July 2022 arXiv papers — page 121

Shintarou Yanagida

We introduce an intermediate family of Laurent polynomials between Schur's $Q$-functions and S. Okada's symplectic $Q$-functions. It can also be regarded as a $Q$-function analogue of Proctor's intermediate symplectic characters, and is named the family of intermediate symplectic $Q$-functions. We also derive a tableau-sum formula and a J\'ozefiak-Pragacz-ty

Bozo Vazic, Bilen Emek Abali, Pania Newell

Advancement in manufacturing methods enable designing so called metamaterials with a tailor-made microstructure. Microstructure affects materials response within a length-scale, where we model this behavior by using the generalized thermomechanics. Strain gradient theory is employed as a higher-order theory with thermodynamics modeled as a first-order theory

Joseph Jerome, Gregory Palmer, Rahul Savani

This paper introduces a new representation for the actions of a market maker in an order-driven market. This representation uses scaled beta distributions, and generalises three approaches taken in the artificial intelligence for market making literature: single price-level selection, ladder strategies and "market making at the touch". Ladder strategies plac

Julian De Vuyst, Thomas G. Mertens

In this work, we revisit the problem of finding entanglement islands in 2d Jackiw-Teitelboim (JT) gravity. We implement the following adjustments to the traditional setup: (1) we do not explicitly couple to a non-gravitating system, instead we implement only pure absorption into a fiducial detector, (2) we utilise the operationally defined renormalised matte

Carlos Alvarado, Ghulam Jilani Quadri, Jennifer Adorno Nieves, Paul Rosen

Every year we grow more dependent on wearable devices to gather personalized data, such as our movements, heart rate, respiration, etc. To capture this data, devices contain sensors, such as accelerometers and gyroscopes, that are able to measure changes in their surroundings and pass along the information for better informed decisions. Although these sensor

Guillaume Blanc

Investigating a model of scale-invariant random spatial network suggested by Aldous, Kendall constructed a random metric $T$ on $\mathbb{R}^d$, for which the distance between points is given by the optimal connection time, when travelling on the road network generated by a Poisson process of lines with a speed limit. In this paper, we look into some fractal

Jan Ondras, Abrar Anwar, Tong Wu, Fanjun Bu

We develop data-driven models to predict when a robot should feed during social dining scenarios. Being able to eat independently with friends and family is considered one of the most memorable and important activities for people with mobility limitations. While existing robotic systems for feeding people with mobility limitations focus on solitary dining, c

Stefan O'Toole, Miquel Ramirez, Nir Lipovetzky, Adrian R. Pearce

We introduce a new algorithm, Regression based Supervised Learning (RSL), for learning per instance Neural Network (NN) defined heuristic functions for classical planning problems. RSL uses regression to select relevant sets of states at a range of different distances from the goal. RSL then formulates a Supervised Learning problem to obtain the parameters t

Zhenyi Yuan, Changhong Zhao, Jorge Cortes

This paper proposes a reinforcement learning-based approach for optimal transient frequency control in power systems with stability and safety guarantees. Building on Lyapunov stability theory and safety-critical control, we derive sufficient conditions on the distributed controller design that ensure the stability and transient frequency safety of the close

Zhen Zhang, Lie-Wen Chen

Using the recent model-independent determination of the charge-weak form factor difference $\Delta F_{\rm CW}$ in $^{48}$Ca and $^{208}$Pb by the CREX and PREX-2 collaborations together with some well-determined properties of doubly magic nuclei, we perform Bayesian inference of the symmetry energy $E_{\rm sym}(\rho)$ and the neutron skin thickness $\Delta r

Jia Cheng Hu, Roberto Cavicchioli, Alessandro Capotondi

Most recent state of the art architectures rely on combinations and variations of three approaches: convolutional, recurrent and self-attentive methods. Our work attempts in laying the basis for a new research direction for sequence modeling based upon the idea of modifying the sequence length. In order to do that, we propose a new method called "Expansion M

Sora Akagami, Hiroyuki Tajima, Kei Iida

We theoretically discuss the possible condensation of Cooper triples, which correspond to a three-body version of Cooper pairs, in three-component Fermi systems with three-body attractive interactions. A macroscopic number of Cooper triples can occupy a zero center-of-mass momentum state in the presence of a Fermi surface of constituent particles, even thoug

S. C. İnan, A. V. Kisselev

We have examined the sensitivity to the axion-like particle (ALP) couplings to electroweak gauge bosons in the diphoton production at a future muon collider. The collisions at the $\mu^+ \mu^-$ energies of 3 TeV, 14 TeV, and 100 TeV are addressed. The differential cross sections versus the invariant mass of the final photons and total cross section versus mi

