January 2022 arXiv papers — page 103

Haya Brama, Lihi Dery, Tal Grinshpoun

The problem of attacks on neural networks through input modification (i.e., adversarial examples) has attracted much attention recently. Being relatively easy to generate and hard to detect, these attacks pose a security breach that many suggested defenses try to mitigate. However, the evaluation of the effect of attacks and defenses commonly relies on tradi

C. Galera-Rueda, X. Jin, J. LLorca, M. T. Pérez-Prado

This work provides unambiguous evidence for the occurrence of icosahedral quasicrystal (iQC) enhanced nucleation during selective laser melting of gas atomized commercially-pure Ni powders. This solidification mechanism, which has only been recently reported in a few alloys and has to date never been observed in pure metals, consists on the solidification of

Robert J. Berman

Let X be a compact complex manifold whose anti-canonical line bundle is big. We show that X admits no non-trivial holomorphic vector fields if it is Gibbs stable (at any level). The proof is based on a vanishing result for measure preserving holomorphic vector fields on X of independent interest. As an application it shown that, in general, if the anti-canon

Shahin Mamedov, Narmin Nasibova

The axial-vector form factor of the nucleons is studied at a finite temperature using the holographic soft-wall model with the thermal dilaton field. We use the bulk interaction action known from the zero temperature case and apply the profile functions of fields thermalized by the interaction with the thermal dilaton field. The dependence of the axial form

Viktor Könye, József Cserti

We develop a general method for calculating the thermal efficiency of arbitrary thermodynamic cycles defined in the pressure-volume ($p-V$) diagram. To demonstrate how effective our approach is, we calculate the thermal efficiency of ideal gas engines for a few non-trivial cycles in the $p-V$ diagram, including a circular shape, a heart shape, a cycloid of C

Claudio Filipi Gonçalves dos Santos, Diego de Souza Oliveira, Leandro A. Passos, Rafael Gonçalves Pires

In general, biometry-based control systems may not rely on individual expected behavior or cooperation to operate appropriately. Instead, such systems should be aware of malicious procedures for unauthorized access attempts. Some works available in the literature suggest addressing the problem through gait recognition approaches. Such methods aim at identify

Lama Khalil, Debora Pierucci, Emilio Velez, José Avila

Nearly localized moire flat bands in momentum space, arising at particular twist angles, are the key to achieve correlated effects in transition-metal dichalcogenides. Here, we use angle-resolved photoemission spectroscopy (ARPES) to visualize the presence of a flat band near the Fermi level of van der Waals (vdW) WSe2/MoSe2 heterobilayer grown by molecular

Xin Wang, Junichi Yamagishi

Voice-based human-machine interfaces with an automatic speaker verification (ASV) component are commonly used in the market. However, the threat from presentation attacks is also growing since attackers can use recent speech synthesis technology to produce a natural-sounding voice of a victim. Presentation attack detection (PAD) for ASV, or speech anti-spoof

Sharmila N. Shirodkar, Pratibha Dev

Surface-states of topological insulators are assumed to be robust against non-magnetic defects in the crystal. However, recent theoretical models and experiments indicate that even non-magnetic defects can perturb these states. Our first-principles calculations demonstrate that the presence of Se vacancies in Bi$_2$Se$_3$, has a greater impact than a mere n-

Daniel Wulff, Jannis Hagenah, Floris Ernst

3D ultrasound (3DUS) becomes more interesting for target tracking in radiation therapy due to its capability to provide volumetric images in real-time without using ionizing radiation. It is potentially usable for tracking without using fiducials. For this, a method for learning meaningful representations would be useful to recognize anatomical structures in

Fedor V. Fomin, Petr A. Golovach, William Lochet, Danil Sagunov

We study two "above guarantee" versions of the classical Longest Path problem on undirected and directed graphs and obtain the following results. In the first variant of Longest Path that we study, called Longest Detour, the task is to decide whether a graph has an (s,t)-path of length at least dist_G(s,t)+k (where dist_G(s,t) denotes the length of a shortes

Gerardo Huaroto, Wladimir Neves

We study a new nonlocal approach to the mathematical modelling of the Chemotaxis problem, which describes the random motion of a certain population due a substance concentration. Considering the initial-boundary value problem for the fractional hyperbolic Keller-Segel model, we prove the solvability of the problem. The solvability result relies mostly on fra

X. R. Wang

Anisotropic magnetoresistance (AMR) and related planar Hall resistance (PHR) are ubiquitous phenomena of magnetic materials. Although the universal angular dependences of AMR and PHR in magnetic polycrystalline materials with one order parameter are well known, no similar universal relation for other class of magnetic materials are known to date. Here I pres

