May 2024 arXiv papers — page 77

Vladislav Cherepanov, Sebastian W. Ertel

In this paper we introduce a novel Neural Networks-based approach for approximating solutions to the (2D) incompressible Navier--Stokes equations, which is an extension of so called Deep Random Vortex Methods (DRVM), that does not require the knowledge of the Biot--Savart kernel associated to the computational domain. Our algorithm uses a Neural Network (NN)

Emanuele Massa, Anthony Coolen

We study the asymptotic behaviour of the Regularized Maximum Partial Likelihood Estimator (RMPLE) in the proportional limit, considering an arbitrary convex regularizer and assuming that the covariates $\mathbf{X}_i\in\mathbb{R}^{p}$ follow a multivariate Gaussian law with covariance $\mathbf{I}_p/p$ for each $i=1, \dots, n$. In order to efficiently compute

Clément Salducci, Yannick Bidel, Malo Cadoret, Sarah Darmon

Accurate measurement of inertial quantities is essential in geophysics, geodesy, fundamental physics and navigation. For instance, inertial navigation systems require stable inertial sensors to compute the position and attitude of the carrier. Here, we present an architecture for a compact cold-atom accelerometer-gyroscope based on a magnetically launched at

B. T. Buijtendorp, A. Endo, W. Jellema, K. Karatsu

Low-loss deposited dielectrics are beneficial for the advancement of superconducting integrated circuits for astronomy. In the microwave band ($\mathrm{\sim}$1$\unicode{x2013}$10 GHz) the cryogenic and low-power dielectric loss is dominated by two-level systems. However, the origin of the loss in the millimeter-submillimeter band ($\mathrm{\sim}$0.1$\unicode

Beyhan Karakas, Rahime Matur, Maximilian Ruffert

We investigate the effect of spin on equal and unequal mass binary neutron star mergers using finite-temperature, composition-dependent Steiner-Fischer-Hempel equation of state with parameter set ``o'' (SFHo), via 3+1 general relativistic hydrodynamics simulations which take into account neutrino emission and absorption. Equal mass, irrotational cases that h

Yuyu Jia, Wei Huang, Junyu Gao, Qi Wang

Few-shot segmentation (FSS) for remote sensing (RS) imagery leverages supporting information from limited annotated samples to achieve query segmentation of novel classes. Previous efforts are dedicated to mining segmentation-guiding visual cues from a constrained set of support samples. However, they still struggle to address the pronounced intra-class diff

Divya Kothandaraman, Ming Lin, Dinesh Manocha

We introduce a novel approach for concept blending in pretrained text-to-image diffusion models, aiming to generate images at the intersection of multiple text prompts. At each time step during diffusion denoising, our algorithm forecasts predictions w.r.t. the generated image and makes informed text conditioning decisions. Central to our method is the uniqu

Guangzhi Sun, Potsawee Manakul, Adian Liusie, Kunat Pipatanakul

Multimodal foundation models are prone to hallucination, generating outputs that either contradict the input or are not grounded by factual information. Given the diversity in architectures, training data and instruction tuning techniques, there can be large variations in systems' susceptibility to hallucinations. To assess system hallucination robustness, h

Ingo Nitschke, Axel Voigt

We consider active nematodynamics on deformable surfaces. Based on a thermodynamically consistent surface Beris-Edwards model we add nematic activity and focus on the emerging additional coupling mechanism between the nematic field, the flow field and the curved surface. We analyse the impact of the active nematic force at topological defects. Under the pres

Sho Sonoda, Yuka Hashimoto, Isao Ishikawa, Masahiro Ikeda

We present a constructive universal approximation theorem for learning machines equipped with joint-group-equivariant feature maps, called the joint-equivariant machines, based on the group representation theory. ``Constructive'' here indicates that the distribution of parameters is given in a closed-form expression known as the ridgelet transform. Joint-gro

Liam Collard, Mohammadrahim Kazemzadeh, Massimo De Vittorio, Ferruccio Pisanello

Raman spectroscopy is a label-free, chemically specific optical technique which provides detailed information about the chemical composition and structure of the excited analyte. Because of this, there is growing research interest in miniaturizing Raman probes to reach deep regions of the body. Typically, such probes utilize multiple optical fibers to act as

Ulf Danielsson, Vincent Van Hemelryck

In this paper, we realise the charged Nariai black hole on a braneworld from a nucleated bubble in AdS$_5$, known as the dark bubble model. Geometrically, the black hole takes the form of a cylindrical spacetime pulling on the dark bubble. This is realised by a brane embedding in an AdS$_5$ black string background. Identifying the brane with a D3-brane in st

