March 2023 arXiv papers — page 11

Bo Zhang, Cong Huang, Haixu Zhang, Xiaoshan Bai

In this paper, a novel switching pushing skill algorithm is proposed to improve the efficiency of planar non-prehensile manipulation, which draws inspiration from human pushing actions and comprises two sub-problems, i.e., discrete decision-making of pushing point and continuous feedback control of pushing action. In order to solve the sub-problems above, a

Plastiras Demetriou, Gianluca Rizzi, Angela Madeo

In this paper, we propose an approach for describing wave propagation in finite-size microstructured metamaterials using a reduced relaxed micromorphic model. This method introduces an additional kinematic field with respect to the classical Cauchy continua, allowing to capture the effects of the underlying microstructure with a homogeneous model. We show th

Francisco José Maldonado Torralba

In this work we shall obtain sufficient conditions for the appearance of singularities in gravitational theories which propagate an extra vector degree of freedom, based on the known relaxations of the singularity theorems. We study the cases of a general Proca field and a vector theory with stable self-derivative interactions. In this study we show several

Lucas Beyer, Bo Wan, Gagan Madan, Filip Pavetic

There has been a recent explosion of computer vision models which perform many tasks and are composed of an image encoder (usually a ViT) and an autoregressive decoder (usually a Transformer). However, most of this work simply presents one system and its results, leaving many questions regarding design decisions and trade-offs of such systems unanswered. In

Swagat S. Mishra, Edmund J. Copeland, Anne M. Green

Primordial Black Holes (PBHs) may form in the early Universe, from the gravitational collapse of large density perturbations, generated by large quantum fluctuations during inflation. Since PBHs form from rare over-densities, their abundance is sensitive to the tail of the primordial probability distribution function (PDF) of the perturbations. It is therefo

Pratibha Gautam, Rajib Chattopadhyay, Gill Martin, Susmitha Joseph

What is the role of soil moisture in maintaining the land ITCZ during the active phase of the monsoon? This question has been addressed in this study by using ERA5 reanalysis datasets, and then we evaluate the question in the CFS model-free run. Like rainfall, soil moisture also show intraseasonal oscillation. Furthermore, the sub-seasonal and seasonal featu

Pierre-Victor Besson, Valérie Viet Triem Tong, Gilles Guette, Guillaume Piolle

In this paper we propose a novel way of deploying vulnerable architectures for defense and research purposes, which aims to generate deception platforms based on the formal description of a scenario. An attack scenario is described by an attack graph in which transitions are labeled by ATT&CK techniques or procedures. The state of the attacker is modeled as

Haozhen Li, Xinyu Gu, Boyuan Zhang, Dongliang Li

Deep Learning (DL)-based channel state information (CSI) feedback is a promising technique for the transmitter to accurately acquire the CSI of massive multiple-input multiple-output (MIMO) systems. As critical concerns about DL-based physical layer applications, the intra-domain generalizability affected by dataset bias and inter-domain robustness in data d

Namit Mahajan, Dayanand Mishra

This article explores the calculation of non-perturbative parameters present in the matrix element of semileptonic inclusive $B$ decays. These are important for the inclusive determination of the Cabbibo-Kobayashi-Maskawa (CKM) parameters in the standard model. We focus on calculating the rate for radiative inclusive decay, $B\to X_c\ell \bar{\nu}_{\ell}\gam

Amin Muhammad Shoib, Jabeen Summaira, Changbo Wang, Abdul Jabbar

Content-based fashion image retrieval (CBFIR) has been widely used in our daily life for searching fashion images or items from online platforms. In e-commerce purchasing, the CBFIR system can retrieve fashion items or products with the same or comparable features when a consumer uploads a reference image, image with text, sketch or visual stream from their

Kuan Cheng, Zhengzhong Jin, Xin Li, Zhide Wei

This work continues the study of linear error correcting codes against adversarial insertion deletion errors (insdel errors). Previously, the work of Cheng, Guruswami, Haeupler, and Li \cite{CGHL21} showed the existence of asymptotically good linear insdel codes that can correct arbitrarily close to $1$ fraction of errors over some constant size alphabet, or

Claude Cibils, Marcelo Lanzilotta, Eduardo N. Marcos, Andrea Solotar

We consider stratifying ideals of finite dimensional algebras in relation with Morita contexts. A Morita context is an algebra built on a data consisting of two algebras, two bimodules and two morphisms. For a strongly stratifying Morita context - or equivalently for a strongly stratifying ideal - we show that Han's conjecture holds if and only if it holds f

