August 2022 arXiv papers — page 98

Ibrahim Merad, Stéphane Gaïffas

We propose statistically robust and computationally efficient linear learning methods in the high-dimensional batch setting, where the number of features $d$ may exceed the sample size $n$. We employ, in a generic learning setting, two algorithms depending on whether the considered loss function is gradient-Lipschitz or not. Then, we instantiate our framewor

Jiyang Zhang, Sheena Panthaplackel, Pengyu Nie, Junyi Jessy Li

Pretrained language models have been shown to be effective in many software-related generation tasks; however, they are not well-suited for editing tasks as they are not designed to reason about edits. To address this, we propose a novel pretraining objective which explicitly models edits and use it to build CoditT5, a large language model for software-relat

Jaejin Cho, Jes'us Villalba, Laureano Moro-Velazquez, Najim Dehak

In recent studies, self-supervised pre-trained models tend to outperform supervised pre-trained models in transfer learning. In particular, self-supervised learning (SSL) of utterance-level speech representation can be used in speech applications that require discriminative representation of consistent attributes within an utterance: speaker, language, emoti

Chenru Duan, Aditya Nandy, Gianmarco Terrones, David W. Kastner

Transition metal chromophores with earth-abundant transition metals are an important design target for their applications in lighting and non-toxic bioimaging, but their design is challenged by the scarcity of complexes that simultaneously have optimal target absorption energies in the visible region as well as well-defined ground states. Machine learning (M

Hamed Hojatian, Jérémy Nadal, Jean-François Frigon, François Leduc-Primeau

Hybrid beamforming is a promising technology to improve the energy efficiency of massive MIMO systems. In particular, subarray hybrid beamforming can further decrease power consumption by reducing the number of phase-shifters. However, designing the hybrid beamforming vectors is a complex task due to the discrete nature of the subarray connections and the ph

Yao Yu, Xiong Zhuang, Han Zhang, Bai-Cian Ke

An analysis of the $J/\psi\to \eta\eta^\prime\gamma$ decay by the BESIII collaboration claims the observation of an exotic state $\eta_1(1855)$ with $I^GJ^{PC}=0^+1^{-+}$. To establish its C-parity partner $\eta^\prime_{1}(1855)$ in the picture of the $K \bar{K}_1(1400)$ molecular state, we propose that $J/\psi\to\eta^\prime_{1}(1855)\eta^{(\prime)}$ receive

A. Metelmann

Parametric couplings in engineered quantum systems are a powerful tool to control, manipulate and enhance interactions in a variety of platforms. It allows us to bring systems of different energy scales into communication with each other. This short chapter introduces the basic principles and discusses a few examples of how one can engineer parametric amplif

Nicole Fronda, Houssam Abbas

We demonstrate the first Recurrent Neural Network architecture for learning Signal Temporal Logic formulas, and present the first systematic comparison of formula inference methods. Legacy systems embed much expert knowledge which is not explicitly formalized. There is great interest in learning formal specifications that characterize the ideal behavior of s

Shi-Zhuo Looi

We study the quasilinear wave equation $\Box_{g}\phi=0$ where the metric $g = g(\phi,t,x)$ is close to and asymptotically approaches $g(0,t,x)$, which equals the Schwarzschild metric or a Kerr metric with small angular momentum, as time tends to infinity. Under only weak assumptions on the metric coefficients, we prove an improved pointwise decay rate for th

Hongyang Du, Jiazhen Liu, Dusit Niyato, Jiawen Kang

Metaverse encapsulates our expectations of the next-generation Internet, while bringing new key performance indicators (KPIs). Although conventional ultra-reliable and low-latency communications (URLLC) can satisfy objective KPIs, it is difficult to provide a personalized immersive experience that is a distinctive feature of the Metaverse. Since the quality

Deren Han, Jiaxin Xie

We present a new framework for the analysis and design of randomized algorithms for solving various types of linear systems, including consistent or inconsistent, full rank or rank-deficient. Our method is formulated with four randomized sampling parameters, which allows the method to cover many existing randomization algorithms within a unified framework, i

José M. M. Senovilla

The existence of gravitational radiation arriving at null infinity -- i.e. escaping from the physical system -- is addressed in the presence of a non-negative cosmological constant $\Lambda\geq 0$. The case with vanishing $\Lambda$ is well understood and relies on the properties of the News tensor field (or the News function) defined at infinity. The situati