Chan Xu, Shuowen Zhang

This paper studies an integrated sensing and communication (ISAC) system where a multi-antenna base station (BS) aims to communicate with a single-antenna user in the downlink and sense the unknown and random angle parameter of a target via exploiting its prior distribution information. We consider a general transmit beamforming structure where the BS sends

Jack Fitzsimons, Agustín Freitas Pasqualini, Robert Pisarczyk, Dmitrii Usynin

Often we consider machine learning models or statistical analysis methods which we endeavour to alter, by introducing a randomized mechanism, to make the model conform to a differential privacy constraint. However, certain models can often be implicitly differentially private or require significantly fewer alterations. In this work, we discuss Determinantal

Qian Shen, Zi-Hao Huang, Shao-Ping Hu, Qing-Jie Yuan

In this paper, we give a proof of 5D $A_n$ AGT conjecture at $\beta=1$, where the gauge theory side is one dimension higher than the original 4D case, and corresponds to the q-deformation of the 2D conformal field theory side. We define a q-deformed $A_n$ Selberg integral, which generalizes the $A_n$ Selberg integral and the q-deformed $A_1$ Selberg integral

Zhu Yu, Runmin Zhang, Jiacheng Ying, Junchen Yu

Vision-based Semantic Scene Completion (SSC) has gained much attention due to its widespread applications in various 3D perception tasks. Existing sparse-to-dense approaches typically employ shared context-independent queries across various input images, which fails to capture distinctions among them as the focal regions of different inputs vary and may resu

Francesca Colasuonno, Benedetta Noris, Elisa Sovrano

For the following Neumann problem in a ball $$\begin{cases} -\Delta_p u+u^{p-1}=u^{q-1}\quad&\text{in }B,\\ u>0,\,u\text{ radial}\quad&\text{in }B,\\ \frac{\partial u}{\partial \nu}=0\quad&\text{on }\partial B, \end{cases}$$ with $1<p<q<\infty$, we prove continuous dependence on $p$, for radially nondecreasing solutions. As a byproduct, we obtain an existenc

Don N. Page

The inspiral merger time for two black holes captured into a nonrelativistic bound orbit by gravitational radiation emission has been often calculated by a formula of Peters that assumes the adiabatic approximation that the changes per orbit are small. However, initially this is not true for the semimajor axis and period of most of the initially highly eccen

Yimeng Shan, Malu Zhang, Rui-jie Zhu, Xuerui Qiu

Recent advancements in neuroscience research have propelled the development of Spiking Neural Networks (SNNs), which not only have the potential to further advance neuroscience research but also serve as an energy-efficient alternative to Artificial Neural Networks (ANNs) due to their spike-driven characteristics. However, previous studies often neglected th

Yu Xu, Hui Tian, Astrid M. Veronig, Karin Dissauer

Filament eruptions often lead to coronal mass ejections (CMEs) on the Sun and are one of the most energetic eruptive phenomena in the atmospheres of other late-type stars. However, the detection of filament eruptions and CMEs on stars beyond the solar system is challenging. Here we present six filament eruption cases on the Sun and show that filament materia

Anasuya Chattopadhyay, Daniel Reti, Hans D. Schotten

The early research report explores the possibility of using Graph Neural Networks (GNNs) for anomaly detection in internet traffic data enriched with information. While recent studies have made significant progress in using GNNs for anomaly detection in finance, multivariate time-series, and biochemistry domains, there is limited research in the context of n

Fergus R. Donnan, Dimitra Rigopoulou, Ismael García-Bernete

Polycyclic Aromatic Hydrocarbons (PAHs) are organic molecules which comprise the smallest particles of dust in the interstellar medium (ISM). Due to their broad/complex emission profiles, obtaining kinematics is a challenge with traditional methods, especially before the advent of the JWST. In this work we employ Principal Component Analysis (PCA) tomography

P. Müller, S. Kaufmann, T. Miyagi, J. Billowes

The magnetic dipole and the spectroscopic quadrupole moments of the nuclear ground states in the odd-mass nickel isotopes $^{59-67}$Ni have been determined using collinear laser spectroscopy at the CERN-ISOLDE facility. They are compared to ab initio valence-space in-medium similarity renormalization group (VS-IMSRG) calculations including contributions of t

Ewan O'Sullivan, Kamlesh Rajpurohit, Gerrit Schellenberger, Jan Vrtilek

NGC 777 provides an example of a phenomenon observed in some group-central ellipticals, in which the temperature profile shows a central peak, despite the short central cooling time of the intra-group medium. We use deep Chandra X-ray observations of the galaxy, supported by uGMRT 400 MHz radio imaging, to investigate the origin of this hot core. We confirm

