November 2022 arXiv papers — page 148

Pip Petersen, Yashar Akrami, Craig J. Copi, Andrew H. Jaffe

The Einstein field equations of general relativity constrain the local curvature at every point in spacetime, but say nothing about the global topology of the Universe. Cosmic microwave background anisotropies have proven to be the most powerful probe of non-trivial topology since, within $\Lambda$CDM, these anisotropies have well-characterized statistical p

Majda Smole, João Rino-Silvestre, Santiago González-Gaitán, Marko Stalevski

Aims. Monte Carlo Radiative Transfer (MCRT) simulations are a powerful tool for understanding the role of dust in astrophysical systems and its influence on observations. However, due to the strong coupling of the radiation field and medium across the whole computational domain, the problem is non-local and non-linear and such simulations are computationally

Rimsha Babar, Muhammad Asgher, Riasat Ali

In this paper, we analyze the rotating Einstein-non-linear-Maxwell-Yukawa black hole solution by Janis-Newman algorithmic rule and complex calculations. We investigate the basic properties (i.e., Hawking radiation) for the corresponding black hole solution. From the horizon structure of the black hole, we discuss the graphical behavior of Hawking temperature

Eddie Pei, Ernest Fokoue

This paper computationally demonstrates a sharp improvement in predictive performance for $k$ nearest neighbors thanks to an efficient forward selection of the predictor variables. We show both simulated and real-world data that this novel repeatedly approaches outperformance regression models under stepwise selection

Olga Arroyo-Gascón, Ricardo Fernández-Perea, Eric Suárez Morell, Carlos Cabrillo

We report the existence of moir\'e patterns and magic angle physics in all families of chiral collapsed carbon nanotubes. A detailed study of the electronic structure of all types of chiral nanotubes, previously collapsed via molecular dynamics, has been performed. We find that each family possesses a unique geometry and moir\'e disposition, as well as a cha

Paolo Gibertini, Luca Fehlings, Suzanne Lancaster, Quang Duong

Event-based neuromorphic systems provide a low-power solution by using artificial neurons and synapses to process data asynchronously in the form of spikes. Ferroelectric Tunnel Junctions (FTJs) are ultra low-power memory devices and are well-suited to be integrated in these systems. Here, we present a hybrid FTJ-CMOS Integrate-and-Fire neuron which constitu

Alan Kuntz, Maxwell Emerson, Tayfun Efe Ertop, Inbar Fried

The use of needles to access sites within organs is fundamental to many interventional medical procedures both for diagnosis and treatment. Safe and accurate navigation of a needle through living tissue to an intra-tissue target is currently often challenging or infeasible due to the presence of anatomical obstacles in the tissue, high levels of uncertainty,

Amarendra K. Sarma, Sampreet Kalita

Exploring quantum physics in macroscopic systems and manipulating these systems for various technological applications has been a topic of intense research in the last one decade or so. In this regard, the field of cavity quantum optomechanics turns out to be one of the most rapidly emerging area of research. It has opened many doors to study various open en

Wenkui Du, Jingze Zhu

We study ancient mean curvature flows in $\mathbb{R}^{n+1}$ whose tangent flow at $-\infty$ is a shrinking cylinder $\mathbb{R}^{k}\times S^{n-k}(\sqrt{2(n-k)|t|})$, where $1\leq k\leq n-1$. We prove that the cylindrical profile function $u$ of these flows have the asymptotics $u(y,\omega,\tau)= (y^\top Qy -2\textrm{tr}(Q))/|\tau| + o(|\tau|^{-1})$ as $\tau\

Dorothee D. Haroske, Leszek Skrzypczak

We study nuclear embeddings for spaces of Morrey type, both in its sequence space version and as smoothness spaces of functions defined on a bounded domain $\Omega \subset {\mathbb R}^d$. This covers, in particular, the meanwhile well-known and completely answered situation for spaces of Besov and Triebel-Lizorkin type defined on bounded domains which has be

Lorenzo Bertini, Davide Gabrielli, Claudio Landim

We consider a diffusion process on $\mathbb R^n$ and prove a large deviation principle for the empirical process in the joint limit in which the time window diverges and the noise vanishes. The corresponding rate function is given by the expectation of the Freidlin-Wentzell functional per unit of time. As an application of this result, we obtain a variationa

Anh Nguyen, Galen Pogoncheff, Ban Xuan Dong, Nam Bui

Various intervention therapies ranging from pharmaceutical to hi-tech tailored solutions have been available to treat difficulty in falling asleep commonly caused by insomnia in modern life. However, current techniques largely remain ill-suited, ineffective, and unreliable due to their lack of precise real-time sleep tracking, in-time feedback on the therapi

