October 2022 arXiv papers — page 124

René Bødker Christensen, Petar Popovski

We define a variation on the well-known problem of private message transmission. This new problem called private randomness agreement (PRA) gives two participants access to a public, authenticated channel alongside the main channels, and the 'message' is not fixed a priori. Instead, the participants aim to agree on a random string completely unknown to a com

A. Capetti, B. Balmaverde, R. D. Baldi, S. Baum

This seventh paper of the MUse RAdio Loud Emission lines Snapshot (MURALES) project presents the results of the observations obtained with the VLT/MUSE integral field spectrograph of 3C radio sources and discusses the optical spectral properties of the nuclei of 26 objects with 0.3<z<0.82 (median redshift 0.51). At these redshifts the H$\alpha$ and [NII] emi

Lili Tao, Alexandru-Petre Cazan, Senad Ibraimoski, Sean Moran

The use of packaged libraries can significantly shorten the software development cycle by improving the quality and readability of code. In this paper, we present a recommendation engine called Librarian for open source libraries. A candidate library package is recommended for a given context if: 1) it has been frequently used with the imported libraries in

Ruolin Xing, Xiao Ma, Ao Zhou, Schahram Dustdar

Recent developments in the aerospace industry have led to a dramatic reduction in the manufacturing and launch costs of low Earth orbit satellites. The new trend enables the paradigm shift of satellite-terrestrial integrated networks with global coverage. In particular, the integration of 5G communication systems and satellites has the potential to restructu

Zifan Jiang, Amit Moryossef, Mathias Müller, Sarah Ebling

This paper presents work on novel machine translation (MT) systems between spoken and signed languages, where signed languages are represented in SignWriting, a sign language writing system. Our work seeks to address the lack of out-of-the-box support for signed languages in current MT systems and is based on the SignBank dataset, which contains pairs of spo

Peyman Afshani, Rasmus Killman, Kasper Green Larsen

In colored range counting (CRC), the input is a set of points where each point is assigned a ``color'' (or a ``category'') and the goal is to store them in a data structure such that the number of distinct categories inside a given query range can be counted efficiently. CRC has strong motivations as it allows data structure to deal with categorical data. Ho

Yusuke Namekawa, Kouji Kashiwa, Hidefumi Matsuda, Akira Ohnishi

We investigate efficiency of a gauge-covariant neural network and an approximation of the Jacobian in optimizing the complexified integration path toward evading the sign problem in lattice field theories. For the construction of the complexified integration path, we employ the path optimization method. The $2$-dimensional $\text{U}(1)$ gauge theory with the

Cagri Toraman, Oguzhan Ozcelik, Furkan Şahinuç, Fazli Can

The rapid dissemination of misinformation through online social networks poses a pressing issue with harmful consequences jeopardizing human health, public safety, democracy, and the economy; therefore, urgent action is required to address this problem. In this study, we construct a new human-annotated dataset, called MiDe22, having 5,284 English and 5,064 T

John Morgan, Rajan Chhetri, Ron Ekers

We present a catalogue of over 7000 sources from the GLEAM survey which have significant structure on sub-arcsecond scales at 162MHz. The compact nature of these sources was detected and quantified via their Interplanetary Scintillation (IPS) signature, measured in interferometric images from the Murchison Widefield Array. The advantage of this approach is t

Carlo Collari

A result of Corfield, Sati, and Schreiber asserts that $\mathfrak{gl}_n$-weight systems associated to the defining representation are quantum states. In this short note we extend this result to all $\mathfrak{gl}_n$-weight systems corresponding to labeling by symmetric and exterior powers of the defining representation.

Longhui Yu, Tianyang Hu, Lanqing Hong, Zhen Liu

It has been observed that neural networks perform poorly when the data or tasks are presented sequentially. Unlike humans, neural networks suffer greatly from catastrophic forgetting, making it impossible to perform life-long learning. To address this issue, memory-based continual learning has been actively studied and stands out as one of the best-performin

Zeqiong Lv, Chao Qian, Gary G. Yen, Yanan Sun

Evolutionary computation-based neural architecture search (ENAS) is a popular technique for automating architecture design of deep neural networks. Despite its groundbreaking applications, there is no theoretical study for ENAS. The expected hitting time (EHT) is one of the most important theoretical issues, since it implies the average computational time co

Wenyan Ma, Lipeng Zhu, Rui Zhang

In this paper, we propose a new multiple-input multiple-output (MIMO) communication system with movable antennas (MAs) to exploit the antenna position optimization for enhancing the capacity. Different from conventional MIMO systems with fixed-position antennas (FPAs), the proposed system can flexibly change the positions of transmit/receive MAs, such that t

