November 2022 arXiv papers — page 72

Chaoyue Song, Jiacheng Wei, Ruibo Li, Fayao Liu

The goal of 3D pose transfer is to transfer the pose from the source mesh to the target mesh while preserving the identity information (e.g., face, body shape) of the target mesh. Deep learning-based methods improved the efficiency and performance of 3D pose transfer. However, most of them are trained under the supervision of the ground truth, whose availabi

Tao Yu, Zhihe Lu, Xin Jin, Zhibo Chen

Large-scale vision-language models (VLMs) pre-trained on billion-level data have learned general visual representations and broad visual concepts. In principle, the well-learned knowledge structure of the VLMs should be inherited appropriately when being transferred to downstream tasks with limited data. However, most existing efficient transfer learning (ET

Dario Ascari

Let $F$ be a finitely generated free group, and let $H\le F$ be a finitely generated subgroup. An equation for an element $g\in F$ with coefficients in $H$ is an element $w(x)\in H*\langle x \rangle$ such that $w(g)=1$ in $F$; the degree of the equation is the number of occurrences of $x$ and $x^{-1}$ in the cyclic reduction of $w(x)$. Given an element $g\in

Tommaso Taddei

We develop and assess an optimization-based approach to parametric geometry reduction. Given a family of parametric domains, we aim to determine a parametric diffeomorphism $\Phi$ that maps a fixed reference domain $\Omega$ into each element of the family, for different values of the parameter; the ultimate goal of our study is to determine an effective tool

Hayden Gunraj, Paul Guerrier, Sheldon Fernandez, Alexander Wong

In electronics manufacturing, solder joint defects are a common problem affecting a variety of printed circuit board components. To identify and correct solder joint defects, the solder joints on a circuit board are typically inspected manually by trained human inspectors, which is a very time-consuming and error-prone process. To improve both inspection eff

Jean-Baptiste Gaya, Thang Doan, Lucas Caccia, Laure Soulier

The ability to continuously acquire new knowledge and skills is crucial for autonomous agents. Existing methods are typically based on either fixed-size models that struggle to learn a large number of diverse behaviors, or growing-size models that scale poorly with the number of tasks. In this work, we aim to strike a better balance between an agent's size a

Martin Endres, Artem Kononov, Hasitha Suriya Arachchige, Jiaqiang Yan

When a topological insulator is incorporated into a Josephson junction, the system is predicted to reveal the fractional Josephson effect with a 4$\pi$-periodic current-phase relation. Here, we report the measurement of a $4\pi$-periodic switching current through an asymmetric SQUID, formed by the higher-order topological insulator WTe$_2$. Contrary to the e

Julian Thoenniss, Michael Sonner, Alessio Lerose, Dmitry A. Abanin

We introduce an efficient method to simulate dynamics of an interacting quantum impurity coupled to non-interacting fermionic reservoirs. Viewing the impurity as an open quantum system, we describe the reservoirs by their Feynman-Vernon influence functionals (IF). The IF are represented as matrix-product states in the temporal domain, which enables an effici

Rose Hirigoyen, Amal Zouaq, Samuel Reyd

Neural Machine Translation (NMT) models from English to SPARQL are a promising development for SPARQL query generation. However, current architectures are unable to integrate the knowledge base (KB) schema and handle questions on knowledge resources, classes, and properties unseen during training, rendering them unusable outside the scope of topics covered i

Elena Arcari, Maria Vittoria Minniti, Anna Scampicchio, Andrea Carron

Mobile manipulation in robotics is challenging due to the need of solving many diverse tasks, such as opening a door or picking-and-placing an object. Typically, a basic first-principles system description of the robot is available, thus motivating the use of model-based controllers. However, the robot dynamics and its interaction with an object are affected

Hans van Haren

Turbulent and internal wave motions are important for the exchange of momentum, heat and suspended matter in the deep-sea which is generally stably stratified in density. Turbulence-generation models involve shear of vertical current differences that deforms the stratified waters, and convection that is drive by (unstable) buoyancy. Shear-generation is found

Julia Docampo Sánchez

We present an efficient, parallel, constrained optimization technique for approximating CAD curves with super-convergent rates. The optimization function is a disparity measure in terms of a piece-wise polynomial approximation and a curve re-parametrization. The constrained problem solves the disparity functional fixing the mesh element interfaces. We have n

Margherita Disertori, Valentin Rapenne, Constanza Rojas-Molina, Xiaolin Zeng

We study the Integrated Density of States (IDS) of the random Schr\"odinger operator appearing in the study of certain reinforced random processes in connection with a supersymmetric sigma-model. We rely on previous results on the supersymmetric sigma-model to obtain lower and upper bounds on the asymptotic behavior of the IDS near the bottom of the spectrum

