May 2022 arXiv papers — page 123

Zijie J. Wang, David Munechika, Seongmin Lee, Duen Horng Chau

How can we develop visual analytics (VA) tools that can be easily adopted? Visualization researchers have developed a large number of web-based VA tools to help data scientists in a wide range of tasks. However, adopting these standalone systems can be challenging, as they require data scientists to create new workflows to streamline the VA processes. Recent

Haiwen Feng, Timo Bolkart, Joachim Tesch, Michael J. Black

Virtual facial avatars will play an increasingly important role in immersive communication, games and the metaverse, and it is therefore critical that they be inclusive. This requires accurate recovery of the appearance, represented by albedo, regardless of age, sex, or ethnicity. While significant progress has been made on estimating 3D facial geometry, alb

Hongkai Chen, Shan Lin, Scott A. Smolka, Nicola Paoletti

Resiliency is the ability to quickly recover from a violation and avoid future violations for as long as possible. Such a property is of fundamental importance for Cyber-Physical Systems (CPS), and yet, to date, there is no widely agreed-upon formal treatment of CPS resiliency. We present an STL-based framework for reasoning about resiliency in CPS in which

Charles Jin, Phitchaya Mangpo Phothilimthana, Sudip Roy

In the past few years, neural architecture search (NAS) has become an increasingly important tool within the deep learning community. Despite the many recent successes of NAS, however, most existing approaches operate within highly structured design spaces, and hence explore only a small fraction of the full search space of neural architectures while also re

Carlos Valcárcel

We study a bi-parametric family of dilaton gravity models with constant and negative curvature. This family includes the Jackiw-Teitelboim gravity and the Liouville gravity model induced by a bosonic string. Furthermore, this family is conformally equivalent to the hiperbolic dilaton models. We propose boundary conditions in the Fefferman-Graham and in the E

A. Venegas-Li, J. P. Crutchfield

If an experimentalist observes a sequence of emitted quantum states via either projective or positive-operator-valued measurements, the outcomes form a time series. Individual time series are realizations of a stochastic process over the measurements' classical outcomes. We recently showed that, in general, the resulting stochastic process is highly complex

Thiago Fassarella, Nivaldo Medeiros, Rodrigo Salomão

Given a hypersurface in a complex projective space, we prove that the multidegrees of its toric polar map agree, up to sign, with the coefficients of the Chern-Schwartz-MacPherson class of a distinguished open set, namely the complement of the union of the hypersurface and the coordinate hyperplanes. In particular, the degree of the toric polar map is given

Faruk Temur

The regularity of the Hardy-Littlewood maximal function, in both discrete and continuous contexts, and for both centered and noncentered variants, has been subjected to intense study for the last two decades. But efforts so far have concentrated on first order differentiability and variation, as it is known that in the continuous context higher order regular

Ziwei Qiu, Assaf Hamo, Uri Vool, Tony X. Zhou

Nitrogen-vacancy (NV) center in diamond is a promising quantum sensor with remarkably versatile sensing capabilities. While scanning NV magnetometry is well-established, NV electrometry has been so far limited to bulk diamonds. Here we demonstrate imaging external alternating (AC) and direct (DC) electric fields with a single NV at the apex of a diamond scan

Bhishan Jacelon

The action on the trace space induced by a generic automorphism of a suitable finite classifiable C*-algebra is shown to be chaotic and weakly mixing. Model C*-algebras are constructed to observe the central limit theorem and other statistical features of strongly chaotic tracial actions. Genericity of finite Rokhlin dimension is used to describe KK-contract

Isha M. Datye, Alwin Daus, Ryan W. Grady, Kevin Brenner

Strain engineering is an important method for tuning the properties of semiconductors and has been used to improve the mobility of silicon transistors for several decades. Recently, theoretical studies have predicted that strain can also improve the mobility of two-dimensional (2D) semiconductors, e.g. by reducing intervalley scattering or lowering effective

Marsel Matdinov

The article introduces some ideas for solving special cases of the following problem, proposed in a somewhat generalized form by Marcus Hutter in 2000. Given two Turing machines $A$ and $C$, it is required to build a Turing machine $B$, such that after interacting of $A$ and $B$ on a shared tape for a fixed number of iterations, the machine $C$ outputs 1 on

Victor Aguirregabiria

This paper studies identification and estimation of a dynamic discrete choice model of demand for differentiated product using consumer-level panel data with few purchase events per consumer (i.e., short panel). Consumers are forward-looking and their preferences incorporate two sources of dynamics: last choice dependence due to habits and switching costs, a

