August 2022 arXiv papers — page 138

Tianliang Zhang, Feiqi Deng, Peng Shi

In this paper, the problem of non-fragile finite-time stabilization for linear discrete mean-field stochastic systems is studied. The uncertain characteristics in control parameters are assumed to be random satisfying the Bernoulli distribution. A new approach called the ``state transition matrix method" is introduced and some necessary and sufficient condit

Xinhua Wang

For a class of uncertain systems with large-error sensing, the low-order stable signal corrector and observer are presented for signal correction and uncertainty estimation according to completely decoupling estimation. The signal corrector can reject the large error in global position sensing, and system uncertainty can be estimated by the observer, even th

Arghajit Jana, Hsiang-Kuang Chang, Arka Chatterjee, Sachindra Naik

We present the results of a broadband (0.5-78 keV) X-ray spectral study of the persistent Galactic black hole X-ray binary GRS 1758-258 observed simultaneously by Swift and NuSTAR. Fitting with an absorbed power-law model revealed a broad Fe line and reflection hump in the spectrum. We used different flavours of the relativistic reflection model for the spec

Zahra Golsanamlou, Poonam Kumari, Luca Sementa, Teresa Cusati

Low-dimensional metal-semiconductor vertical heterostructures (VH) are promising candidates in the search of electronic devices at the extreme limits of miniaturization. Within this line of research, here we present a theoretical/computational study of the NbS$_2$/WSe$_2$ metal-semiconductor vertical hetero-junction using density functional theory (DFT) and

Jitender Singh

A parametric instability of an incompressible, viscous, and Boussinesq fluid layer bounded between two parallel planes is investigated numerically. The layer is assumed to be inclined at an angle with horizontal. The planes bounding the layer are subjected to a time-periodic heating. Above a threshold value, the temperature gradient across the layer leads to

Martin Lorenz, Franziska Kilchert, Pinchas Nürnberg, Max Schammer

While ion transport processes in concentrated electrolytes, e.g. based on ionic liquids (IL), are a subject of intense research, the role of conservation laws and reference frames is still a matter of debate. Employ-ing electrophoretic NMR, we show that momentum conservation, a typical prerequisite in molecular dynamics (MD) simulations, is not governing ion

A Belotto da Silva, A Parusiński, L Rifford

We obtain, under an additional assumption on the subanalytic abnormal distribution constructed in [4], a proof of the minimal rank Sard conjecture in the analytic category. It establishes that from a given point the set of points accessible through singular horizontal curves of minimal rank, which corresponds to the rank of the distribution, has Lebesgue mea

Ivan Fernandez-Corbaton, Roland Griesmaier, Marvin Knöller, Carsten Rockstuhl

Electromagnetic waves impinging on three-dimensional helical metallic metamaterials have been shown to exhibit chiral effects of large magnitude both theoretically and in experimental realizations. Chirality here describes different responses of scatterers, materials, or metamaterials to left and right circularly polarized electromagnetic waves. These differ

Xue-Cheng Tai, Ragnar Winther, Xiaodi Zhang, Weiying Zheng

Solution methods for the nonlinear partial differential equation of the Rudin-Osher-Fatemi (ROF) and minimum-surface models are fundamental for many modern applications. Many efficient algorithms have been proposed. First order methods are common. They are popular due to their simplicity and easy implementation. Some second order Newton-type iterative method

Prottoy Das

We present the measurement of charged-particle jet properties in minimum bias p--Pb collisions at $\sqrt{s_{\rm NN}}$ = 5.02 TeV in ALICE. Jets are reconstructed from charged particles at midrapidity using the anti-$k_{\rm T}$ jet finding algorithm with jet resolution parameter $R$ = 0.4. The mean charged particle multiplicity and jet fragmentation function

Georgy C. Luke, B. Subhash

A homology and cohomology theory for topological quandles are introduced. The relation between these (co)homology groups and quandle (co)homology groups are studied. The 1 - topological quandle cocycles are used to compute state sum invariants corresponding to knot diagrams.

M. Battaglieri, M. Bondì, A. Celentano, P. L. Cole

BDX-MINI is a beam dump experiment optimized to search for Light Dark Matter produced in the interaction of the intense CEBAF 2.176 GeV electron beam with the Hall A beam dump at Jefferson Lab. The BDX-MINI detector consists of a PbWO$_4$ electromagnetic calorimeter surrounded by a hermetic veto system for background rejection. The experiment accumulated $2.