Dan Popovici

We introduce a class of Hermitian metrics, that we call pluriclosed star split, generalising both the astheno-K\"ahler metrics of Jost and Yau and the $(n-2)$-Gauduchon metrics of Fu-Wang-Wu on complex manifolds. They have links with Gauduchon and balanced metrics through the properties of a smooth function associated with any Hermitian metric. After pointin

J. Emmanuel Johnson, Redouane Lguensat, Ronan Fablet, Emmanuel Cosme

Optimal Interpolation (OI) is a widely used, highly trusted algorithm for interpolation and reconstruction problems in geosciences. With the influx of more satellite missions, we have access to more and more observations and it is becoming more pertinent to take advantage of these observations in applications such as forecasting and reanalysis. With the incr

Volodymyr Biloshytskyi, Lucian Harland-Lang, Bogdan Malaescu, Vladimir Pascalutsa

The LHC newly-discovered resonant structures around 7 GeV, such as the $X(6900)$, could be responsible for the observed excess in light-by-light scattering between 5 and 10 GeV. We show that the ATLAS data for light-by-light scattering may indeed be explained by such a state with the $\gamma \gamma$ branching ratio of order of $10^{-4}$. This is much larger

Zonghai Yao, Yi Cao, Zhichao Yang, Hong Yu

Pretrained language models (PLMs) have motivated research on what kinds of knowledge these models learn. Fill-in-the-blanks problem (e.g., cloze tests) is a natural approach for gauging such knowledge. BioLAMA generates prompts for biomedical factual knowledge triples and uses the Top-k accuracy metric to evaluate different PLMs' knowledge. However, existing

Badreddine Benhellal, Konstantin Pankrashkin

We discuss the spectral properties of three-dimensional Dirac operators with critical combinations of electrostatic and Lorentz scalar shell interactions supported by a compact smooth surface. It turns out that the criticality of the interaction may result in a new interval of essential spectrum. The position and the length of the interval are explicitly con

M. Dutra, C. H. Lenzi, O. Lourenço

In this work we study a relativistic mean-field (RMF) hadronic model, with nucleonic short-range correlations (SRC) included, coupled to dark matter (DM) through the Higgs boson. We study different parametrizations of this model by running the dark particle Fermi momentum, and its mass in the range of $50$ GeV $\leqslant M_\chi\leqslant 500$ GeV, compatible

Tianqu Hu, Zihao Huang, Peng Ge, Feng Gao

As a burgeoning medical imaging method based on hybrid fusion of light and ultrasound, photoacoustic imaging (PAI) has demonstrated high potential in various biomedical applications recently, especially in revealing the functional and molecular information to improve diagnostic accuracy. However, stemming from weak amplitude and unavoidable random noise, cau

Felipe Attanasio, Benjamin Jäger, Felix P. G. Ziegler

We use complex Langevin simulations to study the QCD phase diagram with two light quark flavours. In this study, we use Wilson fermions with an intermediate pion mass of $\sim480\,$MeV. By studying thermodynamic quantities, in particular at lower temperatures, we are able to describe the equation of state.

Selen Gecgel Cetin, Berna Ozbek, Gunes Karabulut Kurt

Space has been reforming and this evolution brings new threats that, together with technological developments and malicious intent, can pose a major challenge. Space domain awareness (SDA), a new conceptual idea, has come to the forefront. It aims sensing, detection, identification and countermeasures by providing autonomy, intelligence and flexibility again

Anders Huitfeldt

In the 1958 paper "Shall we count the living or the dead", Canadian physician and biostatistician Mindel C. Sheps proposed a novel approach to choice of effect measure, which resolves key theoretical shortcomings of relative risk models. Sheps' insights have been independently rediscovered multiple times in different academic disciplines, and her approach is

Serhat Gul

The flexibility level allowed in nursing care delivery and uncertainty in infusion durations are very important factors to be considered during the chemotherapy schedule generation task. The nursing care delivery scheme employed in an outpatient chemotherapy clinic (OCC) determines the strictness of the patient-to-nurse assignment policies, while the estimat

Scott Sussex, Anastasiia Makarova, Andreas Krause

How should we intervene on an unknown structural equation model to maximize a downstream variable of interest? This setting, also known as causal Bayesian optimization (CBO), has important applications in medicine, ecology, and manufacturing. Standard Bayesian optimization algorithms fail to effectively leverage the underlying causal structure. Existing CBO