Yunus Emre Demirci, Ümit Işlak, Alperen Yaşar Özdemir

The edge flipping is a non-reversible Markov chain on a given connected graph, which is defined by Chung and Graham in [CG12]. In the same paper, its eigenvalues and stationary distributions for some classes of graphs are identified. We further study its spectral properties to show a lower bound for the rate of convergence in the case of regular graphs. More

Mathias Nyman, Christian Ahläng, Staffan Dahlström, Manasi Pranav

Charge selective interlayers are crucial in thin-film photovoltaics, such as organic and Perovskite solar cells. Charge transporting layers (doped and undoped) constitute perhaps the most important class of charge selective interlayers; however, it is not well understood how a charge transporting layer should be designed in order to ensure efficient extracti

Jing Du, Shiliang Pu, Qinbo Dong, Chao Jin

Although modern automatic speech recognition (ASR) systems can achieve high performance, they may produce errors that weaken readers' experience and do harm to downstream tasks. To improve the accuracy and reliability of ASR hypotheses, we propose a cross-modal post-processing system for speech recognizers, which 1) fuses acoustic features and textual featur

Luqi Wang, Hao Xu, Yichen Zhang, Shaojie Shen

Nowadays, multirotors are playing important roles in abundant types of missions. During these missions, entering confined and narrow tunnels that are barely accessible to humans is desirable yet extremely challenging for multirotors. The restricted space and significant ego airflow disturbances induce control issues at both fast and slow flight speeds, meanw

C. Lagoin, U. Bhattacharya, T. Grass, R. Chhajlany

The Hubbard model constitutes one of the most celebrated theoretical frameworks of condensed-matter physics. It describes strongly correlated phases of interacting quantum particles confined in lattice potentials. For bosons, the Hubbard Hamiltonian has been deeply scrutinised for short-range on-site interactions. However, accessing longer-range couplings ha

Marco Coraggio, Saber Jafarpour, Francesco Bullo, Mario di Bernardo

Given a flow network with variable suppliers and fixed consumers, the minimax flow problem consists in minimizing the maximum flow between nodes, subject to flow conservation and capacity constraints. We solve this problem over acyclic graphs in a distributed manner by showing that it can be recast as a consensus problem between the maximum downstream flows,

Chuangtao Chen, Zhimin He, Shenggen Zheng, Yan Zhou

Current structure optimization algorithms optimize the structure of quantum circuit from scratch for each new task of variational quantum algorithms (VQAs) without using any prior experience, which is inefficient and time-consuming. Besides, the number of quantum gates is a hyper-parameter of these algorithms, which is difficult and time-consuming to determi

Johan Kon, Dennis Bruijnen, Jeroen van de Wijdeven, Marcel Heertjes

Unknown nonlinear dynamics can limit the performance of model-based feedforward control. The aim of this paper is to develop a feedforward control framework for systems with unknown, typically nonlinear, dynamics. To address the unknown dynamics, a physics-based feedforward model is complemented by a neural network. The neural network output in the subspace

Mahesh N. Jayakody, Ismael L. Paiva, Asiri Nanayakkara, Eliahu Cohen

The study of recurrences and revivals in quantum systems has attracted a great deal of interest because of its importance in the control of quantum systems and its potential use in developing new technologies. In this work, we introduce a protocol to induce full-state revivals in a huge class of quantum walks on a $d$-dimensional lattice governed by a $c$-di

Diederik Aerts, Lester Beltran

As a result of the identification of 'identity' and 'indistinguishability' and strong experimental evidence for the presence of the associated Bose-Einstein statistics in human cognition and language, we argued in previous work for an extension of the research domain of quantum cognition. In addition to quantum complex vector spaces and quantum probability m

Tho Nguyen Duc

This article is devoted to the construction of pseudomodes of one-dimensional biharmonic operators with the complex-valued potentials via the WKB method. As a by-product, the shape of pseudospectrum near infinity can be described. This is a newly discovered systematic method that goes beyond the standard semi-classical setting which is a direct consequence.