Marta Bilkova

We prove the uniform interpolation theorem in modal provability logics GL and Grz by a proof-theoretical method, using analytical and terminating sequent calculi for the logics. The calculus for G\"odel-L\"ob's logic GL is a variant of the standard sequent calculus, in the case of Grzegorczyk's logic Grz, the calculus implements an explicit loop-preventing m

Samuel R. Bowman, Jeeyoon Hyun, Ethan Perez, Edwin Chen

Developing safe and useful general-purpose AI systems will require us to make progress on scalable oversight: the problem of supervising systems that potentially outperform us on most skills relevant to the task at hand. Empirical work on this problem is not straightforward, since we do not yet have systems that broadly exceed our abilities. This paper discu

Marin Biloš, Kashif Rasul, Anderson Schneider, Yuriy Nevmyvaka

Temporal data such as time series can be viewed as discretized measurements of the underlying function. To build a generative model for such data we have to model the stochastic process that governs it. We propose a solution by defining the denoising diffusion model in the function space which also allows us to naturally handle irregularly-sampled observatio

Martin J. Falk, Finnegan D. Roach, William Gilpin, Arvind Murugan

Exploring the spectrum of novel behaviors a physical system can produce can be a labor-intensive task. Active learning is a collection of iterative sampling techniques developed in response to this challenge. However, these techniques often require a pre-defined metric, such as distance in a space of known order parameters, in order to guide the search for n

Christian Elsholtz, Benjamin Klahn, Gabriel F. Lipnik

For integers $m$ and $n$, we study the problem of finding good lower bounds for the size of progression-free sets in $(\mathbb{Z}_{m}^{n},+)$. Let $r_{k}(\mathbb{Z}_{m}^{n})$ denote the maximal size of a subset of $\mathbb{Z}_{m}^{n}$ without arithmetic progressions of length $k$ and let $P^{-}(m)$ denote the least prime factor of $m$. We construct explicit

Vincent Bouillaut, Benoît Flesselles, Benjamin Miquel, Sébastien Aumaître

Three-dimensional convection driven by internal heat sources and sinks (CISS) leads to experimental and numerical scaling-laws compatible with a mixing-length - or `ultimate' - scaling regime $Nu \sim \sqrt{Ra}$. However, asymptotic analytic solutions and idealized 2D simulations have shown that laminar flow solutions can transport heat even more efficiently

Keisuke Inomata, Matteo Braglia, Xingang Chen, Sébastien Renaux-Petel

Inflationary models predicting a scale-dependent large amplification of the density perturbations have recently attracted a lot of attention because the amplified perturbations can seed a sizable amount of primordial black holes (PBHs) and stochastic background of gravitational waves (GWs). While the power spectra in these models are computed based on the li

M. Saef Ullah Miah, Junaida Sulaiman

The scientific literature contains a wealth of cutting-edge knowledge in the field of materials science, as well as useful data (e.g., numerical data from experimental results, material properties and structure). These data are critical for data-driven machine learning (ML) and deep learning (DL) methods to accelerate material discovery. Due to the large and

Leeseok Kim, Seth Lloyd, Milad Marvian

We propose Hamiltonian Quantum Generative Adversarial Networks (HQuGANs), to learn to generate unknown input quantum states using two competing quantum optimal controls. The game-theoretic framework of the algorithm is inspired by the success of classical generative adversarial networks in learning high-dimensional distributions. The quantum optimal control

Cassien Habyarimana, Jane A. Aduda, Enrico Scalas, Jing Chen

We characterize a Hawkes point process with kernel proportional to the probability density function of Mittag-Leffler random variables. This kernel decays as a power law with exponent $\beta +1 \in (1,2]$. Several analytical results can be proved, in particular for the expected intensity of the point process and for the expected number of events of the count

Mirko Armillotta, Michail Tsagris, Konstantinos Fokianos

We introduce a new R package useful for inference about network count time series. Such data are frequently encountered in statistics and they are usually treated as multivariate time series. Their statistical analysis is based on linear or log linear models. Nonlinear models, which have been applied successfully in several research areas, have been neglecte

M. Nilton, G. Alencar, R. N. Costa Filho

In this paper, we study black strings in asymptotic safety gravity (ASG) scenario. The ASG approach is introduced by implementing gravitational and cosmological running coupling constants directly in the black string metric. We calculate the Hawking temperature, entropy, and heat capacity of the improved black string metric in two cases: considering the cosm

David Wan, Mohit Bansal

Current metrics for evaluating factuality for abstractive document summarization have achieved high correlations with human judgment, but they do not account for the vision modality and thus are not adequate for vision-and-language summarization. We propose CLIPBERTScore, a simple weighted combination of CLIPScore and BERTScore to leverage the robustness and