Kota Hanzawa, Jumpei Matsumoto, Soshi Iimura, Yoshimitsu Kohama

The electronic transport properties of a highly hydrogen-substituted 1111-type SmFeAsO epitaxial film with high critical-temperature (Tc = 45 K) were investigated under high magnetic fields. By using a single-turn magnet generating up to 130 T, we clarified that the upper critical field ({\mu}0Hc2) of SmFeAsO0.65H0.35 is 120 T at the nearly low-temperature l

Philip Menz, Haissam Hanafi, Jörg Imbrock, Cornelia Denz

Flat band systems are usually associated to compact localized states (CLSs) resulting from the macroscopic degeneracy of eigenstates at the flat band energy. In case of singular flat bands, these conventional localized flat band states have been found to be incomplete leading to the existence of so-called noncontractible loop states (NLSs) with nontrivial re

Regina Schuster, Kathleen Gregory, Torsten Möller, Laura Koesten

Data visualizations play a critical role in both communicating scientific evidence about climate change and in stimulating engagement and action. To investigate how visualizations can be better utilized to communicate the complexities of climate change to different audiences, we conducted interviews with 17 experts in the fields of climate change, data visua

Zekai Xu, Mingyi Zhang, Jiayue Hou, Xing Gong

Incremental semantic segmentation(ISS) is an emerging task where old model is updated by incrementally adding new classes. At present, methods based on convolutional neural networks are dominant in ISS. However, studies have shown that such methods have difficulty in learning new tasks while maintaining good performance on old ones (catastrophic forgetting).

Piyush Kumar, Maria Inês Mendes Martins, Marianne Etzelmüller Bathen, Judith Woerle

Using positive muons as local probes implanted at low energy enables gathering information about the material of interest with nanometer depth resolution (low energy muon spin rotation spectroscopy (LE-$\mu$SR). In this work, we leverage the capabilities of LE-$\mu$SR to perform an investigation of the SiO$_\text{2}$-SiC interface. Thermally oxidized samples

Guillaume Krieger, Aravind Raji, Laurent Schlur, Gilles Versini

The recent discovery of a zero-resistance state in nickel-based compounds has generated a re-excitement about the long-standing problem in condensed matter of high-critical-temperature superconductivity, in light of the analogies between infinite-layer nickelates and cuprates. However, despite some formal valence and crystal symmetry analogies, the electroni

Mohamed Shahawy, Elhadj Benkhelifa

The traditional Neural Network-development process requires substantial expert knowledge and relies heavily on intuition and trial-and-error. Neural Architecture Search (NAS) frameworks were introduced to robustly search for network topologies, as well as facilitate the automated development of Neural Networks. While some optimization approaches -- such as G

Yang-yang Tan, Chuang Huang, Yong-rui Chen, Wei-jie Fu

Fixed-point equations in the functional renormalization group approach are integrated from large to vanishing field, where an asymptotic potential in the limit of large field is implemented as initial conditions. This approach allows us to obtain a global fixed-point potential with high numerical accuracy, that incorporates the correct asymptotic behavior in

Taner Dosluoglu, Martin MacDonald

Industry 4.0 has become a driver for the entire manufacturing industry. Smart systems have enabled 30% productivity increases and predictive maintenance has been demonstrated to provide a 50% reduction in machine downtime. So far, the solution has been based on data analytics which has resulted in a proliferation of sensing technologies and infrastructure fo

Junyi Bian, Xiaodi Huang, Hong Zhou, Shanfeng Zhu

Extracting summaries from long documents can be regarded as sentence classification using the structural information of the documents. How to use such structural information to summarize a document is challenging. In this paper, we propose GoSum, a novel graph and reinforcement learning based extractive model for long-paper summarization. In particular, GoSu

Sasa Prelovsek

A review of QCD-based theory approaches to study the heavy-flavor and exotic hadrons is given. The focus is on the results from lattice QCD and from lattice QCD complemented by effective field theories. Both approaches are first briefly introduced and applied in few examples. Then the status of various hadrons sectors is presented.

