January 2022 arXiv papers — page 80

Ramon Frey, Bastien F. Grosso, Pascal Fandré, Benjamin Mächler

We report the development of a combined machine-learning and high-throughput density functional theory (DFT) framework to accelerate the search for new ferroelectric materials. The framework can predict potential ferroelectric compounds using only elemental composition as input. A series of machine-learning algorithms initially predict the possible stable an

Ignavier Ng, Yujia Zheng, Jiji Zhang, Kun Zhang

Many of the causal discovery methods rely on the faithfulness assumption to guarantee asymptotic correctness. However, the assumption can be approximately violated in many ways, leading to sub-optimal solutions. Although there is a line of research in Bayesian network structure learning that focuses on weakening the assumption, such as exact search methods w

Ivan Corwin, Percy Deift, Alexander Its

This is a survey of Harold Widom's work in random matrices. We start with his pioneering papers on the sine-kernel determinant, continue with his and Craig Tracy's groundbreaking results concerning the distribution functions of random matrix theory, touch on the remarkable universality of the Tracy-Widom distributions in mathematics and physics, and close wi

Jeffrey Tao, Yiru Chen, Eugene Wu

We demonstrate PI2, the first notebook extension that can automatically generate interactive visualization interfaces during SQL-based analyses.

Lukáš Folwarczný

Feasible interpolation is a general technique for proving proof complexity lower bounds. The monotone version of the technique converts, in its basic variant, lower bounds for monotone Boolean circuits separating two NP-sets to proof complexity lower bounds. In a generalized version of the technique, dag-like communication protocols are used instead of monot

Xiao-Chuan Liu, Fabio Armando Tal

We present a dichotomy for surface homeomorphisms in the isotopy class of the identity. We show that, in the absence of a degenerate fixed point set, either there exists a uniform bound on the diameter of orbits of non-wandering points for the lifted dynamics in the universal covering space, or the map has non-contractible periodic points. We then use this n

Tomislav Begušić, Enrico Tapavicza, Jiří Vaníček

Simulating vibrationally resolved electronic spectra of anharmonic systems, especially those involving double-well potential energy surfaces, often requires expensive quantum dynamics methods. Here, we explore the applicability and limitations of the recently proposed single-Hessian thawed Gaussian approximation for the simulation of spectra of systems with

P. Brás, F. Neves, A. Lindote, A. Cottle

Machine learning techniques are now well established in experimental particle physics, allowing detector data to be analysed in new and unique ways. The identification of signals in particle observatories is an essential data processing task that can potentially be improved using such methods. This paper aims at exploring the benefits that a dedicated machin

Ramon Pires, Fábio C. de Souza, Guilherme Rosa, Roberto A. Lotufo

A typical information extraction pipeline consists of token- or span-level classification models coupled with a series of pre- and post-processing scripts. In a production pipeline, requirements often change, with classes being added and removed, which leads to nontrivial modifications to the source code and the possible introduction of bugs. In this work, w

Yucel Aydin, Gunes K. Kurt, Enver Ozdemir, Halim Yanikomeroglu

Drones are begin used for various purposes such as border security, surveillance, cargo delivery, visual shows and it is not possible to overcome such intensive tasks with a single drone. In order to expedite performing such tasks, drone swarms are employed. The number of drones in a swarm can be high depending on the assigned duty. The current solution to a

Nick Ramsey

Given an SFT $\Sigma$ and a finite set $S$ of finite words, let $\Sigma\langle S\rangle$ denote the subshift of $\Sigma$ that avoids $S$. We establish a general criterion under which we can bound the entropy perturbation $h(\Sigma)-h(\Sigma\langle S\rangle)$ from above. As an application, we prove that this entropy difference tends to zero with a sequence of

Greg Acosta, Andrew Reicks, Miguel Moreno, Alireza Borjali

The radiative response of any object is governed by a surface parameter known as emissivity. Tuning the emissivity of surfaces has been of great interest in many applications involving thermal radiation such as thermophotovoltaics, thermal management systems, and passive radiative cooling. Although several surface engineering techniques (e.g., surface functi

Jaroslav Garvardt, Christian Komusiewicz, Frank Sommer

The s-Club problem asks, for a given undirected graph $G$, whether $G$ contains a vertex set $S$ of size at least $k$ such that $G[S]$, the subgraph of $G$ induced by $S$, has diameter at most $s$. We consider variants of $s$-Club where one additionally demands that each vertex of $G[S]$ is contained in at least $\ell$ triangles in $G[S]$, that each edge of