Gregory Scafarto, Nicolas Posocco, Antoine Bonnefoy

Trustworthy machine learning is driving a large number of ML community works in order to improve ML acceptance and adoption. The main aspect of trustworthy machine learning are the followings: fairness, uncertainty, robustness, explainability and formal guaranties. Each of these individual domains gains the ML community interest, visible by the number of rel

Alexander M. G. Cox, Emma Horton, Denis Villemonais

The aim of this paper is to study the large population limit of a binary branching particle system with Moran type interactions: we introduce a new model where particles evolve, reproduce and die independently and, with a probability that may depend on the configuration of the whole system, the death of a particle may trigger the reproduction of another part

Mark O. Goerbig

The fractional quantum Hall effect is a very particular manifestation of electronic correlations in two-dimensional systems in a strong perpendicular magnetic field. It arises as a consequence of a strong Coulomb repulsion between electrons in the same Landau level that conspires with a particular chirality of the electronic states. This chirality is inherit

Kyle P. Kelley, Sergei V. Kalinin, Eugene Eliseev, Shivaranjan Raghuraman

Ferroelectric domain walls have emerged as one of the most fascinating objects in condensed matter physics due to the broad variability of functional behaviors they exhibit. However, the vast majority of domain walls studies have been focused on bias-induced dynamics and transport behaviors. Here, we introduce the scanning probe microscopy approach based on

Ilias Samathrakis, Nuno Fortunato, Harish K. Singh, Chen Shen

Based on first-principles calculations, the anomalous Hall (AHC) and anomalous Nernst conductivities (ANC) of the XMnP (X=Ti, Zr, Hf) compounds were evaluated, and the possibility to tailor such properties by changing the magnetization directions was also investigated. We observed that nodal lines and small gap areas consist the dominant contributions to AHC

Tan Van Vu, Keiji Saito

Any physical system evolves at a finite speed that is constrained not only by the energetic cost but also by the topological structure of the underlying dynamics. In this Letter, by considering such structural information, we derive a unified topological speed limit for the evolution of physical states using an optimal transport approach. We prove that the m

Joonwon Choi, Sooyung Byeon, Inseok Hwang

Reachability analysis is a widely used method to analyze the safety of a Human-in-the-Loop Cyber Physical System (HiLCPS). This strategy allows the HiLCPS to respond against an imminent threat in advance by predicting reachable states of the system. However, it could lead to an unnecessarily conservative reachable set if the prediction only relies on the sys

Sofiane Ouaari, Tsegaye Misikir Tashu, Tomas Horvath

In this study, we propose feature extraction for multimodal meme classification using Deep Learning approaches. A meme is usually a photo or video with text shared by the young generation on social media platforms that expresses a culturally relevant idea. Since they are an efficient way to express emotions and feelings, a good classifier that can classify t

Shivam Yadav, Sajid Sekh, Ipsita Mandal

Magneto-optical conductivity is a very widely studied transport coefficient, useful to understand and characterize the behaviour of materials under magnetic fields. Using the Kubo formula, we compute the components of the conductivity tensor $\sigma_{\mu \nu}$ transverse to a uniform magnetic field $\mathbf B$, for a single node of a multi-Weyl semimetal (wi

M. E. Egwe, S. S. Sangodele

Let $G$ be a locally compact Lie group and $\mathfrak{g}$ its Lie algebra. We consider a fuzzy analogue of $G,$ denoted by $\mathfrak{G_f}$ called a fuzzy Lie group. Spherical functions on $\mathfrak{G_f}$ are constructed and a version of the existence result of the Helgason-spherical function on $G$ is then established on $\mathfrak{G_f}.$

Antonio Alvarez Valdivia, Soheil Habibian, Carly A. Mendenhall, Francesco Fuentes

Humans can leverage physical interaction to teach robot arms. As the human kinesthetically guides the robot through demonstrations, the robot learns the desired task. While prior works focus on how the robot learns, it is equally important for the human teacher to understand what their robot is learning. Visual displays can communicate this information; howe

R. Tripodi, C. Feruglio, F. Fiore, M. Bischetti

The outstanding mass growth of supermassive black holes (SMBHs) at the Reionisation Epoch and how it is related to the concurrent growth of their host galaxies, poses challenges to theoretical models aimed at explaining how these systems formed in short timescales (<1 Gyr). To trace the average evolutionary paths of quasi-stellar objects (QSOs) and their hos