Kotaro Murakami, Yutaro Akahoshi, Sinya Aoki, Takumi Doi

We study decuplet baryons from meson-baryon interactions in lattice QCD, in particular, $\Delta$ and $\Omega$ baryons from P-wave $I=3/2$ $N\pi$ and $I=0$ $\Xi\bar{K}$ interactions, respectively. Interaction potentials are calculated in the HAL QCD method using 3-quark-type source operators at $m_{\pi} \approx 410~\textrm{MeV}$ and $m_{K} \approx 635~\textrm

Felipe Tobar, Elsa Cazelles, Taco de Wolff

We present a computationally-efficient strategy to initialise the hyperparameters of a Gaussian process (GP) avoiding the computation of the likelihood function. Our strategy can be used as a pretraining stage to find initial conditions for maximum-likelihood (ML) training, or as a standalone method to compute hyperparameters values to be plugged in directly

Linhai Zhuo, Yuqian Fu, Jingjing Chen, Yixin Cao

Given sufficient training data on the source domain, cross-domain few-shot learning (CD-FSL) aims at recognizing new classes with a small number of labeled examples on the target domain. The key to addressing CD-FSL is to narrow the domain gap and transferring knowledge of a network trained on the source domain to the target domain. To help knowledge transfe

Chenxia Li, Ruoyu Guo, Jun Zhou, Mengtao An

A large amount of document data exists in unstructured form such as raw images without any text information. Designing a practical document image analysis system is a meaningful but challenging task. In previous work, we proposed an intelligent document analysis system PP-Structure. In order to further upgrade the function and performance of PP-Structure, we

Adrian Dumitru, Heikki Mäntysaari, Risto Paatelainen

The non-forward eikonal scattering matrix for dipole-proton scattering at high energy obtains an imaginary part due to a $C$-odd three gluon exchange. We present numerical estimates for the perturbative Odderon amplitude as a function of dipole size, impact parameter, their relative azimuthal angle, and light-cone momentum cutoff $x$. The proton is approxima

Zongping Gong, Tommaso Guaita, J. Ignacio Cirac

We consider free fermions living on lattices in arbitrary dimensions, where hopping amplitudes follow a power-law decay with respect to the distance. We focus on the regime where this power is larger than the spatial dimension (i.e., where the single particle energies are guaranteed to be bounded) for which we provide a comprehensive series of fundamental co

Remko Fermin, Bob de Wit and, Jan Aarts

The magnetic field dependent critical current $I_{\text{c}}(B)$ of a Josephson junction is determined by the screening currents in its electrodes. In macroscopic junctions, a local vector potential drives the currents, however, in thin film planar junctions, with electrodes of finite size and various shapes, they are governed by non-local electrodynamics. Th

Nicolas Forget, Sophie N. Parragh

In the bi-objective branch-and-bound literature, a key ingredient is objective branching, i.e. to create smaller and disjoint sub-problems in the objective space, obtained from the partial dominance of the lower bound set by the upper bound set. When considering three or more objective functions, however, applying objective branching becomes more complex, an

Kevin Buchin, Will Evans, Fabrizio Frati, Irina Kostitsyna

In this paper, we investigate crossing-free 3D morphs between planar straight-line drawings. We show that, for any two (not necessarily topologically equivalent) planar straight-line drawings of an $n$-vertex planar graph, there exists a piecewise-linear crossing-free 3D morph with $O(n^2)$ steps that transforms one drawing into the other. We also give some

Vicente Villanueva, Alberto D. Bolatto, Stuart Vogel, Tobias Brown

We measure the molecular-to-atomic gas ratio, $R_{\rm mol}$, and the star formation rate (SFR) per unit molecular gas mass, SFE$_{\rm mol}$, in 38 nearby galaxies selected from the Virgo Environment Traced in CO (VERTICO) survey. We determine their scale-lengths for the molecular and stellar components and find a roughly 3:5 ratio between them compared to $\

Zhengwen Zhang, Jinjin Gu, Junhua Zhao, Jianwei Huang

To limit global warming to pre-industrial levels, global governments, industry and academia are taking aggressive efforts to reduce carbon emissions. The evaluation of anthropogenic carbon dioxide (CO$_2$) emissions, however, depends on the self-reporting information that is not always reliable. Society need to develop an objective, independent, and generali