Jean-Philippe Monteuuis, Jonathan Petit, Mohammad Raashid Ansari, Cong Chen

Connected and Automated Vehicles (CAV) use sensors and wireless communication to improve road safety and efficiency. However, attackers may target Vehicle-to-Everything (V2X) communication. Indeed, an attacker may send authenticated-but-wrong data to send false location information, alert incorrect events, or report a bogus object endangering safety of other

Luis Oala, Marco Aversa, Gabriel Nobis, Kurt Willis

Camera images are ubiquitous in machine learning research. They also play a central role in the delivery of important services spanning medicine and environmental surveying. However, the application of machine learning models in these domains has been limited because of robustness concerns. A primary failure mode are performance drops due to differences betw

Yuchen Liu, Li-Chia Yang, Alex Pawlicki, Marko Stamenovic

Speech quality assessment has been a critical component in many voice communication related applications such as telephony and online conferencing. Traditional intrusive speech quality assessment requires the clean reference of the degraded utterance to provide an accurate quality measurement. This requirement limits the usability of these methods in real-wo

Shaul Barkan, Jan Steinebrunner

We define a notion of $\infty$-properads that generalises $\infty$-operads by allowing operations with multiple outputs. Specializing to the case where each operation has a single output provides a simple new perspective on $\infty$-operads, but at the same time the extra generality allows for examples such as bordism categories. We also give an interpretati

Gianmichele Blasi, Géraldine Haack, Vittorio Giovannetti, Fabio Taddei

Robust and tunable topological Josephson junctions (TJJs) are highly desirable platforms for investigating the anomalous Josephson effect and topological quantum computation applications. Experimental demonstrations have been done in hybrid superconducting-two dimensional topological insulator (2DTI) platforms, sensitive to magnetic disorder and interactions

Guangxu Zhu, Zhonghao Lyu, Xiang Jiao, Peixi Liu

Pushing artificial intelligence (AI) from central cloud to network edge has reached board consensus in both industry and academia for materializing the vision of artificial intelligence of things (AIoT) in the sixth-generation (6G) era. This gives rise to an emerging research area known as edge intelligence, which concerns the distillation of human-like inte

Andrea Marini

In model Hamiltonians, like Fr\"ohlich's, the electron-phonon interaction is assumed to be screened from the beginning. The same occurs when this interaction is obtained by using the state-of-the-art density functional perturbation theory as starting point. In this work I formally demonstrate that these approaches are affected by a severe over-screening erro

Pau Varela, Pol Suárez, Francisco Alcántara-Ávila, Arnau Miró

Deep artificial neural networks (ANNs) used together with deep reinforcement learning (DRL) are receiving growing attention due to their capabilities to control complex problems. This technique has been recently used to solve problems related to flow control. In this work, an ANN trained through a DRL agent is used to perform active flow control. Two-dimensi

David Stenger, Dirk Abel

Controller tuning based on black-box optimization allows to automatically tune performance-critical parameters w.r.t. mostly arbitrary high-level closed-loop control objectives. However, a comprehensive benchmark of different black-box optimizers for control engineering problems has not yet been conducted. Therefore, in this contribution, 11 different versio

Barbara Plank

Human variation in labeling is often considered noise. Annotation projects for machine learning (ML) aim at minimizing human label variation, with the assumption to maximize data quality and in turn optimize and maximize machine learning metrics. However, this conventional practice assumes that there exists a ground truth, and neglects that there exists genu

F. Regnault, A. Strugarek, M. Janvier, F. Auchère

Interplanetary Coronal Mass Ejections (ICMEs) originate from the eruption of complex magnetic structures occurring in our star's atmosphere. Determining the general properties of ICMEs and the physical processes at the heart of their interactions with the solar wind is a hard task, in particular using only unidimensional in situ profiles. Thus, these phenome

Carlos Ramos-Carreño, José Luis Torrecilla, Miguel Carbajo-Berrocal, Pablo Marcos

The library scikit-fda is a Python package for Functional Data Analysis (FDA). It provides a comprehensive set of tools for representation, preprocessing, and exploratory analysis of functional data. The library is built upon and integrated in Python's scientific ecosystem. In particular, it conforms to the scikit-learn application programming interface so a

I-Kang Liu, Nick P. Proukakis, Gerasimos Rigopoulos

We show that fuzzy dark matter halos exhibit spatial differentiation in the degree of coherence of the field configuration, ranging from completely coherent in the central solitonic core to incoherent outside it, with a crossover region in between the two phases. The solitonic core is indeed a pure condensate which overlaps almost perfectly with the Penrose-