Rahul Gaur, Ian G. Abel, David Dickinson, William D. Dorland

High-power-density tokamaks offer a potential solution to design cost-effective fusion devices. One way to achieve high power density is to operate at a high $\beta$ value (the ratio of thermal to magnetic pressure), i.e., $\beta \sim 1$. However, a $\beta \sim 1$ state may be unstable to various pressure- and current-driven instabilities or have unfavorable

B. A. Cervantes-Vergara, S. Perez, J. C. D'Olivo, J. Estrada

This work briefly discusses the potential applications of the Skipper-CCD technology in astronomy and reviews its current use in dark matter and neutrino experiments. An overview of the ongoing efforts to build multi-kilogram experiments with these sensors is given, in the context of the Oscura experiment. First results from the characterization of Oscura se

E. Gallego-Cano, R. Schödel, A. T. Gallego-Calvente, A. M. Ghez

Optimal error estimation is key to achieve accurate photometry and astrometry. Stellar fluxes and positions in high angular resolution images are typically measured with PSF fitting routines, such as StarFinder. However, the formal uncertainties computed by these software packages tend to seriously underestimate the relevant uncertainties. We present a new a

Thao Nguyen, Hieu H. Pham, Huy Khiem Le, Anh Tu Nguyen

The COVID-19 pandemic has exposed the vulnerability of healthcare services worldwide, raising the need to develop novel tools to provide rapid and cost-effective screening and diagnosis. Clinical reports indicated that COVID-19 infection may cause cardiac injury, and electrocardiograms (ECG) may serve as a diagnostic biomarker for COVID-19. This study aims t

G. Gilmore, S. Randich, C. C. Worley, A. Hourihane

The Gaia-ESO Public Spectroscopic Survey is an ambitious project designed to obtain astrophysical parameters and elemental abundances for 100,000 stars, including large representative samples of the stellar populations in the Galaxy, and a well-defined sample of 60 (plus 20 archive) open clusters. We provide internally consistent results calibrated on benchm

Nadav Schneider, Matan Rusanovsky, Raz Gvishi, Gal Oren

High energy density physics (HEDP) experiments commonly involve a dynamic wave-front propagating inside a low-density foam. This effect affects its density and hence, its transparency. A common problem in foam production is the creation of defective foams. Accurate information on their dimension and homogeneity is required to classify the foams' quality. The

C. Branchina, V. Branchina, F. Contino

We present a radically new proposal for the solution of the naturalness/hierarchy problem, where the fine-tuning of the Higgs mass finds its physical explanation and the well-known multiplicative renormalization of the usual perturbative approach emerges as an IR property of the non-perturbative running of the mass.

Giuseppina Di Blasio, Giovanni Pisante, Georgios Psaradakis

We fill the gap left open in \cite{MT}, regarding the minimum exponent on the logarithmic correction weight so that the Leray-Trudinger inequality (see \cite{PsSp}) holds. Instead of the representation formula used in \cite{PsSp} and \cite{MT}, our proof uses expansion in spherical harmonics as in \cite{VzZ}.

Hung Viet Chu

For Schauder bases, Dilworth et al. introduced and characterized the partially greedy property, which is strictly weaker than the (almost) greedy property. Later, Berasategui et al. defined and studied the strong partially greedy property for general bases. Let $\mathbf n$ be any strictly increasing sequence of positive integers. In this paper, we define the

Yuankun Fu, Fengguang Song

Lattice Boltzmann method (LBM) is a promising approach to solving Computational Fluid Dynamics (CFD) problems, however, its nature of memory-boundness limits nearly all LBM algorithms' performance on modern computer architectures. This paper introduces novel sequential and parallel 3D memory-aware LBM algorithms to optimize its memory access performance. The

George J. Wilkie, Torsten Keßler, Sergej Rjasanow

The Boltzmann equation describes the evolution of the phase-space probability distribution of classical particles under binary collisions. Approximations to it underlie the basis for several scholarly fields, including aerodynamics and plasma physics. While these approximations are appropriate in their respective domains, they can be violated in niche but di

Hailong Dao, David Eisenbud

The Burch index is a new invariant of a local ring $R$ whose positivity implies a kind of linearity in resolutions of $R$-modules. For example, if $R$ has depth zero and Burch index at least $2$, then any non-free 7th $R$-syzygy contains the residue field as a direct summand. We also compute the Burch index in various cases of interest.