Zhitao Yang, Zhongang Cai, Haiyi Mei, Shuai Liu

Synthetic data has emerged as a promising source for 3D human research as it offers low-cost access to large-scale human datasets. To advance the diversity and annotation quality of human models, we introduce a new synthetic dataset, SynBody, with three appealing features: 1) a clothed parametric human model that can generate a diverse range of subjects; 2)

Nankai Lin, Hongbin Zhang, Menglan Shen, Yu Wang

Grammatical error correction (GEC) is a challenging task of natural language processing techniques. While more attempts are being made in this approach for universal languages like English or Chinese, relatively little work has been done for low-resource languages for the lack of large annotated corpora. In low-resource languages, the current unsupervised GE

David Winderl, Qunsheng Huang, Christian B. Mendl

The synthesis of quantum circuits from phase gadgets in the ZX-calculus facilitates quantum circuit optimization. Our work provides an alternative formulation for the architecture-aware synthesis algorithm of PauliOpt by replacing the stochastic approach of PauliOpt with a heuristic based search and utilizes a divide and conquer method to synthesize an optim

Chaofei Liu, Pedro Portugal, Yi Gao, Jie Yang

Coulomb blockade occurs for electrons tunneling into nanoislands because of the quantization of charge. Here, using spectroscopy measurements of nonmagnetic islands grown on a high-Tc superconductor [one-unit-cell (1-UC) FeSe], we systematically investigate the dynamical Coulomb blockade (DCB), which is found to reflect the Cooper pairing potential in the su

Connor McIsaac, Charlie Hoy, Ian Harry

Gravitational-wave signals from compact binary coalescences are most efficiently identified through matched filter searches, which match the data against a pre-generated bank of gravitational-wave templates. Although different techniques for performing the matched filter, as well as generating the template bank, exist, currently all modelled gravitational-wa

Qiang Gao, Maxim Tsoi

We study the angular dependence of ferromagnetic resonance (FMR) in Ni$_{36}$Fe$_{64}$ wires using both traditional microwave-absorption and electrical-detection techniques. In our experiments we apply a static magnetic field at an angle $\theta$ with respect to the wire, while the microwave current, which is responsible for driving FMR, is always flowing al

Giovanni Alessandrini, Romina Gaburro, Eva Sincich

We consider the inverse problem of determining, the possibly anisotropic, conductivity of a body by means of the so called local Neumann to Dirichlet map on a curved portion $\Sigma$ of the boundary. Motivated by the uniqueness result for piecewise constant anisotropic conductivities proved in \cite{Al-dH-G}, we provide a H\"{o}lder stability estimate on $\S

Bo Li

We show that symmetrically padded convolution can be analytically inverted via DFT. We comprehensively analyze several different symmetric and anti-symmetric padding modes and show that multiple cases exist where the inversion can be achieved. The implementation is available at \url{https://github.com/prclibo/iconv_dft}.

Sahar Diskin, Joshua Erde, Mihyun Kang, Michael Krivelevich

It is known that many different types of finite random subgraph models undergo quantitatively similar phase transitions around their percolation thresholds, and the proofs of these results rely on isoperimetric properties of the underlying host graph. Recently, the authors showed that such a phase transition occurs in a large class of regular high-dimensiona

Nobu Kishimoto, Yoshio Tsutsumi

In this article, we consider the kinetic derivative nonlinear Schr\"odinger equation (KDNLS), which is a one-dimensional nonlinear Schr\"odinger equation with a cubic derivative nonlinear term containing the Hilbert transformation. For the Cauchy problem both on the real line and on the circle, we apply the short-time Fourier restriction method to establish

Nobu Kishimoto, Yoshio Tsutsumi

We consider the kinetic derivative nonlinear Schr\"odinger equation, which is a one-dimensional nonlinear Schr\"odinger equation with a cubic derivative nonlinear term containing the Hilbert transformation. In our previous work, we proved small-data global well-posedness of the Cauchy problem on the torus in Sobolev space $H^s$ for $s>1/2$ by combining the F

Yuxuan Zhang, Chao Xu, Howard H. Yang, Xijun Wang

This paper proposes a client selection (CS) method to tackle the communication bottleneck of federated learning (FL) while concurrently coping with FL's data heterogeneity issue. Specifically, we first analyze the effect of CS in FL and show that FL training can be accelerated by adequately choosing participants to diversify the training dataset in each roun

ATLAS Collaboration

A key open question in the study of multi-particle production in high-energy $pp$ collisions is the relationship between the "ridge'' - observed azimuthal correlations between particles in the underlying event that extend over all rapidities - and hard or semi-hard scattering processes. In particular, it is not known whether jets or their soft fragments are