M. Lyatti, I. Kraiem, T. Röper, I. Gundareva

We fabricate high-quality c-axis oriented epitaxial YBa$_2$Cu$_3$O$_{7-x}$ films with 15% of yttrium atoms replaced by terbium (YTBCO) and study their electrical properties. The Tb substitution reduces the charge carrier density resulting in increased resistivity and decreased critical current density compared to the pure YBa$_2$Cu$_3$O$_{7-x}$ films. The el

Yasmen Wahba, Nazim Madhavji, John Steinbacher

The emergence of pre-trained language models (PLMs) has shown great success in many Natural Language Processing (NLP) tasks including text classification. Due to the minimal to no feature engineering required when using these models, PLMs are becoming the de facto choice for any NLP task. However, for domain-specific corpora (e.g., financial, legal, and indu

Richard Löscher, Olaf Steinbach

We consider space-time tracking type distributed optimal control problems for the wave equation in the space-time domain $Q:= \Omega \times (0,T) \subset {\mathbb{R}}^{n+1}$, where the control is assumed to be in the energy space $[H_{0;,0}^{1,1}(Q)]^*$, rather than in $L^2(Q)$ which is more common. While the latter ensures a unique state in the Sobolev spac

Satoru Fujishige, Tomonari Kitahara, László A. Végh

We consider the minimum-norm-point (MNP) problem over polyhedra, a well-studied problem that encompasses linear programming. We present a general algorithmic framework that combines two fundamental approaches for this problem: active set methods and first order methods. Our algorithm performs first order update steps, followed by iterations that aim to `stab

Hainan Xu, Fei Jia, Somshubra Majumdar, Shinji Watanabe

This paper proposes a modification to RNN-Transducer (RNN-T) models for automatic speech recognition (ASR). In standard RNN-T, the emission of a blank symbol consumes exactly one input frame; in our proposed method, we introduce additional blank symbols, which consume two or more input frames when emitted. We refer to the added symbols as big blanks, and the

E. Knill

A few conventions for thinking about and writing quantum pseudocode are proposed. The conventions can be used for presenting any quantum algorithm down to the lowest level and are consistent with a quantum random access machine (QRAM) model for quantum computing. In principle a formal version of quantum pseudocode could be used in a future extension of a con

F. Crocetti, G. Costante, M. L. Fravolini, P. Valigi

The performances of braking control systems for robotic platforms, e.g., assisted and autonomous vehicles, airplanes and drones, are deeply influenced by the road-tire friction experienced during the maneuver. Therefore, the availability of accurate estimation algorithms is of major importance in the development of advanced control schemes. The focus of this

Suman Banerjee, Rajesh Kumar Yadav, Avinash Khare, Nisha Kumari

We consider $1+1$-dimensional Dirac equation with rationally extended scalar potentials corresponding to the radial oscillator, the trigonometric Scarf and the hyperbolic Poschl-Teller potentials and obtain their solution in terms of exceptional orthogonal polynomials. Further, in the case of the trigonometric Scarf and the hyperbolic Poschl-Teller cases, ne

J. Okołowicz, M. Płoszajczak, W. Nazarewicz

The nucleus 11C plays an important role in the boron-proton fusion reactor environment as a catalyzer of the 10B(p,{\alpha})7Be reaction which, by producing a long-lived isotope of 7Be, poisons the aneutronic fusion process 11B(p,2{\alpha})4He. The low-energy cross section of 10B(p,{\alpha})7Be depends on the near-threshold states 7/2+1 , 5/2+2 , 5/2+3 in 11

Cristiano Capone, Cosimo Lupo, Paolo Muratore, Pier Stanislao Paolucci

The brain can efficiently learn a wide range of tasks, motivating the search for biologically inspired learning rules for improving current artificial intelligence technology. Most biological models are composed of point neurons, and cannot achieve the state-of-the-art performances in machine learning. Recent works have proposed that segregation of dendritic

Samuel Pawel, Guido Consonni, Leonhard Held

Replication studies are essential for assessing the credibility of claims from original studies. A critical aspect of designing replication studies is determining their sample size; a too small sample size may lead to inconclusive studies whereas a too large sample size may waste resources that could be allocated better in other studies. Here, we show how Ba

S. Giraud, J. C. Zamora, R. G. T. Zegers, Y. Ayyad

Charge-exchange $(d,{}^{2}\text{He})$ reactions in inverse kinematics at intermediate energies are a very promising method to investigate the Gamow-Teller transition strength in unstable nuclei. A simulation and analysis software based on the $\rm{\scriptsize ATTPCROOT}$ package was developed to study these type of reactions with the active-target time proje

George Spahn, Doron Zeilberger

Given positive integers $r$ and $s$, we use inclusion-exclusion, weighted-counting of tilings, and dynamical programming, in order to enumerate, semi-efficiently, the classes of permutations mentioned in the title. In the process we revisit beautiful previous work of Enrique Navarrete, Robert Tauraso, David Robbins (to whose memory this article is dedicated)