Mamadou Yauck

This paper deals with the estimation of population sizes for respondent-driven sampling (RDS), a variant of link-tracing sampling that leverages social networks over a number of waves to recruit individuals from hidden populations. The RDS process is mostly controlled by individual participants who might report on recruitment proposals, or nominations, that

Suhyeon Lee, Donghwan Lee, Seungjoo Kim

Proof-of-Work (PoW) is a Sybil control mechanism adopted in blockchain-based cryptocurrencies. It prevents the attempt of malicious actors to manipulate distributed ledgers. Bitcoin has successfully suppressed double-spending by accepting the longest PoW chain. Nevertheless, PoW encountered several major security issues surrounding mining competition. One of

David Jensen, Sarah C. Millholland

Planetary systems with mean-motion resonances (MMRs) hold special value in terms of their dynamical complexity and their capacity to constrain planet formation and migration histories. The key towards making these connections, however, is to have a reliable characterization of the resonant dynamics, especially the so-called "libration amplitude", which quali

Jakob Glas, Leonhard Hochfilzer

Given a non-singular diagonal cubic hypersurface $X\subset\mathbb{P}^{n-1}$ over $\mathbb{F}_q(t)$ with $\mathrm{char} (\mathbb{F}_q)\neq 3$, we show that the number of rational points of height at most $|P|$ is $O(|P|^{3+\varepsilon})$ for $n=6$ and $O(\lvert P \rvert^{2+\varepsilon})$ for $n=4$. In fact, if $n=4$ and $\mathrm{char}(\mathbb{F}_q) >3$ we pro

Jordi Paillisse, Alberto Rodriguez-Natal, Fabio Maino, Albert Cabellos

In the last 15 years, the Internet architecture has continued evolving organically, introducing new headers and protocols to the classic TCP/IP stack. More specifically, we have identified two major trends. First, it is common that most communications are encrypted, either at L3 or L4. And second, due to protocol ossification, developers have resorted to upp

Saket Kapse, Dena Rahman, Eldad J Avital, Taylor Smith

A conceptual design of a novel UVC-LED air-cleaner is presented as part of an international educational-research study. The main components are a dust-filter assembly, a UVC chamber and a fan. The dust-filter aims to suppress dust accumulation that will hamper the UVC chamber operation. The innovation is in the UVC chamber that includes a novel turbulence-ge

L. F. Cugliandolo, M. Mueller

We review recent research on quantum glasses, with a focus on their equilibrium dynamics and the interplay between glassiness and localization phenomena. Interesting relations with the SYK model are discussed.

Maowu Nie, Chunjian Zhang, Zhenyu Chen, Li Yi

Fluctuations of harmonic flow along pseudorapidity, known as flow decorrelations, are an important probe of the initial state geometry of the quark-gluon plasma. The flow decorrelations are shown to be sensitive to the collective structure of the colliding nuclei, as revealed clearly by comparing collisions of isobars, $^{96}$Ru+$^{96}$Ru and $^{96}$Zr+$^{96

Shoaib Khalid, Hadass S. Inbar, Shouvik Chatterjee, Christopher J. Palmstrom

Three-dimensional topological semimetals host a range of interesting quantum phenomena related to band crossing that give rise to Dirac or Weyl fermions, and can be potentially engineered into novel quantum devices. Harvesting the full potential of these materials will depend on our ability to position the Fermi level near the symmetry-protected band crossin

Sidi Wu, Cédric Beaulac, Jiguo Cao

The regression of a functional response on a set of scalar predictors can be a challenging task, especially if there is a large number of predictors, or the relationship between those predictors and the response is nonlinear. In this work, we propose a solution to this problem: a feed-forward neural network (NN) designed to predict a functional response usin

Yuanzhao Zhai, Kele Xu, Bo Ding, Dawei Feng

Aggregating messages is a key component for the communication of multi-agent reinforcement learning (Comm-MARL). Recently, it has witnessed the prevalence of graph attention networks (GAT) in Comm-MARL, where agents can be represented as nodes and messages can be aggregated via the weighted passing. While successful, GAT can lead to homogeneity in the strate

Jaejin Cho, Raghavendra Pappagari, Piotr Żelasko, Laureano Moro-Velazquez

Considering the abundance of unlabeled speech data and the high labeling costs, unsupervised learning methods can be essential for better system development. One of the most successful methods is contrastive self-supervised methods, which require negative sampling: sampling alternative samples to contrast with the current sample (anchor). However, it is hard

Evagoras Stylianou, Lorenz Welter, Rawad Bitar, Antonia Wachter-Zeh

We consider the problem of correcting insertion and deletion errors in the $d$-dimensional space. This problem is well understood for vectors (one-dimensional space) and was recently studied for arrays (two-dimensional space). For vectors and arrays, the problem is motivated by several practical applications such as DNA-based storage and racetrack memories.

