October 2022 arXiv papers — page 16

Vanni Noferini, Paul Van Dooren

In this paper we revisit the greatest common right divisor (GCRD) extraction from a set of polynomial matrices $P_i(\lambda)\in \F[\la]^{m_i\times n}$, $i=1,\ldots,k$ with coefficients in a generic field $\F$, and with common column dimension $n$. We give necessary and sufficient conditions for a matrix $G(\la)\in \F[\la]^{\ell\times n}$ to be a GCRD using t

Frank Trujillo

We show that, generically, the unique invariant measure of a sufficiently regular piecewise smooth circle homeomorphism with irrational rotation number and zero mean nonlinearity (e.g., piecewise linear) has zero Hausdorff dimension. To encode this generic condition, we consider piecewise smooth homeomorphisms as generalized interval exchange transformations

Jihoon Chung, Bo Shen, Zhenyu, Kong

Supervised classification methods have been widely utilized for the quality assurance of the advanced manufacturing process, such as additive manufacturing (AM) for anomaly (defects) detection. However, since abnormal states (with defects) occur much less frequently than normal ones (without defects) in a manufacturing process, the number of sensor data samp

Johan Bremer, Douglas Bryman, Hans Danielsson, Valeri Falaleev

A system for determining the purity of liquid krypton employed in the NA62 rare kaon decay experiment at CERN was developed based on the use of a time projection chamber. The attenuation of drifting ionization electrons from absorption of 511 keV gamma rays in liquid krypton was measured to estimate the purity. The setup was tested with krypton purified from

Sergey Novoselov, Vladimir Volokhov, Galina Lavrentyeva

Creating universal speaker encoders which are robust for different acoustic and speech duration conditions is a big challenge today. According to our observations systems trained on short speech segments are optimal for short phrase speaker verification and systems trained on long segments are superior for long segments verification. A system trained simulta

Sudip Karan, Gurmeet Singh Punia

We calculate the logarithmic correction to the entropy of asymptotically flat and AdS black holes (rotating, non-rotating, charged, and uncharged) embedded in Einstein-Maxwell-dilaton (EMD) theories with $U(1)$-charged. The leading quantum gravitational corrections are achieved in both extremal and non-extremal limits of black hole temperature by designing a

Cheng Li, Boris Braverman, Girish Kulkarni, Robert W. Boyd

The influence of pump coherence on the entanglement produced in spontaneous parametric down-conversion (SPDC) is important to understand, both from a fundamental perspective, and from a practical standpoint for controlled generation of entangled states. In this context, it is known that in the absence of postselection, the pump coherence in a given degree of

Christopher Davis, Christopher Bryant, Andrew Caines, Marek Rei

Targeted studies testing knowledge of subject-verb agreement (SVA) indicate that pre-trained language models encode syntactic information. We assert that if models robustly encode subject-verb agreement, they should be able to identify when agreement is correct and when it is incorrect. To that end, we propose grammatical error detection as a diagnostic prob

Marzieh Hashemipour-Nazari, Renate Debets, Kees Goossens, Alexios Balatsoukas-Stimming

We describe recursive unique projection-aggregation (RUPA) decoding and iterative unique projection-aggregation (IUPA) decoding of Reed-Muller (RM) codes, which remove non-unique projections from the recursive projection-aggregation (RPA) and iterative projection-aggregation (IPA) algorithms respectively. We show that these algorithms have competitive error-

Bruno Sguerra, Viet-Anh Tran, Romain Hennequin

Repetition in music consumption is a common phenomenon. It is notably more frequent when compared to the consumption of other media, such as books and movies. In this paper, we show that one particularly interesting repetitive behavior arises when users are consuming new items. Users' interest tends to rise with the first repetitions and attains a peak after

A. M. Gasparyan, E. Epelbaum

We consider nucleon-nucleon scattering using the formulation of chiral effective field theory which is claimed to be renormalization group invariant. The cornerstone of this framework is the existence of a well-defined infinite-cutoff limit for the scattering amplitude at each order of the expansion, which should not depend on a particular regulator form. Fo

Daniel J. McDonald, Cosma Rohilla Shalizi

Dynamic stochastic general equilibrium (DSGE) models have been an ubiquitous, and controversial, part of macroeconomics for decades. In this paper, we approach DSGEs purely as statstical models. We do this by applying two common model validation checks to the canonical Smets and Wouters 2007 DSGE: (1) we simulate the model and see how well it can be estimate

I. Novikov, I. Tessler, A. Yakirevich

A researcher is interested in what sample size is needed to get the required significance of the same test, assuming exactly the same situation that was in the study with the non-significant result. We propose a simple solution to the problem.