ESSnuSB Collaboration, A. Alekou, E. Baussan, A. K. Bhattacharyya

ESSnuSB is a design study for an experiment to measure the CP violation in the leptonic sector at the second neutrino oscillation maximum using a neutrino beam driven by the uniquely powerful ESS linear accelerator. The reduced impact of systematic errors on sensitivity at the second maximum allows for a very precise measurement of the CP violating parameter

Vishnu Rajendran S, Willow Mandil, Simon Parsons, Amir Ghalamzan E

This paper presents a novel soft tactile skin (STS) technology operating with sound waves. In this innovative approach, the sound waves generated by a speaker travel in channels embedded in a soft membrane and get modulated due to a deformation of the channel when pressed by an external force and received by a microphone at the end of the channel. The sensor

Wenping Jin, Fei Guo, Li Zhu

In the realm of machine learning, the study of anomaly detection and localization within image data has gained substantial traction, particularly for practical applications such as industrial defect detection. While the majority of existing methods predominantly use Convolutional Neural Networks (CNN) as their primary network architecture, we introduce a nov

Guanyang He, Yu Li, Yuxuan Lei, Andreas Kreisel

Despite decades of research in spatially confined superconducting systems to understand the modification of superconductivity from reduced length scales, the investigation of the quantum confinement effect on high-temperature superconductors remains an outstanding challenge. Here, we report scanning tunneling spectroscopy measurements on laterally confined F

Francisco López, Lars Karlsson, Paolo Bientinesi

The product of a matrix chain consisting of $n$ matrices can be computed in $C_{n-1}$ (Catalan's number) different ways, each identified by a distinct parenthesisation of the chain. The best algorithm to select a parenthesisation that minimises the cost runs in $O(n \log n)$ time. Approximate algorithms run in $O(n)$ time and find solutions that are guarante

Marco Venturini, Francesco Freda, Emanuele Miotto, Mauro Conti

Crypto-ransomware attacks have been a growing threat over the last few years. The goal of every ransomware strain is encrypting user data, such that attackers can later demand users a ransom for unlocking their data. To maximise their earning chances, attackers equip their ransomware with strong encryption which produce files with high entropy values. Davies

Igor V. Blinov, Chunli Huang, Nemin Wei, Qin Wei

At a large displacement field, in rhomboedral and Bernal-stacked graphene a normal paramagnetic state transitions to a correlated state. Recent experiments showed that such systems have several phase transitions as a function of the carrier density. The phase adjacent to a paramagnetic state has anomalously high resistance and reduced degeneracy of the Fermi

Satyam Panda, Sanghamitra Das, Basuraj Bhowmik, Budhaditya Hazra

A novel algorithm for real-time modal identification in linear vibrating systems with complex modes is introduced, utilizing a combination of first order eigen-perturbation and second order separation techniques. In practical settings, structures with complex modes are frequently encountered and their presence often poses a challenge in accurately estimating

Aki Ruhtinas, Ilari J. Maasilta

We demonstrate a direct writing method for the fabrication of planar Josephson junctions from high quality superconducting niobium titanium nitride (NbTiN) thin films, by creating local disorder using focused He-ion beam irradiation in a helium ion microscope. We show that we can control the suppression of superconductivity in NbTiN as a function of the heli

Naruhiko Aizawa, Haru-Tada Sato

We discuss the Curtright-Zachos (CZ) deformation of the Virasoro algebra and its extentions in terms of magnetic translation (MT) group in a discrete Bloch electron system, so-called the tight binding model (TBM), as well as in its continuous system. We verify that the CZ generators are essentially composed of a specific combination of MT operators represent

Niklas Berndt, Henri Lotze

Let F be a fixed finite obstruction set of graphs and G be a graph revealed in an online fashion, node by node. The online Delayed F-Node-Deletion Problem (F-Edge-Deletion Problem}) is to keep G free of every H in F by deleting nodes (edges) until no induced subgraph isomorphic to any graph in F can be found in G. The task is to keep the number of deletions

Chunyu Li, Juan Carlos Verduzco, Brian H. Lee, Robert J. Appleton

The response of materials to dynamical, or shock, loading is important to planetary science, aerospace engineering, and energetic materials. Thermal-activated processes, including chemical reactions and phase transitions, are significantly accelerated by the localization of the energy deposited into hotspots. These results from the interaction of a supersoni

Sanath K Devalapurkar

In this article, we study the topological Hochschild homology of $\mathbf{E}_3$-forms of truncated Brown-Peterson spectra, taken relative to certain Thom spectra $X(p^n)$ (introduced by Ravenel and used by Devinatz-Hopkins-Smith in the proof of the nilpotence theorem). We prove analogues of B\"okstedt's calculations $\mathrm{THH}(\mathbf{F}_p) \simeq \mathbf