Shalaleh Rismani, AJung Moon

With the growing need to regulate AI systems across a wide variety of application domains, a new set of occupations has emerged in the industry. The so-called responsible AI practitioners or AI ethicists are generally tasked with interpreting and operationalizing best practices for ethical and safe design of AI systems. Due to the nascent nature of these rol

Robert T. Kozma, Jenő Szirmai

We determine the optimal horoball packing densities for Koszul-type Coxeter simplex tilings in hyperbolic $3$-space. Using a parametrization of horoballs by the Busemann function and the symmetry of the tilings, we obtain families of packings that attain the universal simplicial density upper bound \[ d_3(\infty) \;=\; \left( 2 \sqrt{3}\,\Lambda\!\left(\tfra

Robert Rehammar, Simone Gasparinetti

A new type of low-pass filter based on a leaky coaxial waveguide is presented. The filter has minimal insertion loss in the pass band, while at the same time high attenuation in the stop band is achieved. Thanks to its arrangement, the filter does not present parasitic leakage paths, so that, unlike conventional resonant filters, the stop band extends to ver

Alexander R. Farhang, Jeremy Bernstein, Kushal Tirumala, Yang Liu

Weight norm $\|w\|$ and margin $γ$ participate in learning theory via the normalized margin $γ/\|w\|$. Since standard neural net optimizers do not control normalized margin, it is hard to test whether this quantity causally relates to generalization. This paper designs a series of experimental studies that explicitly control normalized margin and thereby tac

Duilio De Santis, Claudio Guarcello, Bernardo Spagnolo, Angelo Carollo

The dynamics of sine-Gordon breathers is studied in the presence of dissipative and stochastic perturbations. Taking a stationary breather with a random phase value as the initial state, the performed simulations demonstrate that a spatially-homogeneous noisy source can make the oscillatory excitation more stable, i.e., it enables the latter to last signific

Apolline Louvet, Amandine Veber

The k-parent and infinite-parent spatial Lambda-Fleming Viot processes (or SLFV), introduced in Louvet (2023), form a family of stochastic models for spatially expanding populations. These processes are akin to a continuous-space version of the classical Eden growth model (but with local backtracking of the occupied area allowed when k is finite), while bein

LHCb collaboration

The production of prompt $D^0$ mesons in proton-lead collisions in the forward and backward configurations at a center-of-mass energy per nucleon pair of $\sqrt{s_\mathrm{NN}} = 8.16~\mathrm{TeV}$ is measured by the LHCb experiment. The nuclear modification factor of prompt $D^0$ mesons is determined as a function of the transverse momentum $p_\mathrm{T}$, a

Jaime E. Pineda, Doris Arzoumanian, Philippe André, Rachel K. Friesen

The study of the development of structures on multiple scales in the cold interstellar medium has experienced rapid expansion in the past decade, on both the observational and the theoretical front. Spectral line studies at (sub-)millimeter wavelengths over a wide range of physical scales have provided unique probes of the kinematics of dense gas in star-for

Hammaad Adam, Ming Ying Yang, Kenrick Cato, Ioana Baldini

Clinical notes are becoming an increasingly important data source for machine learning (ML) applications in healthcare. Prior research has shown that deploying ML models can perpetuate existing biases against racial minorities, as bias can be implicitly embedded in data. In this study, we investigate the level of implicit race information available to ML mod

Víctor Mayoral-Vilches, Sabrina M. Neuman, Brian Plancher, Vijay Janapa Reddi

Hardware acceleration can revolutionize robotics, enabling new applications by speeding up robot response times while remaining power-efficient. However, the diversity of acceleration options makes it difficult for roboticists to easily deploy accelerated systems without expertise in each specific hardware platform. In this work, we address this challenge wi

Fred Espen Benth, Dennis Schroers, Almut E. D. Veraart

This article establishes an asymptotic theory for volatility estimation in an infinite-dimensional setting. We consider mild solutions of semilinear stochastic partial differential equations and derive a stable central limit theorem for the semigroup adjusted realised covariation (SARCV), which is a consistent estimator of the integrated volatility and a gen

Aditya Jain, Akhil Rao

Orbit-use management efforts can be structured as binding national regulatory policies or as self-enforcing international treaties. New treaties to control space debris growth appear unlikely in the near future. Spacefaring nations can pursue national regulatory policies, though regulatory competition and open access to orbit make their effectiveness unclear

