November 2022 arXiv papers — page 4

Pablo Barcelo, Mikhail Galkin, Christopher Morris, Miguel Romero Orth

Knowledge graphs, modeling multi-relational data, improve numerous applications such as question answering or graph logical reasoning. Many graph neural networks for such data emerged recently, often outperforming shallow architectures. However, the design of such multi-relational graph neural networks is ad-hoc, driven mainly by intuition and empirical insi

Wojciech Bielas, Andrzej Kucharski, Szymon Plewik

We examine dimensional types of scattered $P$-spaces of weight $\omega_1$. Such spaces can be embedded into $\omega_2$. There are established similarities between dimensional types of scattered separable metric spaces and dimensional types of $P$-spaces of weight $\omega_1$ with Cantor--Bendixson rank less than $\omega_1$.

Haniyeh Ehsani Oskouie, Farzan Farnia

Interpreting neural network classifiers using gradient-based saliency maps has been extensively studied in the deep learning literature. While the existing algorithms manage to achieve satisfactory performance in application to standard image recognition datasets, recent works demonstrate the vulnerability of widely-used gradient-based interpretation schemes

Junjie Huang, Guan Huang

We release a new codebase version of the BEVDet, dubbed branch dev2.0. With dev2.0, we propose BEVPoolv2 upgrade the view transformation process from the perspective of engineering optimization, making it free from a huge burden in both calculation and storage aspects. It achieves this by omitting the calculation and preprocessing of the large frustum featur

Jon F. Carlson

We show that counterexamples of Iyengar and Walker to the algebraic version of Gunnar Carlsson's conjecture on the rank of the homology of a free complex can be extended to examples over any finite group with many choices of the complex.

Siddhi Krishna, Hugh Morton

Many well studied knots can be realized as positive braid knots where the braid word contains a positive full twist; we say that such knots are twist positive. Some important families of knots are twist positive, including torus knots, 1-bridge braids, algebraic knots, and Lorenz knots. We prove that if a knot is twist positive, the braid index appears as th

Chengdong Han, Wei Kou, Rong Wang, Xurong Chen

Low-energy scattering processes of vector meson and nucleon are an important window for studying non-perturbative QCD. The interaction of vector meson with nucleon, vector meson-nucleon scattering length $|\alpha_{VN}|$, is an important component of the study of hadronic interactions. Nowadays many scattering length values $|\alpha_{VN}|$ have been reported

Pasquale De Rosa, Valerio Schiavoni

Crypto-coins (also known as cryptocurrencies) are tradable digital assets. Notable examples include Bitcoin, Ether and Litecoin. Ownerships of cryptocoins are registered on distributed ledgers (i.e., blockchains). Secure encryption techniques guarantee the security of the transactions (transfers of coins across owners), registered into the ledger. Cryptocoin

Tim Erdbrügger, Andreas Westhoff, Malte Hoeltershinken, Jan-Ole Radecke

Source analysis of Electroencephalography (EEG) data requires the computation of the scalp potential induced by current sources in the brain. This so-called EEG forward problem is based on an accurate estimation of the volume conduction effects in the human head, represented by a partial differential equation which can be solved using the finite element meth

April Chen, Nathan Kaplan, Liam Lawson, Christopher O'Neill

A numerical set $T$ is a subset of $\mathbb N_0$ that contains $0$ and has finite complement. The atom monoid of $T$ is the set of $x \in \mathbb N_0$ such that $x+T \subseteq T$. Marzuola and Miller introduced the anti-atom problem: how many numerical sets have a given atom monoid? This is equivalent to asking for the number of integer partitions with a giv

Jonathan Elmer

Let $G$ be a linear algebraic group acting linearly on a vector space $V$, and let $k[V]^G$ be the corresponding algebra of invariant polynomial functions. A separating set $S \subseteq k[V]^G$ is a set of polynomials with the property that for all $v,w \in V$, if there exists $f \in k[V]^G$ separating $v$ and $w$, then there exists $f \in S$ separating $v$

Yong Gao, Lijing Shao, Gregory Desvignes, David Ian Jones

Magnetars are conjectured to be highly magnetized neutron stars (NSs). Strong internal magnetic field and elasticity in the crust may deform the stars and lead to free precession. We study the precession dynamics of triaxially-deformed NSs incorporating the near-field and the far-field electromagnetic torques. We obtain timing residuals for different NS geom