Stanislas Ducotterd, Alexis Goujon, Pakshal Bohra, Dimitris Perdios

Lipschitz-constrained neural networks have several advantages over unconstrained ones and can be applied to a variety of problems, making them a topic of attention in the deep learning community. Unfortunately, it has been shown both theoretically and empirically that they perform poorly when equipped with ReLU activation functions. By contrast, neural netwo

Gabriele Grillo, Giulia Meglioli, Fabio Punzo

We consider reaction-diffusion equations driven by the $p$-Laplacian on noncompact, infinite volume manifolds assumed to support the Sobolev inequality and, in some cases, to have $L^2$ spectrum bounded away from zero, the main example we have in mind being the hyperbolic space of any dimension. It is shown that, under appropriate conditions on the parameter

Giovanni Franzese, Leandro de Souza Rosa, Tim Verburg, Luka Peternel

Performing bimanual tasks with dual robotic setups can drastically increase the impact on industrial and daily life applications. However, performing a bimanual task brings many challenges, like synchronization and coordination of the single-arm policies. This article proposes the Safe, Interactive Movement Primitives Learning (SIMPLe) algorithm, to teach an

Mathis Bode

The accurate prediction of small scales in underresolved flows is still one of the main challenges in predictive simulations of complex configurations. Over the last few years, data-driven modeling has become popular in many fields as large, often extensively labeled datasets are now available and training of large neural networks has become possible on grap

Siddarth Sankaran

We formulate and prove a version of the arithmetic Siegel-Weil formula for (zero dimensional) Shimura varieties attached to tori, equipped with some additional data. More precisely, we define a family of ``special" divisors in terms of Green functions at archimedean and non-archimedean places, and prove that their degrees coincide with the Fourier coefficien

Nimmakanti Mahendra, Nagaraju Chilukoti, Jasti S Chowdary, Ashok Karumuri

Summer monsoon rainfall over India depends on synoptic-scale phenomena like lows and depressions. India's summer monsoon season 2020 saw above-average rainfall. North Indian Ocean had 12 LPAs in summer 2020 in JJAS season. This monsoon season has the highest all-India rainfall since 1976 in August 2020. 50% of seasonal LPAs emerged in August 2020, but none i

H. A. Vinutha, Fabiola Diaz Ruiz, Xiaoming Mao, Bulbul Chakraborty

We investigate the spatial correlations of microscopic stresses in soft particulate gels, using 2D and 3D numerical simulations. We use a recently developed theoretical framework predicting the analytical form of stress-stress correlations in amorphous assemblies of athermal grains that acquire rigidity under an external load. These correlations exhibit a pi

Daniel Kelshaw, Luca Magri

Measurements on dynamical systems, experimental or otherwise, are often subjected to inaccuracies capable of introducing corruption; removal of which is a problem of fundamental importance in the physical sciences. In this work we propose physics-informed convolutional neural networks for stationary corruption removal, providing the means to extract physical

Vladimir Petrov Kostov

We prove that for $q\in (0,1)$, the partial theta function $\theta (q,x):=\sum _{j=0}^{\infty}q^{j(j+1)/2}x^j$ has no zeros in the closed domain $\{ \{ |x|\leq 3\} \cap \{${\rm Re}$x\leq 0\} \cap \{ |${\rm Im}$x|\leq 3/\sqrt{2}\} \} \subset \mathbb{C}$ and no real zeros $\geq -5$.

Laura Geatti, Andrea Iannuzzi

Let $\,G/K\,$ be a non-compact irreducible Hermitian symmetric space of rank $\,r\,$ and let $\,NAK\,$ be an Iwasawa decomposition of $\,G$. By the polydisc theorem, $\,AK/K\,$ can be regarded as the base of an $\,r$-dimensional tube domain holomorphically embedded in $\,G/K$. As every $\,N$-orbit in $\,G/K\,$ intersects $\,AK/K$ in a single point, there is

Stijn Cambie, Nika Salia

We present equivalent formulations for concepts related to set families for which every subfamily with empty intersection has a bounded sub-collection with empty intersection. Hereby, we summarize the progress on the related questions about the maximum size of such families. In this work we solve a boundary case of a problem of Tuza for non-trivial $q$-Helly

A. Qamesh, R. Ahmad, D. Ecker, T. Fischer

During the ATLAS phase II upgrade, the tracking system of the ATLAS experiment will be replaced by an all-silicon detector called the inner tracker (ITK) with a pixel detector as the most inner part. The monitoring data of the new system will be aggregated from an on-detector ASIC called Monitoring Of Pixel System (MOPS) and sent to the Detector Control Syst