Kun Fang, Huijie Qiao

The work concerns deviation estimates for multivalued McKean-Vlasov stochastic differential equations. First of all, we prove the large deviation principle for them by the weak convergence approach. Then the central limit theorem for them is shown with the help of a formula for $L$-derivatives. Finally, we establish the moderate deviation principle for them.

Lorenzo Miretti, Renato Luis Garrido Cavalcante, Slawomir Stanczak

We derive a fast and optimal algorithm for solving practical weighted max-min SINR problems in cell-free massive MIMO networks. For the first time, the optimization problem jointly covers long-term power control and distributed beamforming design under imperfect cooperation. In particular, we consider user-centric clusters of access points cooperating on the

Jake S. Bobowski, Hrishikesh Patel, Mir Faizal

In this paper we argue that, even though there are strong theoretical and empirical reasons to expect a violation of spatial isotropy at short distances, contemporary setups for probing gravitational interactions at short distances have not been configured to measure such spatial anisotropies. We propose a simple modification to the state-of-the-art torsion

Chaoyu Quan, Xu Wu

In this work the L2-1$_\sigma$ method on general nonuniform meshes is studied for the subdiffusion equation. When the time step ratio is no less than $0.475329$, a bilinear form associated with the L2-1$_\sigma$ fractional-derivative operator is proved to be positive semidefinite and a new global-in-time $H^1$-stability of L2-1$_\sigma$ schemes is then deriv

Maurantonio Caprolu, Alireza Sadighian, Roberto Di Pietro

Online social networks (OSNs) play a crucial role in today's world. On the one hand, they allow free speech, information sharing, and social-movements organization, to cite a few. On the other hand, they are the tool of choice to spread disinformation, hate speech, and to support propaganda. For these reasons, OSNs data mining and analysis aimed at detecting

Jürgen Werner, Simon Venter, Nicolas Addington

This is an English translation of Werner's 1987 dissertation "Kleine Aufl\"osungen spezieller dreidimensionaler Variet\"aten," originally published as Bonner Mathematische Schriften No. 186.

Minfeng Xu, Heng Guo, Jianfeng Zhang, Ke Yan

Accurate and robust abdominal multi-organ segmentation from CT imaging of different modalities is a challenging task due to complex inter- and intra-organ shape and appearance variations among abdominal organs. In this paper, we propose a probabilistic multi-organ segmentation network with hierarchical spatial-wise feature modulation to capture flexible orga

Luigi Ambrosio, Sebastiano Nicolussi Golo, Francesco Serra Cassano

We show that vector fields $b$ whose spatial derivative $D_xb$ satisfies a Orlicz summability condition have a spatially continuous representative and are well-posed. For the case of sub-exponential summability, their flows satisfy a Lusin (N) condition in a quantitative form, too. Furthermore, we prove that if $D_xb$ satisfies a suitable exponential summabi

Beibei Lin, Shunli Zhang, Ming Wang, Lincheng Li

Existing gait recognition methods either directly establish Global Feature Representation (GFR) from original gait sequences or generate Local Feature Representation (LFR) from several local parts. However, GFR tends to neglect local details of human postures as the receptive fields become larger in the deeper network layers. Although LFR allows the network

Milton Persson, Mykola Kulyk, Anatolii Kravets, Vladislav Korenivski

The demagnetization and associated magnetocaloric effect in strong-weak-strong ferromagnetic trilayers, upon a reorientation of the strong ferromagnets from parallel to antiparallel magnetization, is simulated using atomistic spin dynamics. The simulations yield non-trivial spin distributions in the antiparallel state, which in turn allows entropy to be calc

Nilay Mondal, D. C. Dalal

Electroporation is a very useful tool for drug delivery into various diseased tissues of the human body. This technique helps to improve the clinical treatment by transferring drugs into the targeted cells rapidly. In electroporation, drug particles enter easily into the intracellular compartment through the temporarily permeabilized cell membrane due to the

Hyeong-Soon Jang, Donghwa Lee, Hyungjun Heo, Yong-Su Kim

We demonstrate integrated photonic circuits for quantum devices using sputtered polycrystalline aluminum nitride (AlN) on insulator. The on-chip AlN waveguide directional couplers, which are one of the most important components in quantum photonics, are fabricated and show the output power splitting ratios from 50:50 to 99:1. The polarization beam splitters

Alex Bogatu, Zili Zhou, Dónal Landers, André Freitas

Entailment trees have been proposed to simulate the human reasoning process of explanation generation in the context of open--domain textual question answering. However, in practice, manually constructing these explanation trees proves a laborious process that requires active human involvement. Given the complexity of capturing the line of reasoning from que

