej Mesaros, Pascal Simon

A magnetic impurity on a superconducting substrate induces in-gap Yu-Shiba-Rusinov (YSR) bound states, whose intricate spatial structure crucially influences the possibilities of engineering collective impurity states. By means of a saddle-point approximation we study the scattering processes giving rise to YSR states in gapped, two-dimensional superconducto

Adam Doliwa, Artur Siemaszko

We show that the Wynn recurrence (the missing identity of Frobenius of the Pad\'{e} approximation theory) can be incorporated into the theory of integrable systems as a reduction of the discrete Schwarzian Kadomtsev-Petviashvili equation. This allows, in particular, to present the geometric meaning of the recurrence as a construction of the appropriately con

Jason Miller, Lukas Schoug

We prove the existence and uniqueness of the canonical conformally covariant volume measure on the carpet/gasket of a conformal loop ensemble (CLE$_\kappa$, $\kappa \in (8/3,8)$) which respects the Markov property for CLE. The starting point for the construction is the existence of the canonical measure on CLE in the context of Liouville quantum gravity (LQG

Sebastian C. Carrasco, Michael H. Goerz, Zeyang Li, Simone Colombo

We propose a novel scheme for the generation of optimal squeezed states for Ramsey interferometry. The scheme consists of an alternating series of one-axis twisting pulses and rotations, both of which are straightforward to implement experimentally. The resulting states show a metrological gain proportional to the Heisenberg limit. We demonstrate that the He

Stefano Veronesi, Mario Commodo, Luca Basta, Gianluigi De Falco

Soot nucleation is one of the most complex and debated steps of the soot formation process in combustion. In this work, we used scanning tunneling microscopy (STM) and spectroscopy (STS) to probe morphological and electronic properties of incipient soot particles formed right behind the flame front of a lightly sooting laminar premixed flame of ethylene and

Michael A. Bender, Martín Farach-Colton, William Kuszmaul

In this paper, we revisit the question of how the dynamic optimality of search trees should be defined in external memory. A defining characteristic of external-memory data structures is that there is a stark asymmetry between queries and inserts/updates/deletes: by making the former slightly asymptotically slower, one can make the latter significantly asymp

Robert Bamler

Entropy coding is the backbone data compression. Novel machine-learning based compression methods often use a new entropy coder called Asymmetric Numeral Systems (ANS) [Duda et al., 2015], which provides very close to optimal bitrates and simplifies [Townsend et al., 2019] advanced compression techniques such as bits-back coding. However, researchers with a

Nathan M. Myers, Obinna Abah, Sebastian Deffner

Thermodynamics originated in the need to understand novel technologies developed by the Industrial Revolution. However, over the centuries the description of engines, refrigerators, thermal accelerators, and heaters has become so abstract that a direct application of the universal statements to real-life devices is everything but straight forward. The recent

Niladri Modak, Sayantan Das, Priyanuj Bordoloi, Nirmalya Ghosh

We demonstrate an intriguing giant optical beam shift in a tilted polarizer system analogous to the Imbert-Fedorov shift in partial reflection around the Brewster's angle of incidence. We explain this giant shift using a generalized theoretical treatment for beam shift in a tilted uniaxial anisotropic material incorporating the three-dimensional orientation

Paul A. Monderkamp, René Wittmann, Michael te Vrugt, Axel Voigt

Observing and characterizing the complex ordering phenomena of liquid crystals subjected to external constraints constitutes an ongoing challenge for chemists and physicists alike. To elucidate the delicate balance appearing when the intrinsic positional order of smectic liquid crystals comes into play, we perform Monte-Carlo simulations of rod-like particle

Mayte Bonilla-Quintana, Padmini Rangamani

Effective treatments that prevent or reduce drug relapse vulnerability should be developed to relieve the high burden of drug addiction to society. This will only be possible by enhancing the understanding of the molecular mechanisms underlying the neurobiology of addiction. Recent experimental data have shown that dendritic spines, small protrusions from th

Yoann Brûlé, Peter R. Wiecha, Aurélien Cuche, Vincent Paillard

We design planar silicon antennas for controlling the emission rate of magnetic or electric dipolar emitters. Evolutionary algorithms coupled to the Green Dyadic Method lead to different optimized geometries which depend on the nature and orientation of the dipoles. We discuss the physical origin of the obtained configurations thanks to modal analysis but al

Bowen Shi, Wei-Ning Hsu, Kushal Lakhotia, Abdelrahman Mohamed

Video recordings of speech contain correlated audio and visual information, providing a strong signal for speech representation learning from the speaker's lip movements and the produced sound. We introduce Audio-Visual Hidden Unit BERT (AV-HuBERT), a self-supervised representation learning framework for audio-visual speech, which masks multi-stream vide

A. A. Aguilar-Arevalo, B. C. Brown, J. M. Conrad, R. Dharmapalan

This letter presents the results from the MiniBooNE experiment within a full "3+1" scenario where one sterile neutrino is introduced to the three-active-neutrino picture. In addition to electron-neutrino appearance at short-baselines, this scenario also allows for disappearance of the muon-neutrino and electron-neutrino fluxes in the Booster Neutrino Beam, w