Sung-Shine Lee, Alexandr Murashkin, Martin Derka, Jan Gorzny

The blockchain ecosystem has evolved into a multi-chain world with various blockchains vying for use. Although each blockchain may have its own native cryptocurrency or digital assets, there are use cases to transfer these assets between blockchains. Systems that bring these digital assets across blockchains are called bridges, and have become important part

Simon Donaldson, Fabian Lehmann

We consider the question if a five dimensional manifold can be embedded into a Calabi-Yau manifold of complex dimension three such that the real part of the holomorphic volume form induces a given closed 3-form on the 5-manifold. We define an open set of 3-forms in dimension five which we call strongly pseudoconvex, and show that for closed strongly pseudoco

Keisuke Harigaya, Isaac R. Wang

Space-time parity can solve the strong CP problem and introduces a spontaneously broken $SU(2)_R$ gauge symmetry. We investigate the possibility of baryogenesis from a first-order $SU(2)_R$ phase transition similar to electroweak baryogenesis. We consider a model with the minimal Higgs content, for which the strong CP problem is indeed solved without introdu

Mathis Bode, Michael Gauding, Dominik Goeb, Tobias Falkenstein

Models for finite-rate-chemistry in underresolved flows still pose one of the main challenges for predictive simulations of complex configurations. The problem gets even more challenging if turbulence is involved. This work advances the recently developed PIESRGAN modeling approach to turbulent premixed combustion. For that, the physical information processe

Ilias Driouich, Chuan Xu, Giovanni Neglia, Frederic Giroire

In this paper, we initiate the study of local model reconstruction attacks for federated learning, where a honest-but-curious adversary eavesdrops the messages exchanged between a targeted client and the server, and then reconstructs the local/personalized model of the victim. The local model reconstruction attack allows the adversary to trigger other classi

Masaki Adachi, Yannick Kuhn, Birger Horstmann, Arnulf Latz

A wide variety of battery models are available, and it is not always obvious which model `best' describes a dataset. This paper presents a Bayesian model selection approach using Bayesian quadrature. The model evidence is adopted as the selection metric, choosing the simplest model that describes the data, in the spirit of Occam's razor. However, estimating

Nicola Marinello, Marc Proesmans, Luc Van Gool

3D object tracking is a critical task in autonomous driving systems. It plays an essential role for the system's awareness about the surrounding environment. At the same time there is an increasing interest in algorithms for autonomous cars that solely rely on inexpensive sensors, such as cameras. In this paper we investigate the use of triplet embeddings in

Jihoon Chung, Bo Shen, Andrew Chung Chee Law, Zhenyu

Additive Manufacturing (AM) is a powerful technology that produces complex 3D geometries using various materials in a layer-by-layer fashion. However, quality assurance is the main challenge in AM industry due to the possible time-varying processing conditions during AM process. Notably, new defects may occur during printing, which cannot be mitigated by off

Alba Kalaja, Giorgio Orlando, Aleksandr Bowkis, Anthony Challinor

Weak gravitational lensing by the intervening large-scale structure (LSS) of the Universe is the leading non-linear effect on the anisotropies of the cosmic microwave background (CMB). The integrated line-of-sight mass that causes the distortion -- known as lensing convergence -- can be reconstructed from the lensed temperature and polarization anisotropies

Yuki Inoue, Masaya Hasegawa, Masashi Hazumi, Suguru Takada

We recently developed and characterized an absorber for millimeter wavelengths. To absorb the millimeter wave efficiently, we need to develop the low reflection and high absorption material. To meet these requirements, we tried to add polystyrene beads in the epoxy for multi-scattering in the absorber. The typical diameter of polystyrene beads corresponds to

Linda Goletto, Sara Gómez, Josefine H. Andersen, Henrik Koch

We present a computational study of static and dynamic linear polarizabilities in solution. We use different theoretical approaches to describe solvent effects, ranging from quantum mechanics/molecular mechanics (QM/MM) to quantum embedding approaches. In particular, we consider non-polarizable and polarizable QM/MM methods, the latter based on the fluctuati

Sigurd Nese, Joakim Nystrand

In collisions between heavy ions at ultra-relativistic energies the participating protons lose energy, which is converted into new particles. As the protons slow down, they emit bremsstrahlung radiation. The yield and angular distribution of the emitted radiation are sensitive probes of how much energy the incoming protons have lost. In this paper, the spect