Matteo Lapucci, Christian Kanzow

This paper provides a theoretical and numerical investigation of a penalty decomposition scheme for the solution of optimization problems with geometric constraints. In particular, we consider some situations where parts of the constraints are nonconvex and complicated, like cardinality constraints, disjunctive programs, or matrix problems involving rank con

Monika Eisenmann, Tony Stillfjord

In this paper, we combine the operator splitting methodology for abstract evolution equations with that of stochastic methods for large-scale optimization problems. The combination results in a randomized splitting scheme, which in a given time step does not necessarily use all the parts of the split operator. This is in contrast to deterministic splitting s

Zhuorong Li, Daiwei Yu

There has been a recent surge in single-step adversarial training as it shows robustness and efficiency. However, a phenomenon referred to as ``catastrophic overfitting" has been observed, which is prevalent in single-step defenses and may frustrate attempts to use FGSM adversarial training. To address this issue, we propose a novel method, Stable and Effici

Paul Schmitt, Pallabi Paul, Weiwei Li, Zilong Wang

Nonlinear optical phenomena enable novel photonic and optoelectronic applications. Especially metallic nanoparticles and thin films with nonlinear optical properties offer the potential for micro-optical system integration. For this purpose, new nonlinear materials need to be continuously identified, investigated, and utilized for nonlinear optical applicati

Maximilien Barbier, Christopher J. Fewster, Arseni Goussev, Gregory Morozov

Comment on "Backflow in relativistic wave equations" by I. Bialynicki-Birula, Z. Bialynicka-Birula, and S. Augustynowicz [Journal of Physics A: Mathematical and Theoretical, volume 55, page 255702 (2022)].

Latifah Abduh, Ioannis Ivrissimtzis

The study of bias in Machine Learning is receiving a lot of attention in recent years, however, few only papers deal explicitly with the problem of race bias in face anti-spoofing. In this paper, we present a systematic study of race bias in face anti-spoofing with three key characteristics: the focus is on analysing potential bias in the bona fide errors, w

Yu Wei Tan, Louiz Kim-Chan, Anthony Halim, Anand Bhojan

We introduce a novel distributed rendering approach to generate high-quality graphics in thin-client games and VR applications. Many mobile devices have limited computational power to achieve ray tracing in real-time. Hence, hardware-accelerated cloud servers can perform ray tracing instead and have their output streamed to clients in remote rendering. Apply

Yu Wei Tan, Xiaohan Cui, Anand Bhojan

For a foreground object in motion, details of its background which would otherwise be hidden are uncovered through its inner blur. This paper presents a novel hybrid motion blur rendering technique combining post-process image filtering and hardware-accelerated ray tracing. In each frame, we advance rays recursively into the scene to retrieve background info

Yu Wei Tan, Nicholas Chua, Clarence Koh, Anand Bhojan

Signed distance fields (SDFs) are a form of surface representation widely used in computer graphics, having applications in rendering, collision detection and modelling. In interactive media such as games, high-resolution SDFs are commonly produced offline and subsequently loaded into the application, representing rigid meshes only. This work develops a nove

Chakkrit Kaeonikhom, Hooshyar Assadullahi, Jascha Schewtschenko, David Wands

We explore the bounds that can be placed on interactions between cold dark matter and vacuum energy, with equation of state $w=-1$, using state-of-the-art cosmological observations. We consider linear perturbations about a simple background model where the energy transfer per Hubble time, $Q/H$, is a general linear function of the dark matter density, $\rho_

Henna Koivusalo, Lingmin Liao, Ian Morris, Michal Rams

We calculate the Hausdorff dimension of shrinking target sets of symbolic balls in generic affine iterated function systems with matrix norms bounded by $\tfrac 12$. Relative to earlier works of e.g. Barany and Troscheit, and Koivusalo and Ramirez, we impose only very mild condition, known as complete reducibility, on the iterated function system. We also ge

Yu Wei Tan, Xiaohan Cui, Anand Bhojan

Motion blur is commonly used in game cinematics to achieve photorealism by modelling the behaviour of the camera shutter and simulating its effect associated with the relative motion of scene objects. A common real-time post-process approach is spatial sampling, where the directional blur of a moving object is rendered by integrating its colour based on velo

Ruibo Liu, Jason Wei, Shixiang Shane Gu, Te-Yen Wu

Successful and effective communication between humans and AI relies on a shared experience of the world. By training solely on written text, current language models (LMs) miss the grounded experience of humans in the real-world -- their failure to relate language to the physical world causes knowledge to be misrepresented and obvious mistakes in their reason