Sorabh Chhabra, Abhay A. Kohok, Bhushan S. Joshi, A. N. Ramprakash

The Speckle Imager via MUlti Layer Atmospheric Turbulence Object Reconstructor (SIMULATOR) is a lab-based testbed instrument developed to test for speckle correlation-based techniques in the optical regime. However, this instrument can be used as a testbed against post-processing techniques or algorithms like lucky imaging, phase diversity method etc. The SI

Kasthuri Jayarajah, Aryya Gangopadhyay, Nicholas Waytowich

The availability of sensor-rich smart wearables and tiny, yet capable, unmanned vehicles such as nano quadcopters, opens up opportunities for a novel class of highly interactive, attention-shared human--machine teams. Reliable, lightweight, yet passive exchange of intent, data and inferences within such human--machine teams make them suitable for scenarios s

Stefano Marseglia

We give an algorithm to compute representatives of the conjugacy classes of semisimple square integral matrices with given minimal and characteristic polynomials. We also give an algorithm to compute the $\mathbb{F}_q$-isomorphism classes of abelian varieties over a finite field $\mathbb{F}_q$ which belong to an isogeny class determined by a characteristic p

Sarah Azouvi, Marko Vukolić

Blockchain systems based on a reusable resource, such as proof-of-stake (PoS), provide weaker security guarantees than those based on proof-of-work. Specifically, they are vulnerable to long-range attacks, where an adversary can corrupt prior participants in order to rewrite the full history of the chain. To prevent this attack on a PoS chain, we propose a p

Thomas Lam

This short introduction to positive geometries, targeted at a mathematical audience, is based on my talk at OPAC 2022.

Arpan Mukherjee, Ali Tajer, Pin-Yu Chen, Payel Das

Consider $K$ processes, each generating a sequence of identical and independent random variables. The probability measures of these processes have random parameters that must be estimated. Specifically, they share a parameter $\theta$ common to all probability measures. Additionally, each process $i\in\{1, \dots, K\}$ has a private parameter $\alpha_i$. The

Alexander Barvinok

Let $f: {\Bbb R}^n \longrightarrow {\Bbb R}$ be a positive definite quadratic form and let $y \in {\Bbb R}^n$ be a point. We present a fully polynomial randomized approximation scheme (FPRAS) for computing $\sum_{x \in {\Bbb Z}^n} e^{-f(x)}$, provided the eigenvalues of $f$ lie in the interval roughly between $s$ and $e^{s}$ and for computing $\sum_{x \in {\

James Weng, Wenqian Xu, Kamila M. Wiaderek, Olaf J. Borkiewicz

Gain calibration of x-ray area detectors is a challenge due to the inability to generate an x-ray flat field at the selected photon energy that the beamline operates at, which has a strong influence on the detector's gain behavior. A method is presented in which a gain map is calculated without flat field measurements. Rather, a series of quick scattering me

Angelo Di Canto, Stefan Meinel

Precision measurements in weak decays of heavy flavored hadrons can test in unique ways our understanding of the fundamental interactions and of the observed baryon asymmetry in the Universe. The high sensitivity of such decays to beyond-Standard-Model physics, combined with the lack of major discoveries in direct production of new particles, motivates the c

Pablo Barros, Alessandra Sciutti

Current facial expression recognition systems demand an expensive re-training routine when deployed to different scenarios than they were trained for. Biasing them towards learning specific facial characteristics, instead of performing typical transfer learning methods, might help these systems to maintain high performance in different tasks, but with a redu

Stewart Glegg, Siddhartha Verma, Lyubov Denissova

The modeling of surface pressure wave number spectra beneath a turbulent boundary layer is reviewed and reconsidered in terms of the vorticity in the flow. Using a solution based on the vorticity equation and Squires theorem, which was originally given by Chase(1991), it is shown that the complete solution for surface pressure spectrum can be specified using

Zitong Yu, Rizhao Cai, Zhi Li, Wenhan Yang

Face anti-spoofing (FAS) and face forgery detection play vital roles in securing face biometric systems from presentation attacks (PAs) and vicious digital manipulation (e.g., deepfakes). Despite promising performance upon large-scale data and powerful deep models, the generalization problem of existing approaches is still an open issue. Most of recent appro

Marina Ghisi, Massimo Gobbino

We prove that the classical hyperbolic Kirchhoff equation admits global-in-time solutions for some classes of initial data in the energy space. We also show that there are enough such solutions so that every initial datum in the energy space is the sum of two initial data for which a global-in-time solution exists. The proof relies on the notion of spectral