Boya Wang, Wouter Lueks, Justinas Sukaitis, Vincent Graf Narbel

Humanitarian aid-distribution programs help bring physical goods to people in need. Traditional paper-based solutions to support aid distribution do not scale to large populations and are hard to secure. Existing digital solutions solve these issues, at the cost of collecting large amount of personal information. This lack of privacy can endanger recipients'

Shengjie Zhu, Xiaoming Liu

Dense geometric matching determines the dense pixel-wise correspondence between a source and support image corresponding to the same 3D structure. Prior works employ an encoder of transformer blocks to correlate the two-frame features. However, existing monocular pretraining tasks, e.g., image classification, and masked image modeling (MIM), can not pretrain

Oleksii Sokoliuk, Simran Arora, Subhrat Praharaj, Alexander Baransky

We investigate the exponential $f(Q)$ symmetric teleparallel gravitation, namely $f(Q)=Q+\alpha Q_0(1-e^{-\beta\sqrt{Q/Q_0}})$ using \texttt{ME-GADGET} code to probe the structure formation with box sizes $L_{\mathrm{box}}=10/100$ Mpc$/h$ and middle resolution $N_p^{1/3}=512$. To reproduce viable cosmology within the aforementioned modified gravity theory, w

Jinan A. Jasim, Maysam Rahi Ali, Emad A. Kuff

In this study, a new sort of transform known as (Kuffi- Abbas- Jawad transform) or KAJ- integral transformation is introduced. We introduce and explore important KAJ- transformation features and applications in cryptography. KAJ- transformation is used for encryption and inverse KAJ- transformation is used for decryption; an example is provided to illustrate

P. Agostinetti, S. Dal Bello, F. Dinh, A. Ferrara

The Divertor Tokamak Test (DTT) is a new experimental facility whose construction is starting in Frascati, Rome, Italy; its main goals are improving the understanding of plasma-wall interactions and supporting the development of ITER and DEMO. DTT will be equipped with a Neutral Beam Injector (NBI) based on negative deuterium ions, designed to inject 10 MW o

Kaya Turgut, Helin Dutagaci

Data organization via forming local regions is an integral part of deep learning networks that process 3D point clouds in a hierarchical manner. At each level, the point cloud is sampled to extract representative points and these points are used to be centers of local regions. The organization of local regions is of considerable importance since it determine

Efstathios Konstantinos Chrontsios Garitsis, Aimo Hinkkanen

Quadrilaterals in the complex plane play a significant part in the theory of planar quasiconformal mappings. Motivated by the geometric definition of quasiconformality, we prove that every quadrilateral with modulus in an interval $[1/K, K]$, where $K>1$, contains a disk lying in its interior, of radius depending only on the internal distances between the pa

Ziyu Liu

Given a topologically transitive subshift of finite type, the $u$-dimension of the $\alpha$-level set of the quotient of Birkhoff sums is a well-studied topic. In this paper, we consider the uniform $\alpha$-level set, which is a subset of the $\alpha$-level set. We shall show that the $\alpha$-level set and the uniform $\alpha$-level set have the same $u$-d

Marvin Brieger, Stefan Mitsch, André Platzer

This paper introduces a uniform substitution calculus for $\mathsf{dL}_\text{CHP}$, the dynamic logic of communicating hybrid programs. Uniform substitution enables parsimonious prover kernels by using axioms instead of axiom schemata. Instantiations can be recovered from a single proof rule responsible for soundness-critical instantiation checks rather than

Esteban Marquer, Miguel Couceiro

Analogical inference is a remarkable capability of human reasoning, and has been used to solve hard reasoning tasks. Analogy based reasoning (AR) has gained increasing interest from the artificial intelligence community and has shown its potential in multiple machine learning tasks such as classification, decision making and recommendation with competitive r

Evans Kiptoo Korir, Zsolt Vizi

Introduction. It is well known that social contact patterns differ from country to country. This variation coincides with significant socioeconomic heterogeneity that complicates the design of effective non-pharmaceutical interventions. This study examined how socioeconomic heterogeneity in selected African countries might be factored in to explain better so

Mia S. Tackney, Elizabeth Williamson, Derek G. Cook, Elizabeth Limb

Clinical trials that investigate interventions on physical activity often use accelerometers to measure step count at a very granular level, often in 5-second epochs. Participants typically wear the accelerometer for a week-long period at baseline, and for one or more week-long follow-up periods after the intervention. The data is usually aggregated to provi

Meena Sanjay Babulal, Sunil Kumar Gauttam, Aditya Maheshwari

In this paper, we study the L\'evy process time-changed by independent L\'evy subordinators, namely, the incomplete gamma subordinator, the $\epsilon$-jumps incomplete gamma subordinator and tempered incomplete gamma subordinator. We derive their important distributional properties such as mean, variance, correlation, tail probabilities and fractional moment