Haoning Wu, Chaofeng Chen, Liang Liao, Jingwen Hou

The increased resolution of real-world videos presents a dilemma between efficiency and accuracy for deep Video Quality Assessment (VQA). On the one hand, keeping the original resolution will lead to unacceptable computational costs. On the other hand, existing practices, such as resizing and cropping, will change the quality of original videos due to the lo

S. A. Kadam, B. Mishra, Jackson Levi Said

All degrees of freedom related to the torsion scalar can be explored by analysing, the $f(T,T_G)$ gravity formalism where, $T$ is a torsion scalar and $T_G$ is the teleparallel counterpart of the Gauss-Bonnet topological invariant term. The well-known Noether symmetry approach is a useful tool for selecting models that are motivated at a fundamental level an

Naman Agarwal, Prateek Jain, Suhas Kowshik, Dheeraj Nagaraj

In this work, we consider the problem of collaborative multi-user reinforcement learning. In this setting there are multiple users with the same state-action space and transition probabilities but with different rewards. Under the assumption that the reward matrix of the $N$ users has a low-rank structure -- a standard and practically successful assumption i

Alain Mazzolo, Cécile Monthus

The non-equilibrium Fokker-Planck dynamics in an arbitrary force field $\vec f(\vec r)$ in dimension $N$ is revisited via the correspondence with the non-hermitian quantum mechanics in a scalar potential $V(\vec r)$ and a vector potential $\vec A(\vec r)$. The relevant parameters of irreversibility are then the $\frac{N(N-1)}{2}$ magnetic matrix elements $B_

Jean-François Coulombel, Antoine Benoit

We study the stability of the two-dimensional Lax-Wendroff scheme with a stabilizer that approximates solutions to the transport equation. The problem is first analyzed in the whole space in order to show that the so-called energy method yields an optimal stability criterion for this finite difference scheme. We then deal with the case of a half-space when t

Shane Rupert Koscielniak

Before AI and neural nets, the excitement was about iterative learning control (ILC): the idea to train robots to perform repetitive tasks or train a system to reject quasi-periodic disturbances. The excitement waned after the discovery of "learning transients" in systems which satisfy the ILC asymptotic convergence (AC) stability criteria. The transients ma

Baptiste Chatelier, Luc Le Magoarou, Getachew Redieteab

In modern communication systems, channel state information is of paramount importance to achieve capacity. It is then crucial to accurately estimate the channel. It is possible to perform SISO-OFDM channel estimation using sparse recovery techniques. However, this approach relies on the use of a physical wave propagation model to build a dictionary, which re

Ashwin Agrawal, Vishal Singh, Martin Fischer

Despite the Digital Twin (DT) concept being in the industry for a long time, it remains ambiguous, unable to differentiate itself from information models, general computing, and simulation technologies. Part of this confusion stems from previous studies overlooking the DT's bidirectional nature, that enables the shift of agency (delegating control) from huma

Peng Xu, Zhiyuan Chen, Jiankun Wang, Max Q. -H. Meng

Extrinsic manipulation, a technique that enables robots to leverage extrinsic resources for object manipulation, presents practical yet challenging scenarios. Particularly in the context of extrinsic manipulation on a supporting plane, regrasping becomes essential for achieving the desired final object poses. This process involves sequential operation steps

Alexander V. Gheorghiu, David J. Pym

We give a novel approach to proving soundness and completeness for a logic (henceforth: the object-logic) that bypasses truth-in-a-model to work directly with validity. Instead of working with specific worlds in specific models, we reason with eigenworlds (i.e., generic representatives of worlds) in an arbitrary model. This reasoning is captured by a sequent

Mohamed Barakat, Robin Brüser, Claus Fieker, Tobias Huber

We investigate the reduction of Feynman integrals to master integrals using Gr\"obner bases in a rational double-shift algebra Y in which the integration-by-parts (IBP) relations form a left ideal. The problem of reducing a given family of integrals to master integrals can then be solved once and for all by computing the Gr\"obner basis of the left ideal for

Bruno Dinis, Étienne Miquey

In this paper we propose a new approach to realizability interpretations for nonstandard arithmetic. We deal with nonstandard analysis in the context of (semi)intuitionistic realizability, focusing on the Lightstone-Robinson construction of a model for nonstandard analysis through an ultrapower. In particular, we consider an extension of the $\lambda$-calcul

Ji Li, Jörg Feikes, Tom Mertens, Edward Rial

Modern synchrotron light sources are often characterized with high-brightness synchrotron radiation from insertion devices. Inevitably, insertion devices introduce nonlinear distortion to the beam motion. Symplectic tracking is crucial to study the impact, especially for the low- and medium-energy storage rings. This paper uses a Robinson wiggler as an examp