Sagnik Chatterjee, Manuj Mukherjee, Alhad Sethi

In this work, we upper bound the generalization error of batch learning algorithms trained on samples drawn from a mixing stochastic process (i.e., a dependent data source) both in expectation and with high probability. Unlike previous results by Mohri et al. (2010) and Fu et al. (2023), our work does not require any stability assumptions on the batch learne

Javier E. Gonzalez, Marcelo Ferreira, Leorando R. Colaço, Rodrigo F. L. Holanda

In this work, we obtain Hubble constant ($H_0$) estimates by using two galaxy cluster gas mass fraction measurement samples, Type Ia supernovae luminosity distances, and the validity of the cosmic distance duality relation. Notably, the angular diameter distance (ADD) to each galaxy cluster in the samples is determined by combining its gas mass fraction meas

Chen-Zhong Shi, Xiang-Zhou Cai, De-Qing Fang, Yu-Gang Ma

The Extended Quantum Molecular Dynamics (EQMD) model is one of the few QMD-like transport approaches that can describe the $\alpha$-clustering structure with efficient computational power. However, compared to most QMD-like models, the choice of equation of state (EOS) for nuclear matter is very limited. In this work, a Monte Carlo integral method is employe

Szilárd Kálmán, Gyula M. Szabó, Csaba Kiss

Following the widespread practice of exoplanetary transit simulations, various presumed components of an extrasolar system can be examined in numerically simulated transits, including exomoons, rings around planets, and the deformation of exoplanets. Template signals can then be used to efficiently search for light curve features that mark specific phenomena

Ruishen Qian, Fanglei Wu, Hasi Wulan

Suppose $(C_t)_{t\geq0}$ is the composition semigroup induced by a one-parameter semigroup $(\varphi_t)_{t\geq0}$ of analytic self-maps of the unit disk. The main purpose of the paper is to investigate the spectrum of the infinitesimal generator of $(C_t)_{t\geq0}$ acting on the weighted Bergman space induced by doubling weights, provided $(\varphi_t)_{t\geq

Hong Zhang, Jie Lin, Shengxuan Chen

Timbre, the sound's unique "color", is fundamental to how we perceive and appreciate music. This review explores the multifaceted world of timbre perception and representation. It begins by tracing the word's origin, offering an intuitive grasp of the concept. Building upon this foundation, the article delves into the complexities of defining and measuring t

Yang Yang, Tim Weiss, Hamed Arianfard, Akram Youssry

The field of photonic integrated circuits has witnessed significant progress in recent years, with a growing demand for devices that offer high-performance reconfigurability. Due to the inability of conventional tunable directional couplers (TDCs) to maintain a fixed phase while tuning the reflectivity, Mach-Zehnder interferometers (MZIs) are employed as the

Yuhang Yang, Wei Zhai, Chengfeng Wang, Chengjun Yu

Understanding egocentric human-object interaction (HOI) is a fundamental aspect of human-centric perception, facilitating applications like AR/VR and embodied AI. For the egocentric HOI, in addition to perceiving semantics e.g., ''what'' interaction is occurring, capturing ''where'' the interaction specifically manifests in 3D space is also crucial, which li

Andrey A. Shevyrin, Askhat K. Bakarov, Alexander A. Shklyaev, Arthur G. Pogosov

In a nanomechanical resonator coupled to a quantum point contact, the back action of the electronic state on mechanical motion is studied. The quantum point contact conductance changing with subband index and the eigenfrequency of the resonator are found to correlate. A model is constructed explaining the frequency deviations by the alternating ability of th

Danilo Amigo, Felipe Lepe, Nitesh Verma

In this paper we analyze a conforming virtual element method to approximate the eigenfunctions and eigenvalues of the two dimensional Oseen eigenvalue problem. We consider the classic velocity-pressure formulation which allows us to consider the divergence-conforming virtual element spaces employed for the Stokes equations. Under standard assumptions on the

Rafał Latała

We discuss two-sided non-asymptotic bounds for the mean spectral norm of nonhomogenous weighted Rademacher matrices. We show that the recently formulated conjecture holds up to $\log \log \log n$ factor for arbitrary $n\times n$ Rademacher matrices and the triple logarithm may be eliminated for matrices with $\{0,1\}$-coefficients.