Jaskirat Singh, Stephen Gould, Liang Zheng

Controllable image synthesis with user scribbles has gained huge public interest with the recent advent of text-conditioned latent diffusion models. The user scribbles control the color composition while the text prompt provides control over the overall image semantics. However, we note that prior works in this direction suffer from an intrinsic domain shift

Marco Cè, Antoine Gérardin, Georg von Hippel, Renwick J. Hudspith

Following the publication of the new measurement of the anomalous magnetic moment of the muon, the discrepancy between experiment and the theory prediction from the $g-2$ theory initiative has increased to $4.2\,\sigma$. Recent lattice QCD calculations predict values for the hadronic vacuum polarization contribution that are larger than the data-driven estim

J. Andrés Rojas-Sánchez, Yesenia A. García Jomaso, Brenda Vargas, David Ley Dominguez

Frenkel polaritons, hybrid light-matter quasiparticles, offer promises for the designing of new opto-electronic devices. However, their technological implementations are hindered by sensitivity to imperfections. Topology has raised as a way to circumvent defects and fabrication limitations. Here, we propose a lattice of cavities to realize the one-dimensiona

Lianyu Hu, Liqing Gao, Zekang liu, Wei Feng

Hand and face play an important role in expressing sign language. Their features are usually especially leveraged to improve system performance. However, to effectively extract visual representations and capture trajectories for hands and face, previous methods always come at high computations with increased training complexity. They usually employ extra hea

Linas Nasvytis

Large amounts of evidence suggest that trust levels in a country are an important determinant of its macroeconomic growth. In this paper, we investigate one channel through which trust might support economic performance: through the levels of patience, also known as time preference in the economics literature. Following Gabaix and Laibson (2017), we first ar

I. Szanyi, T. Csörgő

The Real Extended Bialas-Bzdak (ReBB) model study is extended to the 8 TeV $pp$ TOTEM elastic differential cross section data. The analysis shows that the ReBB model describes the $pp$ and $p\bar{p}$ differential cross section data in the limited $0.37 \leq -t \leq 1.2$ GeV$^2$ and $1.96 \leq \sqrt{s} \leq 8$ TeV kinematic region, in a statistically acceptab

Joshua Levin, Randall Correll, Takanori Ide, Takafumi Suzuki

Deep reinforcement learning (RL) has been shown to be effective in producing approximate solutions to some vehicle routing problems (VRPs), especially when using policies generated by encoder-decoder attention mechanisms. While these techniques have been quite successful for relatively simple problem instances, there are still under-researched and highly com

Jason Hughes, Dominic Larkin, Charles O'Donnell, Christopher Korpela

Optimal transport (OT) is a framework that can guide the design of efficient resource allocation strategies in a network of multiple sources and targets. This paper applies discrete OT to a swarm of UAVs in a novel way to achieve appropriate task allocation and execution. Drone swarm deployments already operate in multiple domains where sensors are used to g

Randall Correll, Sean J. Weinberg, Fabio Sanches, Takanori Ide

Problem instances of a size suitable for practical applications are not likely to be addressed during the noisy intermediate-scale quantum (NISQ) period with (almost) pure quantum algorithms. Hybrid classical-quantum algorithms have potential, however, to achieve good performance on much larger problem instances. We investigate one such hybrid algorithm on a

Yawei Liu, Jared A. Wood, Achille Giacometti, Asaph Widmer-Cooper

The propagation of chirality across scales is a common but poorly understood phenomenon in soft matter. In this work, we use computer simulations to study chiral monolayer assemblies formed by hard rod-like colloidal particles in the presence of non-adsorbing polymer and characterize the thermodynamic driving forces responsible for the twisting. Simulations

Shankhanil Mitra, Saiyam Jogani, Rajiv Soundararajan

Designing learning-based no-reference (NR) video quality assessment (VQA) algorithms for camera-captured videos is cumbersome due to the requirement of a large number of human annotations of quality. In this work, we propose a semi-supervised learning (SSL) framework exploiting many unlabelled and very limited amounts of labelled authentically distorted vide

Guanru Pan, Ruchuan Ou, Timm Faulwasser

The fundamental lemma by Jan C. Willems and co-authors enables the representation of all input-output trajectories of a linear time-invariant system by measured input-output data. This result has proven to be pivotal for data-driven control. Building on a stochastic variant of the fundamental lemma, this paper presents a data-driven output-feedback predictiv

Keith Strandell, Sudip Mittal

Recent cybersecurity events have prompted the federal government to begin investigating strategies to transition to Zero Trust Architectures (ZTA) for federal information systems. Within federated mission networks, ZTA provides measures to minimize the potential for unauthorized release and disclosure of information outside bilateral and multilateral agreeme