Syed Raza Bashir, Shaina Raza, Vojislav Misic

Recommending points of interest (POIs) is a challenging task that requires extracting comprehensive location data from location-based social media platforms. To provide effective location-based recommendations, it's important to analyze users' historical behavior and preferences. In this study, we present a sophisticated location-aware recommendation system

Aaron Brunk

The aim of this work is to prove the global-in-time existence of weak solutions for a viscoelastic phase separation model in three space dimensions. To this end we apply the relative energy concept provided by [3]. We consider the case of regular polynomial-type potentials and positive mobilities, as well as the degenerate case with logarithmic potential and

Yanke Li, Hatt Tobias, Ioana Bica, Mihaela van der Schaar

Leveraging labelled data from multiple domains to enable prediction in another domain without labels is a significant, yet challenging problem. To address this problem, we introduce the framework DAPDAG (\textbf{D}omain \textbf{A}daptation via \textbf{P}erturbed \textbf{DAG} Reconstruction) and propose to learn an auto-encoder that undertakes inference on po

Sakin Demir

In this research we introduce the Banach space valued $H^p$ spaces with $A_p$ weight, and prove the following results: Let $\mathbb{A}$ and $\mathbb{B}$ Banach spaces, and $T$ be a convolution operator mapping $\mathbb{A}$-valued functions into $\mathbb{B}$-valued functions, i.e., $$Tf(x)=\int_{\mathbb{R}^n}K(x-y)\cdot f(y)\, dy,$$ where $K$ is a strongly me

Mengzhu Wang, Jianlong Yuan, Qi Qian, Zhibin Wang

Domain generalization (DG) aims to learn a model on one or more different but related source domains that could be generalized into an unseen target domain. Existing DG methods try to prompt the diversity of source domains for the model's generalization ability, while they may have to introduce auxiliary networks or striking computational costs. On the contr

Holger Klein, Noémie Jaquier, Andre Meixner, Tamim Asfour

Dynamic motions of humans and robots are widely driven by posture-dependent nonlinear interactions between their degrees of freedom. However, these dynamical effects remain mostly overlooked when studying the mechanisms of human movement generation. Inspired by recent works, we hypothesize that human motions are planned as sequences of geodesic synergies, an

Mahdi Rezaei, Negar Nayeri, Saeed Farzi, Hossein Sameti

In this paper, we investigate the application of end-to-end and multi-module frameworks for G2P conversion for the Persian language. The results demonstrate that our proposed multi-module G2P system outperforms our end-to-end systems in terms of accuracy and speed. The system consists of a pronunciation dictionary as our look-up table, along with separate mo

Vijay K. Garg

We apply Lattice-Linear Predicate Detection Technique to derive parallel and distributed algorithms for various variants of the stable matching problem. These problems are: (a) the constrained stable marriage problem (b) the super stable marriage problem in presence of ties, and (c) the strongly stable marriage in presence of ties. All these problems are sol

Christian S. Pilz, Benjamin Clemens, Inka C. Hiss, Christoph Weiss

We study the statistical properties of facial behaviour altered by the regulation of brain arousal in the clinical domain of psychiatry. The underlying mechanism is linked to the empirical interpretation of the vigilance continuum as behavioral surrogate measurement for certain states of mind. Referring to the classical scalp-based obtrusive measurements, we

Heng Yang, Chen Zhang, Ke Li

The advancement of aspect-based sentiment analysis (ABSA) has urged the lack of a user-friendly framework that can largely lower the difficulty of reproducing state-of-the-art ABSA performance, especially for beginners. To meet the demand, we present \our, a modularized framework built on PyTorch for reproducible ABSA. To facilitate ABSA research, PyABSA sup

Mario Gutiérrez, Hugo Parlier, Paul Turner

We introduce a family of reconfiguration puzzles arising from ideas in geometry and topology. We present their construction from square-tiled shapes, discuss some of the underlying mathematics and describe how they are naturally associated to puzzle spaces which can be explored through visualization.