Alexander Hicks

Both technical security mechanisms and legal processes serve as mechanisms to deal with misbehaviour according to a set of norms. While they share general similarities, there are also clear differences in how they are defined, act, and the effect they have on subjects. This paper considers the similarities and differences between both types of mechanisms as

Cameron Smith, Hong-Xing Yu, Sergey Zakharov, Fredo Durand

Neural scene representations, both continuous and discrete, have recently emerged as a powerful new paradigm for 3D scene understanding. Recent efforts have tackled unsupervised discovery of object-centric neural scene representations. However, the high cost of ray-marching, exacerbated by the fact that each object representation has to be ray-marched separa

Maciej J. Capinski, Shane Kepley, Jason D. Mireles James

This paper considers two point boundary value problems for conservative systems defined in multiple coordinate systems, and develops a flexible a-posteriori framework for computer assisted existence proofs. Our framework is applied to the study collision and near collision orbits in the circular restricted three body problem. In this case the coordinate syst

Keerti Anand, Rong Ge, Amit Kumar, Debmalya Panigrahi

This paper studies online algorithms augmented with multiple machine-learned predictions. While online algorithms augmented with a single prediction have been extensively studied in recent years, the literature for the multiple predictions setting is sparse. In this paper, we give a generic algorithmic framework for online covering problems with multiple pre

Wei Xie, Giulia Pedrielli

The increasingly pressing demand of novel drugs (e.g., gene therapies for personalized cancer care, ever evolving vaccines) with unprecedented levels of personalization, has put a remarkable pressure on the traditionally long time required by the pharma R&D and manufacturing to go from design to production of new products. The revolution has already brought

Subhadip Dey, Michael Kapovich

We prove a generalization of the classical Klein-Maskit combination theorem, in the free product case, in the setting of Anosov subgroups. Namely, if $\Gamma_A$ and $\Gamma_B$ are Anosov subgroups of a semisimple Lie group $G$ of noncompact type, then under suitable topological assumptions, the group generated by $\Gamma_A$ and $\Gamma_B$ in $G$ is again Ano

Talal Ahmed Chowdhury, Shaikh Saad

Very recently, a substantial $7\sigma$ deviation of the $W$-boson mass from the Standard Model (SM) prediction has been reported by the CDF collaboration. Furthermore, the Muon g-2 Experiment recently confirmed the longstanding tension in $(g-2)_\mu$. Besides, the updated result from the LHCb collaboration found evidence for the breaking of lepton universali

Seungchul Baek

High dimensional classification has been highlighted for last two decades and much research has been conducted in order to circumvent challenges encountered in high dimensions. While existing methods have focused mainly on developing classification rules assuming independence of covariates or using regularization on the sample covariance matrix or the sample

Emilie Bout, Alessandro Brighente, Mauro Conti, Valeria Loscri

Channel hopping provides a defense mechanism against jamming attacks in large scale \ac{iot} networks.} However, a sufficiently powerful attacker may be able to learn the channel hopping pattern and efficiently predict the channel to jam. In this paper, we present FOLPETTI, a MAB-based attack to dynamically follow the victim's channel selection in real-t

Iago Dal-Ri dos Santos, Neda Yaghoobian

This study investigates the role of topography-induced turbulence, generated by an idealized urban region, in the transport of firebrands and risk of spotting. Flight dispersion, deposition, and smoldering state of tens of thousands of individual mass and size-changing firebrands were investigated in the atmospheric boundary layer turbulence, which was obtai

Saurabh Saxena, Ritambhara Dubey, Neda Yaghoobian

Fuel ignition potential is one of the primary drivers influencing the extent of damage in wildland and wildland-urban interface fires. Determining fire and ember exposure of fuels that vary spatially and temporally will help to recognize necessary defensive actions and reduce damages. In this paper, the development of a new computational model, Temperature A

Grigory Malinovsky, Peter Richtárik

Random Reshuffling (RR), which is a variant of Stochastic Gradient Descent (SGD) employing sampling without replacement, is an immensely popular method for training supervised machine learning models via empirical risk minimization. Due to its superior practical performance, it is embedded and often set as default in standard machine learning software. Under

Benjamin Amend, Jonathan Zrake, Dieter H. Hartmann

Compact binary mergers involving at least one neutron star are promising sites for the synthesis of $\textit{r}$-process elements found in stars and planets. However, mergers can take place at significant offsets from their host galaxies, with many occurring several kpc from star-forming regions. It is thus important to understand the physical mechanisms inv