Fariba Karimi, Marcos Oliveira

Nominal assortativity (or discrete assortativity) is widely used to characterize group mixing patterns and homophily in networks, enabling researchers to analyze how groups interact with one another. Here we demonstrate that the measure presents severe shortcomings when applied to networks with unequal group sizes and asymmetric mixing. We characterize these

Youssef Dawoud, Arij Bouazizi, Katharina Ernst, Gustavo Carneiro

In microscopy image cell segmentation, it is common to train a deep neural network on source data, containing different types of microscopy images, and then fine-tune it using a support set comprising a few randomly selected and annotated training target images. In this paper, we argue that the random selection of unlabelled training target images to be anno

Zhihao Du, Shiliang Zhang, Siqi Zheng, Zhijie Yan

Recently, hybrid systems of clustering and neural diarization models have been successfully applied in multi-party meeting analysis. However, current models always treat overlapped speaker diarization as a multi-label classification problem, where speaker dependency and overlaps are not well considered. To overcome the disadvantages, we reformulate overlappe

A. L. Kataev, V. S. Molokoedov

In this work we consider the possibility of representing the perturbative series for renormalization group invariant quantities in QCD in the form of their decomposition in powers of the conformal anomaly $\beta(\alpha_s)/\alpha_s$ in the ${\rm{\overline{MS}}}$-scheme. We remind that such expansion is possible for the Adler function of the process of $e^+e^-

Kilian Fritsch, Victor Hariton, Kevin Schwarz, Nazar Kovalenko

Since its first demonstration in 2016, the multi-pass spectral broadening technique has covered impressive ranges of pulse energy (3 $\mu$J - 100 mJ) and peak power (4 MW - 100 GW). Energy scaling of this technique into the joule-level is currently limited by phenomena such as optical damage, gas ionization and spatio-spectral beam inhomogeneity. These limit

S. R. Das, P. Massopust, R. Radha

In this paper, we characterize the system of left translates $\{L_{(2k,l,m)}g:k,l,m\in\mathbb{Z}\}$, $g\in L^2(\mathbb{H})$, to be a frame sequence or a \emph{Riesz} sequence in terms of the twisted translates of the corresponding function $g^\lambda$. Here, $(\mathbb{H}$ denotes the Heisenberg group and $g^\lambda$ the inverse Fourier transform of $g$ with

Alejandro Bris, Nestor G. Gracia, Vicent Mateu

In this article we compute the cross section for the process $e^+e^- \to Q\overline Q+X$, with $Q$ a heavy quark, differential in a given event shape $e$ and the angle $\theta_T$ between the thrust axis and the beam direction. These observables are usually referred to as oriented event shapes, and it has been shown that the $\theta_T$ dependence can be split

Matheus H. Martins Costa, Jeroen van den Brink, Flavio S. Nogueira, Gastão I. Krein

We show that the Wilsonian formulation of the renormalization group (RG) defines a quantum channel acting on the momentum-space density matrices of a quantum field theory. This information theoretical property of the RG allows us to derive a remarkable consequence for the vacuum of theories at a fixed point: they have no entanglement between momentum scales.

Ho Suk, Taewoo Kim, Hyungbin Park, Pamul Yadav

Despite the rapid improvement of autonomous driving technology in recent years, automotive manufacturers must resolve liability issues to commercialize autonomous passenger car of SAE J3016 Level 3 or higher. To cope with the product liability law, manufacturers develop autonomous driving systems in compliance with international standards for safety such as

H. N. Smitha, M. van Noort, S. K. Solanki, J. S. Castellanos Durán

The current analysis is dedicated to a detailed investigation of the non-Local Thermodynamic Equilibrium (NLTE) effects influencing the formation of the Fe I 6173 A line, which is widely used by many instruments including the Helioseismic and Magnetic Imager (HMI) on-board the Solar Dynamics Observatory (SDO) and the Polarimetric and Helioseismic Imager on b

Javier Hualde, Morten Ørregaard Nielsen

In this chapter we present an overview of the main ideas and methods in the fractional integration and cointegration literature. We do not attempt to give a complete survey of this enormous literature, but rather a more introductory treatment suitable for a researcher or graduate student wishing to learn about this exciting field of research. With this aim,

Melinda Hagedorn, Florian Jarre

This note considers the momentum method by Polyak and the accelerated gradient method by Nesterov, both without line search but with fixed step length applied to strictly convex quadratic functions assuming that exact gradients are used and appropriate upper and lower bounds for the extreme eigenvalues of the Hessian matrix are known. Simple 2-d-examples sho

Patrik Lundström, Johan Öinert

Suppose that $R$ is an associative unital ring and that $E=(E^0,E^1,r,s)$ is a directed graph. Utilizing results from graded ring theory we show, that the associated Leavitt path algebra $L_R(E)$ is simple if and only if $R$ is simple, $E^0$ has no nontrivial hereditary and saturated subset, and every cycle in $E$ has an exit. We also give a complete descrip

Fabien Le Floc'h

What kind of implied volatility extrapolation is appropriate? Roger Lee proved that the Black-Scholes implied variance can not grow faster than linearly in log-moneyness. This paper investigates what happens in the Bachelier (or Normal) implied volatility world, making sure to cover the various aspects of vanilla option arbitrages.

