April 2023 arXiv papers — page 34

Jiamin Hou, Zhanhao Zhao, Zhouyu Wang, Wei Lu

Real world graphs are often dynamic and evolve over time. It is crucial for storing and querying graph evolution in graph databases. However, existing works either suffer from high storage overhead or lack efficient temporal query support, or both. In this paper, we propose AeonG, a new graph database with built-in temporal support. AeonG is based on a novel

V. N. Berestovskii, Yu. G. Nikonorov

The paper is devoted to perfect and almost perfect homogeneous polytopes in Euclidean spaces. We classified perfect and almost perfect polytopes among all regular polytopes and all semiregular polytopes excepting Archimedean solids and two four-dimensional Gosset polytopes. Also we construct some non-regular homogeneous polytopes that are (or are not) perfec

Randall Balestriero, Mark Ibrahim, Vlad Sobal, Ari Morcos

Self-supervised learning, dubbed the dark matter of intelligence, is a promising path to advance machine learning. Yet, much like cooking, training SSL methods is a delicate art with a high barrier to entry. While many components are familiar, successfully training a SSL method involves a dizzying set of choices from the pretext tasks to training hyper-param

P. T. Oikonomou, Ch. C. Moustakidis

The central compact object within HESS J1731- 347 possesses unique mass and radius properties that renders it a compelling candidate for a self-bound star. In this research, we examine the capability of quark stars composed of colour superconducting quark matter to explain the latter object by using its marginalised posterior distribution and imposing it as

Niall T. Macpherson, Anayeli Ramirez

We consider ${\cal N}=(n,0)$ supersymmetric AdS$_3$ vacua of type II supergravity realising the superconformal algebra $\mathfrak{osp}(n|2)$ for $n>4$. For the cases $n=6$ and $n=5$, one can realise these algebras on backgrounds that decompose as foliations of AdS$_3\times \mathbb{CP}^3$ ( squashed $\mathbb{CP}^3$ for $n=5$) over an interval. We classify suc

Bryan Li, Chris Callison-Burch

Existing question answering (QA) systems owe much of their success to large, high-quality training data. Such annotation efforts are costly, and the difficulty compounds in the cross-lingual setting. Therefore, prior cross-lingual QA work has focused on releasing evaluation datasets, and then applying zero-shot methods as baselines. This work proposes a synt

Zhihang Song, Zimin He, Xingyu Li, Qiming Ma

Autonomous driving techniques have been flourishing in recent years while thirsting for huge amounts of high-quality data. However, it is difficult for real-world datasets to keep up with the pace of changing requirements due to their expensive and time-consuming experimental and labeling costs. Therefore, more and more researchers are turning to synthetic d

R. D. Jeffries, R. J. Jackson, Nicholas J. Wright, G. Weaver

We present an empirical model of age-dependent photospheric lithium depletion, calibrated using a large, homogeneously-analysed sample of 6200 stars in 52 open clusters, with ages from 2--6000 Myr and $-0.3<{\rm [Fe/H}]<0.2$, observed in the Gaia-ESO spectroscopic survey. The model is used to obtain age estimates and posterior age probability distributions f

Raquel Blanco, Manuel Trinidad, Maria Jose Suarez-Cabal, Alejandro Calderon

Software testing is an essential knowledge area required by industry for software engineers. However, software engineering students often consider testing less appealing than designing or coding. Consequently, it is difficult to engage students to create effective tests. To encourage students, we explored the use of gamification and investigated whether this

Fabrizio Chiriano, Joseph Ho, Christopher L. Morrison, Jonathan W. Webb

Hyper-entanglement between two or more photonic degrees of freedom (DOF) can enhance and enable new quantum protocols by allowing each DOF to perform the task it is optimally suited for. Here we demonstrate the generation of photon pairs hyper-entangled between pulse modes and frequency bins. The pulse modes are generated via parametric downconversion in a d

Maximilian Pierzyna, Rudolf Saathof, Sukanta Basu

Turbulent fluctuations of the atmospheric refraction index, so-called optical turbulence, can significantly distort propagating laser beams. Therefore, modeling the strength of these fluctuations ($C_n^2$) is highly relevant for the successful development and deployment of future free-space optical communication links. In this letter, we propose a physics-in

Shoyeb Khan, Satyendra Kumar Sharma, Arnab Kumar Laha

Indian Universities and Research Institutions have been the cornerstone of human resource development in the country, nurturing bright minds and shaping the leaders of tomorrow. Their unwavering commitment to excellence in education and research has not only empowered individuals but has also made significant contributions to the overall growth and progress