Srijata Samanta, Kshitij Khare, George Michailidis

The paper addresses joint sparsity selection in the regression coefficient matrix and the error precision (inverse covariance) matrix for high-dimensional multivariate regression models in the Bayesian paradigm. The selected sparsity patterns are crucial to help understand the network of relationships between the predictor and response variables, as well as

Y. M. P. Gomes, M. J. Neves

We propose a model of Majorana fermions with quartic self-couplings. These Majorana fermions acquire masses via a type II seesaw mechanism in which the physical eigenstates are identified as a light Majorana fermion and another heavy Majorana fermion. On a physical basis, the quartic self-couplings involve axial currents of these Majorana fermions, and also

Sujit Roy, Gnaneswara Rao Gorle, Vishal Gaur, Haider Raza

Predicting contextualised engagement in videos is a long-standing problem that has been popularly attempted by exploiting the number of views or the associated likes using different computational methods. The recent decade has seen a boom in online learning resources, and during the pandemic, there has been an exponential rise of online teaching videos witho

John Kalkhof, Camila González, Anirban Mukhopadhyay

Limited amount of labelled training data are a common problem in medical imaging. This makes it difficult to train a well-generalised model and therefore often leads to failure in unknown domains. Hippocampus segmentation from magnetic resonance imaging (MRI) scans is critical for the diagnosis and treatment of neuropsychatric disorders. Domain differences i

Achintha Ihalage, Yang Hao

The success of machine learning (ML) in materials property prediction depends heavily on how the materials are represented for learning. Two dominant families of material descriptors exist, one that encodes crystal structure in the representation and the other that only uses stoichiometric information with the hope of discovering new materials. Graph neural

Grace E. Lee, Aixin Sun

Conducting a systematic review (SR) is comprised of multiple tasks: (i) collect documents (studies) that are likely to be relevant from digital libraries (eg., PubMed), (ii) manually read and label the documents as relevant or irrelevant, (iii) extract information from the relevant studies, and (iv) analyze and synthesize the information and derive a conclus

Ryan Soklaski, Justin Goodwin, Olivia Brown, Michael Yee

Responsible Artificial Intelligence (AI) - the practice of developing, evaluating, and maintaining accurate AI systems that also exhibit essential properties such as robustness and explainability - represents a multifaceted challenge that often stretches standard machine learning tooling, frameworks, and testing methods beyond their limits. In this paper, we

J. Aguzzi, D. Chatzievangelou, S. Marini, E. Fanelli

Increasing interest in the acquisition of biotic and abiotic resources from within the deep sea (e.g. fisheries, oil-gas extraction, and mining) urgently imposes the development of novel monitoring technologies, beyond the traditional vessel-assisted, time-consuming, high-cost sampling surveys. The implementation of permanent networks of seabed and water-col

Véronique Bazier-Matte, Fenghuan He, Ruiyan Huang, Hanyi Yuo

We associate a quiver to a quasi-triangulation of a non-orientable marked surface and define a notion of quiver mutation that is compatible with quasi-cluster algebra mutation defined by Dupont and Palesi. Moreover, we use our quiver to show the unistructurality of the quasi-cluster algebra arising from the Mobius strip.

M. Bianchi, R. D. Camina, Mark L. Lewis

In this paper, we set $\eta (G)$ to be the number of conjugacy classes of maximal cyclic subgroups of $G$. We prove that if $G$ is a $p$-group of order $p^n$ and nilpotence class $l$, then $\eta (G)$ is bounded below by a linear function in $n/l$.

Prashant Kocherlakota, Luciano Rezzolla

Imaging a supermassive black hole and extracting physical information requires good knowledge of both the gravitational and the astrophysical conditions near the black hole. When the geometrical properties of the black hole are well understood, extracting information on the emission properties is possible. Similarly, when the emission properties are well und

Yehonathan Drori, Johannes Eichholz, Tega Edo, Hiro Yamamoto

Optical losses degrade the sensitivity of laser interferometric instruments. They reduce the number of signal photons and introduce technical noise associated with diffuse light. In quantum-enhanced metrology, they break the entanglement between correlated photons. Such decoherence is one of the primary obstacles in achieving high levels of quantum noise red

Jordi Poblador-Ibanez, William A. Sirignano

The injection of liquid fuel at supercritical pressures is a relevant but overlooked topic in combustion. Typically, the role of two-phase dynamics is neglected under the assumption that the liquid rapidly transitions to a supercritical state. However, a transcritical domain exists where a sharp phase interface remains. This scenario is the common case in th

Yeon-jae Jwa, Giuseppe Di Guglielmo, Lukas Arnold, Luca Carloni

We present a custom implementation of a 2D Convolutional Neural Network (CNN) as a viable application for real-time data selection in high-resolution and high-rate particle imaging detectors, making use of hardware acceleration in high-end Field Programmable Gate Arrays (FPGAs). To meet FPGA resource constraints, a two-layer CNN is optimized for accuracy and