Cheyne Glass, Micah Miller, Thomas Tradler, Mahmoud Zeinalian

Coherent sheaves on general complex manifolds do not necessarily have resolutions by finite complexes of vector bundles. However D. Toledo and Y.L.L. Tong showed that one can resolve coherent sheaves by objects analogous to chain complexes of holomorphic vector bundles, whose cocycle relations are governed by a coherent infinite system of homotopies. In the

Dirk Frettlöh, Alexey Garber, Neil Mañibo

In this work, we consider a class of substitutions on infinite alphabets and show that they exhibit a growth behaviour which is impossible for substitutions on finite alphabets. While for both settings the leading term of the tile counting function is exponential (and guided by the inflation factor), the behaviour of the second-order term is strikingly diffe

F. Murgas, G. Nowak, T. Masseron, H. Parviainen

We used TESS light curves and HARPS-N spectrograph radial velocity measurements to establish the physical properties of the transiting exoplanet candidate found around the star HD 20329 (TOI-4524). We performed a joint fit of the light curves and radial velocity time series to measure the mass, radius, and orbital parameters of the candidate. We confirm and

James E. Titus-McQuillan, Adalena V. Nanni, Lauren M. McIntyre, Rebekah L. Rogers

Genomic complexity is a growing field of evolution, with case studies for comparative evolutionary analyses in model and emerging non-model systems. Understanding complexity and the functional components of the genome is an untapped wealth of knowledge ripe for exploration. With the "remarkable lack of correspondence" between genome size and complexity, ther

Rishabh Jain, Gabriele Ciravegna, Pietro Barbiero, Francesco Giannini

Recently, Logic Explained Networks (LENs) have been proposed as explainable-by-design neural models providing logic explanations for their predictions. However, these models have only been applied to vision and tabular data, and they mostly favour the generation of global explanations, while local ones tend to be noisy and verbose. For these reasons, we prop

Alexander Cui, Sergio Casas, Kelvin Wong, Simon Suo

The task of motion forecasting is critical for self-driving vehicles (SDVs) to be able to plan a safe maneuver. Towards this goal, modern approaches reason about the map, the agents' past trajectories and their interactions in order to produce accurate forecasts. The predominant approach has been to encode the map and other agents in the reference frame of e

Joseph Ben Geloun, Sanjaye Ramgoolam

Bi-partite ribbon graphs arise in organising the large $N$ expansion of correlators in random matrix models and in the enumeration of observables in random tensor models. There is an algebra $\mathcal{K}(n)$, with basis given by bi-partite ribbon graphs with $n$ edges, which is useful in the applications to matrix and tensor models. The algebra $\mathcal{K}(

Yiyao Liu, Zhen-Yu Wang

Shortcuts to adiabaticity (STA) are fast methods to realize the same final state evolution of quantum adiabatic process. We develop a general theory to construct a new kind of STA by solely sampling the points of the adiabatic path of the original adiabatic Hamiltonian. In contrast to previous methods, our approach does not require any additional control res

Bryce Irvin, Marko Stamenovic, Mikolaj Kegler, Li-Chia Yang

Modern speech enhancement (SE) networks typically implement noise suppression through time-frequency masking, latent representation masking, or discriminative signal prediction. In contrast, some recent works explore SE via generative speech synthesis, where the system's output is synthesized by a neural vocoder after an inherently lossy feature-denoising st

Ziyao Wang, Lujin Guan, Guanyu Liu

In order to test whether artificial intelligence can create qualified classical poetry like humans, the author proposes a study of Chinese classical poetry generation based on a pre-trained model. This paper mainly tries to use BART and other pre training models, proposes FS2TEXT and RR2TEXT to generate metrical poetry text and even specific style poetry tex

Niranjan Balachandran, Srimanta Bhattacharya, Krishn Vishwas Kher, Rogers Mathew

For a set $L$ of positive proper fractions and a positive integer $r \geq 2$, a fractional $r$-closed $L$-intersecting family is a collection $\mathcal{F} \subset \mathcal{P}([n])$ with the property that for any $2 \leq t \leq r$ and $A_1, \dotsc, A_t \in \mathcal{F}$ there exists $\theta \in L$ such that $\lvert A_1 \cap \dotsb \cap A_t \rvert \in \{ \theta

Dam Quang Nam, Yves Lemiere, Antoine Petiteau, Jean-Baptiste Bayle

The LISA mission is the future space-based gravitational wave (GW) observatory of the European Space Agency. It is formed by 3 spacecraft exchanging laser beams in order to form multiple real and virtual interferometers. The data streams to be used in order to extract the large number and variety of GW sources are Time-Delay Interferometry (TDI) data. One im