Mason B. Peterson, Parker C. Lusk, Jonathan P. How

We present MOTLEE, a distributed mobile multi-object tracking algorithm that enables a team of robots to collaboratively track moving objects in the presence of localization error. Existing approaches to distributed tracking make limiting assumptions regarding the relative spatial relationship of sensors, including assuming a static sensor network or that pe

Yiming Pan, Bin Zhang, Daniel Podolsky

We propose free-electron Rabi oscillation by creating an isolated two-level system in a synthetic energy space induced by laser. The {\pi}/2-pulse and {\pi}-pulse in synthetic Rabi dynamics can function as 'beam splitters' and 'mirrors' for free-electron interferometry, allowing us to detect local electromagnetic fields and plasmonic excitations. When the co

Arafat Abbar, Clément Coine, Colin Petitjean

We consider weighted composition operators, that is operators of the type $g \mapsto w \cdot g \circ f$, acting on spaces of Lipschitz functions. Bounded weighted composition operators, as well as some compact weighted composition operators, have been characterized quite recently. In this paper, we provide a different approach involving their pre-adjoint ope

Altai Perry, Luat Vuong

Hybrid optical neural networks (HONNs) offload some electronic computation to optical preprocessors to achieve low-power and fast training and inference phases in machine learning tasks. Our contribution to the development of HONNs is a spectral-methods paradigm for building synthetic training data for machine-learned models. Here, our synthetic training ima

Alfred Galichon, Yu-Wei Hsieh, Maxime Sylvestre

We propose monotone comparative statics results for maximizers of submodular functions, as opposed to maximizers of supermodular functions as in the classical theory put forth by Veinott, Topkis, Milgrom, and Shannon among others. We introduce matrons, a natural structure that is dual to sublattices that generalizes existing structures such as matroids and p

Vaishali Roondhe, Basant Roondhe, Sumit Saxena, Rajeev Ahuja

The goal of the present study is to explore how the size and functionalization of graphene quantum dots (GQDs) affect their sensing capabilities. Specifically, we investigated the adsorption of SO$_2$, SOF$_2$, SO$_2$F$_2$, and SF$_6$ on GQDs that were functionalized with -CH$_3$, - COCH$_3$, and -NH$_2$. We used density functional theory to analyze the elec

Fraser A. Evans, Alexander Rasskazov, Amber Remmelzwaal, Tommaso Marchetti

We consider a scenario in which Sgr A* is in a massive black hole binary (MBHB) with an as-of-yet undetected supermassive or intermediate-mass black hole companion. Dynamical encounters between this MBHB and single stars in its immediate vicinity would eject hypervelocity stars (HVSs) with velocities beyond the Galactic escape velocity. In this work, we use

Chun Lau, Bahman Kalantari

We present a comprehensive computational study of a class of linear system solvers, called {\it Triangle Algorithm} (TA) and {\it Centering Triangle Algorithm} (CTA), developed by Kalantari \cite{kalantari23}. The algorithms compute an approximate solution or minimum-norm solution to $Ax=b$ or $A^TAx=A^Tb$, where $A$ is an $m \times n$ real matrix of arbitra

Benjamin Haïoun

The inclusion of the unit in a braided tensor category $\mathcal{V}$ induces a 1-morphism in the Morita 4-category of braided tensor categories $BrTens$. We give criteria for the dualizability of this morphism. When $\mathcal{V}$ is a semisimple (resp. non-semisimple) modular category, we show that the unit inclusion induces under the Cobordism Hypothesis a

Andy J. Goldschmidt, Frederic T. Chong

Model-based quantum optimal control promises to solve a wide range of critical quantum technology problems within a single, flexible framework. The catch is that highly-accurate models are needed if the optimized controls are to meet the exacting demands set by quantum engineers. A practical alternative is to directly calibrate control parameters by taking d

Jared Lawson, Rohan Chitale, Nabil Simaan

Small catheters undergo significant torsional deflections during endovascular interventions. A key challenge in enabling robot control of these catheters is the estimation of their bending planes. This paper considers approaches for estimating these bending planes based on bi-plane image feedback. The proposed approaches attempt to minimize error between eit

Benjamin Bolte, Austin Wang, Jimmy Yang, Mustafa Mukadam

In order for robots to follow open-ended instructions like "go open the brown cabinet over the sink", they require an understanding of both the scene geometry and the semantics of their environment. Robotic systems often handle these through separate pipelines, sometimes using very different representation spaces, which can be suboptimal when the two objecti

L. Doyle, H. M. Cegla, D. R. Anderson, M. Lendl

In this paper, we present observations of two high-resolution transit datasets obtained with ESPRESSO of the bloated sub-Saturn planet WASP-131~b. We have simultaneous photometric observations with NGTS and EulerCam. In addition, we utilised photometric lightcurves from {\tess}, WASP, EulerCam and TRAPPIST of multiple transits to fit for the planetary parame