Johannes Rettberg, Dominik Wittwar, Patrick Buchfink, Robin Herkert

Projection-based model order reduction of dynamical systems usually introduces an error between the high-fidelity model and its counterpart of lower dimension. This unknown error can be bounded by residual-based methods, which are typically known to be highly pessimistic in the sense of largely overestimating the true error. This work applies two improved er

Ilkka Rautiainen, Lauri Parviainen, Veera Jakoaho, Sami Äyrämö

We propose a new model for comprehensively monitoring the health status of individuals by calculating a personal health index. The central framework of the model is the International Classification of Functioning, Disability and Health (ICF) developed by the World Health Organization. The model is capable of handling incomplete and heterogeneous data sets co

Aritra Pal, Koushik Ray

Euclidean conformal integrals for an arbitrary number of points in any dimension are evaluated. Conformal transformations in the Euclidean space can be formulated as the Moebius group in terms of Clifford algebras. This is used to interpret conformal integrals as functions on the configuration space of points on the Euclidean space, solving linear differenti

A. A. Mushtukov, S. S. Tsygankov, J. Poutanen, V. Doroshenko

X Persei is a persistent low-luminosity X-ray pulsar of period of $\sim$835 s in a Be binary system. The field strength at the neutron star surface is not known precisely, but indirect signs indicate a magnetic field above $10^{13}$ G, which makes the object one of the most magnetized known X-ray pulsars. Here we present the results of observations X Persei

Anton Thielmann, Quentin Seifert, Arik Reuter, Elisabeth Bergherr

Extracting and identifying latent topics in large text corpora has gained increasing importance in Natural Language Processing (NLP). Most models, whether probabilistic models similar to Latent Dirichlet Allocation (LDA) or neural topic models, follow the same underlying approach of topic interpretability and topic extraction. We propose a method that incorp

Raj Kishor Joshi, Indranil Chattopadhyay

We study the effect of plasma composition on the dynamics and morphology of the relativistic astrophysical jets. Our work is based on a relativistic total variation diminishing (TVD) simulation code. We use a relativistic equation of state in the simulation code which accounts for the thermodynamics of a multispecies plasma which is a mixture of electrons, p

Carlos-Emiliano González-Gallardo, Emanuela Boros, Nancy Girdhar, Ahmed Hamdi

Large language models (LLMs) have been leveraged for several years now, obtaining state-of-the-art performance in recognizing entities from modern documents. For the last few months, the conversational agent ChatGPT has "prompted" a lot of interest in the scientific community and public due to its capacity of generating plausible-sounding answers. In this pa

Nicola Zaupa, Giulia Giordano, Isabelle Queinnec, Sophie Tarbouriech

We propose necessary and sufficient conditions for the synchronization of $N$ identical single-input-single-output (SISO) systems, connected through a directed graph {without imposing any assumption on the graph interconnection}. We consider both the continuous-time and the discrete-time case, and we provide conditions that {are equivalent to} the uniform gl

Dylan Bansard-Tresse, Jorge Milhazes Freitas

We prove an abstract result establishing that one can obtain the convergence of Rare Events Point Processes counting the number of orbital visits to a sequence of shrinking target sets from the convergence of corresponding point processes for some induced system and matching shadowing shrinking sets inside the base of the inducing scheme. We apply this resul

Hendrik Herrmann, Chin-Yu Hsiao, George Marinescu, Wei-Chuan Shen

Let $X$ be a compact strictly pseudoconvex embeddable CR manifold and let $T_P$ be the Toeplitz operator on $X$ associated with some first order pseudodifferential operator $P$. We consider $\chi_k(T_P)$ the functional calculus of $T_P$ by any rescaled cut-off function $\chi$ with compact support in the positive real line. In this work, we show that $\chi_k(

Edward G. A. Henderson, Marcel van Herk, Eliana M. Vasquez Osorio

Convolutional neural networks (CNNs) are increasingly being used to automate segmentation of organs-at-risk in radiotherapy. Since large sets of highly curated data are scarce, we investigated how much data is required to train accurate and robust head and neck auto-segmentation models. For this, an established 3D CNN was trained from scratch with different

Kathyrn R. Fair, Omar A. Guerrero

For many applications of agent-based models (ABMs), an agent's age influences important decisions (e.g. their contribution to/withdrawal from pension funds, their level of risk aversion in decision-making, etc.) and outcomes in their life cycle (e.g. their susceptibility to disease). These considerations make it crucial to accurately capture the age distribu