Reid McIlroy-Young, Russell Wang, Siddhartha Sen, Jon Kleinberg

The advent of machine learning models that surpass human decision-making ability in complex domains has initiated a movement towards building AI systems that interact with humans. Many building blocks are essential for this activity, with a central one being the algorithmic characterization of human behavior. While much of the existing work focuses on aggreg

Sayak Chatterjee, Shirshendu Chatterjee, Soumendu Sundar Mukherjee, Anirban Nath

Network-valued time series are currently a common form of network data. However, the study of the aggregate behavior of network sequences generated from network-valued stochastic processes is relatively rare. Most of the existing research focuses on the simple setup where the networks are independent (or conditionally independent) across time, and all edges

Alfonso Nardi, Shawn Divitt, Massimiliano Rossi, Felix Tebbenjohanns

Coherence has been used as a resource for optical communications since its earliest days. It is widely used for multiplexing of data, but not for encoding of data. Here we introduce a coding scheme, which we call \textit{mutual coherence coding}, to encode information in the mutual coherence of spatially separated light beams. We describe its implementation

Sebastian Moller, Theo Käufer, Ambrish Pandey, Jörg Schumacher

Turbulent superstructures in horizontally extended three-dimensional Rayleigh-B\'enard convection flows are investigated in controlled laboratory experiments in water at Prandtl number $Pr = 7$. A Rayleigh-B\'enard cell with square cross-section, aspect ratio $\Gamma = l/h = 25$, side length $l$ and height $h$ is used. Three different Rayleigh numbers in the

Giacomo Borghi, Michael Herty, Lorenzo Pareschi

In this work we are interested in stochastic particle methods for multi-objective optimization. The problem is formulated using parametrized, single-objective sub-problems which are solved simultaneously. To this end a consensus based multi-objective optimization method on the search space combined with an additional heuristic strategy to adapt parameters du

Samuel Jelbart, Christian Kuehn, Sara-Viola Kuntz

Geometric singular perturbation theory provides a powerful mathematical framework for the analysis of 'stationary' multiple time-scale systems which possess a critical manifold, i.e. a smooth manifold of steady states for the limiting fast subsystem, particularly when combined with a method of desingularization known as blow-up. The theory for 'oscillatory'

Fan Jia, Zerong Huang, Liyuan Qiu, Rongzi Zhou

Bose-Einstein condensates (BECs) confined on shell-shaped surfaces have been proposed as a platform for exploring many nontrivial quantum phenomena on curved spaces. However, as the shell-shaped trapping potential generated with the conventional radio frequency dressing method is very sensitive to gravity, so far experimental studies of shell BECs can only b

Michiel E. Hochstenbach, Christian Mehl, Bor Plestenjak

Generalized eigenvalue problems involving a singular pencil may be very challenging to solve, both with respect to accuracy and efficiency. While Part I presented a rank-completing addition to a singular pencil, we now develop two alternative methods. The first technique is based on a projection onto subspaces with dimension equal to the normal rank of the p

Olivier Risser-Maroix, Benjamin Chamand

This paper seeks to answer the following question: \textit{"What can we learn by predicting accuracy?"}. Indeed, classification is one of the most popular tasks in machine learning, and many loss functions have been developed to maximize this non-differentiable objective function. Unlike past work on loss function design, which was guided mainly by intuition

L. Kelsey, M. Sullivan, P. Wiseman, P. Armstrong

Recent analyses have found intriguing correlations between the colour ($c$) of type Ia supernovae (SNe Ia) and the size of their 'mass-step', the relationship between SN Ia host galaxy stellar mass ($M_\mathrm{stellar}$) and SN Ia Hubble residual, and suggest that the cause of this relationship is dust. Using 675 photometrically-classified SNe Ia from the Da

Pascal Nasahl, Martin Unterguggenberger, Rishub Nagpal, Robert Schilling

Fault injection (FI) is a powerful attack methodology allowing an adversary to entirely break the security of a target device. As finite-state machines (FSMs) are fundamental hardware building blocks responsible for controlling systems, inducing faults into these controllers enables an adversary to hijack the execution of the integrated circuit. A common def

Sajib Kumar Saha Joy, Dibyo Fabian Dofadar, Riyo Hayat Khan, Md. Sabbir Ahmed

The rapid advancement of social networks and the convenience of internet availability have accelerated the rampant spread of false news and rumors on social media sites. Amid the COVID 19 epidemic, this misleading information has aggravated the situation by putting peoples mental and physical lives in danger. To limit the spread of such inaccuracies, identif

Konstantinos D. Katsanos, Paolo Di Lorenzo, George C. Alexandropoulos

The technology of Reconfigurable Intelligent Surfaces (RISs) has lately attracted considerable interest from both academia and industry as a low-cost solution for coverage extension and signal propagation control. In this paper, we study the downlink of a multi-cell wideband communication system comprising single-antenna Base Stations (BSs) and their associa