Jason Hughes, Juntao Chen

This paper considers the security investment problem over a network in which the resource owners aim to allocate their constrained security resources to heterogeneous targets strategically. Investing in each target makes it less vulnerable, and thus lowering its probability of a successful attack. However, humans tend to perceive such probabilities inaccurat

Yu-Xuan Zhang, Hua Meng, Xue-Mei Cao, Zhengchun Zhou

Multi-Instance Learning (MIL) is a recent machine learning paradigm which is immensely useful in various real-life applications, like image analysis, video anomaly detection, text classification, etc. It is well known that most of the existing machine learning classifiers are highly vulnerable to adversarial perturbations. Since MIL is a weakly supervised le

Jason Hughes, Juntao Chen

Optimal transport (OT) is a framework that can guide the design of efficient resource allocation strategies in a network of multiple sources and targets. To ease the computational complexity of large-scale transport design, we first develop a distributed algorithm based on the alternating direction method of multipliers (ADMM). However, such a distributed al

David Alonso-Gutiérrez, Javier Martín Goñi

We consider the problem of finding the best function $\varphi_n:[0,1]\to\mathbb{R}$ such that for any pair of convex bodies $K,L\in\mathbb{R}^n$ the following Brunn-Minkowski type inequality holds $$ |K+_\theta L|^\frac{1}{n}\geq\varphi_n(\theta)(|K|^\frac{1}{n}+|L|^\frac{1}{n}), $$ where $K+_\theta L$ is the $\theta$-convolution body of $K$ and $L$. We prov

Li Sun, Junda Ye, Hao Peng, Feiyang Wang

Continual graph learning routinely finds its role in a variety of real-world applications where the graph data with different tasks come sequentially. Despite the success of prior works, it still faces great challenges. On the one hand, existing methods work with the zero-curvature Euclidean space, and largely ignore the fact that curvature varies over the c

Yahya Saleh, Armin Iske, Andrey Yachmenev, Jochen Küpper

Approximating functions by a linear span of truncated basis sets is a standard procedure for the numerical solution of differential and integral equations. Commonly used concepts of approximation methods are well-posed and convergent, by provable approximation orders. On the down side, however, these methods often suffer from the curse of dimensionality, whi

Andreas Döpp, Christoph Eberle, Sunny Howard, Faran Irshad

Laser-plasma physics has developed rapidly over the past few decades as high-power lasers have become both increasingly powerful and more widely available. Early experimental and numerical research in this field was restricted to single-shot experiments with limited parameter exploration. However, recent technological improvements make it possible to gather

Anay Mehrotra, Nisheeth K. Vishnoi

The fair-ranking problem, which asks to rank a given set of items to maximize utility subject to group fairness constraints, has received attention in the fairness, information retrieval, and machine learning literature. Recent works, however, observe that errors in socially-salient (including protected) attributes of items can significantly undermine fairne

Carolina Luque, Juan Sosa

This manuscript extensively reviews applications, extensions, and models derived from the Bayesian ideal point estimator. We primarily focus our attention on studies conducted in the United States as well as Latin America. First, we provide a detailed description of the Bayesian ideal point estimator. Next, we propose a new taxonomy to synthesize and frame t

Samantha Rath

A comparative study of a set of parametric dark energy models is performed by studying the evolution of dark energy both in the past and future epochs. In addition, the age of the universe and time till the distant future $(a=1000)$ are estimated. The validity of generalized second law of thermodynamic in different parametric models is also ascertained.

Laurids Jeppe

We present the first measurement of the top quark pair production cross section at the new LHC center-of-mass energy of $\sqrt{s} = 13.6 \, \mathrm{TeV}$, using $1.20 \, \mathrm{fb}^{-1}$ of data recorded at the CMS detector. We use a new method combining dilepton and lepton+jets decay channels, constraining several experimental uncertainties in situ. A cros

Ke Gao, Lei-Hua Liu, Mian Zhu

In this paper, we investigate the microlensing effects of wormholes associated to black hole spacetimes. Specifically, we work on three typical wormholes (WH): Schwarzschild WH, Kerr WH, and RN WH, as well as their blackhole correspondences. We evaluate the deflection angle upon the second order under weak field approximation using Gauss-Bonnet theorem. Then

Zbigniew J. Jurek

Selfdecomposable variables obtained from series of Laplace (double exponential) variables are objects of this study. We proved that hyperbolic-sine and hyperbolic-cosine variables are in the difference of the Urbanik classes $L_2$ and $L_3$ while generalized logistic variable is at least in the Urbanik class $L_1$. Hence some ratios of those corresponding se