Abhijeet Bhattacharya

The electroencephalogram (EEG) is one of the most precious technologies to understand the happenings inside our brain and further understand our body's happenings. Automatic prediction of oncoming seizures using the EEG signals helps the doctors and clinical experts and reduces their workload. This paper proposes an end-to-end deep learning algorithm to full

E. Fröjdh, F. Baruffaldi, A. Bergamaschi, M. Carulla

Electrons are emerging as a strong complement to X-rays for diffraction based studies. In this paper we investigate the performance of a JUNGFRAU detector with 320 um thick silicon sensor at a pulsed electron source. Originally developed for X-ray detection at free electron lasers, JUNGFRAU features a dynamic range of 120 MeV/pixel (implemented with in-pixel

Zhenkai Xie, Meng Yang, Zhigang Cheng, Tianping Ying

Previous investigations of 4$H_b$-TaS$_{2-2x}$Se$_{2x}$ mainly focused on the direct competition between superconductivity and charge density wave (CDW). However, the superconductivity itself, although has been prominently enhanced by isovalent Se substitution, has not been adequately investigated. Here, we performed a detailed electrical transport measureme

Shiyi Xia, Mingyang Zhao, Qian Ma, Xunnan Zhang

Beamforming makes possible a focused communication method. It is extensively employed in many disciplines involving electromagnetic waves, including arrayed ultrasonic, optical, and high-speed wireless communication. Conventional beam steering often requires the addition of separate active amplitude phase control units after each radiating element. The high

Fengjiang Fu, Xiaoqun Wang

Deep learning methods have achieved great success in solving partial differential equations (PDEs), where the loss is often defined as an integral. The accuracy and efficiency of these algorithms depend greatly on the quadrature method. We propose to apply quasi-Monte Carlo (QMC) methods to the Deep Ritz Method (DRM) for solving the Neumann problems for the

Dmitri Maslov, Willers Yang

A Hadamard-free Clifford transformation is a circuit composed of quantum Phase (P), CZ, and CNOT gates. It is known that such a circuit can be written as a three-stage computation, -P-CZ-CNOT-, where each stage consists only of gates of the specified type. In this paper, we focus on the minimization of circuit depth by entangling gates, corresponding to the

Sariah Mghames, Marc Hanheide

The majority of motion planning strategies developed over the literature for reaching an object in clutter are applied to two dimensional (2-d) space where the state space of the environment is constrained in one direction. Fewer works have been investigated to reach a target in 3-d cluttered space, and when so, they have limited performance when applied to

Yongchun Li, Weijun Xie

In the rank-constrained optimization problem (RCOP), it minimizes a linear objective function over a prespecified closed rank-constrained domain set and $m$ generic two-sided linear matrix inequalities. Motivated by the Dantzig-Wolfe (DW) decomposition, a popular approach of solving many nonconvex optimization problems, we investigate the strength of DW rela

Yang Zhong, Hongyu Yu, Mao Su, Xingao Gong

Using the message-passing mechanism in machine learning (ML) instead of self-consistent iterations to directly build the mapping from structures to electronic Hamiltonian matrices will greatly improve the efficiency of density functional theory (DFT) calculations. In this work, we proposed a general analytic Hamiltonian representation in an E(3) equivariant

Srshti Putcha, Christopher Nemeth, Paul Fearnhead

Stochastic gradient MCMC (SGMCMC) offers a scalable alternative to traditional MCMC, by constructing an unbiased estimate of the gradient of the log-posterior with a small, uniformly-weighted subsample of the data. While efficient to compute, the resulting gradient estimator may exhibit a high variance and impact sampler performance. The problem of variance

Aurélie Denys, Anthony Leverrier

Quantum computers often manipulate physical qubits encoded on two-level quantum systems. Bosonic qubit codes depart from this idea by encoding information in a well-chosen subspace of an infinite-dimensional Fock space. This larger physical space provides a natural protection against experimental imperfections and allows bosonic codes to circumvent no-go res

Basak Ozaydin, Muriel Médard, Ken Duffy

Optimal modulation (OM) schemes for Gaussian channels with peak and average power constraints are known to require nonuniform probability distributions over signal points, which presents practical challenges. An established way to map uniform binary sources to non-uniform symbol distributions is to assign a different number of bits to different constellation

Ryan Yang, Haizhou Du, Andre Wibisono, Patrick Baker

Distributed machine learning (DML) can be an important capability for modern military to take advantage of data and devices distributed at multiple vantage points to adapt and learn. The existing distributed machine learning frameworks, however, cannot realize the full benefits of DML, because they are all based on the simple linear aggregation framework, bu