Andreas Bock, Martin S. Andersen

We study a preconditioner for a Hermitian positive definite linear system, which is obtained as the solution of a matrix nearness problem based on the Bregman log determinant divergence. The preconditioner is of the form of a Hermitian positive definite matrix plus a low-rank matrix. For this choice of structure, the generalised eigenvalues of the preconditi

Berkan Demirel, Orhun Buğra Baran, Ramazan Gokberk Cinbis

Few-shot object detection, the problem of modelling novel object detection categories with few training instances, is an emerging topic in the area of few-shot learning and object detection. Contemporary techniques can be divided into two groups: fine-tuning based and meta-learning based approaches. While meta-learning approaches aim to learn dedicated meta-

Alexey Gritsenko, Xuehan Xiong, Josip Djolonga, Mostafa Dehghani

The most performant spatio-temporal action localisation models use external person proposals and complex external memory banks. We propose a fully end-to-end, purely-transformer based model that directly ingests an input video, and outputs tubelets -- a sequence of bounding boxes and the action classes at each frame. Our flexible model can be trained with ei

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

Using $7.33~\mathrm{fb}^{-1}$ of $e^+e^-$ collision data taken with the BESIII detector at the BEPCII collider, we report the first experimental study of the purely leptonic decay $D_s^{*+}\to e^+\nu_e$. A signal for the decay $D_s^{*+}\to e^+\nu_e$ is observed with a statistical significance of $2.9\sigma$. The branching fraction of ${D_s^{*+}\to e^+\nu_e}$

Damian Niwiński, Paweł Parys, Michał Skrzypczak

The Rabin tree theorem yields an algorithm to solve the satisfiability problem for monadic second-order logic over infinite trees. Here we solve the probabilistic variant of this problem. Namely, we show how to compute the probability that a randomly chosen tree satisfies a given formula. We additionally show that this probability is an algebraic number. Thi

Raphaël Prunier

This paper is concerned with stability of the ball for a class of isoperimetric problems under convexity constraint. Considering the problem of minimizing $P+\varepsilon R$ among convex subsets of $\mathbb{R}^N$ of fixed volume, where $P$ is the perimeter functional, $R$ is a perturbative term and $\varepsilon>0$ is a small parameter, stability of the ball f

N. Vasantharaju, F. Zuccarello, F. Ferrente, S. L. Guglielmino

The non-association of coronal mass ejections with high energetic flares is sparse. For this reason, the magnetic conditions required for the confinedness of major flares is a topic of active research. Using multi-instrument observations, we investigated the evolution and effects of confinedness in an X3.1 flare, which occurred in active region (AR) 12192. T

Lynn Pickering, Tereso Del Rio Almajano, Matthew England, Kelly Cohen

In recent years there has been increased use of machine learning (ML) techniques within mathematics, including symbolic computation where it may be applied safely to optimise or select algorithms. This paper explores whether using explainable AI (XAI) techniques on such ML models can offer new insight for symbolic computation, inspiring new implementations w

Hiroshi Ito, Kohei Wada, Takatomi Yano, Yota Hino

Americium-beryllium (AmBe), a well-known tagged neutron source, is commonly used for evaluating the neutron detection efficiency of detectors used in ultralow background particle physics experiments, such as reactor neutrino and diffuse supernova neutrino background experiments. In particular, AmBe sources are used to calibrate neutron tagging by selecting t

Haitian Jiang, Dongliang Xiong, Xiaowen Jiang, Li Ding

Halftoning aims to reproduce a continuous-tone image with pixels whose intensities are constrained to two discrete levels. This technique has been deployed on every printer, and the majority of them adopt fast methods (e.g., ordered dithering, error diffusion) that fail to render structural details, which determine halftone's quality. Other prior methods of

Hang Xu, Xinghua Qu, Zinovi Rabinovich

This paper investigates policy resilience to training-environment poisoning attacks on reinforcement learning (RL) policies, with the goal of recovering the deployment performance of a poisoned RL policy. Due to the fact that the policy resilience is an add-on concern to RL algorithms, it should be resource-efficient, time-conserving, and widely applicable w

David Garfinkle, Anna Ijjas, Paul J. Steinhardt

We present first results from a novel numerical relativity code based on a tetrad formulation of the Einstein-scalar field equations combined with recently introduced gauge/frame invariant diagnostics indicating that inflation does not solve the homogeneity and isotropy problem beginning from generic initial conditions following a big bang.