Ray Maresca

In this note, we will illuminate some immediate consequences of work done by Reineke that may prove to be useful in the study of elliptic curves. In particular, we will construct an isomorphism between the category of smooth projective curves with a category of quiver grassmannians. We will use this to provide a 4-fold categorical equivalence between a categ

Vladimir A. Yerokhin, Vojtěch Patkóš, Krzysztof Pachucki

We perform ab initio calculations of the QED effects of order $m\alpha^7$ for the $2^3S$ and $2^3P$ states of He-like ions. The computed effects are combined with previously calculated energies from [V. A. Yerokhin and K. Pachucki, Phys. Rev. A 81, 022507 (2010)], thus improving the theoretical accuracy by an order of magnitude. The obtained theoretical valu

Su-Zhi Wu, Pei Wu, You-Wei Li

Non-relativistic quantum chromodynamics (NRQCD) factorization formulism is an important approach to investigate the production of the heavy quarkonium. In this paper, we study the production of the $\Omega_{ccc}$ and $\Omega_{bbb}$ at the $e^+e^-$ collider, using the NRQCD factorization formulism. We calculate the total and differential cross sections exactl

Mahadevan Subramanian, Amal Mathew, Bhaskaran Muralidharan

Quantum metrology that employs weak-values can potentially effectuate parameter estimation with an ultra-high sensitivity and has been typically explored across quantum optics setups. Recognizing the importance of sensitive parameter estimation in the solid-state, we propose a spintronic device platform to realize this. The setup estimates a very weak locali

Jorge Pérez-Aracil, Carlos Camacho-Gómez, Eugenio Lorente-Ramos, Cosmin M. Marina

In this paper we propose new probabilistic and dynamic (adaptive) strategies to create multi-method ensembles based on the Coral Reefs Optimization with Substrate Layers (CRO-SL) algorithm. The CRO-SL is an evolutionary-based ensemble approach, able to combine different search procedures within a single population. In this work we discuss two different proba

Yiyang Liu, Chenxin Li, Xiaotong Tu, Xinghao Ding

Knowledge Distillation (KD) transfers the knowledge from a high-capacity teacher model to promote a smaller student model. Existing efforts guide the distillation by matching their prediction logits, feature embedding, etc., while leaving how to efficiently utilize them in junction less explored. In this paper, we propose Hint-dynamic Knowledge Distillation,

Jordi Gaset, Manuel Lainz, Arnau Mas, Xavier Rivas

In the recent years, with the incorporation of contact geometry, there has been a renewed interest in the study of dissipative or non-conservative systems in physics and other areas of applied mathematics. The equations arising when studying contact Hamiltonian systems can also be obtained via the Herglotz variational principle. The contact Lagrangian and Ha

Huirong Yan, Parth Pavaskar

High energy emissions near particle accelerators provide unique windows to probe the particle acceleration and ensuing escape process determined by local medium properties, particularly the turbulence properties. It has been demonstrated both theoretically and observationally that particle diffusion in local environment can differ from the averaged values in

Muhammad Umar Farooq, Michael Lentmaier, Alexandre Graell i Amat

CC-GLPDC codes are a class of generalized low-density parity-check (GLDPC) codes where the constraint nodes (CNs) represent convolutional codes. This allows for efficient decoding in the trellis with the forward-backward algorithm, and the strength of the component codes easily can be controlled by the encoder memory without changing the graph structure. In

T. Gastine, J. M. Aurnou

Convection occurs ubiquitously on and in rotating geophysical and astrophysical bodies. Prior spherical shell studies have shown that the convection dynamics in polar regions can differ significantly from the lower latitude, equatorial dynamics. Yet most spherical shell convective scaling laws use globally-averaged quantities that erase latitudinal differenc

Antun Skuric, Vincent Padois, David Daney

This paper presents an approach for approximating the reachable space of robotic manipulators based on convex polytopes. The proposed approach predicts the reachable space over a given time horizon based on the robot's actuation limits and kinematic constraints. The approach is furthermore extended to integrate the robot's environment, assuming it can be exp

Sotheara Leang, Eric Castelli, Dominique Vaufreydaz, Sethserey Sam

The transition angles are defined to describe the vowel-to-vowel transitions in the acoustic space of the Spectral Subband Centroids, and the findings show that they are similar among speakers and speaking rates. In this paper, we propose to investigate the usage of polar coordinates in favor of angles to describe a speech signal by characterizing its acoust