M. Bianchi, R. D. Camina, Mark L. Lewis, E. Pacifici

In this paper, we set $\eta (G)$ to be the number of conjugacy classes of maximal cyclic subgroups of $G$. We consider $\eta$ and direct and semi-direct products. We characterize the normal subgroups $N$ so that $\eta (G/N) = \eta (G)$. We set $G^- = \{ g \in G \mid \langle g \rangle {\rm ~is~not ~maximal~cyclic} \}$. We show if $\langle G^- \rangle < G$, th

Claire Marie Guimond, John Rudge, Oliver Shorttle

Topography on a wet rocky exoplanet could raise land above its sea level. Although land elevation is the product of many complex processes, the large-scale topographic features on any geodynamically-active planet are the expression of the convecting mantle beneath the surface. This so-called "dynamic topography" exists regardless of a planet's tectonic regim

Alessia Suprano, Danilo Zia, Emanuele Polino, Taira Giordani

Experimentally engineering high-dimensional quantum states is a crucial task for several quantum information protocols. However, a high degree of precision in the characterization of experimental noisy apparatus is required to apply existing quantum state engineering protocols. This is often lacking in practical scenarios, affecting the quality of the engine

Andrew Baumgartner, Sevda Molani, Qi Wei, Jennifer Hadlock

We present a simple yet novel time series imputation technique with the goal of constructing an irregular time series that is uniform across every sample in a data set. Specifically, we fix a grid defined by the midpoints of non-overlapping bins (dubbed "slices") of observation times and ensure that each sample has values for all of the features at that give

C Alard

Numerical simulations demonstrate a link between dynamically cold initial solutions and self-similarity. However the nature of this link is not fully understood. Cold initial conditions alone without further symmetry do not lead to self-similarity. Here we show that when the system approaches equilibrium a new symmetry appears. The combination of this equili

F. Capel, J. M. Burgess, D. J. Mortlock, P. Padovani

Several tentative associations between high-energy neutrinos and astrophysical sources have been recently reported, but a conclusive identification of these potential neutrino emitters remains challenging. We explore the use of Monte Carlo simulations of source populations to gain deeper insight into the physical implications of proposed individual source--n

Salvatore D'Oro, Leonardo Bonati, Michele Polese, Tommaso Melodia

The next generation of cellular networks will be characterized by softwarized, open, and disaggregated architectures exposing analytics and control knobs to enable network intelligence. How to realize this vision, however, is largely an open problem. In this paper, we take a decisive step forward by presenting and prototyping OrchestRAN, a novel orchestratio

Liliana Gabriela Gheorghe

The center of an inscribed conic which have a given perspector is the complement of its isotomic conjugate. We provide a synthetic proof, based on fine proprieties of Lemoine point.

Alberto Roper Pol, Chiara Caprini, Andrii Neronov, Dmitri Semikoz

The NANOGrav, Parkes, European, and International Pulsar Timing Array (PTA) Collaborations have reported evidence for a common-spectrum process that can potentially correspond to a stochastic gravitational wave background (SGWB) in the 1--100 nHz frequency range. We consider the scenario in which this signal is produced by magnetohydrodynamic (MHD) turbulenc

Vikram S Chundawat, Ayush K Tarun, Murari Mandal, Mohan Kankanhalli

Modern privacy regulations grant citizens the right to be forgotten by products, services and companies. In case of machine learning (ML) applications, this necessitates deletion of data not only from storage archives but also from ML models. Due to an increasing need for regulatory compliance required for ML applications, machine unlearning is becoming an e

Thomas P. Wihler

The starting point of this note is a decades-old yet little-noticed sufficient condition, presented by Sassenfeld in 1951, for the convergence of the classical Gauss-Seidel method. The purpose of the present paper is to shed new light on Sassenfeld's criterion and to demonstrate that it is directly related to H-matrices. In particular, our results yield a ne

Jordan Simpson, David Jones, Roger Wesson, Jorge García-Rojas

A30 belongs to a class of planetary nebulae identified as "born-again", containing dense, hydrogen-poor ejecta with extreme abundance discrepancy factors (ADFs), likely associated with a central binary system. We present intermediate-dispersion spectroscopy of one such feature-the J4 equatorial knot. We confirm the apparent physical and chemical segregation

Michael Ryan, David Radice

Several dark matter models allow for the intriguing possibility of exotic compact object formation. These objects might have unique characteristics that set them apart from their baryonic counterparts. Furthermore, gravitational wave observations of their mergers may provide the only direct window on a potentially entirely hidden sector. Here we discuss dark

