July 2023 arXiv papers — page 56

B. Benhamou-Bui, C. Consejo, S. S. Krishtopenko, M. Szoła

Two-dimensional Dirac fermions in HgTe quantum wells close to the topological phase transition can generate significant cyclotron emission that is magnetic field tunable in the Terahertz (THz) frequency range. Due to their relativistic-like dynamics, their cyclotron mass is strongly dependent on their electron concentration in the quantum well, providing a s

Aditya Singh, Poulami Mukherjee, Chandrasekhar Bhamidipati

Sign and magnitude of the thermodynamic curvature provides empirical information about the nature of microstructures of a general thermodynamic system. For charged black holes in AdS, thermodynamic curvature is positive for large charge or chemical potential, and diverges for extremal black holes, indicating strongly repulsive nature. We compute the thermody

Pasquale Blasi

The theory of transport of charged particles in cosmic magnetic fields is at the very center of the investigation of non-thermal phenomena in the universe, ranging from our local neighborhood to supernovae, clusters of galaxies or distant active galaxies. It is crucial to understand how particles get energized to non-thermal energies as well as to describe t

Wander Siemers, June Sallou, Luís Cruz

Artificial intelligence is bringing ever new functionalities to the realm of mobile devices that are now considered essential (e.g., camera and voice assistants, recommender systems). Yet, operating artificial intelligence takes up a substantial amount of energy. However, artificial intelligence is also being used to enable more energy-efficient solutions fo

Iason Baldes, María Olalla Olea-Romacho

We show that primordial black holes - in the observationally allowed mass window with $f_{\rm pbh}=1$ - formed from late nucleating patches in a first order phase transition imply upcoming gravitational wave interferometers will see a large stochastic background arising from the bubble collisions. As an example, we use a classically scale invariant $B-L$ mod

Charlie Budd, Jianrong Qiu, Oscar MacCormac, Martin Huber

Hyperspectral imaging (HSI) captures a greater level of spectral detail than traditional optical imaging, making it a potentially valuable intraoperative tool when precise tissue differentiation is essential. Hardware limitations of current optical systems used for handheld real-time video HSI result in a limited focal depth, thereby posing usability issues

Milapji Singh Gill, Tom Westermann, Marvin Schieseck, Alexander Fay

In the age of Industry 4.0 and Cyber-Physical Production Systems (CPPSs) vast amounts of potentially valuable data are being generated. Methods from Machine Learning (ML) and Data Mining (DM) have proven to be promising in extracting complex and hidden patterns from the data collected. The knowledge obtained can in turn be used to improve tasks like diagnost

Runjia Li, Shuyang Sun, Mohamed Elhoseiny, Philip Torr

This paper presents OxfordTVG-HIC (Humorous Image Captions), a large-scale dataset for humour generation and understanding. Humour is an abstract, subjective, and context-dependent cognitive construct involving several cognitive factors, making it a challenging task to generate and interpret. Hence, humour generation and understanding can serve as a new task

Stanley H. Chan

At the pinnacle of computational imaging is the co-optimization of camera and algorithm. This, however, is not the only form of computational imaging. In problems such as imaging through adverse weather, the bigger challenge is how to accurately simulate the forward degradation process so that we can synthesize data to train reconstruction models and/or inte

Daniele Iannotti, Antonio Pittelli

We introduce the topologically twisted index for four-dimensional $\mathcal N=1$ gauge theories quantized on ${\rm AdS}_2 \times S^1$. We compute the index by applying supersymmetric localization to partition functions of vector and chiral multiplets on ${\rm AdS}_2 \times T^2$, with and without a boundary: in both instances we classify normalizability and b

Shinji Watanabe, Tatsuya Iwasaki

The lack of the theory of the crystalline electric field (CEF) in rare-earth based quasicrystal (QC) and approximant crystal (AC) has prevented us from understanding the electronic states. Recent success of the formulation of the CEF theory on the basis of the point charge model has made it possible to analyze the CEF microscopically. Here, by applying this

Alexander Van Werde, Jaron Sanders

We prove that a sum of random matrices generated by a $\psi$-mixing Markov chain has similar spectral properties to a Gaussian matrix with the same mean and covariance structure. This nonasymptotic universality principle enables sharp concentration inequalities when combined with recent advances in the Gaussian literature. We illustrate the theory with examp

Jia-Ming Xie, Jun-Xu Lu, Li-Sheng Geng, Bing-Song Zou

In the past two decades, one of the most puzzling phenomena discovered in hadron physics is that a nominal hadronic state can actually correspond to two poles on the complex energy plane. This phenomenon was first noticed for the $\Lambda(1405)$, then for $K_1(1270)$, and to a lesser extent for $D_0^*(2300)$. In this Letter, we show explicitly how the two-po