Jérémi Dardé, Armand Koenig, Julien Royer

We consider the null-controllability problem for the generalized Baouendi-Grushin equation $(\partial_t - \partial_x^2 - q(x)^2\partial_y^2)f = 1_\omega u$ on a rectangular domain. Sharp controllability results already exist when the control domain $\omega$ is a vertical strip, or when $q(x) = x$. In this article, we provide upper and lower bounds for the mi

Benjamin Schäfer, Leonardo Rydin Gorjão, G. Cigdem Yalcin, Ellen Förstner

Complex systems, such as the power grid, are essential for our daily lives. Many complex systems display (multi-)fractal behavior, correlated fluctuations and power laws. Whether the power-grid frequency, an indicator about the balance on supply and demand in the electricity grid, also displays such complexity remains a mostly open question. Within the prese

Julio Backhoff-Veraguas, Clara Unterberger

The specific relative entropy, introduced by N. Gantert, allows to quantify the discrepancy between the laws of potentially mutually singular measures. It appears naturally as the large deviations rate function in a randomized version of Donsker's invariance principle, as well as in a novel transport-information inequality recently derived by H. Foellmer. A

B. J. Jacot, S. Vèlez, P. Noël, P. Helbingk

We investigate the motion of magnetic domain walls driven by magnetic fields and current-driven spin-orbit torques in an exchange-biased system with perpendicular magnetization. We consider Cr2O3/Co/Pt trilayers as model system, in which the magnetization of the Co layer can be exchanged-biased out-of-plane or in-plane depending on the field cooling directio

Colin Cros, Pierre-Olivier Amblard, Christophe Prieur, Jean-François Da Rocha

This paper introduces new structures called conic frameworks and their rigidity. They are composed by agents and a set of directed constraints between pairs of agents. When the structure cannot be flexed while preserving the constraints, it is said to be rigid. If only smooth deformations are considered a sufficient condition for rigidity is called infinites

Manjul Bhargava, Wei Ho

We determine average sizes/bounds for the $2$- and $3$-Selmer groups in various families of elliptic curves with marked points, thus confirming several cases of the Poonen--Rains heuristics. As a consequence, we deduce that the average ranks of the elliptic curves in all of these families are bounded. Our proofs are uniform and make use of parametrizations i

Sudin Ganguly, Souvik Roy, Santanu K. Maiti

The environmental influence is inevitable but often ignored in the study of electronic transport properties of small-scale systems. Such an environment-mediated interaction can generally be described by a parity-time symmetric non-Hermitian system with a balanced distribution of physical gain and loss. It is quite known in the literature that along with the

Johanna N. Borissova, Bianca Dittrich

Spin foams arise from a quantization of classical gravity expressed via the Plebanski action. Key open questions related to the continuum limit of spin foams are whether general relativity is reproduced and what type of corrections could emerge. As a central component for spin foam dynamics, recent results on the continuum limit of the Area Regge action sugg

Enes Yigitbas, Sebastian Krois, Timo Renzelmann, Gregor Engels

Basic life support (BLS) is crucial in the emergency response system as sudden cardiac arrest is still a major cause of death worldwide. In the majority of cases, cardiac arrest is witnessed out-of-hospital where execution of BLS including resuscitation through by-standers gets indispensable. However, survival rates of cardiac arrest victims could majorly in

Tsegaye Misikir Tashu, Sara Fattouh, Peter Kiss, Tomas Horvath

In this work, we present a multi-modal model for commercial product classification, that combines features extracted by multiple neural network models from textual (CamemBERT and FlauBERT) and visual data (SE-ResNeXt-50), using simple fusion techniques. The proposed method significantly outperformed the unimodal models' performance and the reported performan

Ora Nova Fandina, Mikael Møller Høgsgaard, Kasper Green Larsen

The Johnson-Lindenstrauss transform allows one to embed a dataset of $n$ points in $\mathbb{R}^d$ into $\mathbb{R}^m,$ while preserving the pairwise distance between any pair of points up to a factor $(1 \pm \varepsilon)$, provided that $m = \Omega(\varepsilon^{-2} \lg n)$. The transform has found an overwhelming number of algorithmic applications, allowing

Gonçalo M. Quinta, Alexandre Sousa, Yasser Omar

We show how a minimization principle of quantum entanglement between the oscillating flavors of a neutrino leads to a unique prediction for the CP-violation phase in the neutrino sector without assuming extra symmetries in the Standard Model. We find a theoretical prediction consistent with either no CP-violation or a very small presence of it.