Lucas W. Remedios, Leon Y. Cai, Samuel W. Remedios, Karthik Ramadass

Deep learning has made great strides in medical imaging, enabled by hardware advances in GPUs. One major constraint for the development of new models has been the saturation of GPU memory resources during training. This is especially true in computational pathology, where images regularly contain more than 1 billion pixels. These pathological images are trad

Justin Janquart, K. Haris, Otto A. Hannuksela, Chris Van Den Broeck

Owing to the forecasted improved sensitivity of ground-based gravitational-wave detectors, new research avenues will become accessible. This is the case for gravitational-wave strong lensing, predicted with a non-negligible observation rate in the coming years. However, because one needs to investigate all the event pairs in the data, searches for strongly-l

Subhayan Maity, Manojit Das

The general theory of relativity is the most popular theory to describe the dynamics of a system (especially the Universe) under gravity. In this framework, the solution of the Einstein field equation under curved space-time yields the cosmic evolution equation. Besides the evolutionary dynamics of the Universe may also be obtained from the other aspects lik

Cyril Grelier, Olivier Goudet, Jin-Kao Hao

This work investigates the Monte Carlo Tree Search (MCTS) method combined with dedicated heuristics for solving the Weighted Vertex Coloring Problem. In addition to the basic MCTS algorithm, we study several MCTS variants where the conventional random simulation is replaced by other simulation strategies including greedy and local search heuristics. We condu

Ksenia Bestuzheva, Helena Völker, Ambros Gleixner

Nonnegativity certificates can be used to obtain tight dual bounds for polynomial optimization problems. Hierarchies of certificate-based relaxations ensure convergence to the global optimum, but higher levels of such hierarchies can become very computationally expensive, and the well-known sums of squares hierarchies scale poorly with the degree of the poly

Michael G. Christiansen, Lucien Stöcklin, Cameron Forbrigger, Shashaank Abhinav Venkatesh

The engineering space for magnetically manipulated biomedical microrobots is rapidly expanding. This includes synthetic, bioinspired, and biohybrid designs, some of which may eventually assume clinical roles aiding drug delivery or performing other therapeutic functions. Actuating these microrobots with rotating magnetic fields (RMFs) and the magnetic torque

Jonathan Dumas, Viktor Terrier, Frédéric Bienvenu, Sébastien Finet

System operators employ operating reserves to deal with unexpected variations of demand and generation and guarantee the security of supply. However, they face new challenges to ensure this mission with the increasing share of renewable generation. This article focuses on the operational approach adopted by the French transmission system operator RTE for dyn

Beth Romano

A paper of Reeder-Yu gives a construction of epipelagic supercuspidal representations of $p$-adic groups. The input for this construction is a pair $(\lambda, \chi)$ where $\lambda$ is a stable vector in a certain representation coming from a Moy-Prasad filtration, and $\chi$ is a character of the additive group of the residue field. We say two such pairs ar

Georgios Batzolis, Jan Stanczuk, Carola-Bibiane Schönlieb

As a widely recognized approach to deep generative modeling, Variational Auto-Encoders (VAEs) still face challenges with the quality of generated images, often presenting noticeable blurriness. This issue stems from the unrealistic assumption that approximates the conditional data distribution, $p(\textbf{x} | \textbf{z})$, as an isotropic Gaussian. In this

L. Mauro, J. Fregoni, J. Feist, R. Avriller

We provide a theoretical framework based on classical electromagnetism, to describe optical properties of Fabry-P\'erot cavities, filled with multilayered and linear chiral materials. We find a formal link between transfer-matrix, scattering-matrix and Green-function approaches to compute the polarization-dependent optical transmission, and cavity-modified c

Xueguang Ma, Tommaso Teofili, Jimmy Lin

Anserini is a Lucene-based toolkit for reproducible information retrieval research in Java that has been gaining traction in the community. It provides retrieval capabilities for both "traditional" bag-of-words retrieval models such as BM25 as well as retrieval using learned sparse representations such as SPLADE. With Pyserini, which provides a Python interf

Jaan Übi, Evald Übi

In order to nd a non-negative solution to a system of inequalities, the corresponding dual problem is composed, which has a suitable unity basic matrix. In such a formulation, the objective function is replaced by set of constraints based on that function. Additional constraints can be used for accelerating calculations in the rst phase of the simplex method

Mitsuyasu Hashimoto, Fumiya Kobayashi

Let $k$ be a perfect field of prime characteristic $p$, $G$ a finite group scheme over $k$, and $V$ a finite-dimensional $G$-module. Let $S=\mathop{\mathrm{Sym}}V$ be the symmetric algebra with the standard grading. Let $M$ be a $\Bbb Q$-graded $S$-finite $S$-free $(G,S)$-module, and $L$ be its $S$-reflexive graded $(G,S)$-submodule. Assume that the action o