Ali Rejali, Ahmad Minapoor

In this paper, we introduce a new notion of amenability, $\sigma-$Connes ideal, say, for a large class of dual Banach algebras. We extend the concept of ideal Connes amenability and study their properties. Let $\sigma$ be a $weak^{*}$-continuous endomorphism on a dual Banach algebra $\mathcal{A}$ with dense range. Then the concept of ideal Connes-amenability

Salvatore Cuomo, Vincenzo Schiano di Cola, Fabio Giampaolo, Gianluigi Rozza

Physics-Informed Neural Networks (PINN) are neural networks (NNs) that encode model equations, like Partial Differential Equations (PDE), as a component of the neural network itself. PINNs are nowadays used to solve PDEs, fractional equations, integral-differential equations, and stochastic PDEs. This novel methodology has arisen as a multi-task learning fra

Foteini Oikonomou

Active galactic nuclei (AGN) with relativistic jets are the most powerful persistent astrophysical sources of electromagnetic radiation in the Universe. Blazars are the most extreme subclass of AGN with jets directed along the line of sight of the observer. Their high-energy photon emission dominates the extragalactic gamma-ray sky and reaches multi-TeV ener

Sowrabh Sudevan, Sourin Das

We discuss the construction of $n$-qubit pure states with maximum bipartite entanglement across all possible choices of $k$ vs $n-k$ bi-partitioning, which implies that the Von Neumann entropy of every $k$-qubit reduced density matrix corresponding to this state should be $k \ln 2 $. Such states have been referred to as $k$-uniform, $k$-MM states. We show th

Bruno Balthazar, Victor A. Rodriguez, Xi Yin

We study the perturbative S-matrix of closed strings in the two-dimensional type 0B string theory from the worldsheet perspective, by directly integrating correlation functions of ${\cal N}=1$ Liouville theory. The latter is computed numerically using recurrence relations for super-Virasoro conformal blocks. We show that the tree level 3- and 4-point amplitu

Sayantan Auddy, Shantanu Basu, Takahiro Kudoh

We study the magnetic field to density ($B-\rho$) relation in turbulent molecular clouds with dynamically important magnetic fields using nonideal three-dimensional magnetohydrodynamic simulations. Our simulations show that there is a distinguishable break density $\rho_{\rm T}$ between the relatively flat low density regime and a power-law regime at higher

Alessia Franchini, Alessandro Lupi, Alberto Sesana

The study of the interaction of a massive black hole binary with its gaseous environment is crucial in order to be able to predict merger rates and possible electromagnetic counterparts of gravitational wave signals. The evolution of the binary semi-major axis resulting from this interaction has been recently debated, and a clear consensus is still missing,

Marvin Gerlach, Florian Herren, Martin Lang

The demand for precision predictions in the field of high energy physics has dramatically increased over recent years. Experiments conducted at the LHC, as well as precision measurements at the intensity frontier such as Belle II require equally precise theoretical predictions to make full use of the acquired data. To match the experimental precision, two-,

Ruobing Dong, Hauyu Baobab Liu, Nicolas Cuello, Christophe Pinte

Close encounters between young stellar objects in star forming clusters are expected to dramatically perturb circumstellar disks. Such events are witnessed in numerical simulations of star formation, but few direct observations of ongoing encounters have been made. Here we report sub-0".1 resolution Atacama Large Millimeter Array (ALMA) and Jansky Very Large

Benjamin Michen, Jan Carl Budich

We investigate the impact on basic quantum transport properties of disorder-induced exceptional points (EPs) that emerge in a disorder-averaged Green's function description of two-dimensional (2D) Dirac semimetals with spin- or orbital-dependent potential scattering. Remarkably, we find that EPs may promote the nearly vanishing conductance of a finite sample

Todd M. Tripp

The high-velocity clouds (HVCs) in the outer Milky Way at $20^{\circ} < l < 190^{\circ}$ have similar spatial locations, metallicities, and kinematics. Moreover, their locations and kinematics are coincident with several extraplanar stellar streams. The HVC origins may be connected to the stellar streams, either stripped directly from them or precipitated by

Kareem El-Badry, Charlie Conroy, Eliot Quataert, Hans-Walter Rix

Motivated by recent suggestions that many Be stars form through binary mass transfer, we searched the APOGEE survey for Be stars with bloated, stripped companions. From a well-defined parent sample of 297 Be stars, we identified one mass-transfer binary, HD 15124. The object consists of a main-sequence Be star ($M_{\rm Be}=5.3\pm 0.6 \,M_{\odot}$) with a low