Tania Robens

Although many suggestions for BSM searches at future colliders exist, most of them concentrate on additional scalars that have masses higher than the current SM scalar mass. I will give a short overview on the current status of models and searches for scalars with masses below this. This work is mainly based on arXiv:2203.08210, arXiv:2205.09687.

Vanamali Shastry

The hybrid mesons form a part of the exotic spectrum of the standard model. The recent observation of the isoscalar hybrid, called the $\eta_1(1855)$, provides an important step towards the completion of the $1^{-+}$ nonet. In the present work, we analyze the masses and two-body decays of the members of this nonet using a model hadronic Lagrangian. The isove

Max W. J. Beard, Ian M. McHardy, Kavita Kumari, Gulab C. Dewangan

We present a 140ks observation of NGC 4593 with XMM-Newton providing simultaneous and continuous PN X-ray and OM UV (UVW1 2910\AA) lightcurves which sample short-timescale variations better than previous observations. These observations were simultaneous with 22d of Swift X-ray and UV/optical monitoring, reported previously, and 4d of AstroSat X-ray (SXT), f

Krishna Kumar, Joseph Vantassel

We develop a PyTorch-based Graph Network Simulator (GNS) that learns physics and predicts the flow behavior of particulate and fluid systems. GNS discretizes the domain with nodes representing a collection of material points and the links connecting the nodes representing the local interaction between particles or clusters of particles. The GNS learns the in

T. Windeatt

Despite being effective in many application areas, Deep Neural Networks (DNNs) are vulnerable to being attacked. In object recognition, the attack takes the form of a small perturbation added to an image, that causes the DNN to misclassify, but to a human appears no different. Adversarial attacks lead to defences that are themselves subject to attack, and th

Hailong Gong, Zirui Li, Chao Lu, Guodong Du

Trajectory prediction is a fundamental problem and challenge for autonomous vehicles. Early works mainly focused on designing complicated architectures for deep-learning-based prediction models in normal-illumination environments, which fail in dealing with low-light conditions. This paper proposes a novel approach for trajectory prediction in low-illuminati

Angshuman Bhattacharya, Chaitanya J. Kulkarni

A classical result by Effros connects the barycentric decomposition of a state on a C*-algebra to the disintegration of the GNS representation of the state with respect to an orthogonal measure on the state space of the C*-algebra. In this note, we take this approach to the space of unital completely positive maps on a C*-algebra with values in B(H), connect

F. Vazart, C. Ceccarelli, D. Skouteris, N. Balucani

Despite the detection of numerous interstellar complex organic molecules (iCOMs) for decades, it is still a matter of debate whether they are synthesized in the gas-phase or on the icy surface of interstellar grains. In the past, molecular deuteration has been used to constrain the formation paths of small and abundant hydrogenated interstellar species. More

Angshuman Bhattacharya, Chaitanya J. Kulkarni

The space of weak expectations for a given representation of a (unital) separable C*-algebra is a compact convex set of (unital) completely positive maps in the BW topology, when it is non-empty. An application of the classical Choquet theory gives a barycentric decomposition of a weak expectation in that set. However, to complete the barycentric picture, on

Roman Bause, Arthur Christianen, Andreas Schindewolf, Immanuel Bloch

Collisional complexes, which are formed as intermediate states in molecular collisions, are typically short-lived and decay within picoseconds. However, in ultracold collisions involving bialkali molecules, complexes can live for milliseconds, completely changing the collision dynamics. This can lead to unexpected two-body loss in samples of nonreactive mole

Jiaji Zhao, Bingyan Jiang, Jinying Yang, Lujunyu Wang

In a magnetic metal, the Hall resistance is generally taken to be the sum of the ordinary Hall resistance and the anomalous Hall resistance. Here it is shown that this empirical relation is no longer valid when either the ordinary Hall angle or the anomalous Hall angle is not small. Using the proper conductivity relation, we reveal an unexpected magnetoresis

Puneet Sharma, Knut M. Heidemann, Helge Heuer, Steffen Muehle

Mobility is an indispensable part of modern human societies, but the dominance of motorized individual traffic (MIV, i.e., the private car) leads to a prohibitive waste of energy as well as other resources. Here we show that by combining a line service (e.g., railway) system with a fleet of ride-pooling shuttles connecting line stops to desired pick-up and d