Renzi Wang, Mathijs Schuurmans, Panagiotis Patrinos

Lane changing and lane merging remains a challenging task for autonomous driving, due to the strong interaction between the controlled vehicle and the uncertain behavior of the surrounding traffic participants. The interaction induces a dependence of the vehicles' states on the (stochastic) dynamics of the surrounding vehicles, increasing the difficulty of p

Mohamed Amazioug, Berihu Teklu, Muhammad Asjad

We propose a scheme to improve magnon-photon-phonon entanglement in cavity magnomechanics using coherent feedback loop. In addition, we prove that the steady state and dynamical state of the system is a genuine tripartite entanglement state. We use the logarithmic negativity as the witness of quantum correlations to quantify the entanglement of all bipartite

J P Boeuf

Long wavelength plasma non-uniformities rotating in the azimuthal direction ("rotating spokes") have been observed in a number of experiments on Hall thrusters or magnetron discharges. We use a two-dimensional (2D), axial-azimuthal Particle-In-Cell Monte Carlo Collisions (PIC-MCC) model to study the formation of instabilities in a direct current (dc) magnetr

Yuri Faenza, Clifford Stein, Jia Wan

Let $G$ be a graph and suppose we are given, for each $v \in V(G)$, a strict ordering of the neighbors of $v$. A set of matchings ${\cal M}$ of $G$ is called internally stable if there are no matchings $M,M' \in {\cal M}$ such that an edge of $M$ blocks $M'$. The sets of stable (\`a la Gale and Shapley) matchings and of von Neumann-Morgenstern stable matchin

Miguel Salg, Dalibor Djukanovic, Georg von Hippel, Harvey B. Meyer

We present results for the electromagnetic form factors of the proton and neutron computed on the Coordinated Lattice Simulations (CLS) ensembles with $N_f = 2 + 1$ flavors of $\mathcal{O}(a)$-improved Wilson fermions and an $\mathcal{O}(a)$-improved conserved vector current. In order to estimate the excited-state contamination, we employ several source-sink

Yu Fang, Lanzhuju Mei, Changjian Li, Yuan Liu

Cone beam computed tomography (CBCT) has been widely used in clinical practice, especially in dental clinics, while the radiation dose of X-rays when capturing has been a long concern in CBCT imaging. Several research works have been proposed to reconstruct high-quality CBCT images from sparse-view 2D projections, but the current state-of-the-arts suffer fro

Rafael López-Soriano, Alejandro Ortega

This paper is focused on the solvability of a family of nonlinear elliptic systems defined in $\mathbb{R}^N$. Such equations contain Hardy potentials and Hardy-Sobolev criticalities coupled by a possible critical Hardy-Sobolev term. That problem arises as a generalization of Gross-Pitaevskii and Bose-Einstein type systems. By means of variational techniques,

Punyajoy Saha, Divyanshu Sheth, Kushal Kedia, Binny Mathew

Abusive language is a concerning problem in online social media. Past research on detecting abusive language covers different platforms, languages, demographies, etc. However, models trained using these datasets do not perform well in cross-domain evaluation settings. To overcome this, a common strategy is to use a few samples from the target domain to train

Mateus Roder, Jurandy Almeida, Gustavo H. de Rosa, Leandro A. Passos

In the last decade, exponential data growth supplied machine learning-based algorithms' capacity and enabled their usage in daily-life activities. Additionally, such an improvement is partially explained due to the advent of deep learning techniques, i.e., stacks of simple architectures that end up in more complex models. Although both factors produce outsta

Thierry Huillet, Martin Möhle

A Bernoulli scheme with unequal harmonic success probabilities is investigated, together with some of its natural extensions. The study includes the number of successes over some time window, the times to (between) successive successes and the time to the first success. Large sample asymptotics, statistical parameter estimation, and relations to Sibuya distr

Stefan Noll, Carsten Schmidt, Wolfgang Kausch, Michael Bittner

Chemiluminescent radiation of the vibrationally and rotationally excited OH radical, which dominates the nighttime near-infrared emission of the Earth's atmosphere in wide wavelength regions, is an important tracer of the chemical and dynamical state of the mesopause region between 80 and 100 km. As radiative lifetimes and rate coefficients for collision-rel

Sepehr Sameni, Simon Jenni, Paolo Favaro

We propose Spatio-temporal Crop Aggregation for video representation LEarning (SCALE), a novel method that enjoys high scalability at both training and inference time. Our model builds long-range video features by learning from sets of video clip-level features extracted with a pre-trained backbone. To train the model, we propose a self-supervised objective