Victor P. Goncalves, Lucas Lazzari

In this paper, we investigate the impact of the phase conversion speed on the properties of hybrid stars with sequential sharp QCD phase transitions. We consider that these hybrid stars possess an inner (outer) core of CFL (2SC) quark matter surrounded by hadronic matter. Assuming that the phase conversions can be slow or rapid, we analyze the dynamical stab

Pasquale C. Africa, Roberto Piersanti, Marco Fedele, Luca Dede'

Modeling the whole cardiac function involves the solution of several complex multi-physics and multi-scale models that are highly computationally demanding, which call for simpler yet accurate, high-performance computational tools. Despite the efforts made by several research groups, no software for whole-heart fully-coupled cardiac simulations in the scient

Stefan Wurster, Martin Stückler, Lukas Weissitsch, Heinz Krenn

The paper describes the capability of magnetic softening of a coarse grained bulk material by a severe deformation technique. Connecting the microstructure with magnetic properties, the coercive field decreases dramatically for grains smaller than the magnetic exchange length. This makes the investigation of soft magnetic properties of severely drawn pearlit

Ruo Ando, Yoshiyasu Takefuji

In this paper, we present a curious experiment with the hot list strategy in solving sliding block puzzles by paramodulation. The hot list strategy is one of the look-ahead strategies using paramodulation in automated reasoning. We define two heat flows in the reasoning process - vertical with the hot list of permutations along the Y-axis and horizontal alon

Kapil Motla, Arushi, Pavan K. Meena, R. P. Singh

Superconducting high entropy alloys (HEAs) are new members of disordered superconductors. We report the synthesis and investigation of a new superconducting high entropy alloy Mo$_{0.11}$W$_{0.11}$V$_{0.11}$Re$_{0.34}$B$_{0.33}$ (MWVRB). It crystallized in the tetragonal CuAl$_2$ crystal structure with space group (I4/$mcm$). Comprehensive transport, magneti

Claudio Filipi Gonçalves dos Santos, João Paulo Papa

Several image processing tasks, such as image classification and object detection, have been significantly improved using Convolutional Neural Networks (CNN). Like ResNet and EfficientNet, many architectures have achieved outstanding results in at least one dataset by the time of their creation. A critical factor in training concerns the network's regulariza

Ouassef Nahi, Alexander Broad, Alexander N. Kulak, Helen M. Freeman

Incorporation of guest additives within inorganic single crystals offers a unique strategy for creating nanocomposites with tailored properties. While anionic additives have been widely used to control the properties of crystals, their effective incorporation remains a key challenge. Here, we show that cationic additives are an excellent alterative for the s

Kai Han, Yunhe Wang, Chang Xu, Jianyuan Guo

Deploying convolutional neural networks (CNNs) on mobile devices is difficult due to the limited memory and computation resources. We aim to design efficient neural networks for heterogeneous devices including CPU and GPU, by exploiting the redundancy in feature maps, which has rarely been investigated in neural architecture design. For CPU-like devices, we

Bethan Easeman, Patricia Schady, Stijn Wuyts, Robert M. Yates

Radial metallicity trends provide a key indicator of physical processes such as star formation and radial gas migration within a galaxy. Large IFU surveys allow for detailed studies of these radial variations, with recent observations detecting central dips in the metallicity, which may trace the impact of various evolutionary processes. However, the origin

Alberto Facchini

General results on multiplicative lattices found recently by Facchini, Finocchiaro and Janelidze have been studied in the particular case of groups by Facchini, de Giovanni and Trombetti. In this paper we prove that these results hold not only for the multiplicative lattices of all normal subgroups of a group, but also for much more general multiplicative la

F. Spiegelman, N. F. Allard, J. F. Kielkopf

In this paper we emphasize the non-Lorentzian behavior of the Balmer series in helium-dominated DBA white dwarf stars for which the decades-old problem exists for the determination of the hydrogen abundance. In a very recent work, we have shown that quasi-molecular line satellites due to H-He and H-H collisions are responsible for the asymmetrical shape of t

Akhileswar Chowdary, Garima Chopra, Abhinav Kumar, Linga Reddy Cenkeramaddi

Non-orthogonal multiple access (NOMA) is a promising multiple access technology to improve the throughput and spectral efficiency of the users for 5G and beyond cellular networks. Similarly, coordinated multi-point transmission and reception (CoMP) is an existing technology to improve the coverage of cell-edge users. Hence, NOMA along with CoMP can potential

R. D. H. Hinlopen, F. A. Hinlopen, J. Ayres, N. E. Hussey

Strange metals exhibit a variety of anomalous magnetotransport properties, the most striking of which is a resistivity that increases linearly with magnetic field $B$ over a broad temperature and field range. The ubiquity of this behavior across a spectrum of correlated metals - both single- and multi-band, with either dominant spin and/or charge fluctuation

Yilin Ning, Siqi Li, Marcus Eng Hock Ong, Feng Xie

Risk scores are widely used for clinical decision making and commonly generated from logistic regression models. Machine-learning-based methods may work well for identifying important predictors, but such 'black box' variable selection limits interpretability, and variable importance evaluated from a single model can be biased. We propose a robust and interp