Elisa Alòs, Eulalia Nualart, Makar Pravosud

In this paper we study the short-time behavior of the at-the-money implied volatility for arithmetic Asian options with fixed strike price. The asset price is assumed to follow the Black-Scholes model with a general stochastic volatility process. Using techniques of the Malliavin calculus such as the anticipating Ito's formula we first compute the level of t

Milad Ganjalizadeh, Hossein S. Ghadikolaei, Johan Haraldson, Marina Petrova

Distributed artificial intelligence (AI) has recently accomplished tremendous breakthroughs in various communication services, ranging from fault-tolerant factory automation to smart cities. When distributed learning is run over a set of wireless connected devices, random channel fluctuations, and the incumbent services simultaneously running on the same net

Laurens Martin Tetzlaff

Machine learning (ML) continues to permeate all layers of academia, industry and society. Despite its successes, mental frameworks to capture and represent machine learning workflows in a consistent and coherent manner are lacking. For instance, the de facto process modeling standard, Business Process Model and Notation (BPMN), managed by the Object Manageme

Cunzhi Sun, Cheng Xiang, Rongdun Hong, Feng Zhang

Strong Fermi level pinning (FLP) - often attributed to metal-induced gap states at the interfacial contacts - severely reduces the tunability of the Schottky barrier height of the junction and limits applications of the 2D materials in electronics and optoelectronics. Here, we show that fluorinated bilayer graphene (FBLG) can be used as a barrier to effectiv

Kamal Kishor Singh

With technological advances and the establishment of e-commerce models, business challenges have shifted to online platforms. The promise of embedding self-executing and autonomous programs into blockchain technologies has attracted increased interest and its use in niche solutions. Using qualitative interviews, this paper sought the opinions of the eleven i

Akshay Pal, Jayanta Kumar Bhattacharjee

We consider the stochastically driven one dimensional nonlinear oscillator $\ddot{x}+2\Gamma\dot{x}+\omega^2_0 x+\lambda x^3 = f(t)$ where f(t) is a Gaussian noise which, for the bulk of the work, is delta correlated (white noise). We construct the linear response function in frequency space in a systematic Feynman diagram-based perturbation theory. As in ot

Alexander A. Kichigin, Maxim A. Yurkin

Electron energy-loss spectroscopy (EELS) and cathodoluminescence (CL) are widely used experimental techniques for characterization of nanoparticles. The discrete dipole approximation (DDA) is a numerically exact method for simulating interaction of electromagnetic waves with particles of arbitrary shape and internal structure. In this work we extend the DDA

Dominik Wurzer, Yumeng Qin

First Story Detection describes the task of identifying new events in a stream of documents. The UMass-FSD system is known for its strong performance in First Story Detection competitions. Recently, it has been frequently used as a high accuracy baseline in research publications. We are the first to discover that UMass-FSD inadvertently leverages temporal bi

A. C. D. Hoffmann, B. J. Frei, P. Ricci

The first nonlinear gyrokinetic simulations obtained using a moment approach based on the Hermite-Laguerre decomposition of the distribution function are presented, implementing advanced models for the collision operator. Turbulence in a \modif{two-dimensional} Z-pinch is considered within a flux tube configuration. In the collisionless regime, our gyromomen

Bartolomeo Fiorini, Kazuya Koyama, Albert Izard

We study the effect of two Modified Gravity (MG) theories, $f(R)$ and nDGP, on three probes of large-scale structure, the real space power spectrum estimator $Q_0$, bispectrum and voids, and validate fast approximate COLA simulations against full $N$-body simulations for the prediction of these probes. We find that using the first three even multipoles of th

Sunil Chhita, Maurice Duits

This paper is motivated by computing correlations for domino tilings of the Aztec diamond. It is inspired by two of the three distinct methods that have recently been used in the simplest case of a doubly periodic weighting, that is the two-periodic Aztec diamond. One of the methods, powered by the domino shuffle, involves inverting the Kasteleyn matrix givi

Erwan Rousseau, Behrouz Taji

It is known that projective minimal models satisfy the celebrated Miyaoka-Yau inequalities. In this article, we extend these inequalities to the set of all smooth, projective and non-uniruled varieties.