Alexander V. Gheorghiu, David J. Pym

Proof-theoretic semantics (P-tS) is the approach to meaning in logic based on 'proof' (as opposed to 'truth'). There are two major approaches to P-tS: proof-theoretic validity (P-tV) and base-extension semantics (B-eS). The former is a semantics of arguments, and the latter is a semantics of logical constants. This paper demonstrates that the B-eS for intuit

Roman Chaban, Olga Taran, Joakim Tutt, Yury Belousov

Copy detection pattern (CDP) is a novel solution for products' protection against counterfeiting, which gains its popularity in recent years. CDP attracts the anti-counterfeiting industry due to its numerous benefits in comparison to alternative protection techniques. Besides its attractiveness, there is an essential gap in the fundamental analysis of CDP au

Andrew Mummery

The leading order Green's function solutions of the general relativistic thin disc equations are computed, using a pseudo-Newtonian potential and asymptotic Laplace mode matching techniques. This solution, valid for a vanishing ISCO stress, is constructed by ensuring that it reproduces the leading order asymptotic behaviour of the near-ISCO, Newtonian, and g

Kwing Hei Li

This report presents a formalization of May's theorem in the proof assistant Coq. It describes how the theorem statement is first translated into Coq definitions, and how it is subsequently proved. Various aspects of the proof and related work are discussed. To the best of the author's knowledge, this project is the first documented attempt in mechanizing Ma

Madhura Ghosh Dastidar, Gniewomir Sarbicki, Vidya Praveen Bhallamudi

In the following paper, we discuss a possible detection of non-locality in two-mode light states in the Bell protocol, where the local observables are constructed using displacement operators, implemented by Mach-Zender Interferometers fed by strong coherent states. We report numerical results showing that maximizing the Braunstein-Caves Chained Bell (BCCB)

Siyao Peng, Yang Janet Liu, Amir Zeldes

This document provides extensive guidelines and examples for Rhetorical Structure Theory (RST) annotation in Mandarin Chinese. The guideline is divided into three sections. We first introduce preprocessing steps to prepare data for RST annotation. Secondly, we discuss syntactic criteria to segment texts into Elementary Discourse Units (EDUs). Lastly, we prov

Astrid Barreiro, Gabriele Liga, Alex Alvarado

A normalized batch gradient descent optimizer is proposed to improve the first-order regular perturbation coefficients of the Manakov equation, often referred to as kernels. The optimization is based on the linear parameterization offered by the first-order regular perturbation and targets enhanced low-complexity models for the fiber channel. We demonstrate

Lucca Kühner, Fedja J. Wendisch, Alexander A. Antonov, Johannes Bürger

The realization of lossless metasurfaces with true chirality crucially requires the fabrication of three-dimensional structures, constraining their feasibility for experiments and hampering practical implementations. Even though the three-dimensional assembly of metallic nanostructures has been demonstrated previously, the resulting plasmonic resonances suff

Supriyo Mandal, Abyayananda Maiti

Traditional Collaborative Filtering (CF) based methods are applied to understand the personal preferences of users/customers for items or products from the rating matrix. Usually, the rating matrix is sparse in nature. So there are some improved variants of the CF method that apply the increasing amount of side information to handle the sparsity problem. Onl

Maksym Andriushchenko, Aditya Varre, Loucas Pillaud-Vivien, Nicolas Flammarion

We showcase important features of the dynamics of the Stochastic Gradient Descent (SGD) in the training of neural networks. We present empirical observations that commonly used large step sizes (i) lead the iterates to jump from one side of a valley to the other causing loss stabilization, and (ii) this stabilization induces a hidden stochastic dynamics orth

Alexander V. Gheorghiu, David J. Pym

Proof-theoretic semantics (P-tS) is the paradigm of semantics in which meaning in logic is based on proof (as opposed to truth). A particular instance of P-tS for intuitionistic propositional logic (IPL) is its base-extension semantics (B-eS). This semantics is given by a relation called support, explaining the meaning of the logical constants, which is para

Yatai Ji, Junjie Wang, Yuan Gong, Lin Zhang

Multimodal semantic understanding often has to deal with uncertainty, which means the obtained messages tend to refer to multiple targets. Such uncertainty is problematic for our interpretation, including inter- and intra-modal uncertainty. Little effort has studied the modeling of this uncertainty, particularly in pre-training on unlabeled datasets and fine