Robin Tibor Schirrmeister, Rosanne Liu, Sara Hooker, Tonio Ball

How do neural network image classifiers respond to simpler and simpler inputs? And what do such responses reveal about the learning process? To answer these questions, we need a clear measure of input simplicity (or inversely, complexity), an optimization objective that correlates with simplification, and a framework to incorporate such objective into traini

Chester Palen-Michel, June Kim, Constantine Lignos

We present Multilingual Open Text (MOT), a new multilingual corpus containing text in 44 languages, many of which have limited existing text resources for natural language processing. The first release of the corpus contains over 2.8 million news articles and an additional 1 million short snippets (photo captions, video descriptions, etc.) published between

E. Vitral, J. A. Hanna

We derive stretching and bending energies for isotropic elastic plates and shells. Through the dimensional reduction of a bulk elastic energy quadratic in Biot strains, we obtain two-dimensional bending energies quadratic in bending measures featuring a bilinear coupling of stretches and geometric curvatures. For plates, the bending measure is invariant unde

Anik Halder, Alexandre Barreira

The integrated shear 3-point correlation function $\zeta_{\pm}$ is a higher-order statistic of the cosmic shear field that describes the modulation of the 2-point correlation function $\xi_{\pm}$ by long-wavelength features in the field. Here, we introduce a new theoretical model to calculate $\zeta_{\pm}$ that is accurate on small angular scales, and that a

Sergiy Perepelytsya, Oleksii Zdorevskyi

DNA is strong polyelectrolyte macromolecule making metal ions (counterions) condense to a cloud around the double helix. The counterions may be localized outside the macromolecule and inside the minor and major grooves of the double helix. In the present work, the distribution of condensed counterions between inner and outer regions of DNA has been studied u

Hamid Reza Daneshpajouh

A family of sets is called star-shaped if all the members of the family have a point in common. The main aim of this paper is to provide a negative answer to the following question raised by James Aisenberg et al [Short proofs of the kneser-Lovasz coloring principle, Information and Computation, 261:296-310, 2018.], for the case k=2.

Binping Xiao, K. Mernick, F. Severino, K. Smith

The Low Energy Relativistic Heavy Ion Collider (RHIC) electron Cooler (LEReC) is designed to deliver a 1.6 MeV to 2.6 MeV electron beam, with rms dp/p less than 5e-4. The superconducting radiofrequency (SRF) Booster Cavity is the major accelerating component in LEReC. It is a 0.4 cell cavity operating at 2 K, providing a maximum energy gain of 2.2 MeV. It is

Tonima Tasnim Ananna, Anna K. Weigel, Benny Trakhtenbrot, Michael J. Koss

We determine the low-redshift X-ray luminosity function (XLF), active black hole mass function (BHMF), and Eddington-ratio distribution function (ERDF) for both unobscured (Type 1) and obscured (Type 2) active galactic nuclei (AGN) using the unprecedented spectroscopic completeness of the BAT AGN Spectroscopic Survey (BASS) data release 2. In addition to a s

Chiara Animali, Pietro Conzinu, Giovanni Marozzi

We introduce a new approach to renormalize physical quantities in curved space-time by adiabatic subtraction. We use a comoving infrared cut-off in defining the adiabatic counterpart of the physical quantity under consideration, building on the fact that the adiabatic approximation is ill-defined in the infrared tail of the spectrum. We show how this infrare

Vésteinn Snæbjarnarson, Haukur Barri Símonarson, Pétur Orri Ragnarsson, Svanhvít Lilja Ingólfsdóttir

We train several language models for Icelandic, including IceBERT, that achieve state-of-the-art performance in a variety of downstream tasks, including part-of-speech tagging, named entity recognition, grammatical error detection and constituency parsing. To train the models we introduce a new corpus of Icelandic text, the Icelandic Common Crawl Corpus (IC3

Aynur Bulut, Manh Khang Huynh, Stan Palasek

We consider the hypodissipative Navier-Stokes equations on $[0,T]\times\mathbb{T}^{d}$ and seek to construct non-unique, H\"older-continuous solutions with epochs of regularity (smooth almost everywhere outside a small singular set in time), using convex integration techniques. In particular, we give quantitative relationships between the power of the fracti

Michael R. Behrens, Warren C. Ruder

Swimming microrobots are increasingly developed with complex materials and dynamic shapes and are expected to operate in complex environments in which the system dynamics are difficult to model and positional control of the microrobot is not straightforward to achieve. Deep reinforcement learning is a promising method of autonomously developing robust contro