Huiyu Duan, Wei Shen, Xiongkuo Min, Danyang Tu

Transformers have shown significant effectiveness for various vision tasks including both high-level vision and low-level vision. Recently, masked autoencoders (MAE) for feature pre-training have further unleashed the potential of Transformers, leading to state-of-the-art performances on various high-level vision tasks. However, the significance of MAE pre-t

Sergey Foss, Dmitry Korshunov, Zbigniew Palmowski

We derive subexponential tail asymptotics for the distribution of the maximum of a compound renewal process with linear component and of a L\'evy process, both with negative drift, over random time horizon $\tau$ that does not depend on the future increments of the process. Our asymptotic results are uniform over the whole class of such random times. Particu

Stefano M. Nicoletti, Milan Lopuhaä-Zwakenberg, E. Moritz Hahn, Mariëlle Stoelinga

Safety-critical infrastructures must operate in a safe and reliable way. Fault tree analysis is a widespread method used for risk assessment of these systems: fault trees (FTs) are required by, e.g., the Federal Aviation Administration and the Nuclear Regulatory Commission. In spite of their popularity, little work has been done on formulating structural que

Hanna Bogucka, Bartosz Kopras

This paper discusses the uberization of telecommunication and computing network services. The Uber-like platform business model is discussed for application in future networks together with interesting analogies of communication and computing (2C) resource-sharing models. The economy of this sharing is discussed, and some recommendations for network uberizat

J. R. Nascimento, Gonzalo J. Olmo, A. Yu. Petrov, P. J. Porfirio

We consider the coupling of the metric-affine bumblebee gravity model to scalar matter and calculate the lower-order contributions to two-point functions of bumblebee and scalar fields in the weak gravity approximation. We also obtain the one-loop effective potentials for both scalar and vector fields.

ATLAS Collaboration

A determination of the jet energy scale is presented using proton$-$proton collision data with a centre-of-mass energy of $\sqrt{s}=13$ TeV, corresponding to an integrated luminosity of 140 $\mbox{fb\(^{-1}\)}$ collected using the ATLAS detector at the LHC. Jets are reconstructed using the ATLAS particle-flow method that combines charged-particle tracks and

Sandeep Kumar Acharya, Bryce Cyr, Jens Chluba

The ARCADE radio excess and EDGES measurement remain puzzling. A link between the two has been previously considered, however, in this work we highlight an important related effect that was not analyzed in detail before. By performing cosmological thermalization calculations with soft photon injection using {\tt CosmoTherm}, we show that for the 21 cm signal

Pooja Prajod, Matteo Lavit Nicora, Matteo Malosio, Elisabeth André

Attention (and distraction) recognition is a key factor in improving human-robot collaboration. We present an assembly scenario where a human operator and a cobot collaborate equally to piece together a gearbox. The setup provides multiple opportunities for the cobot to adapt its behavior depending on the operator's attention, which can improve the collabora

Belle Collaboration, L. Cao, F. Bernlochner, K. Tackmann

The first simultaneous determination of the absolute value of the Cabibbo-Kobayashi-Maskawa matrix element $V_{ub}$ using inclusive and exclusive decays is performed with the full Belle data set at the $\Upsilon(4S)$ resonance, corresponding to an integrated luminosity of 711 fb${}^{-1}$. We analyze collision events in which one $B$ meson is fully reconstruc

François-Marie Le Régent, Pierre Rouchon

Consider an open quantum system governed by a Gorini, Kossakowski, Sudarshan, Lindblad (GKSL) master equation with two times-scales: a fast one, exponentially converging towards a linear subspace of quasi-equilibria; a slow one resulting from perturbations (small arbitrary decoherence and Hamiltonian dynamics). Usually adiabatic elimination is performed in t

Robert Thomas, Haoyang Li, Jude Laverock, Krishna C. Balram

Understanding and mitigating optical loss is critical to the development of high-performance photonic integrated circuits (PICs). Especially in high refractive index contrast compound semiconductor (III-V) PICs, surface absorption and scattering can be a significant loss mechanism, and needs to be suppressed. Here, we quantify the optical propagation loss du

Chiara Castello, Olga Polverino, Paolo Santonastaso, Ferdinando Zullo

Sidon spaces have been introduced by Bachoc, Serra and Z\'emor in 2017 as the $q$-analogue of Sidon sets. The interest on Sidon spaces has increased quickly, especially after the work of Roth, Raviv and Tamo in 2018, in which they highlighted the correspondence between Sidon spaces and cyclic subspace codes. Up to now, the known constructions of Sidon Spaces