Marek Gagolewski

A proper fusion of complex data is of interest to many researchers in diverse fields, including computational statistics, computational geometry, bioinformatics, machine learning, pattern recognition, quality management, engineering, statistics, finance, economics, etc. It plays a crucial role in: synthetic description of data processes or whole domains, cre

Nicki Holighaus, Felix Voigtlaender

Warped time-frequency systems have recently been introduced as a class of structured continuous frames for functions on the real line. Herein, we generalize this framework to the setting of functions of arbitrary dimensionality. After showing that the basic properties of warped time-frequency representations carry over to higher dimensions, we determine cond

Gizem Sogancioglu, Fabian Mijsters, Amar van Uden, Jelle Peperzak

Clinical word embeddings are extensively used in various Bio-NLP problems as a state-of-the-art feature vector representation. Although they are quite successful at the semantic representation of words, due to the dataset - which potentially carries statistical and societal bias - on which they are trained, they might exhibit gender stereotypes. This study a

Tiange Li, Xiangyu Yang, Hao Wang

In this paper, we develop a simple yet effective screening rule strategy to improve the computational efficiency in solving structured optimization involving nonconvex $\ell_{q,p}$ regularization. Based on an iteratively reweighted $\ell_1$ (IRL1) framework, the proposed screening rule works like a preprocessing module that potentially removes the inactive g

Dominik Wurzer, Yumeng Qin

Kterm Hashing provides an innovative approach to novelty detection on massive data streams. Previous research focused on maximizing the efficiency of Kterm Hashing and succeeded in scaling First Story Detection to Twitter-size data stream without sacrificing detection accuracy. In this paper, we focus on improving the effectiveness of Kterm Hashing. Traditio

L. Bergamaschi, M. Ferronato, G. Isotton, C. Janna

We develop a robust matrix-free, communication avoiding parallel, high-degree polynomial preconditioner for the Conjugate Gradient method for large and sparse symmetric positive definite linear systems. We discuss the selection of a scaling parameter aimed at avoiding unwanted clustering of eigenvalues of the preconditioned matrices at the extrema of the spe

Rodrigo E. Catalan, Alexandros A. Fragkopoulos, Nicolas von Trott, Simon Kelterborn

Microbial colonization of surfaces represents the first step towards biofilm formation, which is a recurring phenomenon in nature with beneficial and detrimental implications in technological and medical settings. Consequently, there is a current interest in elucidating the fundamental aspects of the initial stages of biofilm formation of microorganisms on s

E. Ferronato Bueno, L. Derome, Y. Génolini, D. Maurin

The AMS-02 collaboration recently released cosmic-ray F/Si data of unprecedented accuracy. Cosmic-ray (CR) fluorine is predominantly produced by fragmentation of heavier progenitors, while silicon is mostly accelerated at source. This ratio is thus maximally sensitive to CR propagation. We study the compatibility of the transport parameters derived from the

Valentin Pomakov, Shane O'Sullivan, Marcus Bruggen, Franco Vazza

Faraday rotation studies of distant radio sources can constrain the evolution and the origin of cosmic magnetism. We use data from the LOFAR Two Metre Sky Survey: Data Release 2 (LoTSS DR2) to study the dependence of the Faraday rotation measure (RM) on redshift. By focusing on radio sources that are close in terms of their projection on the sky, but physica

Linfeng Zhang, Zunqi Li, Dongyu Liu, Chengyin Wu

Einstein, Podolsky and Rosen's prediction on incompleteness of quantum mechanics was overturned by experimental tests on Bell's inequality that confirmed the existence of quantum entanglement. In X-ray optics, entangled photon pairs can be generated by X-ray parametric down conversion (XPDC), which has certain wavelength window. Meanwhile, free electron lase

Samantha Lynn Stever, François Couchot

Electro-thermal coupling in semiconductor bolometers is known to create nonlinearities in transient detector response, particularly when such detectors are biased outside of their ideal regions (i.e. past the turnover point in their IV curves). This effect is further compounded in the case where a stray capacitance in the bias circuit is present, for example

Ankur Srivastav, Sunandan Gangopadhyay, Ashis Saha

In this work, we have analytically computed the holographic transport coefficients for (2 + 1)- dimensional strongly coupled field theories, placed in a spatially modulated chemical potential along the x-direction, in the presence of Born-Infeld electrodynamics. We have obtained these coefficients in terms of the black hole horizon data only. We have observe

Saeed Seyedfaraji, Baset Mesgari, Semeen Rehman

State-of-the-art in-memory computation has recently emerged as the most promising solution to overcome design challenges related to data movement inside current computing systems. One of the approaches to performing in-memory computation is based on the analog behavior of the data stored inside the memory cell. These approaches proposed various system archit

G. Lombardi, D. Bonaccini Calia, M. Centrone, A. de Ugarte Postigo

Laser Guide Star Adaptive Optics (LGS-AO) is becoming routine in several astronomical observatories. The use of powerful lasers generates sensible Raman emissions on the uplink laser beam path, plus secondary Rayleigh scattering from atmospheric molecules and Mie scattering from aerosols. This paper reports the results of a campaign done with the 10.4m Gran