Thomas Vuillaume, Enrique Garcia, Christian Tacke, Tamas Gal

The astronomy, astroparticle and particle physics communities are brought together through the ESCAPE (European Science Cluster of Astronomy and Particle Physics ESFRI research infrastructures) project to create a cluster focused on common issues in data-driven research. Among the ESCAPE work packages, the OSSR (ESCAPE Open-source Scientific Software and Ser

M Hamza Sajjad

Minesweeper is an interesting single player game based on logic, memory and guessing. Solving Minesweeper has been shown to be an NP-hard task. Deterministic solvers are the best known approach for solving Minesweeper. This project proposes a neural network based learner for solving Minesweeper. To choose the best learner, different architectures and configu

Nasr Ahmed, M. Fekry, Tarek M. Kamel

We study the big rip scienario in Swiss-cheese Brane-worlds. The results obtained have been found to be independent of the value of the cosmological constant $\Lambda$ whether its positive, negative or zero. Negative tension branes are not allowed in the current model. There is a sign flipping in cosmic pressure corresponding to the sign flipping in the dece

Frank Alvarez, Yannick Viossat

Some clinical and pre-clinical data suggests that treating some tumors at a mild, patient-specific dose might delay resistance to treatment and increase survival time. A recent mathematical model with sensitive and resistant tumor cells identified conditions under which a treatment aiming at tumor containment rather than eradication is indeed optimal. This m

Esther Cabezas-Rivas, Julian Scheuer

We introduce a mean curvature flow with global term of convex hypersurfaces in the sphere, for which the global term can be chosen to keep any quermassintegral fixed. Then, starting from a strictly convex initial hypersurface, we prove that the flow exists for all times and converges smoothly to a geodesic sphere. This provides a workaround to an issue prese

Rainald Löhner, Harbir Antil

Deep neural network (DNN) architectures are constructed that are the exact equivalent of explicit Runge-Kutta schemes for numerical time integration. The network weights and biases are given, i.e., no training is needed. In this way, the only task left for physics-based integrators is the DNN approximation of the right-hand side. This allows to clearly delin

Yuri Santos Rego, Petra Schwer

In this paper we introduce the galaxy of Coxeter groups -- an infinite dimensional, locally finite, ranked simplicial complex which captures isomorphisms between Coxeter systems. In doing so, we would like to suggest a new framework to study the isomorphism problem for Coxeter groups. We prove some structural results about this space, provide a full characte

Ying Chen, Siwei Qiang, Mingming Ha, Xiaolei Liu

In recent years, semi-supervised graph learning with data augmentation (DA) is currently the most commonly used and best-performing method to enhance model robustness in sparse scenarios with few labeled samples. Differing from homogeneous graph, DA in heterogeneous graph has greater challenges: heterogeneity of information requires DA strategies to effectiv

S. Gwon, P. Granger, G. Yang, S. Bolognesi

Neutrino oscillation experiments require a precise measurement of the neutrino energy. However, the kinematic detection of the final-state neutron in the neutrino interaction is missing in current neutrino oscillation experiments. The missing neutron kinematic detection results in a feed-down of the detected neutrino energy compared to the true neutrino ener

Mieczysław A. Kłopotek

Kleinberg's axioms for distance based clustering proved to be contradictory. Various efforts have been made to overcome this problem. Here we make an attempt to handle the issue by embedding in high-dimensional space and granting wide gaps between clusters.

E. Knudstrup, D. Gandolfi, G. Nowak, C. M. Persson

We report the discovery and confirmation of the planetary system TOI-1288. This late G dwarf harbours two planets: TOI-1288 b and TOI-1288 c. We combine TESS space-borne and ground-based transit photometry with HARPS-N and HIRES high-precision Doppler measurements, which we use to constrain the masses of both planets in the system and the radius of planet b.

Tianyu Wu, Yang Tang

Antimicrobial resistance is one of the biggest health problem, especially in the current period of COVID-19 pandemic. Due to the unique membrane-destruction bactericidal mechanism, antimicrobial peptide-mimetic copolymers are paid more attention and it is urgent to find more potential candidates with broad-spectrum antibacterial efficacy and low toxicity. Ar

C. Wetterich

We propose that a quantum particle in a potential in one space dimension can be described by a probabilistic cellular automaton. While the simple updating rule of the automaton is deterministic, the probabilistic description is introduced by a probability distribution over initial conditions. The proposed automaton involves right- and left-movers, jumping fr