Angshuman Bhattacharya, Chaitanya J. Kulkarni

In this article we define a special class of weak expectations for a representation of a separable unital C*-algebra, called decomposable weak expectation. We give necessary and sufficient conditions for such kind of weak expectations to exist for a given representation. Then we define decomposable measures on the state space of a C*-algebra and show that th

Shaowei Cai, Bohan Li, Xindi Zhang

Satisfiability Modulo Theories (SMT) refers to the problem of deciding the satisfiability of a formula with respect to certain background first order theories. In this paper, we focus on Satisfiablity Modulo Integer Arithmetic, which is referred to as SMT(IA), including both linear and non-linear integer arithmetic theories. Dominant approaches to SMT rely o

Kevin Issler, Roland Mitric, Jens Petersen

We present a novel method for the simulation of the vibration-induced autoionization dynamics in molecular anions in the framework of the quantum-classical surface hopping approach. Classical trajectories starting from quantum initial conditions are propagated on a quantum-mechanical potential energy surface while allowing for autoionization through transiti

Jonas H. Osório, Thiago D. Cabral, Eric Fujiwara, Marcos A. R. Franco

The research enterprise towards achieving high-performance hollow-core photonic crystal fibers has led to impressive advancements in the latest years. Indeed, using this family of fibers becomes nowadays an overarching strategy for building a multitude of optical systems ranging from beam delivery devices to optical sources and sensors. In most applications,

Huidong Hu, Ying D. Liu, Lakshmi Pradeep Chitta, Hardi Peter

On the Sun, Doppler shifts of bidirectional outflows from the magnetic-reconnection site have been found only in confined regions through spectroscopic observations. Without spatially resolved spectroscopic observations across an extended region, the distribution of reconnection and its outflows in the solar atmosphere cannot be made clear. Magnetic reconnec

Hideaki Takemura, Fumitaka Nakamura, Héctor G. Arce, Nicola Schneider

The mass distribution of dense cores is a potential key to understand the process of star formation. Applying dendrogram analysis to the CARMA-NRO Orion C$^{18}$O ($J$=1--0) data, we identify 2342 dense cores, about 22 \% of which have virial ratios smaller than 2, and can be classified as gravitationally bound cores. The derived core mass function (CMF) for

Chien-Yeah Seng, Mikhail Gorchtein

We analyze the axial $\gamma W$-box diagram for $I(J^P)=1(0^+)$ nuclei and provide a dispersion representation of the nuclear-structure correction $\delta_\text{NS}$ including its energy-dependent part. We also summarize useful isospin rotation formula and representations in nuclear theory that could facilitate the calculation of the parity-odd nuclear struc

S. Otten, A. Kario, W. A. J. Wessel. J. Leferink, H. H. J. ten Kate

Training of accelerator magnets is a costly and time consuming process. The number of training quenches must therefore be reduced to a minimum. We investigate training of impregnated Nb3Sn Rutherford cable in a small-scale experiment. The test involves a Rutherford cable impregnated in a meandering channel simulating the environment of a canted-cosine-theta

Jose Ameijeiras-Alonso

A new data-based smoothing parameter for circular kernel density (and its derivatives) estimation is proposed. Following the plug-in ideas, unknown quantities on an optimal smoothing parameter are replaced by suitable estimates. This paper provides a circular version of the well-known Sheather and Jones bandwidths (DOI: 10.1111/j.2517-6161.1991.tb01857.x), w

Lorenzo Campana, Mireille Bossy, Christophe Henry

In this work, we propose a model for the orientation of inertialess spheroidal particles suspended in turbulent flows. This model consists in a stochastic version of the Jeffery equation that can be included in a statistical Lagrangian description of particles suspended in a flow. It is compatible and coherent with turbulence models that are widely used in C

Komninos-John Plows, Xianguo Lu

Heavy Neutral Leptons (HNLs) with masses $\mathcal{O}(0.1 - 1\,\,\text{GeV}/c^{2})$ are promising candidates for the simultaneous explanation of the smallness of the observed neutrino masses as well as the matter-antimatter asymmetry in the observable Universe. These particles can be produced in the decay of hadrons typically produced in a neutrino beamline

Jan Aalmoes, Vasisht Duddu, Antoine Boutet

Group fairness and privacy are fundamental aspects in designing trustworthy machine learning models. Previous research has highlighted conflicts between group fairness and different privacy notions. We are the first to demonstrate the alignment of group fairness with the specific privacy notion of attribute privacy in a blackbox setting. Attribute privacy, q