Helmut Gfrerer, Jiri V. Outrata

The paper deals with an extension of the available theory of SCD (subspace containing derivatives) mappings to mappings between spaces of different dimensions. This extension enables us to derive workable sufficient conditions for the isolated calmness of implicitly defined multifunctions around given reference points. This stability property differs substan

Adrian Ka-Wai Chung, Alexander C. Jenkins, Joseph D. Romano, Mairi Sakellariadou

There is growing interest in using current and future gravitational-wave interferometers to search for anisotropies in the gravitational-wave background. One guaranteed anisotropic signal is the kinematic dipole induced by our peculiar motion with respect to the cosmic rest frame, as measured in other full-sky observables such as the cosmic microwave backgro

Robin Schmid, Deegan Atha, Frederik Schöller, Sharmita Dey

Navigating off-road with a fast autonomous vehicle depends on a robust perception system that differentiates traversable from non-traversable terrain. Typically, this depends on a semantic understanding which is based on supervised learning from images annotated by a human expert. This requires a significant investment in human time, assumes correct expert c

Umar. F. Burhanudin, Justyn. R. Maund

Time-domain astronomy is entering a new era as wide-field surveys with higher cadences allow for more discoveries than ever before. The field has seen an increased use of machine learning and deep learning for automated classification of transients into established taxonomies. Training such classifiers requires a large enough and representative training set,

Dirk Frettlöh, Alexey Garber, Neil Mañibo

For any $\lambda>2$, we construct a substitution on an infinite alphabet which gives rise to a substitution tiling with inflation factor $\lambda$. In particular, we obtain the first class of examples of substitutive systems with transcendental inflation factors that possess usual dynamical properties enjoyed by primitive substitutions on finite alphabets. W

Dominik Sidler, Michael Ruggenthaler, Angel Rubio

The first exact quantum simulation of a real molecular system (HD$^+$) under strong ro-vibrational coupling to a quantized optical cavity mode in thermal equilibrium is presented. Theoretical challenges in describing strongly coupled systems of mixed quantum statistics (Bosons and Fermions) are discussed and circumvented by the specific choice of our molecul

MohammadJavad Kazemi, Vahid Hosseinzadeh

In this paper, we analyze the statistics of detection data in a general double-double-slit experiment. The two particles are detected at random times which are not equal in general and because we do not have any constraint on the distances of left and right screens from their slits and the ratio as well, they can be detected in completely different timescale

Wei Jiang, Chunmei Su, Ganghui Zhang

We propose and analyze a semi-discrete parametric finite element scheme for solving the area-preserving curve shortening flow. The scheme is based on Dziuk's approach (SIAM J. Numer. Anal. 36(6): 1808-1830, 1999) for the anisotropic curve shortening flow. We prove that the scheme preserves two fundamental geometric structures of the flow with an initially co

Subhomoy Haldar, Harald Havir, Waqar Khan, Sebastian Lehmann

We explore the energetics of microwaves interacting with a double quantum dot photodiode and show wave-particle aspects in photon-assisted tunneling. The experiments show that the single photon energy sets the relevant absorption energy in a weak-drive limit, which contrasts the strong drive limit where the wave amplitude determines the relevant-energy scale

Weiwei Cui, Yaqi Wang, Yilong Li, Dan Song

Accurate tooth volume segmentation is a prerequisite for computer-aided dental analysis. Deep learning-based tooth segmentation methods have achieved satisfying performances but require a large quantity of tooth data with ground truth. The dental data publicly available is limited meaning the existing methods can not be reproduced, evaluated and applied in c

Alexandra Dias

Maximum pseudo-likelihood (MPL) is a semiparametric estimation method often used to obtain the dependence parameters in copula models from data. It has been shown that despite being consistent, and in some cases efficient, MPL estimation can overestimate the level of dependence especially for small weakly dependent samples. We show that the MPL method uses t

Deepika Tiwari, Martin Monperrus, Benoit Baudry

Mocking allows testing program units in isolation. A developer who writes tests with mocks faces two challenges: design realistic interactions between a unit and its environment; and understand the expected impact of these interactions on the behavior of the unit. In this paper, we propose to monitor an application in production to generate tests that mimic

Yuxi Liu, Shaowen Qin, Zhenhao Zhang, Wei Shao

Electronic Health Records (EHRs) exhibit a high amount of missing data due to variations of patient conditions and treatment needs. Imputation of missing values has been considered an effective approach to deal with this challenge. Existing work separates imputation method and prediction model as two independent parts of an EHR-based machine learning system.