Damir B. Krklješ, Goran V. Kitić, Csaba M. Petes, Slobodan S. Birgermajer

Due to the global water crisis there is a strong need for real-time water quality monitoring with high temporal and spatial resolution. This paper presents an economical multiparameter water quality monitoring system for continuous monitoring of fresh waters. It is based on a sensor node that integrates turbidity, temperature, and conductivity sensors, a min

Jiayu Chen, Jingdi Chen, Tian Lan, Vaneet Aggarwal

Covering skill (a.k.a., option) discovery has been developed to improve the exploration of RL in single-agent scenarios with sparse reward signals, through connecting the most distant states in the embedding space provided by the Fiedler vector of the state transition graph. Given that joint state space grows exponentially with the number of agents in multi-

Xingyu Zhu, Guanhui Ye, Xiapu Luo, Xuetao Wei

The goal of 3D mesh watermarking is to embed the message in 3D meshes that can withstand various attacks imperceptibly and reconstruct the message accurately from watermarked meshes. The watermarking algorithm is supposed to withstand multiple attacks, and the complexity should not grow significantly with the mesh size. Unfortunately, previous methods are le

F. Lesjak, L. Nortmann, F. Yan, D. Cont

Accurately estimating the C/O ratio of hot Jupiter atmospheres is a promising pathway towards understanding planet formation and migration, as well as the formation of clouds and the overall atmospheric composition. The atmosphere of the hot Jupiter WASP-43b has been extensively analysed using low-resolution observations with HST and Spitzer, but these previ

Ülle-Linda Talts, Helena C. Weigand, Grégoire Saerens, Peter Benedek

The quest of a nonlinear optical material that can be easily nanostructured over a large surface area is still ongoing. Here, we demonstrate a nanoimprinted nonlinear barium titanate 2D nanohole array that shows optical properties of a 2D photonic crystal and metasurface, depending on the direction of the optical axis. The challenge of nanostructuring the in

Hojin Chu, Suh-Ryung Kim

If each vertex of an acyclic digraph has indegree at most $i$ and outdegree at most $j$, then it is called an $(i,j)$ digraph, which was introduced by Hefner~{\it et al.}~(1991). Whereas Hefner~{\it et al.} characterized $(i,j)$ digraphs whose competition graphs are interval, characterizing the competition graphs of $(i,j)$ digraphs is not an easy task. In t

Saba Karimeddiny, Thow Min Jerald Cham, Orion Smedley, Daniel C. Ralph

Sagnac interferometry can provide a significant improvement in signal-to-noise ratio compared to conventional magnetic imaging based on the magneto-optical Kerr effect (MOKE). We show that this improvement is sufficient to allow quantitative measurements of current-induced magnetic deflections due to spin-orbit torque even in thin-film magnetic samples with

Sergiy Stryzhenko, Alexander Bruns, Thorsten Peters

We experimentally study collective decay of an extended disordered ensemble of $N$ atoms inside a hollow-core fiber. We observe up to $300$-fold enhanced decay rates, strong optical bursts and a coherent ringing. Due to inhomogeneities limiting the synchronization of atoms, the data does not show the typical scaling with $N$. We show that an effective number

Bharath K Rameshbabu, Sumukh S Balakrishna, Brian Flynn, Vinayak Kapoor

We present a benchmarking study of vision-based robotic grasping algorithms and provide a comparative analysis. In particular, we compare two machine-learning-based and two analytical algorithms using an existing benchmarking protocol from the literature and determine the algorithms strengths and weaknesses under different experimental conditions. These cond

Teresa Alsinet, Josep Argelich, Ramón Béjar, Santi Martínez

The Bipartite Polarization Problem is an optimization problem where the goal is to find the highest polarized bipartition on a weighted and labelled graph that represents a debate developed through some social network, where nodes represent user's opinions and edges agreement or disagreement between users. This problem can be seen as a generalization of the

Xiangsen Wang, Haoran Xu, Yinan Zheng, Xianyuan Zhan

Offline reinforcement learning (RL) has received considerable attention in recent years due to its attractive capability of learning policies from offline datasets without environmental interactions. Despite some success in the single-agent setting, offline multi-agent RL (MARL) remains to be a challenge. The large joint state-action space and the coupled mu

Lauritz van Luijk, René Schwonnek, Alexander Stottmeister, Reinhard F. Werner

In quantum information theory, the Schmidt rank is a fundamental measure for the entanglement dimension of a pure bipartite state. Its natural definition uses the Schmidt decomposition of vectors on bipartite Hilbert spaces, which does not exist (or at least is not canonically given) if the observable algebras of the local systems are allowed to be general C