M. K. Lenzi, E. K. Lenzi, L. M. S. Guilherme, L. R. Evangelista

We investigate a diffusion process in heterogeneous media where particles stochastically reset to their initial positions at a constant rate. The heterogeneous media is modeled using a spatial-dependent diffusion coefficient with a power-law dependence on particles' positions. We use the Green function approach to obtain exact solutions for the probability d

Arthur A. B. Pessa, Rafael S. Zola, Matjaz Perc, Haroldo V. Ribeiro

Machine learning methods are becoming increasingly important for the development of materials science. In spite of this, the use of image analysis in the development of these systems is still recent and underexplored, especially in materials often studied via optical imaging techniques such as liquid crystals. Here we apply the recently proposed method of or

Samyam Rajbhandari, Conglong Li, Zhewei Yao, Minjia Zhang

As the training of giant dense models hits the boundary on the availability and capability of the hardware resources today, Mixture-of-Experts (MoE) models become one of the most promising model architectures due to their significant training cost reduction compared to a quality-equivalent dense model. Its training cost saving is demonstrated from encoder-de

Ovidiu Munteanu, Jiaping Wang

The purpose of this paper is to derive volume and other geometric information for three-dimensional complete manifolds with positive scalar curvature. In the case that the Ricci curvature is nonnegative, it is shown that the volume of the manifold must be of linear growth when the scalar curvature is bounded from below by a positive constant. This answers a

Francisco Peña-Camargo, Jarla Thiesbrummel, Hannes Hempel, Artem Musiienko

Traditional inorganic semiconductors can be electronically doped with high precision. Conversely, there is still conjecture regarding the assessment of the electronic doping density in metal-halide perovskites, not to mention of a control thereof. This paper presents a multifaceted approach to determine the electronic doping density for a range of different

Sarah Mubeen, Alpha Tom Kodamullil, Martin Hofmann-Apitius, Daniel Domingo-Fernández

Pathway enrichment analysis has become a widely used knowledge-based approach for the interpretation of biomedical data. Its popularity has led to an explosion of both enrichment methods and pathway databases. While the elegance of pathway enrichment lies in its simplicity, multiple factors can impact the results of such an analysis which may not be accounte

Julian D. Cortes

Governments and organizations recognize the need to revisit a mission-driven innovation amidst national and organizational innovation policy formulations. Notwithstanding a fertile research agenda on mission statements (hereafter mission(s)), several lines of inquiry remain open, such as crossnational and multisectorial studies and an examination of research

E. Rubino, S. L. Tabor, Vandana Tripathi, R. S. Lubna

This experimental study of high-spin structure near N = Z = 20 nuclei was focused on $^{41}$K, but will also mention three newly observed $\gamma$ transitions in $^{41}$Ca observed in the same reaction. High-spin states were populated using the $^{26}$Mg($^{18}$O, $p2n\gamma$)$^{41}$K and $^{26}$Mg($^{18}$O, $3n\gamma$)$^{41}$Ca reactions. The experiment was

Gunnar S. Bali, Sara Collins, Wolfgang Söldner, Simon Weishäupl

We determine the leading order mesonic~($B_0$ and $F_0$) and baryonic~($m_0$, $D$ and $F$) SU(3) chiral perturbation theory low energy constants from lattice QCD. We employ gauge ensembles with $N_f=3$ (i.e., $m_u=m_d=m_s$) non-perturbatively improved Wilson fermions at six distinct values of the lattice spacing in the range $a\approx (0.039 - 0.098)$ fm, wh

Jakub Náplava, Milan Straka, Jana Straková, Alexandr Rosen

We introduce a large and diverse Czech corpus annotated for grammatical error correction (GEC) with the aim to contribute to the still scarce data resources in this domain for languages other than English. The Grammar Error Correction Corpus for Czech (GECCC) offers a variety of four domains, covering error distributions ranging from high error density essay

Simon Rozier, Benoit Famaey, Arnaud Siebert, Giacomo Monari

We model the response of spherical, non-rotating Milky Way (MW) dark matter and stellar halos to the Large Magellanic Cloud (LMC) using the matrix method of linear response theory. Our computations reproduce the main features of the dark halo response from simulations. We show that these features can be well separated by a harmonic decomposition: the large s

Michael Blondin, Filip Mazowiecki, Philip Offtermatt

Workflow nets are a popular variant of Petri nets that allow for algorithmic formal analysis of business processes. The central decision problems concerning workflow nets deal with soundness, where the initial and final configurations are specified. Intuitively, soundness states that from every reachable configuration one can reach the final configuration. W

Perry Gibson, José Cano

Auto-scheduling for tensor programs is a process where a search algorithm automatically explores candidate schedules (program transformations) for a given program on a target hardware platform to improve its performance. However this can be a very time consuming process depending on the complexity of the tensor program and the capacity of the target device,