Roberto Emparan, Juan F. Pedraza, Andrew Svesko, Marija Tomašević

In three-dimensional de Sitter space classical black holes do not exist, and the Schwarzschild-de Sitter solution instead describes a conical defect with a single cosmological horizon. We argue that the quantum backreaction of conformal fields can generate a black hole horizon, leading to a three-dimensional quantum de Sitter black hole. Its size can be as l

Bhupen Dabholkar, G. J. Sreejith, Fabien Alet

We present a quantum Monte Carlo investigation of the finite-temperature phase diagram of the quantum dimer model on the square lattice. We use the sweeping cluster algorithm, which allows to implement exactly the dimer constraint, supplemented with a equal-time directed loop move that allows to sample winding sectors. We find a high-temperature critical pha

Bin Ji, Shasha Li, Jie Yu, Jun Ma

For Named Entity Recognition (NER), sequence labeling-based and span-based paradigms are quite different. Previous research has demonstrated that the two paradigms have clear complementary advantages, but few models have attempted to leverage these advantages in a single NER model as far as we know. In our previous work, we proposed a paradigm known as Bundl

Juan Pablo Bascur, Suzan Verberne, Nees Jan van Eck, Ludo Waltman

The field of scientometrics has shown the power of citation-based clusters for literature analysis, yet this technique has barely been used for information retrieval tasks. This work evaluates the performance of citation based-clusters for information retrieval tasks. We simulated a search process using these clusters with a tree hierarchy of clusters and a

Shengru Chen, Qinghua Zhang, Xujing Li, Jiali Zhao

Emergent phenomena at heterointerfaces are directly associated with the bonding geometry of adjacent layers. Effective control of accessible parameters, such as the bond length and bonding angles, offers an elegant method to tailor competing energies of the electronic and magnetic ground states. In this study, we construct unit thick syntactic layers of coba

Mingqun Qi, Zhen Yang, Shengru Chen, Shan Lin

Misfit strain delivered from single-crystal substrates typically modifies the ground states of transition metal oxides, generating increasing interests in designing modern transducers and sensors. Here, we demonstrate that magnetotransport properties of La$_{0.67}$Sr$_{0.33}$MnO$_3$ (LSMO) films were continuously tuned by uniaxial strain produced by a home-d

Jérémie Francfort

In this thesis, I present three projects I carried out during m PhD. In the first project, I introduce Conformal Transformations and the Galaxy Number County. I explicitly show that the Galaxy Number Counts is invariant under Conformal Transformations, which makes it a good physical observable. In the second project, I study how weak lensing, and in particul

Manzoor Ahmed, Zain Ali, Wali Ullah Khan, Omer Waqar

The combination of backscatter communication with non-orthogonal multiple access (NOMA) has the potential to support low-powered massive connections in upcoming sixth-generation (6G) wireless networks. More specifically, backscatter communication can harvest and use the existing RF signals in the atmosphere for communication, while NOMA provides communicatio

Yuzhi Zhao, Yongzhe Xu, Qiong Yan, Dingdong Yang

Night imaging with modern smartphone cameras is troublesome due to low photon count and unavoidable noise in the imaging system. Directly adjusting exposure time and ISO ratings cannot obtain sharp and noise-free images at the same time in low-light conditions. Though many methods have been proposed to enhance noisy or blurry night images, their performances

L. Naponiello, L. Mancini, M. Damasso, A. S. Bonomo

We investigate the exoplanet candidate TOI-1422b, which was discovered by the TESS space telescope around the high proper-motion G2V star TOI-1422 ($V=10.6$ mag), 155pc away, with the primary goal of confirming its planetary nature and characterising its properties. We monitored TOI-1422 with the HARPS-N spectrograph for 1.5 years to precisely quantify its r

Yitong Li, Yunjie Gu

The emphasis on inertia for system stability has been a long-held tradition in conventional grids. The fast and flexible controllability of inverters opens up new possibilities. This paper investigates the {first-swing stability} of inverter-based inertia-free power systems. We illustrate that by replacing inertia with fast primary control (i.e. inertia-free

Man Yiu Tsang, Karmel S. Shehadeh, Frank E. Curtis

We propose a new inexact column-and-constraint generation (i-C&CG) method to solve two-stage robust optimization problems. The method allows solutions to the master problems to be inexact, which is desirable when solving large-scale and/or challenging problems. It is equipped with a backtracking routine that controls the trade-off between bound improvement a

Teemu Loippo, Antti Kanniainen, Juha T. Muhonen

Donor spin states in silicon are a promising candidate for quantum information processing. One possible donor spin readout mechanism is the bound exciton transition that can be excited optically and creates an electrical signal when it decays. This transition has been extensively studied in bulk, but in order to scale towards localized spin readout, microfab