Duojun Huang, Jichang Li, Weikai Chen, Junshi Huang

Active domain adaptation (ADA) aims to improve the model adaptation performance by incorporating active learning (AL) techniques to label a maximally-informative subset of target samples. Conventional AL methods do not consider the existence of domain shift, and hence, fail to identify the truly valuable samples in the context of domain adaptation. To accomm

Zehan Zhu, Ye Tian, Yan Huang, Jinming Xu

Perfect synchronization in distributed machine learning problems is inefficient and even impossible due to the existence of latency, package losses and stragglers. We propose a Robust Fully-Asynchronous Stochastic Gradient Tracking method (R-FAST), where each device performs local computation and communication at its own pace without any form of synchronizat

Zoe A. Le Conte, Martin Elvis, Philipp A. Gläser

The origin and evolution of structure in the Universe could be studied in the Dark Ages. The highly redshifted HI signal between 30 < z < 80 is the only observable signal from this era. Human radio interference and ionospheric effects limit Earth-based radio astronomy to frequencies > 30 MHz. To observe the low-frequency window with research from compact ste

Lorenzo Gavassino, Masoud Shokri

We obtain stability criteria for diffusive inviscid multicomponent Israel-Stewart hydrodynamics with and without background or dynamic electromagnetic fields. Our analysis is grounded on the maximum entropy principle, and it provides stability conditions that are valid around all thermodynamic equilibria, including rotating equilibria, charged equilibria, an

Luis Almeida, Jesús Bellver Arnau, Yannick Privat, Carlota Rebelo

This paper is devoted to the study of optimal release strategies to control vector-borne diseases, such as dengue, Zika, chikungunya and malaria. Two techniques are considered: the sterile insect one (SIT), which consists in releasing sterilized males among wild vectors in order to perturb their reproduction, and the Wolbachia one (presently used mainly for

Rachel Cionitti, Brandon Coleman, Allison Kirkpatrick, Greg Troiani

Active Galactic Nuclei (AGN) are intensely accreting supermassive black holes at the centers of massive galaxies. Though these objects occupy little spatial extent of the galaxy itself, they are thought to have far reaching affects, impacting the galaxy's star formation, and possibly it's lifespan until it becomes 'red and dead'. Typical galaxies demonstrate

Sushant G. Ghosh, Shafqat Ul Islam, Sunil D. Maharaj

Exact solutions describing rotating black holes can provide significant opportunities for testing modified theories of gravity, which are motivated by the challenges posed by dark energy and dark matter. Starting with a spherical Kiselev black hole as a seed metric, we construct rotating Kiselev black holes within the $f(R,T)$ gravity framework using the rev

Yichi Zhang, Wen Zhang

Knowledge graph embedding (KGE) focuses on representing the entities and relations of a knowledge graph (KG) into the continuous vector spaces, which can be employed to predict the missing triples to achieve knowledge graph completion (KGC). However, KGE models often only briefly learn structural correlations of triple data and embeddings would be misled by

Ying Lu, Pei Shi, Xiao-Han Wang, Jie Hu

Entanglement propagation provides a key routine to understand quantum many-body dynamics in and out of equilibrium. The entanglement entropy (EE) usually approaches to a sub-saturation known as the Page value $\tilde{S}_{P} =\tilde{S} - dS$ (with $\tilde{S}$ the maximum of EE and $dS$ the Page correction) in, e.g., the random unitary evolutions. The ballisti

Gabriel Fernández-Fernández, Carlo Manzo, Maciej Lewenstein, Alexandre Dauphin

Stochastic processes have found numerous applications in science, as they are broadly used to model a variety of natural phenomena. Due to their intrinsic randomness and uncertainty, they are, however, difficult to characterize. Here, we introduce an unsupervised machine learning approach to determine the minimal set of parameters required to effectively des

Jakob Bach

Feature selection is popular for obtaining small, interpretable, yet highly accurate prediction models. Conventional feature-selection methods typically yield one feature set only, which might not suffice in some scenarios. For example, users might be interested in finding alternative feature sets with similar prediction quality, offering different explanati

Raja Yehia, Matteo Schiavon, Valentina Marulanda Acosta, Tim Coopmans

We present and analyse an architecture for a European-scale quantum network using satellite links to connect Quantum Cities, which are metropolitan quantum networks with minimal hardware requirements for the end users. Using NetSquid, a quantum network simulation tool based on discrete events, we assess and benchmark the performance of such a network linking