John Darges, Alen Alexanderian, Pierre Gremaud

Variance-based global sensitivity analysis (GSA) can provide a wealth of information when applied to complex models. A well-known Achilles' heel of this approach is its computational cost which often renders it unfeasible in practice. An appealing alternative is to analyze instead the sensitivity of a surrogate model with the goal of lowering computational c

Eduardo R. Corral-Soto, Mrigank Rochan, Yannis Y. He, Shubhra Aich

In this paper we address the challenging problem of domain adaptation in LiDAR semantic segmentation. We consider the setting where we have a fully-labeled data set from source domain and a target domain with a few labeled and many unlabeled examples. We propose a domain adaption framework that mitigates the issue of domain shift and produces appealing perfo

Colin Davalo

We prove that any Borel Anosov representations of a surface group into $Sp(4,\mathbb{R})$ that has maximal Toledo invariant must be Hitchin. We also prove that a representation of a surface group into $Sp(2n,\mathbb{R})$ that is $\{n-1,n\}$-Anosov is maximal if and only if it satisfies the hyperconvexity property $H_n$.

Jessica Di Cocco, Bernardo Monechi

This paper is a corrigendum and addendum to the previously published article: 'How Populist are Parties? Measuring Degrees of Populism in Party Manifestos Using Supervised Machine Learning' (Political Analysis, 1-17. doi:10.1017/pan.2021.29). These corrigendum and addendum were prepared to correct errors in data labelling and show some extra insights not inc

Alireza Tavanfar, Aliasghar Parvizi, Marco Pezzutto

We propose, formulate and examine novel quantum systems and behavioral phases in which momentary choices of the system's memories interact in order to source the internal interactions and unitary time evolutions of the system. In a closed system of the kind, the unitary evolution operator is updated, moment by moment, by being remade out of the system's `exp

Philippe Moreillon, Kevin Schnelli

We consider the free additive convolution $\mu_\alpha\boxplus\mu_\beta$ of two probability measures $\mu_\alpha$ and $\mu_\beta$, supported on respectively $n_\alpha$ and $n_\beta$ disjoint bounded intervals on the real line, and derive a lower bound and an upper bound that is strictly smaller than $2n_\alpha n_\beta$, on the number of connected components i

Nelson R. F. Braga, Luiz F. Faulhaber, Octavio C. Junqueira

Non-central heavy ion collisions lead to the production of a quark gluon plasma with angular momentum. We investigate, using holographic AdS/QCD models, how does rotation of the medium affects the confinement/deconfinement transition temperature $T_c$. In holographic models, this transition is represented by a Hawking-Page process involving two asymptoticall

Bhavna Yadav, Trisha Sarkar, Khushboo Dixit, Ashutosh Kumar Alok

Non-local correlations in entangled systems are usually captured by measures such as Bell's inequality violation. It was recently shown that in neutrino systems, a measure of non-local advantage of quantum coherence (NAQC) can be considered as a stronger measure of non-local correlations as compared to the Bell's inequality violation. In this work, we analyz

Danilo Vilela Avelar, Fabio Enrique Brochero Martínez, Sávio Ribas

Let $C_n$ be the cyclic group of order $n$. In this paper, we provide the exact values of some zero-sum constants over $C_n \rtimes_s C_2$ where $s \not\equiv \pm1 \pmod n$, namely $\eta$-constant, Gao constant, and Erd\H{o}s-Ginzburg-Ziv constant (the latter for all but a "small" family of cases). As a consequence, we prove the Gao's and Zhuang-Gao's Conjec

CMS Collaboration

A search for heavy neutral leptons (HNLs), the right-handed Dirac or Majorana neutrinos, is performed in final states with three charged leptons (electrons or muons) using proton-proton collision data collected by the CMS experiment at $\sqrt{s} =$ 13 TeV at the CERN LHC. The data correspond to an integrated luminosity of 138 fb$^{-1}$. The HNLs could be pro

Nicomino Fiscante, Pia Addabbo, Filippo Biondi, Gaetano Giunta

In this letter, a new approach for the retrieval of the vertical column concentrations of trace gases from hyperspectral satellite observations, is proposed. The main idea is to perform a linear spectral unmixing by estimating the abundances of trace gases spectral signatures in each mixed pixel collected by an imaging spectrometer in the ultraviolet region.