Zhongliang Jiang, Yuan Gao, Le Xie, Nassir Navab

Robotic ultrasound (US) imaging aims at overcoming some of the limitations of free-hand US examinations, e.g. difficulty in guaranteeing intra- and inter-operator repeatability. However, due to anatomical and physiological variations between patients and relative movement of anatomical substructures, it is challenging to robustly generate optimal trajectorie

Szabolcs Borsanyi, Zoltan Fodor, Matteo Giordano, Jana N. Guenther

The equation of state of the quark gluon plasma is a key ingredient of heavy ion phenomenology. In addition to the traditional Taylor method, several novel approximation schemes have been proposed with the aim of calculating it at finite baryon density. In order to gain a pragmatic understanding of the limits of these schemes, we compare them to direct resul

Sorabh Chhabra, Michele Frangiamore, Stefan Kraus, Andrea Bianco

The BIFROST instrument will be the first VLTI instrument optimised for high spectral resolution up to R=25,000 and operate between 1.05 and 1.7 $\mu$m. A key component of the instrument will be the spectrograph, where we require a high throughput over a broad bandwidth. In this contribution, we discuss the four planned spectral modes (R=50, R=1000, R=5000, a

Andreas Abels, Leon Ladewig, Kevin Schewior, Moritz Stinzendörfer

We revisit the knapsack-secretary problem (Babaioff et al.; APPROX 2007), a generalization of the classic secretary problem in which items have different sizes and multiple items may be selected if their total size does not exceed the capacity $B$ of a knapsack. Previous works show competitive ratios of $1/(10e)$ (Babaioff et al.), $1/8.06$ (Kesselheim et al

Yeqi Gao, Lianke Qin, Zhao Song, Yitan Wang

Adversarial training is a widely used strategy for making neural networks resistant to adversarial perturbations. For a neural network of width $m$, $n$ input training data in $d$ dimension, it takes $\Omega(mnd)$ time cost per training iteration for the forward and backward computation. In this paper we analyze the convergence guarantee of adversarial train

Takeshi Seki, Yong-Chang Lau, Junya Ikeda, Kohei Fujiwara

Co$_{3}$Sn$_{2}$S$_{2}$ (CSS) is one of the shandite compounds and becomes a magnetic Weyl semimetal candidate below the ferromagnetic phase transition temperature ($\textit{T}_\textrm{C}$). In this paper, we investigate the temperature ($\textit{T}$) dependence of conversion between charge current and spin current for the CSS thin film by measuring the spin

Hadi Wazni, Kin Ian Lo, Lachlan McPheat, Mehrnoosh Sadrzadeh

We use the Lambek Calculus with soft sub-exponential modalities to model and reason about discourse relations such as anaphora and ellipsis. A semantics for this logic is obtained by using truncated Fock spaces, developed in our previous work. We depict these semantic computations via a new string diagram. The Fock Space semantics has the advantage that its

Daniel Elfverson, Robert Scheichl, Simon Weissmann, F. Alejandro DiazDelaO

In this work we propose an adaptive multilevel version of subset simulation to estimate the probability of rare events for complex physical systems. Given a sequence of nested failure domains of increasing size, the rare event probability is expressed as a product of conditional probabilities. The proposed new estimator uses different model resolutions and v

Jue Hou

We show that method of characteristics provides a powerful new point of view on $T\bar{T}$-and related deformations. Previously, the method of characteristics has been applied to $T\bar{T}$-deformation mainly to solve Burgers' equation, which governs the deformation of the \emph{quantum} spectrum. In the current work, we study \emph{classical} deformed quant

Piero Nicolini

In this paper, we present an overview of some of the existing issues of the research in quantum gravity. We also introduce the basic ideas that led Padmanabhan to consider a duality property in path integrals. Such a duality is consistent with the T-duality in string theory. More importantly, the path integral duality discloses a universal feature of any qua

Tomas Sauer, A. Michael Stock

We show how total variation regularization of images in arbitrary dimensions can be approximately performed by applying appropriate shrinkage to some Haar wavelets coefficients. The approach works directly on the wavelet coefficients and is therefore suited for the application on large volumes from computed tomography.