Yulia V. Novakovskaya

Nonempirical modeling of hydrated single-layer graphene oxide (GO) fragments revealed that at least one, but substantial origin of the acidity of aqueous GO solutions is the dissociation in closely grouped and favorably H-bonded hydroxyls. The process can further be promoted by the adjacent $\pi$-conjugated carbon segments at the edges of GO flakes or their

Huigen Ye, Hongyan Wang, Hua Xu, Chengming Wang

Integer programming problems (IPs) are challenging to be solved efficiently due to the NP-hardness, especially for large-scale IPs. To solve this type of IPs, Large neighborhood search (LNS) uses an initial feasible solution and iteratively improves it by searching a large neighborhood around the current solution. However, LNS easily steps into local optima

Gil Einziger, Gabriel Scalosub, Carla Fabiana Chiasserini, Francesco Malandrino

Deploying services efficiently while satisfying their quality requirements is a major challenge in network slicing. Effective solutions place instances of the services' virtual network functions (VNFs) at different locations of the cellular infrastructure and manage such instances by scaling them as needed. In this work, we address the above problem and the

Zhen Li, Lingli Wang, Mofang Cheng, Cihui Pan

We present a efficient multi-view inverse rendering method for large-scale real-world indoor scenes that reconstructs global illumination and physically-reasonable SVBRDFs. Unlike previous representations, where the global illumination of large scenes is simplified as multiple environment maps, we propose a compact representation called Texture-based Lightin

Georgina Al-Badri, James B. Phillips, Rebecca J. Shipley, Nicholas C. Ovenden

We propose a continuum model for pattern formation, based on the multiphase model framework, to explore in vitro cell patterning within an extracellular matrix. We demonstrate that, within this framework, chemotaxis-driven cell migration can lead to formation of cell clusters and vascular-like structures in 1D and 2D respectively. The influence on pattern fo

Levente Rózsa, Unai Atxitia

The temperature dependence of mesoscopic spin-model parameters is derived in two-sublattice antiferromagnetically aligned systems based on Green's function theory. It is found that transversal spin correlations decrease the anisotropy terms while increasing the Heisenberg and Dzyaloshinsky--Moriya exchange interactions and the latter's contribution to the an

Yi Ding, Xinghua Zheng

We study the estimation of the high-dimensional covariance matrix andits eigenvalues under dynamic volatility models. Data under such modelshave nonlinear dependency both cross-sectionally and temporally. We firstinvestigate the empirical spectral distribution (ESD) of the sample covariancematrix under scalar BEKK models and establish conditions under which

Zhengmao He, Bin Zhao

In this paper, we first prove that the retract of a consonant space (or co-consonant space) is consonant (co-consonant). Using this result, some related results have obtained. Simultaneously, we proved that (1) the co-consonance of the Smyth powerspace implies the co-consonance of a topological space under a necessary condition; (2) the co-consonance of a to

Hee Sok Chung

We review the current status of heavy quarkonium production phenomenology based on nonrelativistic effective field theories, focusing on spin-triplet $S$-wave states such as $J/\psi$, $\psi(2S)$, and $\Upsilon$. We present some representative examples for heavy quarkonium production mechanisms proposed in the literature, which vary significantly depending on

O V Chernoyarov, S Dachian, Yu A Kutoyants

The problem of parameter estimation by i.i.d. observations of an inhomogeneous Poisson process is considered in situation of misspecification. The model is that of a Poissonian signal observed in presence of a homogeneous Poissonian noise. The intensity function of the process is supposed to have a cusp-type singularity at the change-point (the unknown momen

Stephane Kirsch, Paul Laurain

Here are the proofs of your article. $\bullet$ You can submit your corrections online or by fax. $\bullet$ For online submission please insert your corrections in the online correction form. Always indicate the line number to which the correction refers. $\bullet$ Please return your proof together with the permission to publish confirmation. $\bullet$ For fa

Nathan A. Brooks, Simon T. Powers, James M. Borg

As we transition to renewable energy sources, addressing their inflexibility during peak demand becomes crucial. It is therefore important to reduce the peak load placed on our energy system. For households, this entails spreading high-power appliance usage like dishwashers and washing machines throughout the day. Traditional approaches to spreading out usag

Carlos Maciel, Damon Mayaffre, Laurent Vanni

Is there an ADT method that can deal with non-aligned bilingual corpora? Does the textual genre exert a sufficiently strong constraint on the discourse that would make texts written in different languages comparable, provided they are of identical genre? To answer these two questions, one methodological, the other linguistic, this contribution gathers in a s