Marissa Vlasblom, Guido De Marchi

We studied the properties of the young stellar populations in the NGC 299 cluster in the Small Magellanic Cloud using observations obtained with the Hubble Space Telescope in the $V, I$, and $H\alpha$ bands. We identified 250 stars with H$\alpha$ excess exceeding 5 $\sigma$ and an equivalent width of the H$\alpha$ emission line of at least 20 \r{A}, indicati

Patrick N. Raanes, Andreas S. Stordal, Rolf J. Lorentzen

In robust optimisation problems the objective function consists of an average over (an ensemble of) uncertain parameters. Ensemble optimisation (EnOpt) implements steepest descent by estimating the gradient using linear regression on Monte-Carlo simulations of (an ensemble of) control parameters. Applying EnOpt for robust optimisation is costly unless the ev

Christian Porter

In this paper, we show that for each lattice basis, there exists an equivalent basis which we describe as ``strongly reduced''. We show that bases reduced in this manner exhibit rather ``short'' basis vectors, that is, the length of the $i$th basis vector of a strongly reduced basis is upper bounded by a polynomial factor in $i$ multiplied by the $i$th succe

Puyi Fang, Zhaoxing Gao, Ruey S. Tsay

This paper proposes a new approach to identifying the effective cointegration rank in high-dimensional unit-root (HDUR) time series from a prediction perspective using reduced-rank regression. For a HDUR process $\mathbf{x}_t\in \mathbb{R}^N$ and a stationary series $\mathbf{y}_t\in \mathbb{R}^p$ of interest, our goal is to predict future values of $\mathbf{

Leyla Loued-Khenissi, Christian Pfeiffer, Rupal Saxena, Shivam Adarsh

Does gravity affect decision-making? This question comes into sharp focus as plans for interplanetary human space missions solidify. In the framework of Bayesian brain theories, gravity encapsulates a strong prior, anchoring agents to a reference frame via the vestibular system, informing their decisions and possibly their integration of uncertainty. What ha

Martino Fortuna, Adriana Garroni

We prove an homogenization result, in terms of $\Gamma$-convergence, for energies concentrated on rectifiable lines in $\R^3$ without boundary. The main application of our result is in the context of dislocation lines in dimension $3$. The result presented here shows that the line tension energy of unions of single line defects converge to the energy associa

Thomas Aird

We study the semigroup identities satisfied by finite rank plactic monoids. We find a new set of semigroup identities of the plactic monoid of rank $n$ for $n \geq 4$, which are shorter than those previously known when $n \geq 6$. Using these semigroup identities we show that for all $n \in \mathbb{N}$, the plactic monoid of rank $n$ satisfies a semigroup id

Shengyu Chen, Tianshu Bao, Peyman Givi, Can Zheng

Simulating turbulence is critical for many societally important applications in aerospace engineering, environmental science, the energy industry, and biomedicine. Large eddy simulation (LES) has been widely used as an alternative to direct numerical simulation (DNS) for simulating turbulent flows due to its reduced computational cost. However, LES is unable

John P. Moroney, Paul R. Eastham

Driven-dissipative condensates, such as those formed from polaritons, expose how the coherence of Bose-Einstein condensates evolves far from equilibrium. We consider the phase and frequency ordering in the steady-states of a one-dimensional lattice of condensates, described by a coupled oscillator model with non-odd couplings, and include both time-dependent

Hang Liu, Chang Yang

In this study, we investigate the nonleptonic decays of the charmed-baryon Xi^ {0} _ c induced by the c -> u(d\bar{d})/(s\bar{s}) transition. Utilizing the factorization assumption, we decompose the decay amplitudes in terms of transition form factors which are then calculated within the light-front quark model. We employ helicity amplitudes to analyze the n

D. Barbier, C Lucibello, L. Saglietti, F. Krzakala

Noiseless compressive sensing is a protocol that enables undersampling and later recovery of a signal without loss of information. This compression is possible because the signal is usually sufficiently sparse in a given basis. Currently, the algorithm offering the best tradeoff between compression rate, robustness, and speed for compressive sensing is the L

Dawei Wu, Shan-Chang Tang, Yu Shi

We consider two accelerating Unruh-DeWitt detectors coupled linearly or quadratically with a scalar field. We show that entanglement can be created by acceleration, and is divergent only when the two detectors coincide. For linear coupling, entanglment decreases monotonically with the increase of acceleration. For quadratic coupling, entanglement behaves non