Lucia Scardia, Konstantinos Zemas, Caterina Ida Zeppieri

In this paper we study the convergence of integral functionals with $q$-growth in a randomly perforated domain of $\mathbb R^n$, with $1<q<n$. Under the assumption that the perforations are small balls whose centres and radii are generated by a \emph{stationary short-range marked point process}, we obtain in the critical-scaling limit an averaged analogue of

Qingyue Wei, Lequan Yu, Xianhang Li, Wei Shao

Medical imaging has witnessed remarkable progress but usually requires a large amount of high-quality annotated data which is time-consuming and costly to obtain. To alleviate this burden, semi-supervised learning has garnered attention as a potential solution. In this paper, we present Meta-Learning for Bootstrapping Medical Image Segmentation (MLB-Seg), a

Pierre Rougé, Nicolas Passat, Odyssée Merveille

Vessel segmentation and centerline extraction are two crucial preliminary tasks for many computer-aided diagnosis tools dealing with vascular diseases. Recently, deep-learning based methods have been widely applied to these tasks. However, classic deep-learning approaches struggle to capture the complex geometry and specific topology of vascular networks, wh

Alberto Bressan, Geng Chen, Shoujun Huang

In this paper, we consider the Cauchy problem for pressureless gases in two space dimensions with generic smooth initial data (density and velocity). These equations give rise to singular curves, where the mass has positive density w.r.t.~1-dimensional Hausdorff measure. We observe that the system of equations describing these singular curves is not hyperbol

Luisa Fermo, Lothar Reichel, Giuseppe Rodriguez, Miodrag M. Spalević

Fredholm integral equations of the second kind that are defined on a finite or infinite interval arise in many applications. This paper discusses Nystr\"om methods based on Gauss quadrature rules for the solution of such integral equations. It is important to be able to estimate the error in the computed solution, because this allows the choice of an appropr

Dominic Hunter, Marcin S. Mrozowski, Allan McWilliam, Stuart J. Ingleby

Spin preparation prior to a free-induction-decay (FID) measurement can be adversely affected by transverse bias fields, particularly in the geophysical field range. A strategy that enhances the spin polarization accumulated before readout is demonstrated, by synchronizing optical pumping with a magnetic field pulse that supersedes any transverse fields by ov

Jie Wang

This note proposes a new reformulation of complex semidefinite programs (SDPs) as real SDPs. As an application, we present an economical reformulation of complex SDP relaxations of complex polynomial optimization problems as real SDPs and derive some further reductions by exploiting inner structure of the complex SDP relaxations. Various numerical examples d

Catia Grimani, Vincenzo Andretta, Ester Antonucci, Paolo Chioetto

Context. Galactic cosmic rays (GCRs) and solar particles with energies greater than tens of MeV penetrate spacecraft and instruments hosted aboard space missions. The Solar Orbiter Metis coronagraph is aimed at observing the solar corona in both visible (VL) and ultraviolet (UV) light. Particle tracks are observed in the Metis images of the corona. An algori

Tianyi Ren, An Zhang

We improve Frank-Sabin's work concerning the spectral cluster bounds for orthonormal systems at $p=\infty$, on the flat torus and spaces of nonpositive sectional curvature, by shrinking the spectral band from $[\lambda^{2}, (\lambda+1)^{2})$ to $[\lambda^{2}, (\lambda+\epsilon(\lambda))^{2})$, where $\epsilon(\lambda)$ is a function of $\lambda$ that goes to

Victoria Gould, Ambroise Grau, Marianne Johnson

The full transformation semigroups $\mathcal{T}_n$, where $n\in \mathbb{N}$, consisting of all maps from a set of cardinality $n$ to itself, are arguably the most important family of finite semigroups. This article investigates the endomorphism monoid End($\mathcal{T}_n$) of $\mathcal{T}_n$. The determination of the elements of End($\mathcal{T}_n$) is due Sc

Dyna Ibrahim, Chiaki Kobayashi

Metallicity is a fundamental physical property that strongly constrains galaxy formation and evolution. The formation of stars in galaxies is suppressed by the energy released from supernova explosions and can be enhanced by metal production. In order to understand the impact of this supernova feedback, we compare four different feedback methods, ejecting en

Takeshi Kato, Jyunichi Miyakoshi, Tadayuki Matsumura, Ryuji Mine

Social isolation is caused by the impoverishment of community (atomism) and fragmentation is caused by the enlargement of in-group (mobism), both of which can be viewed as social problems related to communication. To solve these problems, the philosophical world has proposed the concept of "mixbiotic society," in which individuals with freedom and diverse va

Allan Kardec de Almeida Junior, Safwan Aljbaae, Timothée Vaillant, Jhonathan M. Piñeros