Ruiyang Zhou, Fengying Wei

In this article, we construct an age-structured model for COVID-19 with vaccination and analyze it from multiple perspectives. We derive the unique disease-free equilibrium point and the basic reproduction number $ \mathscr{R}_0 $, then we show that the disease-free equilibrium is locally asymptotically stable when $ \mathscr{R}_0 < 1 $, while is unstable wh

Adir Kobovich, Orian Leitersdorf, Daniella Bar-Lev, Eitan Yaakobi

Reliability is an inherent challenge for the emerging nonvolatile technology of racetrack memories, and there exists a fundamental relationship between codes designed for racetrack memories and codes with constrained periodicity. Previous works have sought to construct codes that avoid periodicity in windows, yet have either only provided existence proofs or

Tommaso Comparin, Fabio Mezzacapo, Tommaso Roscilde

The scalable production of multipartite entangled states in ensembles of qubits is a fundamental function of quantum devices, as such states are an essential resource both for fundamental studies on entanglement, as well as for applied tasks. Here we focus on the $U(1)$ symmetric Hamiltonians for qubits with dipolar interactions -- a model realized in severa

Shun Imamura, Kohei Sawaki, John J. Molina, Matthew S. Turner

A Quincke roller is a unique active particle that can run and tumble freely on a flat plate due to the torque generated by a uniform DC electric field applied perpendicular to the plate. A system involving many such particles exhibits a variety of collective dynamics, such as the disordered gas, polar liquid, and active crystal states. We performed direct nu

Alessandro Ferrari, Francisco Queirós

We study how firm heterogeneity and market power affect macroeconomic fragility, defined as the probability of long slumps. We propose a theory in which the positive interaction between firm entry, competition and factor supply can give rise to multiple steady-states. We show that when firms are highly heterogeneous in terms of productivities, even small tem

Brandon T. Shapiro, David I. Spivak

Natural organized systems adapt to internal and external pressures and this happens at all levels of the abstraction hierarchy. Wanting to think clearly about this idea motivates our paper, and so the idea is elaborated extensively in the introduction, which should be broadly accessible to a philosophically-interested audience. In the remaining sections, we

Jiawei Wang, Ruiyang Zhou, Fengying Wei

This paper considers a single-population model with age structure and psychological effects in a polluted environment. We divide the single population into two stages of larval and adult structure. The model uses Logistic input, and the larvae are converted into adult bodies by constant ratio. We only consider adulthood. The role of psychological effects mak

Khanh Nguyen Duc, Nguyen Thi Ngoc Giao, Dang Tuan Hiep, Do Le Hai Thuy

We introduce a general class of symmetric polynomials that have saturated Newton polytope and their Newton polytope has integer decomposition property. The class covers numerous previously studied symmetric polynomials.

Arya Bangun, Oleh Melnyk, Benjamin März, Benedikt Diederichs

We propose algorithms based on an optimisation method for inverse multislice ptychography in, e.g. electron microscopy. The multislice method is widely used to model the interaction between relativistic electrons and thick specimens. Since only the intensity of diffraction patterns can be recorded, the challenge in applying inverse multislice ptychography is

Hesham Sharkas

This study introduces a new multi-antenna array synthesizer based on Slepian functions. The synthesizer concentrates beamforming (BF) gain within a spatial region (i.e., an angular sector), optimizing Shannon capacity of the targeted region, which is suitable for codebook-based analog BF. Starting with the mean capacity formula incorporating the effect of BF

Arnav Joshi, Andy Eskenazi, Landon Butler, Megan Ryerson

Restructuring route networks (i.e., modifying the graph of origin-destination pairs) remains a promising alternative for reducing the airline industry's environmental impact. However, there exists a fundamental trade-off between emissions from flight and airport accessibility, since flights connecting underserved, low-accessibility communities tend to posses

Dan Dai, Yu Zhai

In this paper, we consider the deformed Fredholm determinant of the confluent hypergeometric kernel. This determinant represents the gap probability of the corresponding determinantal point process where each particle is removed independently with probability $1- γ$, $0 \leq γ<1$. We derive asymptotics of the deformed Fredholm determinant when the gap interv

Swagata Ghosh

At the Large Hadron Collider (LHC), ATLAS and CMS collaborations observed various decay modes of the light charged Higgs bosons produced by top (anti)quark decays. In this paper, we are interested in the subsequent decay of the light charged Higgs boson into a charm and a strange quark-antiquark pair and into a tau and a tau-neutrino pair, separately, in the