Yi Xia, Aman R. Agrawal, Christian M. Pluchar, Anthony J. Brady

Optomechanical systems have been exploited in ultrasensitive measurements of force, acceleration, and magnetic fields. The fundamental limits for optomechanical sensing have been extensively studied and now well understood -- the intrinsic uncertainties of the bosonic optical and mechanical modes, together with the backaction noise arising from the interacti

Darlayne Addabbo, Lisa Carbone, Elizabeth Jurisich, Maryam Khaqan

The Monster Lie algebra $\mathfrak m$ is a quotient of the physical space of the vertex algebra $V=V^\natural\otimes V_{1,1}$, where $V^\natural$ is the Moonshine module vertex operator algebra of Frenkel, Lepowsky, and Meurman, and $V_{1,1}$ is the vertex algebra corresponding to the rank 2 even unimodular lattice $\textrm{II}_{1,1}$. We construct vertex al

Aharon Davidson

Nucleons and electrons were once considered elementary particles, a role nowadays taken by quarks and leptons. Here, mainly at the group theoretical level, we examine the unorthodox idea that nucleons and electrons share the same level of compositeness after all. We do it by first trading color $SU(3)_C$ for color/leptocolor $SU(3)_C\times SU(3)_{\ell C}$ co

Yury Belousov, Brian Pulfer, Roman Chaban, Joakim Tutt

In this paper, we address the problem of modeling a printing-imaging channel built on a machine learning approach a.k.a. digital twin for anti-counterfeiting applications based on copy detection patterns (CDP). The digital twin is formulated on an information-theoretic framework called Turbo that uses variational approximations of mutual information develope

Jihoon Chung, Bo Shen, Zhenyu, Kong

This paper addresses the problem of fault diagnosis in multistation assembly systems. Fault diagnosis is to identify process faults that cause the excessive dimensional variation of the product using dimensional measurements. For such problems, the challenge is solving an underdetermined system caused by a common phenomenon in practice; namely, the number of

Dong-Ki Kim, Matthew Riemer, Miao Liu, Jakob N. Foerster

Multiagent learning settings are inherently more difficult than single-agent learning because each agent interacts with other simultaneously learning agents in a shared environment. An effective approach in multiagent reinforcement learning is to consider the learning process of agents and influence their future policies toward desirable behaviors from each

Stephen D. Liang, Jerry M. Mendel

In this paper, we propose a multimodal transformer using parallel concatenated architecture. Instead of using patches, we use column stripes for images in R, G, B channels as the transformer input. The column stripes keep the spatial relations of original image. We incorporate the multimodal transformer with variational autoencoder for synthetic cross-modal

Tianci Zhang, Shutong Chen, Zhengchuan Chen, Zhong Tian

Lots of real-time applications over Internet of things (IoT)-based status update systems have imperative demands on information freshness, which is usually evaluated by age of information (AoI). Compared to the average AoI and peak AoI (PAoI), violation probabilities and distributions of AoI and PAoI characterize the timeliness in more details. This paper st

Qihan Wang, Chen Dun, Fangshuo Liao, Chris Jermaine

Recent work on the Lottery Ticket Hypothesis (LTH) shows that there exist ``\textit{winning tickets}'' in large neural networks. These tickets represent ``sparse'' versions of the full model that can be trained independently to achieve comparable accuracy with respect to the full model. However, finding the winning tickets requires one to \emph{pretrain} the

Ryiaadh Gani, Lisa Chalaguine

In this paper, we compare the performances of traditional machine learning models using feature engineering and word vectors and the state-of-the-art language model BERT using word embeddings on three datasets. We also consider the time and cost efficiency of feature engineering compared to BERT. From our results we conclude that the use of the BERT model wa

Lisa M. Pietrek, Lukas S. Stelzl, Gerhard Hummer

Disordered proteins and nucleic acids play key roles in cellular function and disease. Here we review recent advances in the computational exploration of the conformational dynamics of flexible biomolecules. We focus on hierarchical chain growth (HCG) from fragment libraries built with atomistic molecular dynamics simulations. HCG combines chain fragments in

Qihong Huang, Kaituo Zhang, He Huang, Bing Xu

The emergent universe provides a possible method to avoid the big bang singularity by considering that the universe stems from an stable Einstein static universe rather than the singularity. Since the Einstein static universe exists before inflation, it may leave some relics in the CMB power spectrum. In this paper, we analyze the stability condition for the