Yu Song, Shan Wu, Xiang Chen, Yu He

BaNi$_2$As$_2$ is a nonmagnetic analogue of the iron pnictide superconductors, and in its tetragonal state exhibits an incommensurate charge-density-wave (IC-CDW) and a sizable elastoresistance. In this work, phonons in BaNi$_2$As$_2$ associated with the IC-CDW and uniform in-plane lattice distortions are investigated using high-resolution inelastic X-ray sc

Adrian Jones, Steven E. Massey, Daoyu Zhang, Yuri Deigin

The only animals other than bats reported to have been infected with SARS-CoV-2-related coronaviruses (SARS2r-CoVs) prior to the COVID-19 pandemic are pangolins. In early 2020 multiple papers reported the identification of two clades of SARS2r-CoVs, GD and GX, infecting pangolins. However the RNA-Seq datasets supporting pangolin genome assembly were widely c

C. Attaccalite, M. S. Prete, M. Palummo, O. Pulci

Transition metal dichalcogenides (TMD) monolayers, holding potential as good sunlight absorbers, are promising materials for next-generation optoelectronic devices. They may enable ultrathin photovoltaic(PV) devices thanks to their semiconducting character. In addition, heterocombinations of AlN and GaN sheets with MoS$_2$ monolayers have been suggested to b

Qianzhi Zhang, Fankun Bu, Yi Guo, Zhaoyu Wang

This paper proposes a tractable distributionally robust chance-constrained conservation voltage reduction (DRCC-CVR) method with enriched data-based ambiguity set in unbalanced three-phase distribution systems. The increasing penetration of distributed renewable energy not only brings clean power but also challenges the voltage regulation and energy-saving p

Kenichi Bannai, Hohto Bekki, Kei Hagihara, Tatsuya Ohshita

In this article, we construct the Hodge realization of the polylogarithm class in the equivariant Deligne-Beilinson cohomology of a certain algebraic torus associated to a totally real field. We then prove that the de Rham realization of this polylogarithm gives the Shintani generating class, a cohomology class generating the values of the Lerch zeta functio

Marco Castrillón López, Álvaro Rodríguez Abella

For each positive integer $k$, the bundle of $k$-jets of functions from a smooth manifold, $X$, to a Lie group, $G$, is denoted by $J^k(X,G)$ and it is canonically endowed with a Lie groupoid structure over $X$. In this work, we utilize a linear connection to trivialize this bundle, i.e., to build an injective bundle morphism from $J^k(X,G)$ into a vector bu

Yohan Brunebarbe

We prove that the projective complex algebraic varieties admitting a large complex local system satisfy a strong version of the Green-Griffiths-Lang conjecture.

Nicola Pia, Kishan Gupta, Srikanth Korse, Markus Multrus

Neural networks have proven to be a formidable tool to tackle the problem of speech coding at very low bit rates. However, the design of a neural coder that can be operated robustly under real-world conditions remains a major challenge. Therefore, we present Neural End-2-End Speech Codec (NESC) a robust, scalable end-to-end neural speech codec for high-quali

Jichang Yu, Haibo Zhou, Jianwen Cai

Correctly identifying treatment effects in observational studies is very difficult due to the fact that the outcome model or the treatment assignment model must be correctly specified. Taking advantages of semiparametric models in this article, we use single-index models to establish the outcome model and the treatment assignment model, which can allow the l

Franco Galante, Chiara Ravazzi, Michele Garetto, Emilio Leonardi

Restrictions on social and economic activities, as well as vaccinations, have been a key intervention in containing the COVID-19 epidemic. Our work focuses on better understanding the options available to policymakers under the conditions and uncertainties created by the onset of a new pandemic. More precisely, we focus on two control strategies. The first a

L. Bonora

Usually, in order to compute an anomaly (be it chiral or trace) with a perturbative method, the lowest significant order is sufficient. With the help of gauge or diffeomorphism invariance it uniquely identifies the anomaly. This note is a short review of the ambiguities that arise in the calculation of trace anomalies, and is meant, in particular, to signal

Karandeep Jandu Singh

We compute an $L_\infty$-algebroid structure on a projective resolution of some classes of singular foliations on a vector space $V$ induced by the linear action of some Lie subalgebra of $\mathfrak {gl}(V)$. This $L_\infty$-algebroid provides invariants of the singular foliations, and also provides a constant-rank replacement of the singular foliation. We d