Heinrich van Deventer, Anna Bosman

Artificial neural networks (ANNs), despite their universal function approximation capability and practical success, are subject to catastrophic forgetting. Catastrophic forgetting refers to the abrupt unlearning of a previous task when a new task is learned. It is an emergent phenomenon that hinders continual learning. Existing universal function approximati

Venelin Kovatchev

This dissertation explores the linguistic and computational aspects of the meaning relations that can hold between two or more complex linguistic expressions (phrases, clauses, sentences, paragraphs). In particular, it focuses on Paraphrasing, Textual Entailment, Contradiction, and Semantic Similarity. In Part I: "Similarity at the Level of Words and Phrases

Kangqing Ye, Peng Liu, Xiaoyang Zou, Qin Zhou

Three-dimensional (3D) integrated renal structures (IRS) segmentation is important in clinical practice. With the advancement of deep learning techniques, many powerful frameworks focusing on medical image segmentation are proposed. In this challenge, we utilized the nnU-Net framework, which is the state-of-the-art method for medical image segmentation. To r

Doudou Hei, Xinmin Hou

Given an $(r+1)$-chromatic graph $F$ and a graph $H$ that does not contain $F$ as a subgraph, we say that $H$ is strictly $F$-Tur\'an-good if the Tur\'an graph $T_{r}(n)$ is the unique graph containing the maximum number of copies of $H$ among all $F$-free graphs on $n$ vertices for every $n$ large enough. Gy\H{o}ri, Pach and Simonovits (1991) proved that cy

Ya-Wen Pan, Tian-Wei Wu, Ming-Zhu Liu, Li-Sheng Geng

The three pentaquark states, $P_c(4312)$, $P_c(4440)$ and $P_c(4457)$, discovered by the LHCb Collaboration in 2019, can be arranged into a complete heavy quark spin symmetry multiplet of hadronic molecules of $\bar{D}^{(\ast)}\Sigma_{c}^{(\ast)}$. In the heavy quark mass limit, the $\Sigma_{c}^{(\ast)}$ baryons can be related to the doubly charmed tetraquar

Tobias Bätge, Itzhak Fouxon, Michael Wilczek

Collisional growth of droplets, such as occurring in warm clouds, is known to be significantly enhanced by turbulence. Whether particles collide depends on their flow history, in particular on their encounters with highly intermittent small-scale turbulent structures, which despite their rarity can dominate the overall collision rate. Intuitively, strong vor

Zhongliang Jiang, Nehil Danis, Yuan Bi, Mingchuan Zhou

Robotic ultrasound (US) imaging has been seen as a promising solution to overcome the limitations of free-hand US examinations, i.e., inter-operator variability. However, the fact that robotic US systems cannot react to subject movements during scans limits their clinical acceptance. Regarding human sonographers, they often react to patient movements by repo

Zhenkun Li, Fan Ye

The guts of a knot is an invariant defined for the knot complement by Agol-Zhang. Nearly fibered knots, which are defined as knots whose Floer homology has dimension two in the top Alexander grading, were introduced by Baldwin-Sivek. In this note, we provide three models for the guts of nearly fibered knots in the $3$-sphere. As a corollary, the nearly fiber

Emeka Obiodu, Aravindh Raman, Abdullahi Abubakar, Simone Mangiante

Connected Cars (CCs) and vehicle-to-everything (V2X) use cases require stringent reliability for safety and non-safety uses. With increasing network softwarisation, it has become easier to use multiple, redundant connectivity options instead of relying on a single network connectivity. But where should these redundant connections be managed? Is it at a netwo

Lucas Labadie

Long-baseline interferometry and high-resolution spectroscopy are two examples of areas that have benefited from astrophotonics devices, but the application range is expanding to other subareas and other wavelength ranges. The VLTI has been one of the pioneering astronomical infrastructure to exploit the potential of astrophotonics instrumentation for high-a

Guy Rotman, Roi Reichart

Multi-task learning, in which several tasks are jointly learned by a single model, allows NLP models to share information from multiple annotations and may facilitate better predictions when the tasks are inter-related. This technique, however, requires annotating the same text with multiple annotation schemes which may be costly and laborious. Active learni

Huarui He, Jie Wang, Yunfei Liu, Feng Wu

Single-step retrosynthesis is the cornerstone of retrosynthesis planning, which is a crucial task for computer-aided drug discovery. The goal of single-step retrosynthesis is to identify the possible reactants that lead to the synthesis of the target product in one reaction. By representing organic molecules as canonical strings, existing sequence-based retr

Chen Ding, Xiao-Yue Xu, Shuo Zhang, Wan-Su Bao

As we are entering the era of constructing practical quantum computers, suppressing the inevitable noise to accomplish reliable computational tasks will be the primary goal. Leakage noise, as the amplitude population leaking outside the qubit subspace, is a particularly damaging source of error that error correction approaches cannot handle. However, the imp