Jan H. Hoekstra, Bence Cseppentő, Gerben I. Beintema, Maarten Schoukens

Artificial neural networks (ANN) have been shown to be flexible and effective function estimators for identification of nonlinear state-space models. However, if the resulting models are used directly for nonlinear model predictive control (NMPC), the resulting nonlinear optimization problem is often overly complex due the size of the network, requires the u

Irene Schimperna, Lalo Magni

This paper develops a control scheme, based on the use of Long Short-Term Memory neural network models and Nonlinear Model Predictive Control, which guarantees recursive feasibility with slow time variant set-points and disturbances, input and output constraints and unmeasurable state. Moreover, if the set-point and the disturbance are asymptotically constan

Paul Creutz, Nikita Evseev

We show that Sobolev maps with values in a dual Banach space can be characterized in terms of weak derivatives in a weak* sense. Since every metric space embeds isometrically into a dual Banach space, this implies a characterization of metric space valued Sobolev maps in terms of such derivatives. Furthermore, we investigate for which target spaces Sobolev m

Emmanuel Witrant, Ioan DorÉ Landau, Marie-Pierre Vaillant

Electric throttle valves represent a challenge for control design, as their dynamics involve strong nonlinearities, characterized by an asymmetric hysteresis. Carrying experiments on multiple valves, a large variability in the characteristics of each valve and erratic steady-state behaviors can also be noticed, impairing classical model-based control strateg

Cong Li, Jianfeng Zhang, Yang Wang, Hongxiong Liu

The study of interaction between electromagnetism and elementary particles is a long-standing topic in physics. Likewise, the connection between particle physics and emergent phenomena in condensed matter physics is a recurring theme and condensed matter physics has often provided a platform for investigating the interplay between particles and fields in cas

Lorenzo Maggi, Ryo Koblitz, Qiping Zhu, Matthew Andrews

The standard beam management procedure in 5G requires the user equipment (UE) to periodically measure the received signal reference power (RSRP) on each of a set of beams proposed by the basestation (BS). It is prohibitively expensive to measure the RSRP on all beams and so the BS should propose a beamset that is large enough to allow a high-RSRP beam to be

Ofer Neufeld, Nicolas Tancogne-Dejean, Hannes Hübener, Umberto De Giovannini

High harmonic generation (HHG) has developed in recent years as a promising tool for ultrafast materials spectroscopy. At the forefront of these advancements, several works proposed to use HHG as an all-optical probe for topology of quantum matter by identifying its signatures in the emission spectra. However, it remains unclear if such spectral signatures a

Adrien Banse, Licio Romao, Alessandro Abate, Raphaël M. Jungers

We introduce an adaptive refinement procedure for smart, and scalable abstraction of dynamical systems. Our technique relies on partitioning the state space depending on the observation of future outputs. However, this knowledge is dynamically constructed in an adaptive, asymmetric way. In order to learn the optimal structure, we define a Kantorovich-inspire

Esfandiar Nava-Yazdani, Felix Ambellan, Martin Hanik, Christoph von Tycowicz

We propose a generic spatiotemporal framework to analyze manifold-valued measurements, which allows for employing an intrinsic and computationally efficient Riemannian hierarchical model. Particularly, utilizing regression, we represent discrete trajectories in a Riemannian manifold by composite B\' ezier splines, propose a natural metric induced by the Sasa

Yichuan Zhang, Changrong Zhu

Treatment rate has always been one of the most important factors affecting the spread of infectious diseases. In this paper, we study a treatment function SIR model with treatment rate related to the maximum treatment capacity, whose infection rate is also saturated nonlinear. By calculating and analyzing based on planar dynamic system, the existence and sta

Zijian Zhu, Yichi Zhang, Hai Chen, Yinpeng Dong

3D object detection is an essential perception task in autonomous driving to understand the environments. The Bird's-Eye-View (BEV) representations have significantly improved the performance of 3D detectors with camera inputs on popular benchmarks. However, there still lacks a systematic understanding of the robustness of these vision-dependent BEV models,

João Luís Rosa, Caio F. B. Macedo, Diego Rubiera-Garcia

In this work we consider the observational properties of compact boson stars with self-interactions orbited by isotropically emitting (hot-spot) sources and optically thin accretion disks. We consider two families of boson stars supported by quartic and sixth-order self-interaction potentials, and choose three samples of each of them in growing compactness;

Jacopo de Berardinis, Albert Meroño-Peñuela, Andrea Poltronieri, Valentina Presutti

The annotation of music content is a complex process to represent due to its inherent multifaceted, subjectivity, and interdisciplinary nature. Numerous systems and conventions for annotating music have been developed as independent standards over the past decades. Little has been done to make them interoperable, which jeopardises cross-corpora studies as it