V. Courtillot, JL. Le Mouël, F. Lopes

Variations in sea-level, based on tide gauge data (GSLTG) and on combining tide gauges and satellite data (GSLl) are subjected to singular spectrum analysis (SSA), to determine their trends and periodic or quasi-periodic components. GLSTG increases by 90 mm from 1860 to 2020, a contribution of 0.56 mm/yr to the mean rise rate. Annual to multi-decadal periods

Bjoern Bringmann, Yu Deng, Andrea R. Nahmod, Haitian Yue

We prove the invariance of the Gibbs measure under the dynamics of the three-dimensional cubic wave equation, which is also known as the hyperbolic $Φ^4_3$-model. This result is the hyperbolic counterpart to seminal works on the parabolic $Φ^4_3$-model by Hairer &#39;14 and Hairer-Matetski &#39;18. The heart of the matter lies in establishing local in time e

Peng Gao, Teli Ma, Hongsheng Li, Ziyi Lin

Vision Transformers (ViT) become widely-adopted architectures for various vision tasks. Masked auto-encoding for feature pretraining and multi-scale hybrid convolution-transformer architectures can further unleash the potentials of ViT, leading to state-of-the-art performances on image classification, detection and semantic segmentation. In this paper, our C

Peeravit Koad, Jatechan Channuie, Phongpichit Channuie

In this work, we investigate the preheating mechanism after inflation in general scalar-tensor theories of gravity. In the present scenario, we consider two-field scenario and then derive the potential of exponential and hyperbolic tangent forms. We study the evolution of the background system when the back reaction on the background field is neglected. We e

Chen Cheng, Gia-Wei Chern

We present a general theory of atomic self-diffusion in the vicinity of a Mott metal-insulator transition in fluid metals. Upon decreasing the electron correlation from the Mott insulating phase, the delocalization of electrons gives rise to an increasing attractive interatomic interaction, which is expected to introduce an additional friction, hence reducin

Mi Jin Lee, Jung-Ho Kim, Kwang-Il Goh, Sang Hoon Lee

Perturbations made to networked systems may result in partial structural loss, such as a blackout in a power-grid system. Investigating the resultant disturbance in network properties is quintessential to understand real networks in action. The removal of nodes is a representative disturbance, but previous studies are seemingly contrasting about its effect o

Hanju Yoo, Taehun Jung, Linglong Dai, Songkuk Kim

Semantic communications are expected to enable the more effective delivery of meaning rather than a precise transfer of symbols. In this paper, we propose an end-to-end deep neural network-based architecture for image transmission and demonstrate its feasibility in a real-time wireless channel by implementing a prototype based on a field-programmable gate ar

Zongjiang Tu, Die Liu, Xiaoqing Wang, Chen Jiang

Deep learning based parallel imaging (PI) has made great progresses in recent years to accelerate magnetic resonance imaging (MRI). Nevertheless, it still has some limitations, such as the robustness and flexibility of existing methods have great deficiency. In this work, we propose a method to explore the k-space domain learning via robust generative modeli

Yuki Fujimoto, Kenji Fukushima, Kenta Hotokezaka, Koutarou Kyutoku

The cores of neutron stars (NSs) near the maximum mass realize the most highly compressed matter in the universe where quark degrees of freedom may be liberated. Such a state of dense matter is hypothesized as quark matter (QM) and its presence has awaited to be confirmed for decades in nuclear physics. Gravitational waves from binary NS mergers are expected

Kuntal Panwar, Prabhu Babu, R. Jyothi

This paper investigates the hybrid source localization problem using the four radio measurements - time of arrival (TOA), time difference of arrival (TDOA), received signal strength (RSS), and angle of arrival (AOA). First, after invoking tractable approximations in the RSS and AOA models, the maximum likelihood estimation (MLE) problem for the hybrid TOA-TD

Zifeng Zhao, Xiaokai Luo, Zongge Liu, Daren Wang

In this paper, we study change-point testing for high-dimensional linear models, an important problem that has not been well explored in the literature. Specifically, we propose a quadratic-form cumulative sum (CUSUM) statistic to test the stability of regression coefficients in high-dimensional linear models. The test controls type-I error at any desired le

Alexei Entin, Noam Pirani

We prove that for any prime $p>2$, $q=p^\nu$ a power of $p$, $n\ge p$ and $G=S_n$ or $G=A_n$ (symmetric or alternating group) there exists a Galois extension $K/\mathbb F_q(T)$ ramified only over $\infty$ with $\mathrm{Gal}(K/\mathbb F_q(T))=G$. This confirms a conjecture of Abhyankar for the case of symmetric and alternating groups over finite fields of odd