Ivan Chajda, Miroslav Kolařík, Helmut Länger

We prove that the 18-element non-lattice orthomodular poset depicted in the paper is the smallest one and unique up to isomorphism. Since not every Boolean poset is orthomodular, we consider the class of the so-called generalized orthomodular posets introduced by the first and third author in a previous paper. We show that this class contains all Boolean pos

Sam Coy, Artur Czumaj, Christian Scheideler, Philipp Schneider

We consider the problem of computing routing schemes in the $\mathsf{HYBRID}$ model of distributed computing where nodes have access to two fundamentally different communication modes. In this problem nodes have to compute small labels and routing tables that allow for efficient routing of messages in the local network, which typically offers the majority of

Iris Dominguez-Catena, Daniel Paternain, Mikel Galar

Facial Expression Recognition (FER) uses images of faces to identify the emotional state of users, allowing for a closer interaction between humans and autonomous systems. Unfortunately, as the images naturally integrate some demographic information, such as apparent age, gender, and race of the subject, these systems are prone to demographic bias issues. In

Masaaki Nishino, Kengo Nakamura, Norihito Yasuda

Machine learning technologies have been used in a wide range of practical systems. In practical situations, it is natural to expect the input-output pairs of a machine learning model to satisfy some requirements. However, it is difficult to obtain a model that satisfies requirements by just learning from examples. A simple solution is to add a module that ch

Reihaneh Torkzadehmahani, Reza Nasirigerdeh, Daniel Rueckert, Georgios Kaissis

In learning tasks with label noise, improving model robustness against overfitting is a pivotal challenge because the model eventually memorizes labels, including the noisy ones. Identifying the samples with noisy labels and preventing the model from learning them is a promising approach to address this challenge. When training with noisy labels, the per-cla

K. Öcal, G. Sanguinetti, R. Grima

The complexity of mathematical models in biology has rendered model reduction an essential tool in the quantitative biologist's toolkit. For stochastic reaction networks described using the Chemical Master Equation, commonly used methods include time-scale separation, the Linear Mapping Approximation and state-space lumping. Despite the success of these tech

Sunwoo Kim, Minyoung Choe, Jaemin Yoo, Kijung Shin

Group interactions are prevalent in a variety of areas. Many of them, including email exchanges, chemical reactions, and bitcoin transactions, are directional, and thus they are naturally modeled as directed hypergraphs, where each hyperarc consists of the set of source nodes and the set of destination nodes. For directed graphs, which are a special case of

Sander Beckers, Hana Chockler, Joseph Y. Halpern

As autonomous systems rapidly become ubiquitous, there is a growing need for a legal and regulatory framework to address when and how such a system harms someone. There have been several attempts within the philosophy literature to define harm, but none of them has proven capable of dealing with with the many examples that have been presented, leading some t

Dicle Zengin Çamurdan, Burcu Özkardeş

This study aims at timing the eclipses of the binary star TU UMi. The times of minima are taken from the literature, from our observations in April 2004 and from TESS observations between 2019 and 2022. The orbital period analysis of the system indicates that there is a cyclic oscillation with an amplitude of 0.0081d and a period of 9.03 yr, accompanied by a

Lipeng Zhu, Wenyan Ma, Rui Zhang

In this paper, we propose a novel antenna architecture called movable antenna (MA) to improve the performance of wireless communication systems. Different from conventional fixed-position antennas (FPAs) that undergo random wireless channel variation, the MAs with the capability of flexible movement can be deployed at positions with more favorable channel co

P. L. Silvestrelli, A. Seif, S. Subashchandrabose, A. Ambrosetti

We investigate from first principles screening effects in endohedral complexes when small molecules, characterized by a finite electronic dipole moment, such as HF, LiF, NaCl, and H$_2$O, are encapsulated into different nanoscale cages. We find that screening effects crucially depend on the nature of the intramolecular bonds of the cage: screening is maximum

Maria Maffei, Cyril Elouard, Bruno O. Goes, Benjamin Huard

Anomalous weak values and Wigner function's negativity are well known witnesses of quantum contextuality. We show that these effects occur when analyzing the energetics of a single qubit gate generated by a resonant coherent field traveling in a waveguide. The buildup of correlations between the qubit and the field is responsible for bounds on the gate fidel

Cosimo Bambi

The analysis of the properties of the X-ray radiation emitted from geometrically thin accretion disks around black holes can be a powerful tool to test General Relativity in the strong field regime. This chapter reviews the state-of-the-art of gravity tests with black hole X-ray data. So far, most efforts have been devoted to test the Kerr hypothesis - namel