Federico Califano, Ramy Rashad, Cristian Secchi, Stefano Stramigioli

In this document we describe and discuss energy tanks, a control algorithm which has gained popularity inside the robotics and control community over the last years. This article has the threefold scope of i) introducing to the reader the topic in a simple yet precise way, starting with a throughout description of the energy-aware framework, where energy tan

Jann van der Meer, Julius Degünther, Udo Seifert

Irreversibility is commonly quantified by entropy production. An external observer can estimate it through measuring an observable that is antisymmetric under time-reversal like a current. We introduce a general framework that, inter alia, allows us to infer a lower bound on entropy production through measuring the time-resolved statistics of events with any

Zhengyang Duan, Hang Chen, Xing Lin

Photonic neural networks are brain-inspired information processing technology using photons instead of electrons to perform artificial intelligence (AI) tasks. However, existing architectures are designed for a single task but fail to multiplex different tasks in parallel within a single monolithic system due to the task competition that deteriorates the mod

Stefan Scherer, Matthias R. Schindler

Chiral perturbation theory (ChPT) is an effective field theory that describes the properties of strongly-interacting systems at energies far below typical hadron masses. The degrees of freedom are hadrons instead of the underlying quarks and gluons. ChPT is a systematic and model-independent approximation method based on an expansion of amplitudes in terms o

Andrea Eichenseer, André Kaup

In video surveillance as well as automotive applications, so-called fisheye cameras are often employed to capture a very wide angle of view. As such cameras depend on projections quite different from the classical perspective projection, the resulting fisheye image and video data correspondingly exhibits non-rectilinear image characteristics. Typical image a

Shaohua Fan, Shuyang Zhang, Xiao Wang, Chuan Shi

Estimating the structure of directed acyclic graphs (DAGs) of features (variables) plays a vital role in revealing the latent data generation process and providing causal insights in various applications. Although there have been many studies on structure learning with various types of data, the structure learning on the dynamic graph has not been explored y

Mingyu Huang, Ji Guan, Wang Fang, Mingsheng Ying

Simulating noisy quantum circuits is vital in designing and verifying quantum algorithms in the current NISQ (Noisy Intermediate-Scale Quantum) era, where quantum noise is unavoidable. However, it is much more inefficient than the classical counterpart because of the quantum state explosion problem (the dimension of state space is exponential in the number o

Yanan Li, Huichao Wang, Jingyue Wang, Chunming Wang

Extensive studies of electron transport in Dirac materials have shown positive magneto-resistance (MR) and positive magneto-thermopower (MTP) in a magnetic field perpendicular to the excitation current or thermal gradient. In contrast, measurements of electron transport often show a negative longitudinal MR and negative MTP for a magnetic field oriented alon

Griselda Deelstra, Lech A. Grzelak, Felix L. Wolf

Exposure simulations are fundamental to many xVA calculations and are a nested expectation problem where repeated portfolio valuations create a significant computational expense. Sensitivity calculations which require shocked and unshocked valuations in bump-and-revalue schemes exacerbate the computational load. A known reduction of the portfolio valuation c

Ogun Yurdakul, Feng Qiu, Sahin Albayrak

To take unit commitment (UC) decisions under uncertain net load, most studies utilize a stochastic UC (SUC) model that adopts a one-size-fits-all representation of uncertainty. Disregarding contextual information such as weather forecasts and temporal information, these models are typically plagued by a poor out-of-sample performance. To effectively exploit

Rutger A. Biezemans, Claude Le Bris, Frédéric Legoll, Alexei Lozinski

Multiscale Finite Element Methods (MsFEMs) are now well-established finite element type approaches dedicated to multiscale problems. They first compute local, oscillatory, problem-dependent basis functions that generate a suitable discretization space, and next perform a Galerkin approximation of the problem on that space. We investigate here how these appro

Dor Elboim, Allan Sly

In the interchange process on a graph $G=(V,E)$, distinguished particles are placed on the vertices of $G$ with independent Poisson clocks on the edges. When the clock of an edge rings, the two particles on the two sides of the edge interchange. In this way, a random permutation $\pi_\beta:V\to V$ is formed for any time $\beta >0$. One of the main objects of

Shiqi Yang, Kaiwen Xue, Minen Lv, Yingtai Xu

Multi-modal robots expand their operations from one working medium to another, land to air for example. The majorities of multi-modal robots mainly refer to platforms that operate in two different media. However, for all-terrain tasks, there are seldom research to date in the literature. Generally, locomotions in different working media, i.e. land, water and