The growing population of man-made objects with the build up of mega-constellations not only increases the potential danger to all space vehicles and in-space infrastructures (including space observatories), but above all poses a serious threat to astronomy and dark skies. Monitoring of this population requires precise satellite characterization, which is is

Rupal Kaushik, Suvendu Nandi, Mahitosh mandal, Amar Nath Gupta

The development of multi-drug-resistant bacterial infections seriously threatens public health, so efforts are needed to develop a new class of safe and effective antibacterial agents. Here, we report a bio-inspired synthesis of surface-modified MoS$_2$ Nanoflowers with L-cysteine (MoS$_2$-cys NFs) that show good colloidal stability in an aqueous medium. The

Ming-Da Huang, Zhan-Feng Jiang, Hong-Yi Chen, Ying Zuo

The range and speed of a moving object can be ascertained using the sensing technique known as light detection and ranging (LiDAR). It has recently been suggested that quantum LiDAR, which uses entangled states of light, can enhance the capabilities of LiDAR. Entangled pulsed light is used in prior quantum LiDAR approaches to assess both range and velocity a

Mohammad Alsalti, Ivan Markovsky, Victor G. Lopez, Matthias A. Müller

Non-parametric representations of dynamical systems based on the image of a Hankel matrix of data are extensively used for data-driven control. However, if samples of data are missing, obtaining such representations becomes a difficult task. By exploiting the kernel structure of Hankel matrices of irregularly measured data generated by a linear time-invarian

Damian Owerko, Charilaos I. Kanatsoulis, Jennifer Bondarchuk, Donald J. Bucci

Recent advances in hardware and big data acquisition have accelerated the development of deep learning techniques. For an extended period of time, increasing the model complexity has led to performance improvements for various tasks. However, this trend is becoming unsustainable and there is a need for alternative, computationally lighter methods. In this pa

Ignasi Vélez-Cerón, Pau Guillamat, Francesc Sagués, Jordi Ignés-Mullol

In this work, we report a direct measurement of the forces exerted by a tubulin/kinesin active nematic gel as well as its complete rheological characterization, including the quantification of its shear viscosity, {\eta}, and its activity parameter, {\alpha}. For this, we develop a novel method that allows us to rapidly photo-polymerize compliant elastic inc

C. Grazioli, Dario Alfè, S. R. Krishnakumar, Subhra Sen Gupta

The occurrence of a noncollinear magnetic structure at a Mn monolayer grown epitaxially on Fe(100) is predicted theoretically, using spinor density-functional theory, and observed experimentally, using x-ray magnetic circular dichroism (XMCD) and linear dichroism (XMLD) spectroscopies. The combined use of XMCD and XMLD at the Mn-absorption edge allows us to

Jinchao Huang, Sibo Wang

This paper studies the \emph{subset sampling} problem. The input is a set $\mathcal{S}$ of $n$ records together with a function $\textbf{p}$ that assigns each record $v\in\mathcal{S}$ a probability $\textbf{p}(v)$. A query returns a random subset $X$ of $\mathcal{S}$, where each record $v\in\mathcal{S}$ is sampled into $X$ independently with probability $\te

Zeinab Sadat Taghavi, Ali Satvaty, Hossein Sameti

Speech Emotion Recognition (SER) is a challenging task. In this paper, we introduce a modality conversion concept aimed at enhancing emotion recognition performance on the MELD dataset. We assess our approach through two experiments: first, a method named Modality-Conversion that employs automatic speech recognition (ASR) systems, followed by a text classifi

Jasashwi Mandal, Adrijit Goswami, Lakshman Thakur, Manoj Kumar Tiwari

Due to a substantial growth in the world waterborne trade volumes and drastic changes in the global climate accounted for CO2 emissions, the shipping companies need to escalate their operational and energy efficiency. Therefore, a multi-objective mixed-integer non-linear programming (MINLP) model is proposed in this study to simultaneously determine the opti

Iris Fürst-Walter, Antonio Nappi, Tanja Harbaum, Jürgen Becker

Human Pose Estimation (HPE) to assess human motion in sports, rehabilitation or work safety requires accurate sensing without compromising the sensitive underlying personal data. Therefore, local processing is necessary and the limited energy budget in such systems can be addressed by Inertial Measurement Units (IMU) instead of common camera sensing. The cen

Pouya Bakhti, Meshkat Rajaee, Seon-Hee Seo, Seodong Shin

We investigate the sensitivities of the liquid scintillator counter (LSC) at Yemilab and JUNO to solar neutrino oscillation parameters, focusing on $\theta_{12}$ and $\Delta m^2_{21}$. We compare the potential of JUNO with LSC at Yemilab utilizing both reactor and solar data in determining those parameters. We find that the solar neutrino data of LSC at Yemi