Qiang Pan, Haonan Tong, Jie Lv, Tao Luo

In this paper, the problem of semantic-based efficient image transmission is studied over the Internet of Vehicles (IoV). In the considered model, a vehicle shares massive amount of visual data perceived by its visual sensors to assist other vehicles in making driving decisions. However, it is hard to maintain a high reliable visual data transmission due to

Alex J. Chan, Mihaela van der Schaar

Consider making a prediction over new test data without any opportunity to learn from a training set of labelled data - instead given access to a set of expert models and their predictions alongside some limited information about the dataset used to train them. In scenarios from finance to the medical sciences, and even consumer practice, stakeholders have d

Piotr B. Mucha, Jan Peszek

The paper examines the problems related to the well-posedness of the Cucker-Smale model with communication restricted to the $q$-closest neighbors, known also as the Cucker-Dong model. With agents oscillating on the boundary of different clusters, the system becomes difficult to precisely define, which leads to further problems with kinetic limits as the num

Niklas Gard, Anna Hilsmann, Peter Eisert

Applications in the field of augmented reality or robotics often require joint localisation and 6D pose estimation of multiple objects. However, most algorithms need one network per object class to be trained in order to provide the best results. Analysing all visible objects demands multiple inferences, which is memory and time-consuming. We present a new s

Jeremiah D. Deng

For energy-harvesting sensor nodes, rechargeable batteries play a critical role in sensing and transmissions. By coupling two simple Markovian queue models in a delay-tolerant networking setting, we consider the problem of battery sizing for these sensor nodes to operate effectively: given the intended energy depletion and overflow probabilities, how to deci

T. A. Stuber, T. Löhne, S. Wolf

Aims. We analyze whether the effects of secular perturbations, originating from a substellar companion, on the dust dynamics in a debris disk can be investigated with spatially resolved observations. Methods. We numerically simulated the collisional evolution of narrow and eccentric cold planetesimal belts around a star of spectral type A3V that are secularl

Wolfgang Quapp, Josep Maria Bofill

We propose a new but simpler explanation of the phases of a Frenkel-Kontorova chain of atoms, and we demonstrate it by examples. Combined with this, we present a criticism of the theory of so-called commensurate and incommensurate states, especially for finite chains. We reject the putative observation of an Aubry-phase transition in a finite chain.

Ermiyas Birihanu, Jiyan Mahmud, Péter Kiss, Adolf Kamuzora

Content delivery networks (CDNs) are the backbone of the Internet and are key in delivering high quality video on demand (VoD), web content and file services to billions of users. CDNs usually consist of hierarchically organized content servers positioned as close to the customers as possible. CDN operators face a significant challenge when analyzing billion

Loic Themyr, Clément Rambour, Nicolas Thome, Toby Collins

Transformer models achieve state-of-the-art results for image segmentation. However, achieving long-range attention, necessary to capture global context, with high-resolution 3D images is a fundamental challenge. This paper introduces the Full resolutIoN mEmory (FINE) transformer to overcome this issue. The core idea behind FINE is to learn memory tokens to

P. Gaulme, T. Borkovits, T. Appourchaux, K. Pavlovski

KIC 7955301 is a hierarchical triple system with eclipse timing and depth variations discovered by the Kepler mission. It is composed of a non-eclipsing primary star at the bottom of the red giant branch on a 209-day orbit with a K/G-type main-sequence inner eclipsing binary, orbiting in 15.3 days. This system was noted for the large amplitude of its eclipse

Wuti Xiong

In this paper, we propose a study of the cross-domain few-shot object detection (CD-FSOD) benchmark, consisting of image data from a diverse data domain. On the proposed benchmark, we evaluate state-of-art FSOD approaches, including meta-learning FSOD approaches and fine-tuning FSOD approaches. The results show that these methods tend to fall, and even under

Rostislav Duda, Moein N. Ivaki, Isac Sahlberg, Kim Pöyhönen

Discrete-time quantum walks, quantum generalizations of classical random walks, provide a framework for quantum information processing, quantum algorithms and quantum simulation of condensed matter systems. The key property of quantum walks, which lies at the heart of their quantum information applications, is the possibility for a parametric quantum speed-u

Artem E. Shitikov, Ilya I. Lykov, Oleg V. Benderov, Dmitry A. Chermoshentsev

Self-injection locking of a diode laser to a high-quality-factor microresonator is widely used for frequency stabilization and linewidth narrowing. We constructed several microresonator-based laser sources with measured instantaneous linewidths of 1 Hz and used them for investigation and implementation of the self-injection locking effect. We studied analyti