Qing-Yu Zhai, Ming-Zhu Liu, Jun-Xu Lu, Li-Sheng Geng

We revisit the $D_s^-D^{*0}$/$D_s^{*-}D^0$ interaction and the $Z_{cs}(3985)$ state in chiral effective field theory(EFT) up to the next-to-leading order. We examine the relative importance of the leading-order contact, one-eta exchange, next-to-leading-order contact, and two-kaon-exchange contributions. We show that the leading-order and next-to-leading-ord

Jason L. Evans, Tsutomu T. Yanagida, Norimi Yokozaki

It is known that the recently reported shift of the W boson mass can be easily explained by an $SU(2)_L$ triplet Higgs boson with a zero hypercharge if it obtains a vacuum expectation value (VEV) of $O(1)$ GeV. Surprisingly, the addition of a TeV scale complex triplet Higgs boson to the standard model (SM) leads to a precise unification of the gauge coupling

Evgenii Simakov, Andrey Tyukhtin

We analyze electromagnetic radiation from a bunch passing through a corrugated conductive planar structure. The wavelengths of the radiation are assumed to be much greater than the corrugation period. Under this approximation, the corrugated structure can be replaced with a smooth surface on which the so-called equivalent boundary conditions (EBC) are fulfil

Xin He, Baihua Wu, Youhao Shang, Bingqi Li

We report recent progress on the phase space formulation of quantum mechanics with coordinate-momentum variables, focusing more on new theory of (weighted) constraint coordinate-momentum phase space for discrete-variable quantum systems. This leads to a general coordinate-momentum phase space formulation of composite quantum systems, where conventional repre

Jingzhe Guo, Huazhe Lou, Riling Li, Wang Fang

We introduce isQ, a new software stack for quantum programming in an imperative programming language, also named isQ. The aim of isQ is to make the programmers write quantum programs as conveniently as possible. In particular: 1) The isQ language and its compiler contain many features, including some not well supported by (most) other quantum programming pla

Ziv Roi-Cohen, Merav Kahn, Stefania Residori, Umberto Bortolozzo

We simplify the Ashworth-Davies special relativistic theory of a uniformly translating mirror with an arbitrary angle of incidence and direction of propagation in the non-relativistic limit. We show that it is in good agreement with a more intuitive derivation that only considers the constancy of the speed of light. We experimentally confirm the theory predi

C. Aydin, O. Uzun, A. I. Ahmadov

We have investigated the contribution of the Higher Twist (HT) Feynman diagrams to the large-$p_T$ inclusive $ρ_L$ meson production cross section in proton-proton and proton-antiproton collisions and we discuss the phenomenological consequences of possible HT contributions to cross sections. To extract HT subprocesses from Leading Twist (LT) background, we u

Alessandro Ferrari

I study the role of industries' position in supply chains in shaping the transmission of final demand shocks. First, I use a novel shift-share design leveraging destination-specific final demand shocks and a new measure of destination exposure accounting for direct and indirect linkages. I find that demand shocks amplify significantly as they propagate upstr

V. Guzey, M. Strikman, M. Zhalov

In this Letter, we consider strong and electromagnetic (ultraperipheral) mechanisms in proton-nucleus coherent diffraction at the CERN Large Hadron Collider. We explicitly demonstrate the dominance of the latter and explain the CMS data on the forward rapidity gap distribution in $pPb$ collisions at $\sqrt{s_{NN}}=8.16$ TeV. In particular, we provide simple

Chunyu Xie, Heng Cai, Jincheng Li, Fanjing Kong

Vision-language pre-training (VLP) on large-scale datasets has shown premier performance on various downstream tasks. In contrast to plenty of available benchmarks with English corpus, large-scale pre-training datasets and downstream datasets with Chinese corpus remain largely unexplored. In this work, we build a large-scale high-quality Chinese Cross-Modal

Dipankar Roy, Abhishek Dhar, Herbert Spohn, Manas Kulkarni

Recent investigations have observed superdiffusion in integrable classical and quantum spin chains. An intriguing connection between these spin chains and Kardar-Parisi-Zhang (KPZ) universality class has emerged. Theoretical developments (e.g. generalized hydrodynamics) have highlighted the role of integrability as well as spin-symmetry in KPZ behaviour. How

Lokahith Agasthya, Andreas Bartel, Luca Biferale, Matthias Ehrhardt

Non-isothermal particles suspended in a fluid lead to complex interactions -- the particles respond to changes in the fluid flow, which in turn is modified by their temperature anomaly. Here, we perform a novel proof-of-concept numerical study based on tracer particles that are thermally coupled to the fluid. We imagine that particles can adjust their intern