Peter Athron, Csaba Balazs, Andrew Fowlie, Lachlan Morris

We investigate the extent to which perturbative calculations of the electroweak phase transition are arbitrary and uncertain, owing to their gauge, renormalisation scale and scheme dependence, as well as treatments of the Goldstone catastrophe and daisy diagrams. Using the complete parameter space of the Standard Model extended by a real scalar singlet with

Di Lu, Ke Yang, Lu Liu, Guangyu Wang

The insulating iron compounds Eu$_2$SrFe$_2$O$_6$ and Sr$_3$Fe$_2$O$_4$Cl$_2$ have high-temperature antiferromagnetic (AF) order despite their different layered structures. Here we carry out density functional calculations and Monte Carlo simulations to study their electronic structures and magnetic properties aided with analyses of the crystal field, magnet

Tim Puhlfürß, Lloyd Montgomery, Walid Maalej

[Background] In large open-source software projects, development knowledge is often fragmented across multiple artefacts and contributors such that individual stakeholders are generally unaware of the full breadth of the product features. However, users want to know what the software is capable of, while contributors need to know where to fix, update, and ad

Dongling Li, Pengchao Wu, Yuehu Dong, Jinghang Gu

Causal relation extraction of biomedical entities is one of the most complex tasks in biomedical text mining, which involves two kinds of information: entity relations and entity functions. One feasible approach is to take relation extraction and function detection as two independent sub-tasks. However, this separate learning method ignores the intrinsic cor

Silvan Käser, Jeremy O. Richardson, Markus Meuwly

The combination of transfer learning (TL) a low level potential energy surface (PES) to a higher level of electronic structure theory together with ring-polymer instanton (RPI) theory is explored and applied to malonaldehyde. The RPI approach provides a semiclassical approximation of the tunneling splitting and depends sensitively on the accuracy of the PES.

Romain Cerubini, Antoine Pommerol, André Galli, Bernhard Jost

Recent laboratory efforts and telescopic observations of Europa have shown the relevance of a yellow colouration of sodium chloride (NaCl) caused by crystal defects generated by irradiation. We further investigate this process by irradiating (with energetic electrons) different types of analogues where NaCl is associated in different ways to water ice. We pr

Qiming Yang, Kai Zhang, Chaoxiang Lan, Zhi Yang

Solid results from Transformers have made them prevailing architectures in various natural language and vision tasks. As a default component in Transformers, Layer Normalization (LN) normalizes activations within each token to boost the robustness. However, LN requires on-the-fly statistics calculation in inference as well as division and square root operati

Yong Deng, Chenxiao Dou, Liangyu Chen, Deqiang Miao

PCL detection task is aimed at identifying and categorizing language that is patronizing or condescending towards vulnerable communities in the general media.Compared to other NLP tasks of paragraph classification, the negative language presented in the PCL detection task is usually more implicit and subtle to be recognized, making the performance of common

Ken-ichi Sasaki, Kenichi Hitachi, Masahiro Kamada, Takamoto Yokosawa

Monolayer graphene absorbs 2.3 percent of the incident visible light. This 'small' absorption has been used to emphasize the visual transparency of graphene, but it in fact means that multilayer graphene absorbs a sizable fraction of incident light, which causes non-negligible fluorescence. In this paper, we formulate the light emission properties of multila

Christian Voigt

We define and study quantum permutations of infinite sets. This leads to discrete quantum groups which can be viewed as infinite variants of the quantum permutation groups introduced by Wang. More precisely, the resulting quantum groups encode universal quantum symmetries of the underlying sets among all discrete quantum groups. We also discuss quantum autom

Jiri Hlubucek, Jakub Lukes, Jan Vaclavik, Karel Zidek

We propose a novel concept of differential coded aperture snapshot spectral imaging (D-CASSI) technique exploiting the benefits of using {-1,+1} random mask, which is demonstrated by a broadband single-snapshot hyperspectral camera using compressed sensing. To double the information, we encode the image by two complementary random masks, which proved to be s

Jiri Hlubucek, Jakub Lukes, Jan Vaclavik, Karel Zidek

Coded aperture snapshot spectral imaging (CASSI) makes it possible to recover 3D hyperspectral data from a single 2D image. However, the reconstruction problem is severely underdetermined and efforts to improve the compression ratio typically make the imaging system more complex and cause a significant loss of incoming light intensity. In this paper, we prop