Zhenpeng Chen, Jie M. Zhang, Federica Sarro, Mark Harman

Software bias is an increasingly important operational concern for software engineers. We present a large-scale, comprehensive empirical study of 17 representative bias mitigation methods for Machine Learning (ML) classifiers, evaluated with 11 ML performance metrics (e.g., accuracy), 4 fairness metrics, and 20 types of fairness-performance trade-off assessm

Merab Gogberashvili

We attempt to describe geometry in terms of informational quantities for the universe considered as a finite ensemble of correlated quantum particles. As the main dynamical principle, we use the conservation of the sum of all kinds of entropies: thermodynamic, quantum and informational. The fundamental constant of speed is interpreted as the information velo

Olivier Mailhot, Francois Major, Rafael Najmanovich

Summary: The DynaSig-ML (Dynamical Signatures - Machine Learning) Python package allows the efficient, user-friendly exploration of 3D dynamics-function relationships in biomolecules, using datasets of experimental measures from large numbers of sequence variants. The DynaSig-ML package is built around the Elastic Network Contact Model (ENCoM), the first and

Nada Almalki, Othon Michail

In this work, we investigate novel algorithmic growth processes. In particular, we propose three growth operations, full doubling, RC doubling and doubling, and explore the algorithmic and structural properties of their resulting processes under a geometric setting. In terms of modeling, our system runs on a 2-dimensional grid and operates in discrete time-s

Tilman Becker

A unit vector field on a Riemannian manifold $M$ is called geodesic if all of its integral curves are geodesics. We show, in the case of $M$ being a flat 3-manifold not equal to $\mathbb{E}^3$, that every such vector field is tangent to a 2-dimensional totally geodesic foliation. Furthermore, it is shown that a geodesic vector field $X$ on a closed flat 3-ma

Kaizhe Zhang

The grid-following and grid-forming controls in voltage-source converters are considered as different operation modes and the synchronization mechanism of them are studied separately. In this article, the intrinsic relationships between gridfollowing and grid-forming controlled converters are established as follows: 1) the proportional gain of PLL is in inve

Jakub Ripa, Andras Pal, Masanori Ohno, Norbert Werner

We present the detector performance and early science results from GRBAlpha, a 1U CubeSat mission, which is a technological pathfinder to a future constellation of nanosatellites monitoring gamma-ray bursts (GRBs). GRBAlpha was launched in March 2021 and operates on a 550 km altitude sun-synchronous orbit. The gamma-ray burst detector onboard GRBAlpha consis

Zhenyu Ni, Lele Liu, Liying Kang

Let $G$ be a cancellative $3$-uniform hypergraph in which the symmetric difference of any two edges is not contained in a third one. Equivalently, a $3$-uniform hypergraph $G$ is cancellative if and only if $G$ is $\{F_4, F_5\}$-free, where $F_4 = \{abc, abd, bcd\}$ and $F_5 = \{abc, abd, cde\}$. A classical result in extremal combinatorics stated that the m

Romain Gautron, Emilio J. Padrón, Philippe Preux, Julien Bigot

Addressing a real world sequential decision problem with Reinforcement Learning (RL) usually starts with the use of a simulated environment that mimics real conditions. We present a novel open source RL environment for realistic crop management tasks. gym-DSSAT is a gym interface to the Decision Support System for Agrotechnology Transfer (DSSAT), a high fide

Marco Angelini, Silvia Bonomi, Alessandro Palma

Cyber risk assessment is a fundamental activity for enhancing the protection of an organization, identifying and evaluating the exposure to cyber threats. Currently, this activity is carried out mainly manually and the identification and correct quantification of risks deeply depend on the experience and confidence of the human assessor. As a consequence, th

Kasper Green Larsen

Efficiently computing low discrepancy colorings of various set systems, has been studied extensively since the breakthrough work by Bansal (FOCS 2010), who gave the first polynomial time algorithms for several important settings, including for general set systems, sparse set systems and for set systems with bounded hereditary discrepancy. The hereditary disc

An-Ke Lei, Dai-Mei Zhou, Yu-Liang Yan, Du-Juan Wang

We have systematically studied the connection between hadron and its quark component nuclear modification factors and the flavor (mass) ordering at both parton and hadron levels in the nucleus-nucleus collisions at the LHC energies by the PACIAE model. It turns out that these two physical phenomena explored in our last publication (J. Phys. G 49 065104, 2022

Jérémy Auffinger, Alexandre Arbey

We present the new version of BlackHawk v2.0. BlackHawk is a public code designed to compute the Hawking radiation spectra of (primordial) black holes. In the version 2.0, we have added several non-standard BH metrics: charged, higher dimensional and polymerized black holes, in addition to the usual rotating (Kerr) BHs. BlackHawk also embeds some additional