Kotaro Shimizu, Shun Okumura, Yasuyuki Kato, Yukitoshi Motome

A periodic array of topological spin textures, such as skyrmions and hedgehogs, is called the multiple-$Q$ spin texture, as it is represented by a superposition of multiple spin density waves. Depending on the way of superposition, not only the magnetic but also the topological properties are modified, leading to a variety of quantum transport and optical ph

Francois-Igor Pris

The article suggests that quantum mechanics is a science of a new type, which refutes the classical metaphysical concept of reality. The notion of a quantum concept is introduced. The possibility of a Wittgensteinian 'dissolution' of the measurement problem with the help of the notion of a language game and the possibility of a metaphysical solution of this

Christodoulos Skouroumounis, Ioannis Krikidis

By utilizing the combination of two powerful tools i.e., stochastic geometry (SG) and evolutionary game theory (EGT), in this paper, we study the problem of mobile user (MU) mode selection in heterogeneous sub-$6$ GHz/millimeter wave (mmWave) cellular networks. Particularly, by using SG tools, we first propose an analytical framework to assess the performanc

Matthias Schaufelberger, Reinald Peter Kühle, Andreas Wachter, Frederic Weichel

The assessment of craniofacial deformities requires patient data which is sparsely available. Statistical shape models provide realistic and synthetic data enabling comparisons of existing methods on a common dataset. We build the first publicly available statistical 3D head model of craniosynostosis patients and the first model focusing on infants younger t

Shanee Honig, Alon Bartal, Yisrael Parmet, Tal Oron-Gilad

There is a knowledge gap regarding which types of failures robots undergo in domestic settings and how these failures influence customer experience. We classified 10,072 customer reviews of small utilitarian domestic robots on Amazon by the robotic failures described in them, grouping failures into twelve types and three categories (Technical, Interaction, a

Luke De Clerk, Sergey Savl'ev

Here, we use Machine Learning (ML) algorithms to update and improve the efficiencies of fitting GARCH model parameters to empirical data. We employ an Artificial Neural Network (ANN) to predict the parameters of these models. We present a fitting algorithm for GARCH-normal(1,1) models to predict one of the model's parameters, $\alpha_1$ and then use the anal

Michael Mueller, Christopher Aleshire, Joachim Buldt, Henning Stark

The impact of nonlinear refraction and residual absorption on the achievable peak and average power in beam-splitter-based coherent beam combination is analyzed theoretically. While the peak power remains limited only by the aperture size, a fundamental average power limit is given by the thermo-optical and thermo-mechanical properties of the beam splitter m

Ilka Brunner, Nils Carqueville, Daniel Roggenkamp

We construct extended TQFTs associated to Rozansky--Witten models with target manifolds $T^*\mathbb{C}^n$. The starting point of the construction is the 3-category whose objects are such Rozansky--Witten models, and whose morphisms are defects of all codimensions. By truncation, we obtain a (non-semisimple) 2-category $\mathcal{C}$ of bulk theories, surface

Dan Crisan, Alexander Lobbe, Salvador Ortiz-Latorre

The filtering equations govern the evolution of the conditional distribution of a signal process given partial, and possibly noisy, observations arriving sequentially in time. Their numerical approximation plays a central role in many real-life applications, including numerical weather prediction, finance and engineering. One of the classical approaches to a

Anis Allagui, Hachemi Benaoum, Chunlei Wang

The Butler-Volmer (BV) equation links the current flux crossing an electrochemical interface to the electric potential drop across it with the assumption of Arrhenius kinetics and the Boltzmann factor. Applying the semilogarithmic Tafel analysis in which the logarithm of current is plotted vs. the overpotential one expects straight lines from which the funda

Tao Hou, Tao Wang, Zhuo Lu, Yao Liu

With the proliferation of IoT devices, researchers have developed a variety of IoT device identification methods with the assistance of machine learning. Nevertheless, the security of these identification methods mostly depends on collected training data. In this research, we propose a novel attack strategy named IoTGAN to manipulate an IoT device's traffic

Xiaocui Wang, Robin Y. Engel, Igor Vaskivskyi, Diego Turenne

Wide-band-gap insulators such as NiO offer the exciting prospect of coherently manipulating electronic correlations with strong optical fields. Contrary to metals where rapid dephasing of optical excitation via electronic processes occurs, the sub-gap excitation in charge-transfer insulators has been shown to couple to low-energy bosonic excitations. However