R. J. Hudspith, D. Mohler

We use $n_f=2+1$ Wilson-clover gauge-field ensembles from the CLS consortium in a Lattice NRQCD setup to predict the binding energy of a $I(J^P)=0(1^+)$ $ud\bar{b}\bar{b}$ tetraquark and a $\frac{1}{2}(1^+)$ $\ell s\bar{b}\bar{b}$ tetraquark. We determine the binding energies with respect to the relevant $BB^*$ and $B_sB^*$ thresholds respectively to be $112

Yifu Liu, Xiaoxia Li, Zhiling Luo, Wei Zhou

Weakly-supervised temporal action localization aims to localize action instances in untrimmed videos with only video-level supervision. We witness that different actions record common phases, e.g., the run-up in the HighJump and LongJump. These different actions are defined as conjoint actions, whose rest parts are definite phases, e.g., leaping over the bar

Lin Chen, Changrong Zhu

In this paper, the dynamical behaviors of a Leslie-Gower predator-prey model with Allee effect and fear effect are studied. First, we use Blow-Up method to explore the stability of the original point. Analyze the local stability of the non-negative equilibriums of the system. Taking the growth rate of predators as the Hopf bifurcation parameters. And give th

Qingfeng Li, Songlin Lyu, Chen Ji, Bingwei Long

A new effective field theory has been developed to describe shallow $P$-wave resonances using nonlocal, momentum-dependent two-body potentials. This approach is expected to facilitate many-body calculations and has been demonstrated to converge and to be renormalizable in perturbative calculations at subleading orders. The theory has been applied to the neut

Adrián P. Bustamante, Rafael de la Llave

We consider standard-like/Froeschl\'e maps with a dissipation and nonlinear perturbation. That is \[ T_\varepsilon(p,q) = \left( (1 - \gamma \varepsilon^3) p + \mu + \varepsilon V'(q), q + (1 - \gamma \varepsilon^3) p + \mu + \varepsilon V'(q) \mod 2 \pi \right) \] where $p \in \mathbb{R}^D$, $q \in 2 \pi \mathbb{T}^D$ are the dynamical variables. The $\mu \

Muhammad F. Emzir, Zheng Zhao, Lahouari Cheded, Simo Särkkä

The automatic projection filter is a recently developed numerical method for projection filtering that leverages sparse-grid integration and automatic differentiation. However, its accuracy is highly sensitive to the accuracy of the cumulant-generating function computed via the sparse-grid integration, which in turn is also sensitive to the choice of the bij

Ferdinand Ihringer

We construct a new family of strongly regular graphs with the same parameters as the strongly regular graphs $D_{5,5}(q)$. The construction can be seen as a variant of the construction of twisted Grassmann graphs by Van Dam and Koolen.

Chao Liu, Jun yang

We consider one dimensional generalized parabolic Cahn-Hilliard equation $$ u_t=-\partial_{xx}\big[\partial_{xx}u-W'(u)\big]+W''(u)\big[\partial_{xx} u -W'(u)\big], \qquad \forall\, (t,x)\in [0,+\infty)\times {\mathbb R}, $$ where the function $W(\cdot)$ is the standard double-well potential. For any given positive integer $k\geq2$, we construct a solution $

Mads Greisen Højlund, Alberto Zoccante, Ove Christiansen

We present equations of motion (EOMs) for general time-dependent wave functions with exponentially parametrized biorthogonal basis sets. The equations are fully bivariational in the sense of the time-dependent bivariational principle (TDBVP) and offer an alternative, constraint free formulation of adaptive basis sets for bivariational wave functions. We simp

Andrea Poltronieri, Aldo Gangemi

In this paper we propose the Music Note Ontology, an ontology for modelling music notes and their realisation. The ontology addresses the relation between a note represented in a symbolic representation system, and its realisation, i.e. a musical performance. This work therefore aims to solve the modelling and representation issues that arise when analysing

Ziyan Li, Xueheng Kuang, Alejandro Jimeno-Pozo, Héctor Sainz-Cruz

Motivated by the recent experimental detection of superconductivity in Bernal bilayer (AB) and rhombohedral trilayer (ABC) graphene, we study the emergence of superconductivity in multilayer graphene based on a Kohn-Luttinger (KL)-like mechanism in which the pairing glue is the screened Coulomb interaction. We find that electronic interactions alone can driv

Pilhyeon Lee, Taeoh Kim, Minho Shim, Dongyoon Wee

Temporal action detection aims to predict the time intervals and the classes of action instances in the video. Despite the promising performance, existing two-stream models exhibit slow inference speed due to their reliance on computationally expensive optical flow. In this paper, we introduce a decomposed cross-modal distillation framework to build a strong