Eric Séré

The Dirac-Fock (DF) model replaces the Hartree-Fock (HF) approximation in quantum chemistry when relativistic effects cannot be neglected. Since the Dirac operator is not bounded from below, the notion of ground state is problematic in this model, and several definitions have been proposed in the literature. We give a new definition for the ground state of t

C. P. Felix, E. S. Moreira

This paper presents a toy model of a charged relativistic classical gas in flat spacetime of an arbitrary number of dimensions equipped with some ``pair production'' mechanism. Working with the microcanonical ensemble, the charge is taken to be conserved in contrast with the total number of ``particles'' plus ``antiparticles'' which varies with temperature $

Kohei Saijo, Tetsuji Ogawa

We present Self-Remixing, a novel self-supervised speech separation method, which refines a pre-trained separation model in an unsupervised manner. The proposed method consists of a shuffler module and a solver module, and they grow together through separation and remixing processes. Specifically, the shuffler first separates observed mixtures and makes pseu

Amr Khalifa, Michael C. Mozer, Hanie Sedghi, Behnam Neyshabur

Recent works demonstrate that early layers in a neural network contain useful information for prediction. Inspired by this, we show that extending temperature scaling across all layers improves both calibration and accuracy. We call this procedure "layer-stack temperature scaling" (LATES). Informally, LATES grants each layer a weighted vote during inference.

Shixu Meng

We consider the inverse medium scattering of reconstructing the medium contrast using Born data, including the full aperture, limited-aperture, and multi-frequency data. We propose data-driven basis functions for these inverse problems based on the generalized prolate spheroidal wave functions and related eigenfunctions. Such data-driven eigenfunctions are e

Ulf Danielsson, Oscar Henriksson, Daniel Panizo

In this paper we construct a stringy embedding of the dark bubble model of an expanding 4D cosmology with the help of branes rotating in extra dimensions. The universe rides a bubble which has nucleated in an unstable higher dimensional background. Our construction is therefore a string theoretical realization of Vilenkin's quantum cosmology. While the cosmo

Vrizlynn L. L. Thing

Smart sensors, devices and systems deployed in smart cities have brought improved physical protections to their citizens. Enhanced crime prevention, and fire and life safety protection are achieved through these technologies that perform motion detection, threat and actors profiling, and real-time alerts. However, an important requirement in these increasing

Ian M. Musson

This paper is a contribution to the study of the geometry of algebras related the Weyl groupoid initiated in \cite{M22}. The Nullstellensatz gives a bijection between radical ideals of such an algebra and their zero loci, the superalgebraic sets. Such sets are exactly the (Zariski) closed sets that are invariant under the action of a suitable groupoid, and t

Nicola Plutino, Francesco Berrilli, Dario Del Moro, Luca Giovannelli

Solar flares, along with other sun-originated events such as Coronal Mass Ejections, fast solar wind streams, and solar energetic particles are among the most relevant events in Space Weather. Moreover, solar flares are the most energetic processes that occur in our solar system. The in-depth study of their occurrence statistics, both over extended periods o

Francesco Stella, Qinghua Guan, Jinsong Leng, Cosimo Della Santina

Soft robot are celebrated for their propensity to enable compliant and complex robot-environment interactions. Soft robotic manipulators, or slender continuum structure robots have the potential to exploit these interactions to enable new exploration and manipulation capabilities and safe human-robot interactions. However, the interactions, or perturbations

Chen Su, Huanyuan Shan, Jiajun Zhang, Cheng Zhao

Weak lensing studies via cosmic voids are a promising probe of Modified Gravity (MG). Excess surface mass density (ESD) is widely used as a lensing statistic in weak lensing research. In this paper, we use the ray-tracing method to study the ESD around voids in simulations based on Cubic Galileon (CG) gravity. With the compilation of N-body simulation and ra

Benjamin Jourdain, Gilles Pagès

In this paper, we are interested in comparing solutions to stochastic Volterra equations for the convex order on the space of continuous $\R^d$-valued paths and for the monotonic convex order when $d=1$. Even if in general these solutions are neither semi-martingales nor Markov processes, we are able to exhibit conditions on their coefficients enabling the c

Rafael L. Delgado, Sebastian Steinbeißer, Michael Strickland, Johannes H. Weber

We extend the publicly available quantumfdtd code. It was originally intended for solving the time-independent three-dimensional Schr\"odinger equation via the finite-difference time-domain (FDTD) method and for extracting the ground, first, and second excited states. We (a) include the case of the relativistic Schr\"odinger equation and (b) add two optimize