Ming-Zhe Han, Shao-Peng Tang, Yi-Zhong Fan

We introduce a new nonparametric representation of the neutron star (NS) equation of state (EoS) by using the variational autoencoder (VAE). As a deep neural network, the VAE is frequently used for dimensionality reduction since it can compress input data to a low-dimensional latent space using the encoder component and then reconstruct the data using the de

Ling Luo, Chih-Hsuan Wei, Po-Ting Lai, Qingyu Chen

The automatic assignment of species information to the corresponding genes in a research article is a critically important step in the gene normalization task, whereby a gene mention is normalized and linked to a database record or identifier by a text-mining algorithm. Existing methods typically rely on heuristic rules based on gene and species co-occurrenc

Cyril Bachelard, Apostolos Chalkis, Vissarion Fisikopoulos, Elias Tsigaridas

We propose novel randomized geometric tools to detect low-volatility anomalies in stock markets; a principal problem in financial economics. Our modeling of the (detection) problem results in sampling and estimating the (relative) volume of geodesically non-convex and non-connected spherical patches that arise by intersecting a non-standard simplex with a sp

Ngan Nguyen, Feng Liang, Dominik Engel, Ciril Bohak

We propose a new microscopy simulation system that can depict atomistic models in a micrograph visual style, similar to results of physical electron microscopy imaging. This system is scalable, able to represent simulation of electron microscopy of tens of viral particles and synthesizes the image faster than previous methods. On top of that, the simulator i

Yasuyuki Hamura

In this note, we consider the problem of estimating multinomial cell probabilities under the entropy loss when side information in aggregated data is available. We use the Jeffreys prior to obtain Bayes estimators. It is shown that by incorporating the side information, we can construct an improved estimator.

Tatiana Yu. Alekhina, Andrey V. Tyukhtin

We analyze radiation from a bunch that uniformly moves in a circular waveguide and crosses the boundary between two areas: with a corrugated wall and with a smooth wall. It is assumed that the corrugation period is much less than the wavelengths under consideration. However, in difference with our pervious works, the corrugation depth is of the same order as

Vladimir S. Gerdjikov, Georgi G. Grahovski, Alexander A. Stefanov

The paper is devoted to real Hamiltonian forms of 2-dimensional Toda field theories related to exceptional simple Lie algebras, and to the spectral theory of the associated Lax operators. Real Hamiltonian forms are a special type of "reductions" of Hamiltonian systems, similar to real forms of semi-simple Lie algebras. Examples of real Hamiltonian forms of a

Maria Spethmann, Xian-Peng Zhang, Jelena Klinovaja, Daniel Loss

Superconducting spin qubits, also known as Andreev spin qubits, promise to combine the benefits of superconducting qubits and spin qubits defined in quantum dots. While most approaches to control these qubits rely on controlling the spin degree of freedom via the supercurrent, superconducting spin qubits can also be coupled to each other via the superconduct

Shokoufe Faraji, Audrey Trova, Hernando Quevedo

We investigate the physical properties of equilibrium sequences of non-self-gravitating surfaces that characterize thick disks around a rotating deformed compact object described by a stationary generalization of the static q-metric. The spacetime corresponds to an exact solution of Einstein's field equations so that we can perform the analysis for arbitrary

Diego Berti, Luca Bisconti, Davide Catania

In this paper we deal with the 3D tropical climate model with damping terms in the equation of the barotropic mode $u$ and in the equation of the first baroclinic mode $v$ of the velocity, and we establish a regularity criterion for this system thanks to which the local smooth solution $(u, v, θ)$ can actually be extended globally in time.

Tomasz Komorowski, Joel L. Lebowitz, Stefano Olla

We investigate the properties of a harmonic chain in contact with a thermal bath at one end and subjected, at its other end, to a periodic force. The particles also undergo a random velocity reversal action, which results in a finite heat conductivity of the system. We prove the approach of the system to a time periodic state and compute the heat current, eq

Hisanori Suzuki, Takumi Omori, Kazuhiko Hara, Hiroki Yamauchi

We developed a beam telescope system comprising five layers of 300-$μ$m-thick INTPIX4NA monolithic pixel sensors with each pixel size of 17 $μ$m square. The sensors were fabricated using silicon-on-insulator (SOI) technology. The signal-to-noise ratio of 140--230 is realized at a bias voltage of 20~V. The tracker system was tested using a positron beam of 20