Elisa Prandini, Konstantinos Dialektopoulos, Jelena Strišković

Gamma rays constitute a privileged point of view for the study of the extreme Universe. Unlike charged cosmic rays, which are thought to have a common origin, gamma rays are not deflected by galactic and intergalactic magnetic fields. This offers the opportunity to unveil the most powerful particle accelerators, still largely unknown, once modifications in t

Michael F. Staddon, Arthur Hernandez, Mark J. Bowick, Michael Moshe

The vertex model of epithelia describes the apical surface of a tissue as a tiling of polygonal cells, with a mechanical energy governed by deviations in cell shape from preferred, or target, area, $A_0$, and perimeter, $P_0$. The model exhibits a rigidity transition driven by geometric incompatibility as tuned by the target shape index, $p_0 = P_0 / \sqrt{A

Foram P Shingala, Natarajan Venkatachalam, Selvagangai C, Hema Priya S

Key Distillation is an essential component of every Quantum Key Distribution system because it compensates the inherent transmission errors of quantum channel. However, throughput and interoperability aspects of post-processing engine design often neglected, and exiting solutions are not providing any guarantee. In this paper, we propose multiple protocol su

Yassine Kamri, Julien M. Hendrickx, François Glineur

We propose a unifying framework for the automated computer-assisted worst-case analysis of cyclic block coordinate algorithms in the unconstrained smooth convex optimization setup. We compute exact worst-case bounds for the cyclic coordinate descent and the alternating minimization algorithms over the class of smooth convex functions, and provide sublinear u

Ionel Ciuperca, Laurent Pujo-Menjouet, Leon Matar-Tine, Nicolas Torres

We introduce and study a new model for the progression of Alzheimer's disease incorporating the interactions of A$\beta$-monomers, oligomers, microglial cells and interleukins with neurons through different mechanisms such as protein polymerization, inflammation processes and neural stress reactions. In order to understand the complete interactions between t

Dominic Breit, Alan Dodgson

We consider the 3D stochastic Navier-Stokes equation on the torus. Our main result concerns the temporal and spatio-temporal discretisation of a local strong pathwise solution. We prove optimal convergence rates in for the energy error with respect to convergence in probability, that is convergence of order 1 in space and of order (up to) 1/2 in time. The re

William Detmold, Anthony V. Grebe, Issaku Kanamori, C. -J. David Lin

The pion light-cone distribution amplitude (LCDA) is a central non-perturbative object of interest for the calculation of high-energy exclusive processes in quantum chromodynamics. This article describes the progress in the lattice QCD calculation of the fourth Mellin moment of the pion LCDA using a heavy-quark operator product expansion (HOPE).

Robin Y. Engel, Oliver Alexander, Kaan Atak, Uwe Bovensiepen

The pulse intensity from X-ray free-electron lasers (FELs) can create extreme excitation densities in solids, entering the regime of non-linear X-ray-matter interactions. We show L3-edge absorption spectra of metallic nickel thin films with fluences entering a regime where several X-ray photons are incident per absorption cross-section. Main features of the

Adel Messaoudi, Regis Cottereau, Christophe Gomez

This paper concerns the derivation of radiative transfer equations for acoustic waves propagating in a randomly fluctuating half-space in the weak-scattering regime, and the study of boundary effects through an asymptotic analysis of the Wigner transform of the wave solution. These radiative transfer equations allow to model the transport of wave energy dens

Virgile Tapiero

We study the dynamical properties of endomorphisms $f$ of $\mathbb{P}^k$ of algebraic degree $d \geq 2$. We investigate the relationships between the Green current $T$ of $f$, the equilibrium measure $\mu = T^k$, and the Lyapunov exponents $\lambda\_1 \geq \cdots \geq \lambda\_k$ of $\mu$. The latter are bounded below by $\frac{1}{2} \mathrm{Log} \ d$. Dujar

Lokman Abbas-Turki, Stéphane Crépey, Bouazza Saadeddine

We consider the computation by simulation and neural net regression of conditional expectations, or more general elicitable statistics, of functionals of processes $(X, Y )$. Here an exogenous component $Y$ (Markov by itself) is time-consuming to simulate, while the endogenous component $X$ (jointly Markov with $Y$) is quick to simulate given $Y$, but is res

Debarshi Basu, Qiang Wen, Shangjie Zhou

In this paper we propose a mechanism to generate entanglement islands in quantum systems from a purely quantum information perspective. More explicitly we show that, if we impose certain constraints on a quantum system by projecting out certain states in the Hilbert space, it is possible that for all the states remaining in the reduced Hilbert space, there e