Feimin Huang, Houzhi Tang, Weiyuan Zou

In this paper, we present a new framework for the global well-posedness and large-time behavior of a two-phase flow system, which consists of the pressureless Euler equations and incompressible Navier-Stokes equations coupled through the drag force. To overcome the difficulties arising from the absence of the pressure term in the Euler equations, we establis

Ismael Bailleul, Ilya Chevyrev, Massimiliano Gubinelli

We introduce Wilson-It\^o diffusions, a class of random fields on $\mathbb{R}^d$ that change continuously along a scale parameter via a Markovian dynamics with local coefficients. Described via forward-backward stochastic differential equations, their observables naturally form a pre-factorization algebra \`a la Costello-Gwilliam. We argue that this is a new

Timur Sadykov

We revisit the classical problem of construction of a fundamental system of solutions to a linear ODE whose elements remain analytic and linearly independent for all values of the roots of the characteristic polynomial.

Lorenzo Brandolese, Yuliia Samoilenko, Valerii Samoilenko

The paper deals with the construction of the asymptotic soliton-like and the asymptotic peakon-like solutions to the modified Camassa-Holm equation with variable coefficicents and a singular perturbation. This equation is a generalization of the well known modified Camassa-Holm equation which is integrable system and in addition to the soliton solutions the

Marco Knöll, Robert Roth

Ab initio structure calculations for p-shell hypernuclei have recently become accessible through extensions of nuclear many-body methods, such as the no-core shell model, in combination with hyperon-nucleon interactions from chiral effective field theory. However, the low-energy constants in these hyperon-nucleon interactions are poorly constraint due to the

Y. J. Aidelman, M. Borges Fernandes, L. S. Cidale, A. Smith Castelli

Context. Stars in transition phases, like those showing the B[e] phenomenon and luminous blue variables (LBVs), undergo strong, often irregular mass ejection events. The prediction of these phases in stellar evolution models is therefore extremely difficult if not impossible. As a result, their effective temperatures, their luminosities and even their true n

Elisabeth Stockinger, Riccardo Gallotti, Carina I. Hausladen

Social media manipulation poses a significant threat to cognitive autonomy and unbiased opinion formation. Prior literature explored the relationship between online activity and emotional state, cognitive resources, sunlight and weather. However, a limited understanding exists regarding the role of time of day in content spread and the impact of user activit

Vipin Kumar, A. S. Rajpurohit, Mudit K. Srivastava, José G. Fernández-Trincado

The time scales of variability in active M dwarfs can be related to their various physical parameters. Thus, it is important to understand such variability to decipher the physics of these objects. In this study, we have performed the low resolution ($\sim$5.7\AA) spectroscopic monitoring of 83 M dwarfs (M0-M6.5) to study the variability of H$\alpha$ / H$\be

Youngwoo Sim, Guillermo Colin, Joao Ramos

Athletic robots demand a whole-body actuation system design that utilizes motors up to the boundaries of their performance. However, creating such robots poses challenges of integrating design principles and reasoning of practical design choices. This paper presents a design framework that guides designers to find optimal design choices to create an actuatio

Valerio Capraro, Roberto Di Paolo, Veronica Pizziol

Generative artificial intelligence (AI) holds enormous potential to revolutionize decision-making processes, from everyday to high-stake scenarios. By leveraging generative AI, humans can benefit from data-driven insights and predictions, enhancing their ability to make informed decisions that consider a wide array of factors and potential outcomes. However,

Yuexin Li, Bryan Hooi

Multimodal data empowers machine learning models to better understand the world from various perspectives. In this work, we study the combination of \emph{text and graph} modalities, a challenging but understudied combination which is prevalent across multiple settings including citation networks, social media, and the web. We focus on the popular task of no

Maxime L. D. Nicolas, Adrien Desroziers, Fabio Caccioli, Tomaso Aste

We investigate the response of shareholders to Environmental, Social, and Governance-related reputational risk (ESG-risk), focusing exclusively on the impact of social media. Using a dataset of 114 million tweets about firms listed on the S&P100 index between 2016 and 2022, we extract conversations discussing ESG matters. In an event study design, we define

Luca Buonocore, Massimiliano Grazzini, Jürg Haag, Luca Rottoli

We consider the class of inclusive hadron collider processes in which one or more energetic jets are produced, possibly accompanied by colourless particles. We provide a general formulation of a slicing scheme for this class of processes, by identifying the various contributions that need to be computed up to next-to-leading order (NLO) in QCD perturbation t