Anis Allagui, Hachemi Benaoum, Oleg Olendski

The classical treatment of the electrical double-layer (EDL) structure at a planar metal/electrolyte junction via the Gouy-Chapman-Stern (GCS) approach is based on the Poisson equation relating the electrostatic potential to the net mean charge density. The ions concentration in the diffuse layer are assumed to follow the Boltzmann distribution law, i.e. $\p

Mylène Sauty, Nicolas M. S. Lopes, Jean-Philippe Banon, Yves Lassailly

Near-bandgap photoemission spectroscopy experiments were performed on p-GaN and p-InGaN/GaN photocathodes activated to negative electron affinity. The photoemission quantum yield of the InGaN samples drops by more than one order of magnitude when the temperature is decreased while it remains constant on the GaN sample. This indicates a freezing of photoelect

Danial Saadatmand, Aliakbar Moradi Marjaneh

Interaction of asymmetric $\phi^6$ kinks with a spatially localized $\mathcal{PT}$-symmetric perturbation is investigated numerically. It has been shown that when the kink (antikink) hits the defect from the gain side, a final velocity of the kink decreases (increases), while for the kink and antikink coming from the opposite direction their final velocities

Michael Mueller, Joachim Buldt, Henning Stark, Christian Grebing

A multipass cell for nonlinear compression to few-cycle pulse duration is introduced comprising dielectrically enhanced silver mirrors on silicon substrates. Spectral broadening with 388 W output average power and 776 {\mu}J pulse energy is obtained at 82% cell transmission. A high output beam quality (M2<1.2) and a high spatio-spectral homogeneity (97.5%) a

Héctor Cadavid, Vasilios Andrikopoulos, Paris Avgeriou, P. Chris Broekema

Context: The challenges posed by the architecting of System of Systems (SoS) has motivated a significant number of research efforts in the area. However, literature is lacking when it comes to the interplay between the disciplines involved in the architecting process, a key factor in addressing these challenges.Objective: This paper aims to contribute to thi

Jay Solanki, Volker Perlick

In this paper we derive exact analytical formulas for the evolution of the photon sphere and for the angular radius of the shadow in a special Vaidya spacetime. The Vaidya metric describes a spherically symmetric object that gains or loses mass, depending on a mass function $m(v)$ that can be freely chosen. Here we consider the case that $m(v)$ is a linearly

Anatolii A. Puhalskii

A trajectorial large deviation principle is established in a mean field thermodynamic limit for a multiclass loss network with diminishing rates, which may have several stable equilibria. The large deviation limit is identified as a unique solution to a maxingale problem with a Markov property. The invariant measure of the network process obeys a large devia

Alberto Lusiani

We update the |V$_{us}$| determinations using the HFLAV 2018 report tau branching fraction results with recent new estimates of the $\pi\ell2$ and $K\ell2$ radiative corrections. There are minor changes of the central values and uncertainties.

Aditya Kumar, K. Ravi-Chandar, Oscar Lopez-Pamies

In a recent contribution, Kumar, Bourdin, Francfort, and Lopez-Pamies (J. Mech. Phys. Solids 142:104027, 2020) have introduced a comprehensive macroscopic phase-field theory for the nucleation and propagation of fracture in linear elastic brittle materials under arbitrary quasistatic loading conditions. The theory can be viewed as a natural generalization of

Andrea Sacchetti, Benjamin Bachmann, Kaspar Löffel, Urs-Martin Künzi

We compare the Finite Element Method (FEM) simulation of a standard Partial Differential Equation thermal problem of a plate with a hole with a Neural Network (NN) simulation. The largest deviation from the true solution obtained from FEM ($0.015$ for a solution on the order of unity) is easily achieved with NN too without much tuning of the hyperparameters.

Jan Boschheidgen, Andrei Jaikin-Zapirain

Wolfang L\"uck asked if twisted $L^2$-Betti numbers of a group are equal to the usual $L^2$-Betti numbers rescaled by the dimension of the twisting representation. We confirm this for sofic groups.

Sören Kohnert, Reinhard Stolle

As sensors get more and more integrated, signal processing functions, like tracking, are performed closer to the sensor. Consequently, high level fusion is on the rise. Presented here is a high level fusion scheme incorporating not only linear,but circular quantities as well. Monte Carlo experiments are used to verify our novel fusion operators that work as

Jan Moritz Petschick, Anitha Thillaisundaram

Spinal groups and multi-GGS groups are both generalisations of the well-known Grigorchuk-Gupta-Sidki (GGS-)groups. Here we give a necessary condition for spinal groups to be conjugate, and we establish a necessary and sufficient condition for multi-GGS groups to be conjugate. We also introduce a natural common generalisation of both classes, which we call po