Manish K Gupta

This paper introduces an isometry between the modular rings $\Z_{2^s}$ and $\Z_{2^{s-1}}$ with respect to the homogeneous weights. Certain product of these maps gives Carlet's generalised Gray map and also Vega's Gray map. For $s=2$ this reduces to popular Gray map. Several interesting properties of these maps are studied. Towards the end we list several int

Marco Fraccaroli, Olli Saari, Christoph Thiele

We construct phase space localizing operators in all dimensions. These are frequency localized variants of the conditional expectation operator related to a dyadic stopping time. Our construction is an improvement over the so-called phase plane projections of Muscalu, Tao and the third author in one dimension. The motivation for such operators comes from tim

Khoi Nguyen

We prove a formula involving the scalar curvature of a Riemannian manifold endowed with a distribution in terms of an adapted orthonormal frame for its tangent bundle. Using the formula, we then investigate the effect of collapsing the metric along the distribution on the scalar curvature. This result contributes to the question of finding a positive scalar

Alexander Hoyle, Pranav Goel, Rupak Sarkar, Philip Resnik

Recently, the relationship between automated and human evaluation of topic models has been called into question. Method developers have staked the efficacy of new topic model variants on automated measures, and their failure to approximate human preferences places these models on uncertain ground. Moreover, existing evaluation paradigms are often divorced fr

Lars Gerchow, Sayani Biswas, Gianluca Janka, Carlos Vigo

The usage of muonic X-rays to study elemental properties like nuclear radii ranges back to the seventies. This triggered the pioneering work at the Paul Scherrer Institute (PSI), during the eighties, on the Muon Induced X-ray Emission (MIXE) technique for a non-destructive assessment of elemental compositions. In the recent years, this method has seen a rebi

Matthew R. Carbone, Fanchen Meng, Christian Vorwerk, Benedikt Maurer

First-principles computational spectroscopy is a critical tool for interpreting experiment, performing structure refinement, and developing new physical understanding. Systematically setting up input files for different simulation codes and a diverse class of materials is a challenging task with a very high barrier-to-entry, given the complexities and nuance

Melissa Antonelli

Counting propositional logic was recently introduced in relation to randomized computation and shown able to logically characterize the full counting hierarchy. In this paper we aim to clarify the intuitive meaning and expressive power of its univariate fragment. On the one hand, we provide an effective procedure to measure the probability of counting formul

Askar Ali, Khalid Saifullah

We study higher dimensional quartic quasi-topological black holes in the framework of non-abelian power-Yang-Mills theory. It is shown that real solutions of the gravitational field equations exist only for positive values of quartic quasi-topological coefficient. Depending on the values of the mass parameter and Yang-Mills charge, they can be interpreted as

Donghan Kim, Lane Chun Yeung

We consider degenerate diffusion equations of the form $\partial_tp_t = \Delta f(p_t)$ on a bounded domain and subject to no-flux boundary conditions, for a class of nonlinearities $f$ that includes the porous medium equation. We derive for them a trajectorial analogue of the entropy dissipation identity, which describes the rate of entropy dissipation along

Gregor Bayer, Robert Berghaus, Selene Sachero, Andrea B. Filipovski

Quantum key distribution enables secure communication based on the principles of quantum mechanics. The distance in fiber-based quantum communication is limited to about a hundred kilometers due to signal attenuation. Thus, quantum repeaters are required to establish large-scale quantum networks. Ideal quantum repeater nodes possess a quantum memory which is

MohammadReza Davari, Stefan Horoi, Amine Natik, Guillaume Lajoie

Comparing learned neural representations in neural networks is a challenging but important problem, which has been approached in different ways. The Centered Kernel Alignment (CKA) similarity metric, particularly its linear variant, has recently become a popular approach and has been widely used to compare representations of a network's different layers, of

Scott W Hegerty

In the United States, large post-industrial cites such as Detroit are well-known for high levels of socioeconomic deprivation. But while Detroit is an exceptional case, similar levels of deprivation can still be found in other large cities, as well as in smaller towns and rural areas. This study calculates a standardized measure for all block groups in the l

Daichi Hirobe, Yoji Nabei, Hiroshi M. Yamamoto

We report gate-induced enhancement of intrinsic charge rectification without p-n junctions in chiral semiconductor Te under magnetic field B. As gating shifts the chemical potential to the valence band maximum of Te, the charge rectification efficiency is enhanced hundredfold. By integrating model calculations, we attribute the charge rectification to the B-

Izzy Friedlander, Thanasis Bouganis, Maximilien Gadouleau

The weight distribution of an error correcting code is a crucial statistic in determining it's performance. One key tool for relating the weight of a code to that of it's dual is the MacWilliams Identity, first developed for the Hamming metric. This identity has two forms: one is a functional transformation of the weight enumerators, while the other is a dir

Minhao Hong, Qian Yu

In this paper, we prove two limit laws for functionals of self-intersection symmetric alpha-stable processes with alpha\in(1,2). The results are obtained based on the method of moments, the sample configuration and the chaining argument introduced in (Nualart and Xu 2013) are employed.