Iacopo Catalano, Ha Sier, Xianjia Yu, Tomi Westerlund

With the increasing use of drones across various industries, the navigation and tracking of these unmanned aerial vehicles (UAVs) in challenging environments (such as GNSS-denied environments) have become critical issues. In this paper, we propose a novel method for a ground-based UAV tracking system using a solid-state LiDAR, which dynamically adjusts the L

David M. J. Dykstra, Corentin Coulais

Multishape metamaterials exhibit more than one target shape change, e.g. the same metamaterial can have either a positive or negative Poisson's ratio. So far, multishape metamaterials have mostly been obtained by trial-and-error. The inverse design of multiple target deformations in such multishape metamaterials remains a largely open problem. Here, we demon

Charles Le Losq, Barbara Baldoni

The first version of the machine learning greybox model i-Melt was trained to predict latent and observed properties of K$_2$O-Na$_2$O-Al$_2$O$_3$-SiO$_2$ melts and glasses. Here, we extend the model compositional range, which now allows accurate predictions of properties for glass-forming melts in the CaO-MgO-K$_2$O-Na$_2$O-Al$_2$O$_3$-SiO$_2$ system, inclu

Manuel Schwonberg, Fadoua El Bouazati, Nico M. Schmidt, Hanno Gottschalk

Unsupervised Domain Adaptation (UDA) and domain generalization (DG) are two research areas that aim to tackle the lack of generalization of Deep Neural Networks (DNNs) towards unseen domains. While UDA methods have access to unlabeled target images, domain generalization does not involve any target data and only learns generalized features from a source doma

Tomislav Došlić, Luka Podrug

We consider two division problems on narrow strips of square and hexagonal lattices. In both cases we compute the bivariate enumerating sequences and the corresponding generating functions, which allowed us to determine the asymptotic behavior of the total number of such subdivisions and the expected number of parts. For the square lattice we extend results

Chaoan Li, Xianjie Yan, Dachun Yang

Let $A$ be a general expansive matrix and let $X$ be a ball quasi-Banach function space on $\mathbb R^n$, which supports both a Fefferman--Stein vector-valued maximal inequality and the boundedness of the powered Hardy--Littlewood maximal operator on its associate space. The authors first introduce some anisotropic ball Campanato-type function spaces associa

Romain Petrides

We give a sufficient condition for branched minimal immersions of spheres into ellipsoids to be embedded: we show that if the coordinate functions of the branched minimal immersion are first or second eigenfunctions with respect to a natural metric on the sphere involved in this problem, called critical metric, then it is an embedding into a 2-dimensional el

Jianmei Wang, Jin Dai, Antti J. Niemi, Xubiao Peng

Cats use the connection governing parallel transport in the space of shapes to land safely on their feet. Here we argue that this connection also explains the impressive performance of molecular motors by enabling molecules to evade conclusions of Feynman's ratchet-and-pawl analysis. We first demonstrate, using simple molecular models, how directed rotationa

Leon Mächler, Ivan Ezhov, Suprosanna Shit, Johannes C. Paetzold

This paper presents FedPIDAvg, the winning submission to the Federated Tumor Segmentation Challenge 2022 (FETS22). Inspired by FedCostWAvg, our winning contribution to FETS21, we contribute an improved aggregation strategy for federated and collaborative learning. FedCostWAvg is a weighted averaging method that not only considers the number of training sampl

Ananthu P. Surendran, Domenico Montemurro, Gunta Kunakova, Xavier Palermo

We used the asymmetric superconducting quantum interference device (SQUID) technique to extract the current phase relation (CPR) of a Josephson junction with a 3D-topological insulator (TI) Bi2Se3 nanobelt as the barrier. The obtained CPR shows deviations from the standard sinusoidal CPR with a pronounced forward skewness. At temperatures below 200 mK, the j

Balazs Pejo, Nikolett Kapui

Almost 50 years after the invention of SQL, injection attacks are still top-tier vulnerabilities of today's ICT systems. Consequently, SQLi detection is still an active area of research, where the most recent works incorporate machine learning techniques into the proposed solutions. In this work, we highlight the shortcomings of the previous ML-based results

Pau Colomer, Andreas Winter

We show that a simple telescoping sum trick, together with the triangle inequality and a tensorisation property of expected-contractive coefficients of random channels, allow us to achieve general simultaneous decoupling for multiple users via local actions. Employing both old [Dupuis et al. Commun. Math. Phys. 328:251-284 (2014)] and new methods [Dupuis, ar

Zsombor Fehér

We give families of knots and links with pairs of Seifert surfaces that are topologically non-isotopic in $D^4$. This generalizes the main example of Hayden-Kim-Miller-Park-Sundberg and the proof is similarly based on the double branched cover and the Seifert form. Moreover, using Conway's theory of topographs, we implement an algorithm that decides whether