Joachim Buldt, Henning Stark, Michael Mueller, Christian Grebing

We present a high-power source of broadband terahertz radiation covering the whole THz spectral region (0.1-30 THz). The two-color gas plasma generation process is driven by a state-of-the-art Ytterbium fiber chirped pulse amplification system based on coherent combination of 16 rod-type amplifiers. Prior to the THz generation, the pulses are spectrally broa

Jose Mujica

Limit cycles of planar polynomial vector fields have been an active area of research for decades; the interest in periodic-orbit related dynamics comes from Hilbert's 16th problem and the fact that oscillatory states are often found in applications. We study the existence of limit cycles and their coexistence with invariant algebraic curves in two families o

Pascal Gerber, Lisa Jöckel, Michael Kläs

Outcomes of data-driven AI models cannot be assumed to be always correct. To estimate the uncertainty in these outcomes, the uncertainty wrapper framework has been proposed, which considers uncertainties related to model fit, input quality, and scope compliance. Uncertainty wrappers use a decision tree approach to cluster input quality related uncertainties,

J. Dominique, J. Van den Berghe, C. Schram, M. A. Mendez

We analyse and compare various empirical models of wall pressure spectra beneath turbulent boundary layers and propose an alternative machine learning approach using Artificial Neural Networks (ANN). The analysis and the training of the ANN are performed on data from experiments and high-fidelity simulations by various authors, covering a wide range of flow

Wittaya Thipaksorn, Stharporn Sapa, Khamphee Karwan

We study the coupled dark energy model constructed from the general conformal transformation in which the coefficient of the conformal transformation depends on both the scalar field and its kinetic term. Under this conformal transformation, the action for subclass of Degenerate Higher-Order Scalar-Tensor (DHOST) theories is related to the Einstein-Hilbert a

Brajesh Kumar, Avinash Singh, D. K. Sahu, G. C. Anupama

We report results of optical imaging and low-resolution spectroscopic monitoring of supernova (SN) 2017iro that occurred in the nearby ($\sim$\,31 Mpc) galaxy NGC 5480. The \ion{He}{1} 5876 \AA\, feature present in the earliest spectrum (--\,7 d) classified it as a Type Ib SN. The follow-up observations span from --\,7 to +\,266 d with respect to the $B$-ban

Lucia Vigliotti, Alessio Calzona, Björn Trauzettel, Maura Sassetti

We theoretically analyse a long constriction between the helical edge states of a two-dimensional topological insulator. The constriction is laterally tunnel-coupled to two superconductors and a magnetic field is applied perpendicularly to the plane of the two-dimensional topological insulator. The Josephson current is calculated analytically up to second or

Vinayak Jagadish, R. Srikanth, Francesco Petruccione

We study the convex combinations of the $(d+1)$ generalized Pauli dynamical maps in a Hilbert space of dimension $d$. For certain choices of the decoherence function, the maps are noninvertible and they remain under convex combinations as well. For the case of dynamical maps characterized by the decoherence function $(1-e^{-ct})/n$ with the decoherence param

B. Nugmanov, N. Zunikov, F. Ya. Khalili

Non-Gaussian quantum states, described by negative valued Wigner functions, are important both for fundamental tests of quantum physics and for emerging quantum information technologies. However, they are vulnerable to dissipation. It is known, that the Wigner functions negativity could exist only if the overall quantum efficiency $\eta$ of the setup is high

Tristan Braud, Lik-Hang Lee, Ahmad Alhilal, Carlos Bermejo Fernández

Driven by the recent improvements in device and networks capabilities, Extended Reality (XR) is becoming more pervasive; industry and academia alike envision ambitious projects such as the metaverse. However, XR is still limited by the current architecture of mobile systems. This paper makes the case for an XR-specific operating system (XROS). Such an XROS i

B. I. Bantysh, Yu. I. Bogdanov

Debugging quantum states transformations is an important task of modern quantum computing. The use of quantum tomography for these purposes significantly expands the range of possibilities. However, the presence of preparation and measurement errors complicates the practical use of this procedure. In this work, we investigate the possibility of estimating th

Huan Nguyen, Sondre Holm Fyhn, Paolo De Petris, Kostas Alexis

This paper contributes a method to design a novel navigation planner exploiting a learning-based collision prediction network. The neural network is tasked to predict the collision cost of each action sequence in a predefined motion primitives library in the robot's velocity-steering angle space, given only the current depth image and the estimated linear an