Đorđe Žikelić, Mathias Lechner, Thomas A. Henzinger, Krishnendu Chatterjee

We study the problem of learning controllers for discrete-time non-linear stochastic dynamical systems with formal reach-avoid guarantees. This work presents the first method for providing formal reach-avoid guarantees, which combine and generalize stability and safety guarantees, with a tolerable probability threshold $p\in[0,1]$ over the infinite time hori

Su-Ping Chen, Pei-Hong Gu

The standard model left-handed neutrinos and several right-handed neutrinos can obtain a tiny Dirac mass matrix through their mixings with relatively heavy Dirac fermions. In this Dirac seesaw scenario, the mixings involving the left-handed neutrinos can be allowed much larger than those involving the right-handed neutrinos. This undemocratic parameter choic

Vladimir Lukoshkin, Evgeny Sedov, Vladimir Kalevich, Z. Hatzopoulos

Concentric ring exciton polariton condensates emerging under non-resonant laser pump in an annular trapping potential support persistent circular currents of polaritons. The trapping potential is formed by a cylindrical micropillar etched in a semiconductor microcavity with embedded quantum wells and a repulsive cloud of optically excited excitons under the

Linde Frölke, Eléa Prat, Pierre Pinson, Richard M. Lusby

Energy market designs with non-merchant storage have been proposed in recent years, with the aim of achieving optimal market integration of storage. In order to handle the time-linking constraints that are introduced in such markets, existing works commonly make simplifying assumptions about the end-of-horizon storage level, e.g., by imposing an exogenous le

Matin Ansaripour, Krishnendu Chatterjee, Thomas A. Henzinger, Mathias Lechner

We consider the problem of learning control policies in discrete-time stochastic systems which guarantee that the system stabilizes within some specified stabilization region with probability~$1$. Our approach is based on the novel notion of stabilizing ranking supermartingales (sRSMs) that we introduce in this work. Our sRSMs overcome the limitation of meth

Brian B. Haidet, Jarod Meyer, Pooja Reddy, Eamonn T. Hughes

PbSe and related IV-VI rocksalt-structure semiconductors have important electronic properties that may be controlled by epitaxial strain and interfaces, thus harnessed in an emerging class of IV-VI/III-V heterostructures. The synthesis of such heterostructures and understanding mechanisms for strain-relief is central to achieving this goal. We show that a ra

Qiwei Peng, David Weir, Julie Weeds

Previous works have demonstrated the effectiveness of utilising pre-trained sentence encoders based on their sentence representations for meaning comparison tasks. Though such representations are shown to capture hidden syntax structures, the direct similarity comparison between them exhibits weak sensitivity to word order and structural differences in given

Maximilian Stubbemann, Tom Hanika, Friedrich Martin Schneider

The concept of dimension is essential to grasp the complexity of data. A naive approach to determine the dimension of a dataset is based on the number of attributes. More sophisticated methods derive a notion of intrinsic dimension (ID) that employs more complex feature functions, e.g., distances between data points. Yet, many of these approaches are based o

Evgeny Sedov, Vladimir Lukoshkin, Vladimir Kalevich, Igor Chestnov

We study formation of superfluid currents of exciton polaritons in annular polariton condensates in a cylindrical micropillar cavity under the spatially localised nonresonant optical pumping. Since polariton condensates are strongly nonequilibrium systems, the trapping potential for polaritons, formed by the pillar edge and the reservoir of optically induced

J. Borat, Roman Cherbunin, Evgeny Sedov, Ekaterina Aladinskaia

We keep track of the orbital degree of freedom of an exciton polariton condensate, confined in an optical trap, and reveal the stochastic switching of persistent annular polariton currents in the pulse-periodic excitation regime.In an elliptic trap, the low-lying in energy polariton current states are inherent in a two-petalled density distribution and swirl

Michael Schelling, Pedro Hermosilla, Timo Ropinski

Indirect Time-of-Flight (iToF) cameras are a widespread type of 3D sensor, which perform multiple captures to obtain depth values of the captured scene. While recent approaches to correct iToF depths achieve high performance when removing multi-path-interference and sensor noise, little research has been done to tackle motion artifacts. In this work we propo

Shashank Kumar Ranu, Anil Prabhakar, Prabha Mandayam

Error mitigation is one of the key challenges in realising the full potential of quantum cryptographic protocols. Consequently, there is a lot of interest in adapting techniques from quantum error correction (QEC) to improve the robustness of quantum cryptographic protocols. In this work, we benchmark the performance of different QKD protocols on noisy quant