Ashwin Agrawal, Martin Fischer, Vishal Singh

Recent technological developments and advances in Artificial Intelligence (AI) have enabled sophisticated capabilities to be a part of Digital Twin (DT), virtually making it possible to introduce automation into all aspects of work processes. Given these possibilities that DT can offer, practitioners are facing increasingly difficult decisions regarding what

Peng Wang, Xin Xie, Xiaohan Wang, Ningyu Zhang

Previous knowledge graph embedding approaches usually map entities to representations and utilize score functions to predict the target entities, yet they typically struggle to reason rare or emerging unseen entities. In this paper, we propose kNN-KGE, a new knowledge graph embedding approach with pre-trained language models, by linearly interpolating its en

Yulin Liu, Yuxuan Lu, Kartik Nayak, Fan Zhang

A transaction fee mechanism (TFM) is an essential component of a blockchain protocol. However, a systematic evaluation of the real-world impact of TFMs is still absent. Using rich data from the Ethereum blockchain, the mempool, and exchanges, we study the effect of EIP-1559, one of the earliest-deployed TFMs that depart from the traditional first-price aucti

Giorgio Metafune, Luigi Negro, Chiara Spina

We study elliptic and parabolic problems governed by the singular elliptic operators \begin{equation*} \mathcal L =y^{\alpha_1}\Delta_{x} +y^{\alpha_2}\left(D_{yy}+\frac{c}{y}D_y -\frac{b}{y^2}\right), \qquad\alpha_1, \alpha_2 \in\mathbb R \end{equation*} in the half-space $\mathbb R^{N+1}_+=\{(x,y): x \in \mathbb R^N, y>0\}$.

S. O. Makarov, D. P. Coster, V. A. Rozhansky, S. P. Voskoboynikov

New Grad's-Zhdanov module is implemented in the SOLPS-ITER code and applied to ITER impurity transport simulations. Significant difference appears in the helium transport due to improved parallel kinetic coefficients. As a result 30\% decrease of the separatrix-averaged helium relative concentration is observed for the constant helium source and pumping spee

D. Cornu, J. Montillaud, D. J. Marshall, A. C. Robin

Context. Several methods have been proposed to build 3D extinction maps of the Milky Way (MW), most often based on Bayesian approaches. Although some studies employed machine learning (ML) methods in part of their procedure, or to specific targets, no 3D extinction map of a large volume of the MW solely based on a Neural Network method has been reported so f

Jaydip Sen, Ashwin Kumar R S, Geetha Joseph, Kaushik Muthukrishnan

Stock price prediction is a challenging task and a lot of propositions exist in the literature in this area. Portfolio construction is a process of choosing a group of stocks and investing in them optimally to maximize the return while minimizing the risk. Since the time when Markowitz proposed the Modern Portfolio Theory, several advancements have happened

Blas Fernandez, Safet Penjic

Let $\Gamma$ denote a bipartite graph with vertex set $X$, color partitions $Y$, $Y'$, and assume that every vertex in $Y$ has eccentricity $D\ge 3$. For $z\in X$ and a non-negative integer $i$, let $\Gamma_{i}(z)$ denote the set of vertices in $X$ that are at distance $i$ from $z$. Graph $\Gamma$ is almost $2$-$Y$-homogeneous whenever for all $i \; (1\leq i

Leo R. Ya. Doktorski, Pedro Fernández-Martínez, Teresa M. Signes

We consider K-interpolation methods involving slowly varying functions. Let $\overline{A}_{\theta,*}^{\mathcal{L}}$ and $\overline{A}_{\theta,*}^{\mathcal{R}}$ $(0\leq\theta\leq1)$ be the so called ${\mathcal{L}}$ or ${\mathcal{R}}$ limiting interpolation spaces which arise naturally in reiteration formulae for the limiting cases. We characterize the interpo

Fabio Acero, Marianne Lemoine-Goumard, Jean Ballet

The Kepler supernova remnant (SNR) is the only historic supernova remnant lacking a detection at GeV and TeV energies which probe particle acceleration. A recent analysis of Fermi-LAT data reported a likely GeV gamma-ray candidate in the direction of the SNR. Using approximately the same dataset but with an optimized analysis configuration, we confirm the ga

Shaleen Deep, Xiao Hu, Paraschos Koutris

Join query evaluation with ordering is a fundamental data processing task in relational database management systems. SQL and custom graph query languages such as Cypher offer this functionality by allowing users to specify the order via the ORDER BY clause. In many scenarios, the users also want to see the first $k$ results quickly (expressed by the LIMIT cl

Maximilian Kertel, Markus Pauly

In this work we present a rigorous application of the Expectation Maximization algorithm to determine the marginal distributions and the dependence structure in a Gaussian copula model with missing data. We further show how to circumvent a priori assumptions on the marginals with semiparametric modelling. The joint distribution learned through this algorithm