Camille Hankel, Eli Tziperman

Abrupt and irreversible winter Arctic sea-ice loss may occur under anthropogenic warming due to the collapse of a sea-ice equilibrium at a threshold value of CO$_2$, commonly referred to as a tipping point. Previous work has been unable to conclusively identify whether a tipping point in Arctic sea ice exists because fully-coupled climate models are too comp

Marek Lassak

Let $C$ and $D$ be convex bodies in the Euclidean space $E^d$. We define the centroid Banach-Mazur distance $\delta_{BM}^{\rm cen} (C, D)$ similarly to the classic Banach-Mazur distance $\delta_{BM} (C, D)$, but with the extra requirement that the centroids of $C$ and an affine image of $D$ coincide. We prove that for the parallelogram $P$ and the triangle $

Sruthy Poulose, M. Venkatesan, Matthias Mobius, J. M. D. Coey

Hypothesis. Ortho and para water are the two nuclear isomers where the hydrogen protons align to give a total nuclear spin of 0 or 1.The equilibrium ratio of 3:1 is established slowly in freshly evaporated water vapour and the isomers then behave distinct gasses, with their own partial pressures. Magnetic-field-induced ortho to para transformations are expec

Miles M. P. Couchman, Stephen M. de Bruyn Kops, Colm-cille P. Caulfield

Understanding how turbulence enhances irreversible scalar mixing in density-stratified fluids is a central problem in geophysical fluid dynamics. While isotropic overturning regions are commonly the focus of mixing analyses, we here investigate whether significant mixing may arise in anisotropic statically-stable regions of the flow. Focusing on a single for

Miloš Stanojević, Jonathan R. Brennan, Donald Dunagan, Mark Steedman

To model behavioral and neural correlates of language comprehension in naturalistic environments researchers have turned to broad-coverage tools from natural-language processing and machine learning. Where syntactic structure is explicitly modeled, prior work has relied predominantly on context-free grammars (CFG), yet such formalisms are not sufficiently ex

R. J. Radwanski

We succeeded in remarkably nice theoretical description of the temperature dependence of the paramagnetic susceptibility of Ba$_2$YMoO$_6$ in the whole temperature range as originating from the atomic-scale discrete electronic structure of Mo$^{5+}$ ions in the 4d$^1$ configuration resulting from crystal-field and spin-orbit interactions. A strong violation

Viktor Könye, Lotte Mertens, Corentin Morice, Dmitry Chernyavsky

We show that tilted Weyl semimetals with a spatially varying tilt of the Weyl cones provide a platform for studying analogues to problems in anisotropic optics as well as curved spacetime. Considering particular tilting profiles, we numerically evaluate the time evolution of electronic wave packets and their current densities. We demonstrate that electron tr

Sandra Carrasco Limeros, Sylwia Majchrowska, Joakim Johnander, Christoffer Petersson

Predicting the motion of other road agents enables autonomous vehicles to perform safe and efficient path planning. This task is very complex, as the behaviour of road agents depends on many factors and the number of possible future trajectories can be considerable (multi-modal). Most prior approaches proposed to address multi-modal motion prediction are bas

Guo-Chin Liu, Kin-Wang Ng

The detection of gravitational waves from the coalescences of binary compact stars by current interferometry experiments has opened up a new era of gravitational-wave astrophysics and cosmology. The search for a stochastic gravitational-wave background is underway by correlating signals from a pair of detectors in the detector network formed by the LIGO, Vir

Yiqing Shen, Baiyun Liu, Ruize Yu, Yudong Wang

Chronic Obstructive Pulmonary Disease (COPD) is the fourth leading cause of death worldwide. Yet, COPD diagnosis heavily relies on spirometric examination as well as functional airway limitation, which may cause a considerable portion of COPD patients underdiagnosed especially at the early stage. Recent advance in deep learning (DL) has shown their promising

Sergio R. Coria, Luz M. Garcia-Garcia

Digital divide is one of the challenges that open government must face in mid- and low-income countries. In these contexts, inhabitants are left out of the benefits of information and communication technology (ICT), such as online government services. The present scenario that has emerged from the COVID-19 pandemic offers opportunities and challenges in ICT