Henrik Martikainen, Mikko Majamaa, Jani Puttonen

The emerging Non-Terrestrial Networks (NTNs) can aid to provide 5G and beyond services everywhere and anytime. However, the vast emergence of NTN systems will introduce an unseen interference to both the existing satellite systems and Terrestrial Networks (TNs). For that, there is a need for novel ideas on how to efficiently utilize the co-existing systems w

Romain Petrides

We prove the existence of embedded non planar free boundary minimal disks into rotationally symmetric ellipsoids of $\mathbb{R}^3$. The construction relies on the optimization of combinations of first and second Steklov eigenvalues renormalized by the length of the boundary, among metrics on the disk. We also prove that non planar free boundary harmonic maps

Hugo Vanneuville

Let us consider subcritical Bernoulli percolation on a connected, transitive, infinite and locally finite graph. In this paper, we propose a new (and short) proof of the exponential decay property for the volume of clusters. We do not rely on differential inequalities and rather use stochastic comparison techniques, which are inspired by several works includ

Jan Dreier, Jamie Tucker-Foltz

We study pseudorandomness and pseudorandom generators from the perspective of logical definability. Building on results from ordinary derandomization and finite model theory, we show that it is possible to deterministically construct, in polynomial time, graphs and relational structures that are statistically indistinguishable from random structures by any s

Johannes Bracher, Lotta Rüter, Fabian Krüger, Sebastian Lerch

In many forecasting settings, there is a specific interest in predicting the sign of an outcome variable correctly in addition to its magnitude. For instance, when forecasting armed conflicts, positive and negative log-changes in monthly fatalities represent escalation and de-escalation, respectively, and have very different implications. In the ViEWS foreca

Hendrik Müller, Alejandro Mus, Andrei Lobanov

Imaging in radioastronomy is an ill-posed inverse problem. Particularly the Event Horizon Telescope (EHT) Collaboration investigated the fidelity of their image reconstructions convincingly by large surveys solving the problem with different optimization parameters. This strategy faces a limitation for the existing methods when imaging the active galactic nu

Anibal Pacheco-Sanchez, Omar Jordán-García, Eloy Ramŕez-García, David Jiménez

A first modeling approximation of the general performance of radiofrequency (RF) switches based on hexagonal boron nitride (hBN), a two-dimensional (2D) dielectric material is presented. The I-V characteristics intrinsic and extrinsic impedance parameters, the return loss, insertion loss and isolation of RF 2D switches fabricated with hBN are described here

Alexander O. Sushkov

Condensed matter systems offer the opportunity to maximize the number of spins, probed in magnetic resonance experiments that search for physics beyond the standard model. EuCl$_3\cdot 6$H$_2$O is a promising solid-state platform for such searches. The narrow inhomogeneous linewidth of the Eu optical $^7\hspace{-0.1em}F_0 \leftrightarrow\,^5\hspace{-0.1em}D_

Pranay P. Nagrani, Ritwik V. Kulkarni, Parth U. Kelkar, Ria D. Corder

Thermal greases, often used as thermal interface materials, are complex paste-like mixtures composed of a base polymer in which dense metallic (or ceramic) filler particles are dispersed to improve the heat transfer properties of the material. They have complex rheological properties that impact the performance of the thermal interface material over its life

Karandeep Jandu Singh, Marco Zambon

Given an $L_{\infty}$-algebra $V$ and an $L_{\infty}$-subalgebra $W$, we give sufficient conditions for all small Maurer-Cartan elements of $V$ to be equivalent to Maurer-Cartan elements lying in $W$. As an application, we obtain a stability criterion for fixed points of a Dirac structure (for instance a twisted Poisson structure), i.e. points where the corr

Yucheng Li

Large language models (LLMs) have received significant attention by achieving remarkable performance across various tasks. However, their fixed context length poses challenges when processing long documents or maintaining extended conversations. This paper proposes a method called \textit{Selective Context} that employs self-information to filter out less in

S. Habib Mazharimousavi

In this study, we present an exact dirty/hairy black hole solution in the context of gravity coupled minimally to a nonlinear electrodynamic (NED) and a Dilaton field. The NED model is known in the literature as the square-root (SR) model i.e., $\mathcal{L}\sim \sqrt{-\mathcal{F}}.$ The black hole solution which is supported by a uniform radial electric fiel