Xiuzhen Ye, Iñaki Esnaola, Samir M. Perlaza, Robert F. Harrison

A novel metric that describes the vulnerability of the measurements in power systems to data integrity attacks is proposed. The new metric, coined vulnerability index (VuIx), leverages information theoretic measures to assess the attack effect on the fundamental limits of the disruption and detection tradeoff. The result of computing the VuIx of the measurem

Yuefan Wu, Zeyuan Chen, Shaowei Liu, Zhongzheng Ren

Recovering the skeletal shape of an animal from a monocular video is a longstanding challenge. Prevailing animal reconstruction methods often adopt a control-point driven animation model and optimize bone transforms individually without considering skeletal topology, yielding unsatisfactory shape and articulation. In contrast, humans can easily infer the art

Nicholas Pellegrino, Zahra Gharaee, Paul Fieguth

The BIOSCAN project, led by the International Barcode of Life Consortium, seeks to study changes in biodiversity on a global scale. One component of the project is focused on studying the species interaction and dynamics of all insects. In addition to genetically barcoding insects, over 1.5 million images per year will be collected, each needing taxonomic cl

Florian L. Kreyssig, Yangyang Shi, Jinxi Guo, Leda Sari

Self-supervised learning via masked prediction pre-training (MPPT) has shown impressive performance on a range of speech-processing tasks. This paper proposes a method to bias self-supervised learning towards a specific task. The core idea is to slightly finetune the model that is used to obtain the target sequence. This leads to better performance and a sub

Jordi Cortés Martinez, Marta Bofill Roig, Guadalupe Gómez Melis

Composite endpoints are widely used as primary endpoints in clinical trials. Designing trials with time-to-event endpoints can be particularly challenging because the proportional hazard assumption usually does not hold when using a composite endpoint, even when the premise remains true for their components. Consequently, the conventional formulae for sample

Marcin Szyniszewski, Oliver Lunt, Arijeet Pal

Scrambling of quantum information in unitary evolution can be hindered due to measurements and localization, which pin quantum mechanical wavefunctions in real space suppressing entanglement in the steady state. In monitored free-fermionic models, the steady state undergoes an entanglement transition from a logarithmically entangled critical state to area-la

Wenting Ye, Hongfei Yang, Shuai Zhao, Haoyang Fang

The substitute-based recommendation is widely used in E-commerce to provide better alternatives to customers. However, existing research typically uses the customer behavior signals like co-view and view-but-purchase-another to capture the substitute relationship. Despite its intuitive soundness, we find that such an approach might ignore the functionality a

Jongchul Park, Matthieu Davy, Victor A. Gopar, Azriel Z. Genack

The statistics of transmission through random 1D media are generally presumed to be universal and to depend only upon a single dimensionless parameter-the ratio of the sample length and the mean free path, s = L/l. Here, we show in numerical simulations and optical measurements of random binary systems, and most prominently in systems for which s is less tha

Raghavendra N. Bhat, Sundarraman Madhusudanan

We defined numbers of the form $p\cdot a^2$ as SP numbers (Square-Prime numbers) ($a\neq1$, $p$ prime) in the paper 'Distribution of Square-Prime numbers' (arXiv:2109.10238) along with proofs on their distribution. Some examples of SP Numbers : 75 = 3 $\cdot$ 25; 108 = 3 $\cdot$ 36; 45 = 5 $\cdot$ 9. These numbers are listed in the OEIS as A228056. In this p

Suman Jyoti De, Ankur Das, Sumathi Rao, Ribhu K. Kaul

Monolayer graphene at charge neutrality in a quantizing magnetic field is a quantum Hall ferromagnet. Due to the spin and valley (near) degeneracies, there is a plethora of possible ground states. Previous theoretical work, based on a stringent ultra short-range assumption on the symmetry-allowed interactions, predicts a phase diagram with distinct regions o

Hossein Dabirian, Radmir Sultamuratov, James Herring, Carlos El Tallawi

Let $\mathcal{D}$ be a dataset of smooth 3D-surfaces, partitioned into disjoint classes $\mathit{CL}_j$, $j= 1, \ldots, k$. We show how optimized diffeomorphic registration applied to large numbers of pairs $S,S' \in \mathcal{D}$ can provide descriptive feature vectors to implement automatic classification on $\mathcal{D}$, and generate classifiers invariant

Ville Cantory, Nathan Ringo

Virtual Reality systems provide many opportunities for scientific research and consumer enjoyment; however, they are more demanding than traditional desktop applications and require a wired connection to desktops in order to enjoy maximum quality. Standalone options that are not connected to computers exist, yet they are powered by mobile GPUs, which provide