Angela Wittmann, Olena Gomonay, Kai Litzius, Allison Kaczmarek

Antiferromagnets have recently been propelled to the forefront of spintronics by their high potential for revolutionizing memory technologies. For this, understanding the formation and driving mechanisms of the domain structure is paramount. In this work, we investigate the domain structure in a thin-film canted antiferromagnet $\alpha$-Fe$_2$O$_3$. We find

Jan Schuchardt, Tom Wollschläger, Aleksandar Bojchevski, Stephan Günnemann

Models for image segmentation, node classification and many other tasks map a single input to multiple labels. By perturbing this single shared input (e.g. the image) an adversary can manipulate several predictions (e.g. misclassify several pixels). Collective robustness certification is the task of provably bounding the number of robust predictions under th

CMS Collaboration

The production of Z bosons associated with jets is measured in pp collisions at $\sqrt{s}$ = 13 TeV with data recorded with the CMS experiment at the LHC corresponding to an integrated luminosity of 36.3 fb$^{-1}$. The multiplicity of jets with transverse momentum $p_\mathrm{T}$ $\gt$ 30 GeV is measured for different regions of the Z boson's $p_\mathrm{T}$(Z

Fan Gao, Nadya Gurevich, Edmund Karasiewicz

We explicate relations among the Gelfand--Graev modules for central covers, the Euler--Poincar\'e polynomial of the Arnold--Brieskorn manifold, and the quantum affine Schur--Weyl duality. These three objects and their relations are dictated by a permutation representation of the Weyl group. Specifically, our main result shows that for certain covers of $\mat

Yeming Gu, Hui Shu, Fei Kang, Fan Hu

Binary code similarity detection (BCSD) is widely used in various binary analysis tasks such as vulnerability search, malware detection, clone detection, and patch analysis. Recent studies have shown that the learning-based binary code embedding models perform better than the traditional feature-based approaches. However, previous studies have not delved dee

Miguel Bello, J. Ignacio Cirac

In this work we discuss particular effects that take place in systems of quantum emitters coupled to two-dimensional bosonic topological insulators. For a single emitter coupled to the Haldane model, we find a "fragile" quasibound state that makes the emitter dynamics very sensitive to the model's parameters, and gives rise to effective long-range interactio

Yu. D. Fomin, I. V. Danilov, E. L. Gromnitskaya

We report an ulsrasonic measurements of density and bulk modulus of propylene glycol at room temperature and at the temperature of liquid nitrogen combined with molecular dynamics simulations with two different force fields. We find that experimental density of propylene glycol at room temperature is well described within COMPASS force fields simulations, wh

G. Quintana-Lacaci, L. Velilla-Prieto, M. Agúndez, J. P. Fonfría

Red supergiant stars (RSGs, Minit = 10-40Msun) are known to eject large amounts of material, as much as half of their initial mass during this evolutionary phase. However, the processes powering the mass ejection in low- and intermediate-mass stars do not work for RSGs and the mechanism that drives the ejection remains unknown. Different mechanisms have been

Edison Fernando García Veloz, Clara Rojas

This article presents the generalization of a zero spin hydrogen atom to a relativistic atomic model of hydrogen with dyons using the Klein--Gordon equation. The derivation of the Klein--Gordon equation for the particle of relative motion is shown. In addition, the analytical solutions of the equation are calculated in terms of Whittaker functions and Jacobi

Joris Baan, Wilker Aziz, Barbara Plank, Raquel Fernández

Calibration is a popular framework to evaluate whether a classifier knows when it does not know - i.e., its predictive probabilities are a good indication of how likely a prediction is to be correct. Correctness is commonly estimated against the human majority class. Recently, calibration to human majority has been measured on tasks where humans inherently d

Raffaele Folino, Ramón G. Plaza, Delyan Zhelyazov

This paper studies the stability of weak dispersive shock profiles for a quantum hydrodynamics system in one space dimension with nonlinear viscosity and dispersive (quantum) effects due to a Bohm potential. It is shown that, if the shock amplitude is sufficiently small, then the profiles are spectrally stable. This analytical result is consistent with numer

Vitalii Vertogradov

In this paper, we consider the gravitational collapse of generalized Vaidya space-time when the matter satisfies the equation of the state either $P=0$ or $P=-\alpha \rho$, where $0 < \alpha < 1$. We show that in the case when type I of matter field is dust, then the apparent horizon will never appear, but there is now a family of null radial future-directed