V. Bertone, M. Cacciari, S. Frixione, G. Stagnitto

We illustrate how electron Parton Distribution Functions (PDFs) with next-to-leading collinear logarithmic accuracy must be employed in the context of perturbative predictions for high-energy $e^+e^-$-collision processes. In particular, we discuss how the renormalisation group equation evolution of such PDFs is affected by the presence of multiple fermion fa

Dhananjay Ashok, Vineel Nagisetty, Christopher Srinivasa, Vijay Ganesh

We present a novel hybrid algorithm for training Deep Neural Networks that combines the state-of-the-art Gradient Descent (GD) method with a Mixed Integer Linear Programming (MILP) solver, outperforming GD and variants in terms of accuracy, as well as resource and data efficiency for both regression and classification tasks. Our GD+Solver hybrid algorithm, c

Juan Davila, Manuel del Pino, Monica Musso, Juncheng Wei

A classical problem in fluid dynamics concerns the interaction of multiple vortex rings sharing a common axis of symmetry in an incompressible, inviscid $3$-dimensional fluid. Helmholtz (1858) observed that a pair of similar thin, coaxial vortex rings may pass through each other repeatedly due to the induced flow of the rings acting on each other. This celeb

María Carmona, Rafael Casado, Aurelio Bermúdez, Miguel Pérez Francisco

Humanity is facing global challenges related to climate change, along with an energetic crisis that urgently requires optimizing any process or system able to improve global economic conditions. Taking fuel as an example, its prices are among the highest increases detected in goods of general use. In this sense, initiatives to mitigate fuel consumption are b

Jarl G. Taxerås Flaten

We show that categories of modules over a ring in Homotopy Type Theory (HoTT) satisfy the internal versions of the AB axioms from homological algebra. The main subtlety lies in proving AB4, which is that coproducts indexed by arbitrary sets are left-exact. To prove this, we replace a set with its strict category of (ordered) finite sub-multisets. From showin

Harley D. Scammell, Oleg P. Sushkov

Excitonic bound states are characterised by a binding energy $\epsilon_b$ and a single-particle band gap $\Delta_b$. This work provides a theoretical description for both strong ($\epsilon_b\sim\Delta_b$) and weak ($\epsilon_b\ll\Delta_b$) excitonic bound states, with particular application to biased bilayer graphene. Standard description of excitons is base

Russell Blyth, Francesco Fumagalli, Francesco Matucci

A group $G$ is integrable if it is isomorphic to the derived subgroup of a group $H$; that is, if $H'\simeq G$, and in this case $H$ is an integral of $G$. If $G$ is a subgroup of $U$, we say that $G$ is integrable within $U$ if $G=H'$ for some $H\leq U$. In this work we focus on two problems posed in [1]. We classify the almost-simple finite groups $G$ that

Léo Vacher, João F. Dias, Nils Schöneberg, C. J. A. P. Martins

Searching for variations of nature's fundamental constants is a crucial step in our quest to go beyond our current standard model of fundamental physics. If they exist, such variations will be very likely driven by the existence of a new fundamental field. The Bekenstein model and its extensions introduce such a scalar field in a purely phenomenological way,

Fabian Hart, Ostap Okhrin, Martin Treiber

While deep reinforcement learning (RL) has been increasingly applied in designing car-following models in the last years, this study aims at investigating the feasibility of RL-based vehicle-following for complex vehicle dynamics and strong environmental disturbances. As a use case, we developed an inland waterways vessel-following model based on realistic v

Tusarkanta Dalai, Tapas Kumar Mishra, Pankaj K Sa

Automatic Part-of-speech (POS) tagging is a preprocessing step of many natural language processing (NLP) tasks such as name entity recognition (NER), speech processing, information extraction, word sense disambiguation, and machine translation. It has already gained a promising result in English and European languages, but in Indian languages, particularly i

Abednego Orobosa Isere

This paper studies the left (right) middle translations on finite involutory latin quandles and their representations. It also shows that a left involutory latin quandle of odd order n can be constructed from a cyclic group of odd order by the application of left middle translations. Furthermore, the concept of spins of involutory latin quandle is investigat

Alistair Savage

We introduce the quantum isomeric supercategory and the quantum affine isomeric supercategory. These diagrammatically defined supercategories, which can be viewed as isomeric analogues of the HOMFLYPT skein category and its affinization, provide powerful categorical tools for studying the representation theory of the quantum isomeric superalgebras (commonly