Izabela Babiarz, Roman Pasechnik, Wolfgang Schäfer, Antoni Szczurek

In this work, we perform a detailed study of transition form factors for axial-vector meson production via the two-photon fusion process $\gamma^* \gamma^* \to 1^{++}$, with space-like virtual photons in the initial state and a $P$-wave axial-vector quarkonium in the final state. In this analysis, we employ the formalism of light-front quarkonium wave functi

Zhujun Zhang

A selfmate is a Chess problem in which White, moving first, needs to force Black to checkmate within a specified number of moves. The reflexmate is a derivative of the selfmate in which White compels Black to checkmate with the added condition that if either player can checkmate, they must do that (when this condition applies only to Black, it is a semi-refl

Sipeng Zheng, Qi Zhang, Bei Liu, Qin Jin

In this paper we provide the technique report of Ego4D natural language query challenge in CVPR 2022. Natural language query task is challenging due to the requirement of comprehensive understanding of video contents. Most previous works address this task based on third-person view datasets while few research interest has been placed in the ego-centric view

Kohei Hayashi

The Kardar-Parisi-Zhang (KPZ) equation is a stochastic partial differential equation which is derived from various microscopic models, and to establish a robust way to derive the KPZ equation is a fundamental problem both in mathematics and in physics. As a microscopic model, we consider multi-species interacting diffusion processes, whose dynamics is driven

Andres F. Castro Torres, Aliakbar Akbaritabar

The importance of research teams' diversity for the progress of science is highlighted extensively. Despite the seemingly hegemonic role of hypothesis testing in modern quantitative research, little attention has been devoted to the diversity of quantitative methods, epitomized by the linear model framework of analysis. Using bibliometric data from the Web o

Jorge Cayao, Annica M. Black-Schaffer

We consider a non-Hermitian superconducting system by coupling a conventional superconductor to a ferromagnet lead and demonstrate the emergence of exceptional points when an external Zeeman field is applied. We discover that, depending on the non-Hermiticity and the Zeeman field, the exceptional points mark the ends of lines with zero real energy, thus givi

Ben Deitmar

Let $S_{p,n}$ denote the sample covariance matrix based on $n$ independent identically distributed $p$-dimensional random vectors in the null-case. The main result of this paper is an explicit expansion of trace moments and power-trace covariances of $S_{p,n}$ simultaneously for both high- and low-dimensional data. To this end we expand a well-known ansatz o

Roberta Mota, Nivan Ferreira, Julio Daniel Silva, Marius Horga

Recent technological innovations have led to an increase in the availability of 3D urban data, such as shadow, noise, solar potential, and earthquake simulations. These spatiotemporal datasets create opportunities for new visualizations to engage experts from different domains to study the dynamic behavior of urban spaces in this under explored dimension. Ho

George Dimas, Eirini Cholopoulou, Dimitris K. Iakovidis

The adoption of Convolutional Neural Network (CNN) models in high-stake domains is hindered by their inability to meet society's demand for transparency in decision-making. So far, a growing number of methodologies have emerged for developing CNN models that are interpretable by design. However, such models are not capable of providing interpretations in acc

Xinxin Guo, Zhongcheng Yu, Fansu Wei, Shengjie Jin

High-precision sensing of vectorial forces has broad impact on both fundamental research and technological applications such as the examination of vacuum fluctuations \cite{casimir09rmp} and the detection of surface roughness of nanostructures \cite{RevModPhys.89.035002}. Recent years have witnessed much progress on sensing alternating electromagnetic forces

Qi-Li Liao

The exclusive production of double excited quarkonium is comprehensive studied, i.e., the production of double excitedcharmonium, double excited bottomonium, and double excited $Bc$-mesons via $e^+e^-\to \gamma^*/Z^0 \to|(Q\bar{Q'})[n]\rangle +|(Q'\bar{Q})[n']\rangle$ ($Q/Q'=c$- or $b$-quarks) at a future $Z$ factory under the nonrelativistic quantum chromod

Olga Egorova, Steven G. Gilmour

Complete reliance on the fitted model in response surface experiments is risky and relaxing this assumption, whether out of necessity or intentionally, requires an experimenter to account for multiple conflicting objectives. This work provides a methodological framework of a compound optimality criterion comprising elementary criteria responsible for: (i) th

Sen Zheng, Renate A. Schmidt

Query answering is an important problem in AI, database and knowledge representation. In this paper, we develop saturation-based Boolean conjunctive query answering and rewriting procedures for the guarded, the loosely guarded and the clique-guarded fragments. Our query answering procedure improves existing resolution-based decision procedures for the guarde