C. Moutou, X. Delfosse, A. C. Petit, J. -F. Donati

SPIRou is a near-infrared spectropolarimeter and a high-precision velocimeter. The SPIRou Legacy Survey collected data from February 2019 to June 2022, half of the time devoted to a blind search for exoplanets around nearby cool stars. The aim of this paper is to present this program and an overview of its properties, and to revisit the radial velocity (RV)

Abderrahmane Benhadjira, Abdelhakim Benkrane, Omar Bentouila, Hadjira Benzair

In this study, an analytical investigation was conducted to assess the effects of the extended uncertainty principle (EUP) on a Bose-Einstein condensate (BEC) described by the deformed one-dimensional Gross-Pitaevskii equation (GPE). Analytical solutions were derived for null potential while we used variational and numerical methods for a harmonic oscillator

Richard McKinley, Christian Rummel

The thickness of the cortical band is linked to various neurological and psychiatric conditions, and is often estimated through surface-based methods such as Freesurfer in MRI studies. The DiReCT method, which calculates cortical thickness using a diffeomorphic deformation of the gray-white matter interface towards the pial surface, offers an alternative to

David J. Armstrong, Ares Osborn, Vardan Adibekyan, Elisa Delgado-Mena

We report the discovery of two exoplanets orbiting around HD 212729 (TOI\,1052, TIC 317060587), a $T_{\rm eff}=6146$K star with V=9.51 observed by TESS in Sectors 1 and 13. One exoplanet, TOI-1052b, is Neptune-mass and transits the star, and an additional planet TOI-1052c is observed in radial velocities but not seen to transit. We confirm the planetary natu

Dong Huang, Qingwen Bu

Deep neural networks have been widely used in many critical applications, such as autonomous vehicles and medical diagnosis. However, their security is threatened by backdoor attacks, which are achieved by adding artificial patterns to specific training data. Existing defense strategies primarily focus on using reverse engineering to reproduce the backdoor t

Peter M. Neumann

This is a transcript of a lecture course on Infinite Permutation Groups given by Peter M. Neumann (1940-2020) in Oxford during the academic year 1988-1989. The field of Infinite Permutation Groups only emerged as an independent field of study in the 1980's. Most of the results described in these notes were at the time of the lectures brand new and had either

Taha Sajjad, Andrew W. Eckford

Existing molecular communication systems, both theoretical and experimental, are characterized by low information rates. In this paper, inspired by time-of-flight mass spectrometry (TOFMS), we consider the design of a molecular communication system in which the channel is a vacuum and demonstrate that this method has the potential to increase achievable info

Dong Huang, Qingwen Bu, Yahao Qing, Yichao Fu

Due to the widespread application of deep neural networks~(DNNs) in safety-critical tasks, deep learning testing has drawn increasing attention. During the testing process, test cases that have been fuzzed or selected using test metrics are fed into the model to find fault-inducing test units (e.g., neurons and feature maps, activating which will almost cert

Sören Buchenau, Benjamin Grimm-Lebsanft, Florian Biebl, Tomke Glier

Degenerate states in condensed matter are frequently the cause of unwanted fluctuations, which prevent the formation of ordered phases and reduce their functionalities. Removing these degeneracies has been a common theme in materials design, pursued for example by strain engineering at interfaces. Here, we explore a non-equilibrium approach to lift degenerac

Saak Gabriyelyan

We prove that a Tychonoff space $X$ is an Ascoli space (resp., a sequentially Ascoli space) if and only if for each Banach space $E$, every $k$-continuous and almost $k$-compact (resp., almost $k$-sequential) map $T$ form $X$ into the Banach dual $E'$ of $E$ is continuous.

Hikaru Watanabe, Kohei Shinohara, Takuya Nomoto, Atsushi Togo

Recent studies identified spin-order-driven phenomena such as spin-charge interconversion without relying on the relativistic spin-orbit interaction. Those physical properties can be prominent in systems containing light magnetic atoms due to sizable exchange splitting and may pave the way for realization of giant responses correlated with the spin degree of

Zsolt Páles, Paweł Pasteczka

In this paper, we consider homogeneous quasideviation means generated by real functions (defined on $(0,\infty)$) which are concave around the point $1$ and possess certain upper estimates near $0$ and $\infty$. It turns out that their concave envelopes can be completely determined. Using this description, we establish sufficient conditions for the Hardy pro

Zhihong Chen, Ruifei Zhang, Yibing Song, Xiang Wan

Visual grounding (VG) aims to establish fine-grained alignment between vision and language. Ideally, it can be a testbed for vision-and-language models to evaluate their understanding of the images and texts and their reasoning abilities over their joint space. However, most existing VG datasets are constructed using simple description texts, which do not re