Arka Adhikari, Izumi Okada

In this paper, we find a natural four dimensional analog of the moderate deviation results of Chen (2004) for the mutual intersection of two independent Brownian motions $B$ and $B'$. In this work, we focus on understanding the following quantity, for a specific family of kernels $H$, \begin{equation*} \int_0^1 \int_0^1 H (B_s - B'_t) \text{d}t \text{d}s . \

Ligang Xiao, Daowen Qiu, Le Luo, Paulo Mateus

Shor's algorithm is one of the most significant quantum algorithms. Shor's algorithm can factor large integers with a certain success probability in polynomial time. However, Shor's algorithm requires an unbearable amount of qubits in the NISQ (Noisy Intermediate-scale Quantum) era. To reduce the resources required for Shor's algorithm, in this paper we firs

Larissa Soares, Edna Canedo, Claudia Pereira, Carla Bezerra

Background: Several researchers report the impact of gender on software development teams, especially in relation to women. In general, women are under-represented on these teams and face challenges and difficulties in their workplaces. When it comes to women who are mothers, these challenges can be amplified and directly impact these women's professional li

Haeone Lee

In this paper, we propose ComGAN(ComparativeGAN) which allows the generator in GANs to refer to the semantics of comparative samples(e.g. real data) by comparison. ComGAN generalizes relativistic GANs by using arbitrary architecture and mostly outperforms relativistic GANs in simple input-concatenation architecture. To train the discriminator in ComGAN, we a

Mikko Majamaa, Henrik Martikainen, Jani Puttonen, Timo Hämäläinen

Due to the ongoing standardization and deployment activities, satellite networks will be supplementing the 5G and beyond Terrestrial Networks (TNs). For the satellite communications involved to be as efficient as possible, techniques to achieve that should be used. Multi-Connectivity (MC), in which a user can be connected to multiple Next Generation Node Bs

Brendan Pelto, Mounika Vanamala, Rushit Dave

The aim of this research paper is to look into the use of continuous authentication with mobile touch dynamics, using three different algorithms: Neural Network, Extreme Gradient Boosting, and Support Vector Machine. Mobile devices are constantly increasing in popularity in the world, today smartphone subscriptions have surpassed 6 billion. Mobile touch dyna

Helmut Abels, Mingwen Fei, Maximilian Moser

We consider the sharp interface limit of a Navier-Stokes/Allen Cahn equation in a bounded smooth domain in two space dimensions, in the case of vanishing mobility $m_\varepsilon=\sqrt{\varepsilon}$, where the small parameter $\varepsilon>0$ related to the thickness of the diffuse interface is sent to zero. For well-prepared initial data and sufficiently smal

Elisa Gorla, Umberto Martínez-Peñas, Flavio Salizzoni

Sum-rank metric codes are a natural extension of both linear block codes and rank-metric codes. They have several applications in information theory, including multishot network coding and distributed storage systems. The aim of this chapter is to present the mathematical theory of sum-rank metric codes, paying special attention to the $\mathbb{F}_q$-linear

Marianna Girlando, Roman Kuznets, Sonia Marin, Marianela Morales

In this paper we demonstrate decidability for the intuitionistic modal logic S4 first formulated by Fischer Servi. This solves a problem that has been open for almost thirty years since it had been posed in Simpson's PhD thesis in 1994. We obtain this result by performing proof search in a labelled deductive system that, instead of using only one binary rela

Liviu Aolaritei, Marta Fochesato, John Lygeros, Florian Dörfler

We study model predictive control (MPC) problems for stochastic LTI systems, where the noise distribution is unknown, compactly supported, and only observable through a limited number of i.i.d. noise samples. Building upon recent results in the literature, which show that distributional uncertainty can be efficiently captured within a Wasserstein ambiguity s

Luc Biasiori-Poulanges, Bratislav Lukic, Outi Supponen

This work investigates the fundamental role of cavitation bubble clouds in stone comminution by focused ultrasound. The fragmentation of stones by ultrasound has applications in medical lithotripsy for the comminution of kidney stones or gall stones, where their fragmentation is widely assumed to result from the high acoustic wave energy. However, high-inten

Chao Yu, Shicheng Ye, Hankz Hankui Zhuo

Reinforcement Learning (RL) has achieved tremendous development in recent years, but still faces significant obstacles in addressing complex real-life problems due to the issues of poor system generalization, low sample efficiency as well as safety and interpretability concerns. The core reason underlying such dilemmas can be attributed to the fact that most

Deokwoo Lim

We consider incompressible Euler equations in any dimension $ d\geq3 $ imposing axisymmetric symmetry without swirl. While the global regularity of smooth flows in this setting has been well-known in $ d=3 $, the same question in higher dimensions $ d\geq4 $ remains unsolved. Recently, global regularity for the case $ d=4 $ with some extra decay assumption o