Andrea Burattin, Hugo A. López, Lasse Starklit

Process discovery is a family of techniques that helps to comprehend processes from their data footprints. Yet, as processes change over time so should their corresponding models, and failure to do so will lead to models that under- or over-approximate behavior. We present a discovery algorithm that extracts declarative processes as Dynamic Condition Respons

Chris Junchi Li, Dongruo Zhou, Quanquan Gu, Michael I. Jordan

We consider learning Nash equilibria in two-player zero-sum Markov Games with nonlinear function approximation, where the action-value function is approximated by a function in a Reproducing Kernel Hilbert Space (RKHS). The key challenge is how to do exploration in the high-dimensional function space. We propose a novel online learning algorithm to find a Na

Fredrik Grönberg, Mats Persson, Hans Bornefalk

Purpose: The set of linear attenuation coefficients that belong to materials in the human body is commonly assumed to be spanned by two basis functions in the range of clinical x-ray energies, even though there is evidence that the dimensionality of this set is greater than two. It has not yet been clear that the use of a third basis function could be benefi

Qing Huang, Zhiqiang Yuan, Zhenchang Xing, Xiwei Xu

Partial code usually involves non-fully-qualified type names (non-FQNs) and undeclared receiving objects. Resolving the FQNs of these non-FQN types and undeclared receiving objects (referred to as type inference) is the prerequisite to effective search and reuse of partial code. Existing dictionary-lookup based methods build a symbolic knowledge base of API

Serena S. Serbinowska, Taylor T. Johnson

Behavior Trees, which originated in video games as a method for controlling NPCs but have since gained traction within the robotics community, are a framework for describing the execution of a task. BehaVerify is a tool that creates a nuXmv model from a py_tree. For composite nodes, which are standardized, this process is automatic and requires no additional

Yue Liu, Christos Matsoukas, Fredrik Strand, Hossein Azizpour

Vision transformers have demonstrated the potential to outperform CNNs in a variety of vision tasks. But the computational and memory requirements of these models prohibit their use in many applications, especially those that depend on high-resolution images, such as medical image classification. Efforts to train ViTs more efficiently are overly complicated,

Xiang Li, Changhe Song, Xianhao Wei, Zhiyong Wu

Cross-speaker style transfer aims to extract the speech style of the given reference speech, which can be reproduced in the timbre of arbitrary target speakers. Existing methods on this topic have explored utilizing utterance-level style labels to perform style transfer via either global or local scale style representations. However, audiobook datasets are t

Adam Dahlgren Lindström, Savitha Sam Abraham

We introduce CLEVR-Math, a multi-modal math word problems dataset consisting of simple math word problems involving addition/subtraction, represented partly by a textual description and partly by an image illustrating the scenario. The text describes actions performed on the scene that is depicted in the image. Since the question posed may not be about the s

Zhihuang Luo, Wenzhao Zhang, Xinfang Nie, Dawei Lu

Topological phases have greatly improved our understanding of modern conception of phases of matter that go beyond the paradigm of symmetry breaking and are not described by local order parameters. Instead, characterization of topological phases requires the robust topological invariants, whereas measuring these global quantities presents an outstanding chal

A. A. Shashkin, S. V. Kravchenko

Using several independent methods, we find that the metal-insulator transition occurs in the strongly-interacting two-valley two-dimensional electron system in ultra-high mobility SiGe/Si/SiGe quantum wells in zero magnetic field. The transition survives in this system in parallel magnetic fields strong enough to completely polarize the electrons' spins, thu

Nora Lützgendorf, Giovanna Giardino, Catarina Alves de Oliveira, Peter Zeidler

The NIRSpec instrument for the James Webb Space Telescope (JWST) is a highly versatile near-infrared spectrograph that can be operated in various observing modes, slit apertures, and spectral resolutions. Obtaining dedicated calibration data for all possible combinations of aperture and disperser is an intractable task. We have therefore developed a procedur

Catarina Alves de Oliveira, Nora Luetzgendorf, Peter Zeidler, Giovanna Giardino

The Near-Infrared Spectrograph (NIRSpec) on board of the James Webb Space Telescope will be the first multi-object spectrograph in space offering ~250,000 configurable micro-shutters, apart from being equipped with an integral field unit and fixed slits. At its heart, the NIRSpec grating wheel assembly is a cryogenic mechanism equipped with six dispersion gr

Antara Dasgupta, Lasse Hybbeneth, Björn Waske

Satellite remote sensing presents a cost-effective solution for synoptic flood monitoring, and satellite-derived flood maps provide a computationally efficient alternative to numerical flood inundation models traditionally used. While satellites do offer timely inundation information when they happen to cover an ongoing flood event, they are limited by their