E. Huguet, J. Queva, J. Renaud

The Laplace-de Rham operator acting on a one-form $a$: $\square a$, in $\mathbb{R}^{n+2}$ or $\mathbb{R}^{n+1}$ spaces is restricted to $n$-dimensional pseudo-spheres. This includes, in particular, the $n$-dimensional de Sitter and Anti-de Sitter space-times. The restriction is designed to extract the corresponding $n$-dimensional Laplace-de Rham operator ac

M. Fouesneau, R. Andrae, T. Dharmawardena, J. Rybizki

Stellar physical and dynamical properties are essential knowledge to understanding the structure, formation, and evolution of our Galaxy. We produced an all-sky uniformly derived catalog of stellar astrophysical parameters (APs; age, mass, temperature, bolometric luminosity, distance, dust extinction) to give insight into the physical properties of Milky-Way

M. A. Clark, M. Della Morte, Z. Hall, B. Hörz

The current precision reached by lattice QCD calculations of low-energy hadronic observables, requires not only the introduction of electromagnetic corrections, but also control over all the potential systematic uncertainties introduced by the lattice version of QED. Introducing a massive photon as an infrared regulator in lattice QED, provides a well define

Ushak Rahaman, Soebur Razzaque, S. Uma Sankar

In this article, we review the status of the tension between the long-baseline accelerator neutrino experiments T2K and NO$\nu$A. The tension arises mostly due to the mismatch in the appearance data of the two experiments. We explain how this tension arises based on $\nu_\mu \to \nu_e$ and $\bar{\nu}_\mu \to \bar{\nu}_e$ oscillation probabilities. We define

Severin Barmeier, Philipp Schmitt

We show how combinatorial star products can be used to obtain strict deformation quantizations of polynomial Poisson structures on $\mathbb R^d$, generalizing known results for constant and linear Poisson structures to polynomial Poisson structures of arbitrary degree. We give several examples of nonlinear Poisson structures and construct explicit formal sta

Alain Deville, Yannick Deville

Quantum electronics is significantly involved in the development of the field of quantum information processing. In this domain, the growth of Blind Quantum Source Separation and Blind Quantum Process Tomography has led, within the formalism of the Hilbert space, to the introduction of the concept of a Random-Coefficient Pure State, or RCPS: the coefficients

Mathieu Servillat, Catherine Boisson, Matthias Fuessling, Bruno Khelifi

We highlight here several solutions developed to make high-level Cherenkov data FAIR: Findable, Accessible, Interoperable and Reusable. The first three FAIR principles may be ensured by properly indexing the data and using community standards, protocols and services, for example provided by the International Virtual Observatory Alliance (IVOA). However, the

Izzeddin Teeti, Valentina Musat, Salman Khan, Alexander Rast

In an autonomous driving system, perception - identification of features and objects from the environment - is crucial. In autonomous racing, high speeds and small margins demand rapid and accurate detection systems. During the race, the weather can change abruptly, causing significant degradation in perception, resulting in ineffective manoeuvres. In order

Andrew Coates, Sebastian H. Völkel, Kostas D. Kokkotas

In this work we argue that black hole area quantization of Bekenstein and Mukhanov should not give rise to measurable effects in terms of so-called gravitational wave echoes during black hole mergers. We outline that the quantum spectrum of a black hole should be washed out during and after black hole mergers, and hence one should not expect echoes in this s

Jiabao Jin, Peng Cheng, Lei Chen, Xuemin Lin

With the development of traffic prediction technology, spatiotemporal prediction models have attracted more and more attention from academia communities and industry. However, most existing researches focus on reducing model's prediction error but ignore the error caused by the uneven distribution of spatial events within a region. In this paper, we study a

Aleena Ajaz, Ayesha Salar, Tauseef Jamal, Asif Ullah Khan

Now a days, UAVs such as drones are greatly used for various purposes like that of capturing and target detection from ariel imagery etc. Easy access of these small ariel vehicles to public can cause serious security threats. For instance, critical places may be monitored by spies blended in public using drones. Study in hand proposes an improved and efficie

Sylvie Boldo, François Clément, Louise Leclerc

The Bochner integral is a generalization of the Lebesgue integral, for functions taking their values in a Banach space. Therefore, both its mathematical definition and its formalization in the Coq proof assistant are more challenging as we cannot rely on the properties of real numbers. Our contributions include an original formalization of simple functions,

Yanan Li, Zhijian Yang

In this paper, we investigate the continuity of the attractors in time-dependent phase spaces. (i) We establish two abstract criteria on the upper semicontinuity and the residual continuity of the pullback $\mathscr D$-attractor with respect to the perturbations, and an equivalence criterion between their continuity and the pullback equi-attraction, which ge

Simão Correia, Raphaël Côte

We prove a first stability result of self-similar blow-up for the modified KdV equation on the line. More precisely, given a self-similar solution and a sufficiently small regular profile, there is a unique global solution which behaves at t tends to 0 as the sum of the self-similar solution and the smooth perturbation.