Gerald Handler, Rahul Jayaraman, Donald W. Kurtz, Jim Fuller

The tidally tilted pulsators are a new type of oscillating star in close binary systems that have their pulsation axis in the orbital plane because of the tidal distortion caused by their companion. We describe this group of stars on the basis of the first three representatives discovered and illustrate the basic methods used for their analysis. Their value

Richard F. Lebed

The 2020 announcement by LHCb of a narrow structure $X(6900)$ in the di-$J/\psi$ spectrum -- a potential $c\bar c c\bar c$ state -- has opened a new era in hadronic spectroscopy. In this talk, we briefly survey theory works preceding this event, examine key features of the observed spectrum, and then discuss how subsequent theory studies (including with the

Sylwia Bujkiewicz, Janharpreet Singh, Lorna Wheaton, David Jenkins

Objective: We aim to utilise real world data in evidence synthesis to optimise an evidence base for the effectiveness of biologic therapies in rheumatoid arthritis in order to allow for evidence on first-line therapies to inform second-line effectiveness estimates. Study design and setting: We use data from the British Society for Rheumatology Biologics Regi

Gennady S. Bisnovatyi-Kogan, Oleg Yu. Tsupko

Gravitational lensing of a light source by a black hole leads to appearance of higher-order images produced by photons that loop around the black hole before reaching the observer. Higher-order images were widely investigated numerically and analytically, in particular using so-called strong deflection limit of gravitational deflection. After recent observat

Samuel Gill, Solene Ulmer-Moll, Peter J. Wheatley, Daniel Bayliss

We are using precise radial velocities from CORALIE together with precision photometry from the Next Generation Transit Survey (NGTS) to follow up stars with single-transit events detected with the Transiting Exoplanet Survey Satellite (TESS). As part of this survey we identified a single transit on the star TIC-320687387, a bright (T=11.6) G-dwarf observed

Zhaonan Dong, Alexandre Ern, Jean-Luc Guermond

We estimate best-approximation errors using vector-valued finite elements for fields with low regularity in the scale of fractional-order Sobolev spaces. By assuming additionally that the target field has a curl or divergence property, we establish upper bounds on these errors that can be localized to the mesh cells. These bounds are derived using the quasi-

Fatemeh Akbari, Diana Shvydka

We investigated the possibility of augmenting the fluence of electrons traversing CdTe thin film and thus increasing the detected signal pursuing two venues: adding a high-Z metal layer to the back of the detector surface, and adding a top low-Z material to the detector layer to return its backscattered electrons. Copper (Cu) and lead (Pb) layers of varying

Srdja Janković, Ana Katić, Milan M. Ćirković

Now that we know that Earth-like planets are ubiquitous in the universe, as well as that most of them are much older than the Earth, it is justified to ask to what extent evolutionary outcomes on other such planets are similar, or indeed commensurable, to the outcomes we perceive around us. In order to assess the degree of specialty or mediocrity of our traj

A. F. A. Bott, L. Chen, P. Tzeferacos, C. A. J. Palmer

It has recently been demonstrated experimentally that a turbulent plasma created by the collision of two inhomogeneous, asymmetric, weakly magnetised laser-produced plasma jets can generate strong stochastic magnetic fields via the small-scale turbulent dynamo mechanism, provided the magnetic Reynolds number of the plasma is sufficiently large. In this paper

R. Xu, L. T. Yang, Q. Yue, K. J. Kang

We present new constraints on light dark matter boosted by cosmic rays (CRDM) using the 205.4 kg day data of the CDEX-10 experiment conducted at the China Jinping Underground Laboratory. The Monte Carlo simulation package CJPL\_ESS was employed to evaluate the Earth shielding effect. Several key factors have been introduced and discussed in our CRDM analysis

Woojoo Lee, Yuanxi Wang, Wei Qin, Hyunsue Kim

2D materials have intriguing quantum phenomena that are distinctively different from their bulk counterparts. Recently, epitaxially synthesized wafer-scale 2D metals, composed of elemental atoms, are attracting attention not only for their potential applications but also for exotic quantum effects such as superconductivity. By mapping momentum-resolved elect

Aamo Iorliam, Orgem Emmanuel, Yahaya I. Shehu

Protecting a fingerprint database against attackers is very vital in order to protect against false acceptance rate or false rejection rate. A key property in distinguishing fingerprint images is by exploiting the characteristics of these different types of fingerprint images. The aim of this paper is to perform the classification of fingerprint images using

M. V. del Valle, A. Araudo, F. Suzuki-Vidal

The termination regions of non-relativistic jets in protostars and supersonic outflows in classical novae are nonthermal emitters. Given the high densities in these systems, radiative shocks are expected to form. However, in the presence of high velocities, the formation of adiabatic shocks is also possible. A case of interest is when the two types of shocks

Andrzej Derdzinski, Paolo Piccione

For warped products with harmonic curvature, nonconstant warping functions $\phi$, and compact two-dimensional bases $(M,h)$, we establish a dichotomy: either the Gaussian curvature $K$ of the metric $g=\phi^{-2}h$ is constant and negative, or $\phi$ equals a specific elementary function of $K$, also depending on the dimension $p$ and Einstein constant $\var