Yairon Cid-Ruiz, Claudia Polini, Bernd Ulrich

We provide a generalization of Jouanolou duality that is applicable to a plethora of situations. The environment where this generalized duality takes place is a new class of rings, that we introduce and call weakly Gorenstein. As a main consequence, we obtain a new general framework to investigate blowup algebras. We use our results to study and determine th

Shishir Kumar Pandey, Ji Feng

In the quest for materials hosting Kitaev spin liquids, much of the efforts have been focused on the fourth- and fifth-row transition metal compounds, which are spin-orbit coupling assisted Mott insulators. Here, we study the structural and magnetic properties of 3$d$ transition metal oxides, Na$_2$Co$_2$TeO$_6$ and Na$_3$Co$_2$SbO$_6$. The partial occupancy

Yongjie Wang, Chuan Wang, Ruobing Li, Hui Lin

In recent years, pre-trained models have become dominant in most natural language processing (NLP) tasks. However, in the area of Automated Essay Scoring (AES), pre-trained models such as BERT have not been properly used to outperform other deep learning models such as LSTM. In this paper, we introduce a novel multi-scale essay representation for BERT that c

Anis Allagui, Hachemi Benaoum, Ahmed S. Elwakil, Mohammad Alshabi

Electrochemical capacitors are a class of energy devices in which complex mechanisms of accumulation and dissipation of electric energy take place when connected to a charging or discharging power system. Reliably modeling their frequency-domain and time-domain behaviors is crucial for their proper design and integration in engineering applications, knowing

Nyothiri Aung, Tahar Kechadi, Tao Zhu, Saber Zerdoumi

With the rapid development of the Internet of Things (IoT) and its potential integration with the traditional Vehicular Ad-Hoc Networks (VANETs), we have witnessed the emergence of the Internet of Vehicles (IoV), which promises to seamlessly integrate into smart transportation systems. However, the key characteristics of IoV, such as high-speed mobility and

Sarbojit Roy, Soham Sarkar, Subhajit Dutta, Anil K. Ghosh

We propose a new model-free feature screening method based on energy distances for ultrahigh-dimensional binary classification problems. With a high probability, the proposed method retains only relevant features after discarding all the noise variables. The proposed screening method is also extended to identify pairs of variables that are marginally undetec

Yuxuan Peng

We obtain new vacuum static black hole solutions with anisotropic horizons in Einstein-Gauss-Bonnet gravity with a negative cosmological constant in five dimensions. The translational invariance along one direction on the 3-dimensional horizon cross section is broken. The Gauss-Bonnet coupling {\alpha} is at the critical point where there is one single AdS v

Dimitri Loutchko, Yuki Sughiyama, Tetsuya J. Kobayashi

It is known that the trajectory of an endoreversibly driven system with minimal dissipation is a geodesic on the equilibrium state space. Thereby, the state space is equipped with the Riemannian metric given by the Hessian of the free energy function, known as Fisher information metric. However, the derivations given until now require both the system and the

Ang Li, Shanshan Zhao, Qingjie Zhang, Qiuhong Ke

Currently, single image inpainting has achieved promising results based on deep convolutional neural networks. However, inpainting on stereo images with missing regions has not been explored thoroughly, which is also a significant but different problem. One crucial requirement for stereo image inpainting is stereo consistency. To achieve it, we propose an It

Yudai Ueki, Shunsuke Kamimura, Yuichiro Matsuzaki, Kyo Yoshida

A quantum battery is a device where an energy is charged by using a quantum effect. Here, we propose a quantum battery with a charger system composed of $N$ qubits by utilizing a collective effect called a superabsorption. Importantly, the coupling strength between the quantum battery and charger system can be enhanced due to an entanglement. While the charg

M. G. Burt

A translation is provided of the nonspecialist article by N G van Kampen which seeks to dispel much of the mysticism surrounding quantum measurement.

Yunsong Luo, Wenyu Chen, Jiang Qiu, Tao Jia

Major depressive disorder (MDD) is one of the most common mental health conditions that has been intensively investigated for its association with brain atrophy and mortality. Recent studies reveal that the deviation between the predicted and the chronological age can be a marker of accelerated brain aging to characterize MDD. However, current conclusions ar

Xijin Chen, Kim May Lee, Sofia S. Villar, David S. Robertson

When comparing the performance of multi-armed bandit algorithms, the potential impact of missing data is often overlooked. In practice, it also affects their implementation where the simplest approach to overcome this is to continue to sample according to the original bandit algorithm, ignoring missing outcomes. We investigate the impact on performance of th