Aleksandar Mijatović, Romain Palfray

This paper develops a novel weak multilevel Monte-Carlo (MLMC) approximation scheme for L\'evy-driven Stochastic Differential Equations (SDEs). The scheme is based on the state space discretization (via a continuous-time Markov chain approximation) of the pure-jump component of the driving L\'evy process and is particularly suited if the multidimensional dri

Hao Yen, François G. Germain, Gordon Wichern, Jonathan Le Roux

Diffusion models have recently shown promising results for difficult enhancement tasks such as the conditional and unconditional restoration of natural images and audio signals. In this work, we explore the possibility of leveraging a recently proposed advanced iterative diffusion model, namely cold diffusion, to recover clean speech signals from noisy signa

Peter S. Shternin, Dmitry D. Ofengeim, Craig O. Heinke, Wynn C. G. Ho

Analysis of Chandra observations of the neutron star (NS) in the centre of the Cassiopeia A supernova remnant taken in the subarray (FAINT) mode of the ACIS detector performed by Posselt and collaborators revealed, after inclusion of the most recent (May 2020) observations, a significant decrease of the source surface temperature from 2006 to 2020. The obtai

Florian Hörsch, Zoltán Szigeti

We say that a tree $T$ is an $S$-Steiner tree if $S \subseteq V(T)$ and a hypergraph is an $S$-Steiner hypertree if it can be trimmed to an $S$-Steiner tree. We prove that it is NP-complete to decide, given a hypergraph $\mathcal{H}$ and some $S \subseteq V(\mathcal{H})$, whether there is a subhypergraph of $\mathcal{H}$ which is an $S$-Steiner hypertree. As

Takuji Tachibana, Kazuki Sawada, Hiroyuki Fujii, Ryo Maruyama

We constructed an open multi-access network platform using open-source hardware and software. The open multi-access network platform is characterized by the flexible utilization of network functions, integral management and control of wired and wireless access networks, zero-touch provisioning, intelligent resource monitoring, and dynamic task offloading. We

Divya Nori, Connor W. Coley, Rocío Mercado

PROteolysis TArgeting Chimeras (PROTACs) are an emerging therapeutic modality for degrading a protein of interest (POI) by marking it for degradation by the proteasome. Recent developments in artificial intelligence (AI) suggest that deep generative models can assist with the de novo design of molecules with desired properties, and their application to PROTA

N. Zen

Recently, the room-temperature superconductor (RTSC) was discovered as a two-dimensional (2D) square lattice made of a metal wherein positive charges, i.e. holes, were heavily concentrated. The experimental result for the critical magnetic field $H_{c}$ was fully consistent with the view on the RTSC that its lattice unit -- a metal island -- is filled with t

Ximena Fernández, Diego Mateos

Real time seizure detection is a fundamental problem in computational neuroscience towards diagnosis and treatment's improvement of epileptic disease. We propose a real-time computational method for tracking and detection of epileptic seizures from raw neurophysiological recordings. Our mechanism is based on the topological analysis of the sliding-window emb

Nick Dimou

For a primal-dual pair of conic linear problems that are described by convex cones $S\subset X$, $T\subset Y$, bilinear symmetric objective functions $\langle\cdot,\cdot\rangle_X$, $\langle\cdot,\cdot\rangle_Y$ and a linear operator $A:X\rightarrow Y$, we show that the existence of optimal solutions $x^*\in S$, $y^*\in T$ that satisfy $Ax^*=b$ and $A^Ty^*=c$

Sergio Iguri, Nicolas Kovensky, Julian H. Toro

We consider three-point correlation functions for superstrings propagating in AdS$_3\times S^3 \times T^4$. In the RNS formalism, these generically involve correlators with current insertions. When vertex operators with non-trivial spectral flow charges are present, their complicated OPEs with the currents imply that standard methods can not be used to compu

Emily Roff

Magnitude is a numerical invariant of metric spaces and graphs, analogous, in a precise sense, to Euler characteristic. Magnitude homology is an algebraic invariant constructed to categorify magnitude. Among the important features of the magnitude of graphs is its behaviour with respect to an operation known as the Whitney twist. We give a homological accoun

Arash Afkanpour, Shabir Adeel, Hansenclever Bassani, Arkady Epshteyn

Transformer models have achieved great success across many NLP problems. However, previous studies in automated ICD coding concluded that these models fail to outperform some of the earlier solutions such as CNN-based models. In this paper we challenge this conclusion. We present a simple and scalable method to process long text with the existing transformer