A. Borga, R. Blair, G. J. Crone, B. Green

The ReadOut System (ROS) is a central part of the data acquisition (DAQ) system of the ATLAS Experiment at the CERN Large Hadron Collider (LHC). The system is responsible for receiving and buffering event data from all detector subsystems and serving these to the High Level Trigger (HLT) system via a 10 GbE network, discarding or transporting data onward onc

Robin Mroß, Aron Schnakenbeck, Marcus Völker, Alexander Fay

IEC 60848 GRAFCET is a standardized, graphical specification language for control functions. Because of the semiformal nature of IEC 60848, the details of specifications created with GRAFCET can be interpreted in different ways, possibly leading to faulty implementations. These ambiguities have been partially addressed in existing literature, but solved in d

Laurent U Perrinet

Recently, interest has grown in exploring the hypothesis that neural activity conveys information through precise spiking motifs. To investigate this phenomenon, various algorithms have been proposed to detect such motifs in Single Unit Activity (SUA) recorded from populations of neurons. In this study, we present a novel detection model based on the inversi

Jan-Gerrit Habekost, Erik Strahl, Philipp Allgeuer, Matthias Kerzel

The paper introduces CycleIK, a neuro-robotic approach that wraps two novel neuro-inspired methods for the inverse kinematics (IK) task, a Generative Adversarial Network (GAN), and a Multi-Layer Perceptron architecture. These methods can be used in a standalone fashion, but we also show how embedding these into a hybrid neuro-genetic IK pipeline allows for f

Imke Botha, Robert Kohn, Leah South, Christopher Drovandi

Sequential Monte Carlo squared (SMC$^2$; Chopin et al., 2012) methods can be used to sample from the exact posterior distribution of intractable likelihood state space models. These methods are the SMC analogue to particle Markov chain Monte Carlo (MCMC; Andrieu et al., 2010) and rely on particle MCMC kernels to mutate the particles at each iteration. Two op

Jakob Schlör, Felix Strnad, Antonietta Capotondi, Bedartha Goswami

El Ni\~no Southern Oscillation (ENSO) diversity is characterized based on the longitudinal location of maximum sea surface temperature anomalies (SSTA) and amplitude in the tropical Pacific, as Central Pacific (CP) events are typically weaker than Eastern Pacific (EP) events. SSTA pattern and intensity undergo low-frequency modulations, affecting ENSO predic

Faezeh Khodabandehlou, Christian Maes

Close to equilibrium, the excess heat governs the static fluctuations. We study the heat capacity in that McLennan regime, i.e., in linear order around equilibrium, using an expression in terms of the average energy that extends the equilibrium formula in the canonical ensemble. It is derivable from an entropy and it always vanishes at zero temperature. Any

Arul Selvam Periyasamy, Arash Amini, Vladimir Tsaturyan, Sven Behnke

6D object pose estimation is a crucial prerequisite for autonomous robot manipulation applications. The state-of-the-art models for pose estimation are convolutional neural network (CNN)-based. Lately, Transformers, an architecture originally proposed for natural language processing, is achieving state-of-the-art results in many computer vision tasks as well

Étienne Payet

We present a new syntactic criterion for the automatic detection of non-termination in an abstract setting that encompasses a simplified form of term rewriting and logic programming.

Cécile Appert-Rolland, Anne-Hélène Olivier, Julien Pettré

This article deals with the experimental study of pedestrian behaviours in some situations of one-dimensional traffic. Participants were pre-organized in a line, and asked to walk either in a straight line with a fast or slow leader, or to form a circle. The originality of our experimental protocol compared to previous ones on similar situations, is to have

Cihan Sabuncu

We study the moments of the function that counts the number of representations of an integer as sums of two prime squares. We refine some of the previous arguments and apply the Selberg sieve to get an unconditional upper bound for all moments. We also prove a lower bound for all moments conditional on some generalization of the Green-Tao theorem on linear e

Brendan D. Tracey, Andrea Michi, Yuri Chervonyi, Ian Davies

Reinforcement learning (RL) has shown promising results for real-time control systems, including the domain of plasma magnetic control. However, there are still significant drawbacks compared to traditional feedback control approaches for magnetic confinement. In this work, we address key drawbacks of the RL method; achieving higher control accuracy for desi

Zunnan Xu, Zhihong Chen, Yong Zhang, Yibing Song

Parameter Efficient Tuning (PET) has gained attention for reducing the number of parameters while maintaining performance and providing better hardware resource savings, but few studies investigate dense prediction tasks and interaction between modalities. In this paper, we do an investigation of efficient tuning problems on referring image segmentation. We