Jungseob Lee, Midan Shim, Suhyune Son, Chanjun Park

BlenderBot 2.0 is a dialogue model that represents open-domain chatbots by reflecting real-time information and remembering user information for an extended period using an internet search module and multi-session. Nonetheless, the model still has room for improvement. To this end, we examine BlenderBot 2.0 limitations and errors from three perspectives: mod

Tiantian Zhang, Daisuke Hara, Shuichi Murakami

In some Dirac systems with time-reversal (T) and glide (G) symmetries, multihelicoid surface states (MHSSs) appear, as discussed in various systems such as electronic and photonic ones. However, the topological nature and the conditions for the appearance of the MHSSs have not been understood. Here we show that MHSSs result from bulk-surface correspondence f

Xiaobin Fan, Xiaoping Wang, Kai Lu, Lei Xue

Nearest neighbor search supports important applications in many domains, such as database, machine learning, computer vision. Since the computational cost for accurate search is too high, the community turned to the research of approximate nearest neighbor search (ANNS). Among them, graph-based algorithm is one of the most important branches. Research by Fu

Monica Nonino, Francesco Ballarin, Gianluigi Rozza, Yvon Maday

We present a partitioned Model Order Reduction method for multiphysics problems, that is based on a semi-implicit treatment of the coupling conditions, and on a projection scheme. The proposed Reduced Order Method is based on the Proper Orthogonal Decomposition and on a Galerkin projection onto the reduced basis spaces; we aim of addressing both time-depende

Masahiro Yukawa, Hiroyuki Kaneko, Kyohei Suzuki, Isao Yamada

We present an efficient mathematical framework based on the linearly-involved Moreau-enhanced-over-subspace (LiMES) model. Two concrete applications are considered: sparse modeling and robust regression. The popular minimax concave (MC) penalty for sparse modeling subtracts, from the $\ell_1$ norm, its Moreau envelope, inducing nearly unbiased estimates and

Arun Sharma, Majid Farhadloo, Yan Li, Aditya Kulkarni

Given aggregated mobile device data, the goal is to understand the impact of COVID-19 policy interventions on mobility. This problem is vital due to important societal use cases, such as safely reopening the economy. Challenges include understanding and interpreting questions of interest to policymakers, cross-jurisdictional variability in choice and time of

Krzysztof Gawarecki, Paweł Scharoch, Michał Wiśniewski, Jakub Ziembicki

In this work we derive a ready-to-use symmetry invariant expansion of the full-zone 30-band k.p Hamiltonian for the Td point group. In order to find respective parameters, the band structures of III-V materials were calculated within a state-of-the-art Density Functional Theory (DFT) approach and used next as targets to adjust the k.p bands. A satisfactory a

Denys Dutykh, Jean-Louis Verger-Gaugry

The reduction modulo $p$ of a family of lacunary integer polynomials, associated with the dynamical zeta function $\zeta_{\beta}(z)$ of the $\beta$-shift, for $\beta > 1$ close to one, is investigated. We briefly recall how this family is correlated to the problem of Lehmer. A variety of questions is raised about their numbers of zeroes in $\mathbb{F}_p$ and

Masari Watanabe, Nobuyuki Kurita, Hidekazu Tanaka, Wataru Ueno

We report the magnetic properties of the double perovskites SrLaCuSbO$_6$ (SLCSO) and SrLaCuNbO$_6$ (SLCNO). The temperature dependence of the magnetic susceptibilities of both compounds shows a broad maximum characteristic of an $S\,=\,1/2$ square lattice Heisenberg antiferromagnet. Magnetic ordering occurs at $T_{\rm N}\,{=}\,13.6$ and 15.7 K for SLCSO and

Jean-François Mathiot

Within the framework of the recently proposed Taylor-Lagrange regularization scheme - which leads to finite elementary amplitudes in $4$-dimensional space-time with no additional dimensionful scales - we show that the trace of the energy-momentum tensor does not show any anomalous contribution even though quantum corrections are considered. Moreover, since t

Jiahao Huang, Yingying Fang, Yinzhe Wu, Huanjun Wu

Magnetic resonance imaging (MRI) is an important non-invasive clinical tool that can produce high-resolution and reproducible images. However, a long scanning time is required for high-quality MR images, which leads to exhaustion and discomfort of patients, inducing more artefacts due to voluntary movements of the patients and involuntary physiological movem