Jacek Dziubański, Agnieszka Hejna

On $\mathbb R^N$ equipped with a root system $R$ and a multiplicity function $k>0$, we study the generalized (Dunkl) translations $\tau_{\mathbf x}g(-\mathbf y)$ of not necessarily radial kernels $g$. Under certain regularity assumptions on $g$, we derive bounds for $\tau_{\mathbf x}g(-\mathbf y)$ by means the Euclidean distance $\|\mathbf x-\mathbf y\|$ and

Gleb A. Egorov, George V. Eleftheriades

Scattering of refracting Huygens' metasurfaces is revisited. A new analytical closed-form solution is obtained for the two-dimensional problem under transverse electric (TE) plane-wave incidence -- a solution which gives the scattering for any (in-plane) angle of incidence and frequency. In the process of obtaining the solution, interesting mathematical conc

Vadim Petruhanov, Alexander Pechen

In this work, we consider a model of two qubits driven by coherent and incoherent time-dependent controls. The dynamics of the system is governed by a Gorini-Kossakowski-Sudarshan-Lindblad master equation, where coherent control enters into the Hamiltonian and incoherent control enters into both the Hamiltonian (via Lamb shift) and the dissipative superopera

Florian Beck, Minh Nhat Vu, Christian Hartl-Nesic, Andreas Kugi

This work proposes a novel singularity avoidance approach for real-time trajectory optimization based on known singular configurations. The focus of this work lies on analyzing kinematically singular configurations for three robots with different kinematic structures, i.e., the Comau Racer 7-1.4, the KUKA LBR iiwa R820, and the Franka Emika Panda, and exploi

Yitang Zhang

Let $\chi$ be a real primitive character to the modulus $D$. It is proved that $$ L(1,\chi)\gg (\log D)^{-2022} $$ where the implied constant is absolute and effectively computable. In the proof, the lower bound for $L(1,\chi)$ is first related to the distribution of zeros of a family of Dirichlet $L$-functions in a certain region, and some results on the ga

Yulia G. Polynskaya, Irina V. Lebedeva, Andrey A. Knizhnik, Andrey M. Popov

Ab initio calculations are performed to study consecutive reconstruction of a zigzag graphene edge. According to the obtained energy profile along the reaction pathway, the first reconstruction step, formation of the first pentagon-heptagon pair, is the slowest one, while the growth of an already nucleated reconstructed edge domain should occur steadily at a

Frits Spieksma, Rudi Pendavingh, Roel Lambers

We investigate a new tournament format that consists of a series of individual knockout tournaments; we call this new format a Serial Knockout Competition (SKC). This format has recently been adopted by the Professional Darts Corporation. Depending on the seedings of the players used for each of the knockout tournaments, players can meet in the various round

Alexei Tsygvintsev

In this paper, we further investigate the planar Newtonian three-body problem with a focus on collinear configurations, where either the three bodies or their velocities are aligned. We provide an independent proof of Montgomery's result, stating that apart from the Lagrange solution, all negative energy solutions to the zero angular momentum case result in

Paolo Caldiroli, Gabriele Cora, Alessandro Iacopetti

We prove existence and nonexistence results for annular type parametric surfaces with prescribed, almost constant mean curvature, characterized as normal graphs of compact portions of unduloids or nodoids in $\mathbb{R}^{3}$, and whose boundary consists of two coaxial circles of the same radius.

L. Ciesla, C. Gómez-Guijarro, V. Buat, D. Elbaz

Recently, a population of compact main sequence (MS) galaxies exhibiting starburst-like properties have been identified in the GOODS-ALMA blind survey at 1.1mm. Several evolution scenarios were proposed to explain their particular physical properties (e.g., compact size, low gas content, short depletion time). In this work, we aim at studying the star format

Kim William Torre, Joost de Graaf

Locally (re)structuring colloidal gels $\unicode{x2013}$ micron-sized particles forming a connected network with arrested dynamics $\unicode{x2013}$ enables precise tuning of the micromechanical and -rheological properties of the system. A recent experimental study [B. Saint-Michel, G. Petekidis, and V. Garbin, Soft Matter $\boldsymbol{18}$, 2092 (2022)] sho

Wenyu Lei, Stefano Piani, Patricio Farrell, Nella Rotundo

In this work we propose a weighted hybridizable discontinuous Galerkin method (W-HDG) for drift-diffusion problems. By using specific exponential weights when computing the $L^2$ product in each cell of the discretization, we are able to mimic the behavior of the Slotboom variables, and eliminate the drift term from the local matrix contributions, while stil

Tobias Fritz, Tomáš Gonda, Nicholas Gauguin Houghton-Larsen, Antonio Lorenzin

We study the positivity and causality axioms for Markov categories as properties of dilations and information flow in Markov categories, and in variations thereof for arbitrary semicartesian monoidal categories. These help us show that being a positive Markov category is merely an additional property of a symmetric monoidal category (rather than extra struct