Sayantani Bhattacharya, Nitin Yadav, Azeem Ahmad, Frank Melandsø

Lead Zirconate Titanate [(ZrxTi1-x)O3 ]is used to make ultrasound transducers, sensors, and actuators due to its large piezoelectric coefficient. Several surfaces and subsurface micro defects develop within the Lead Zirconate Titanate (PZT) sensor due to delamination, corrosion, huge temperature fluctuation, etc., causing a decline in its performance. It is

Atish Dixit, Ahmed H. ElSheikh

Reinforcement learning (RL) is a promising tool to solve robust optimal well control problems where the model parameters are highly uncertain, and the system is partially observable in practice. However, RL of robust control policies often relies on performing a large number of simulations. This could easily become computationally intractable for cases with

V. M. Jiménez, M. de León

In this paper we present an application of the groupoid theory to the study of relevant case of material evolution phenomena, the \textit{process of morphogenesis}. Our theory is inspired by Walter Noll's theories of continuous distributions and provides a unifying and very simple framework of these phenomena. We present the explicit equation, the \textit{mo

Konstantin Niehaus, Andreas Westhoff

We introduce a cost-efficient, and open-source measurement system for measuring and monitoring indoor air quality, aerosol concentration, dust contamination, and comfort-relevant quantities. The system allows to access these quantities simultaneously at multiple sites. The software architecture is described along with the hardware set-up including an overvie

J. Braun, D. Romberger, H. J. Bentz

Linear harmonic number sums had been studied by a variety of authors during the last centuries, but only few results are known about nonlinear Euler sums of quadratic or even higher degree. The first systematic study on nonlinear Euler sums consisting of products of hyperharmonic sums had been published by Flajolet and Salvy in 1997 followed by similar studi

Kiran Sharma, Sudhanwa Patra

We discuss the transition and survival probabilities in $3+1$ neutrino flavor mixing scenario in presence of matter effects. We adopt the well-known OMSD(One Mass Scale Dominance) approximation to carry out our analysis. After that we perform series expansion about $\sin \theta_{13}$ term upto second order. We find that our results are consistent with the al

John E Beasley

In this paper we present a heuristic for the non-unicost set covering problem using local branching. Local branching eliminates the need to define a problem specific search neighbourhood for any particular (zero-one) optimisation problem. It does this by incorporating a generalised Hamming distance neighbourhood into the problem, and this leads naturally to

Virendra Sule

This paper is a short summery of results announced in a previous paper on a new universal method for Cryptanalysis which uses a Black Box linear algebra approach to computation of local inversion of nonlinear maps in finite fields. It is shown that one local inverse $x$ of the map equation $y=F(x)$ can be computed by using the minimal polynomial of the seque

Mark J. Arildsen, Norbert Schuch, Andreas W. W. Ludwig

The Li-Haldane correspondence [PRL 101, 010504 (2008)] is often used to help identify wave functions of (2+1)-D chiral topological phases (i.e., with non-zero chiral central charge) by studying low-lying entanglement spectra (ES) on long cylinders of finite circumference. Here we consider such ES of states [in fact, certain Projected Entangled Pair States (P

Athanasios Chatzistavrakidis

The AKSZ construction was developed as a geometrical formalism to find the solution to the classical master equation in the BV quantization of topological branes based on the concept of QP manifolds. However, the formalism does not apply in presence of Wess-Zumino terms, as demonstrated recently by Ikeda and Strobl in the simplest example of WZW-Poisson sigm

Andrea Corsini, Simone Calderara, Mauro Dell'Amico

In recent years, the power demonstrated by Machine Learning (ML) has increasingly attracted the interest of the optimization community that is starting to leverage ML for enhancing and automating the design of algorithms. One combinatorial optimization problem recently tackled with ML is the Job Shop scheduling Problem (JSP). Most of the works on the JSP usi

Sarasij Maitra

For any finitely generated module $M$ with non-zero rank over a commutative one dimensional Noetherian local domain, the numerical invariant $h(M)$ was introduced and studied in the author's previous work "Partial Trace Ideals and Berger's Conjecture". We establish a bound on it which helps capture information about the torsion submodule of $M$ when $M$ has

Richard D. Payne, Nilabja Guha, Bani K. Mallick

Survival models are used to analyze time-to-event data in a variety of disciplines. Proportional hazard models provide interpretable parameter estimates, but proportional hazards assumptions are not always appropriate. Non-parametric models are more flexible but often lack a clear inferential framework. We propose a Bayesian tree partition model which is bot