William Consagra, Lipeng Ning, Yogesh Rathi

Diffusion MRI (dMRI) is the primary imaging modality used to study brain microstructure in vivo. Reliable and computationally efficient parameter inference for common dMRI biophysical models is a challenging inverse problem, due to factors such as variable dimensionalities (reflecting the unknown number of distinct white matter fiber populations in a voxel),

Yang Yang, Robert J. Chapman, Akram Youssry, Ben Haylock

Over the past decade, integrated quantum photonic technologies have shown great potential as a platform for studying quantum phenomena and realizing large-scale quantum information processing. Recently, there have been proposals for utilizing waveguide lattices to implement quantum gates, providing a more compact and robust solution compared to discrete impl

Akshay Jain, Karthik Upadhya, Mikko A. Uusitalo, Harish Viswanathan

Communication technologies play a crucial role in battlefields. They are an inalienable part of any tactical response, whether at the battlefront or inland. Such scenarios require that the communication technologies be versatile, scalable, cost-effective, and stealthy. While multiple studies and past products have tried to address these requirements, none of

Chen-Zhong Shi, Xiang-Zhou Cai, Bo-Song Huang, Yu-Gang Ma

The extended quantum molecular dynamics (EQMD) model is one of the few quantum molecular dynamics (QMD)-like transport approaches that can be used to study the effective clustering structure as well as heavily deformed nuclei in both ground state nuclei and nuclear reactions. However, there are only two parameter sets that lead to hard incompressibility for

Minghao Zhang, Bifeng Song, Changhao Chen, Xinyu Lang

In control problems for insect-scale direct-drive experimental platforms under tandem wing influence, the primary challenge facing existing reinforcement learning models is their limited safety in the exploration process and the stability of the continuous training process. We introduce the ConcertoRL algorithm to enhance control precision and stabilize the

P. A. C. Cunha, A. Humphrey, J. Brinchmann, S. G. Morais

We aim to identify QSO2 candidates in the redshift desert using optical and infrared photometry. At this intermediate redshift range, most of the prominent optical emission lines in QSO2 sources (e.g. CIV1549; [OIII]4959,5008) fall either outside the wavelength range of the SDSS optical spectra or in particularly noisy wavelength ranges, making QSO2 identifi

Yongjun Chen, Liping Zhang

Dual quaternion matrices have various applications in robotic research and its spectral theory has been extensively studied in recent years. In this paper, we extend Jacobi method to compute all eigenpairs of dual quaternion Hermitian matrices and establish its convergence. The improved version with elimination strategy is proposed to reduce the computationa

Matteo Torzoni, Andrea Manzoni, Stefano Mariani

In the context of structural health monitoring (SHM), the selection and extraction of damage-sensitive features from raw sensor recordings represent a critical step towards solving the inverse problem underlying the identification of structural health conditions. This work introduces a novel approach that employs deep neural networks to enhance stochastic SH

Nicolas Fayard, David Ríos Insua, Alexis Tsoukiàs

This paper addresses decision-aiding problems that involve multiple objectives and uncertain states of the world. Inspired by the capability approach, we focus on cases where a policy maker chooses an act that, combined with a state of the world, leads to a set of choices for citizens. While no preferential information is available to construct importance pa

Mingyu Liu, Nana Bao, Xingting Yan, Chenyang Li

Understanding the combined influences of meteorological and hydrological factors on water level and flood events is essential, particularly in today's changing climate environments. Transformer, as one kind of the cutting-edge deep learning methods, offers an effective approach to model intricate nonlinear processes, enables the extraction of key features an

Fulin Deng, Xing-Yan Chen, Xin-Yu Luo, Wenxian Zhang

We investigate the static and dynamic properties of tetratomic molecules formed by two microwave-shielded polar molecules across field-linked resonances. In particular, we focus on two-body physics and experimental techniques unexplored in the recent experiment [X.-Y. Chen {\it et al}., Nature {\bf626}, 283 (2024)]. We show that, compared to the lowest tetra

James Howie

A conjecture of Rosenberger says that a group of the form $\langle x,y|x^p=y^q=W(x,y)^r=1\rangle$ (with $r>1$) is either virtually solvable or contains a non-abelian free subgroup. This note is an account of an attack on the conjecture in the case $(p,q,r)=(2,4,2)$. The results obtained are only partial, but nevertheless provide strong evidence in support of

Ross Straughan, Karim Kadry, Sahil A. Parikh, Elazer R. Edelman

Despite recent advances in diagnosis and treatment, atherosclerotic coronary artery diseases remain a leading cause of death worldwide. Various imaging modalities and metrics can detect lesions and predict patients at risk; however, identifying unstable lesions is still difficult. Current techniques cannot fully capture the complex morphology-modulated mecha

Simon Messelot, Nicolas Aparicio, Elie de Seze, Eric Eyraud

In a Josephson junction, the current phase relation relates the phase variation of the superconducting order parameter, $\varphi$, between the two superconducting leads connected through a weak link, to the dissipationless current . This relation is the fingerprint of the junction. It is usually dominated by a $\sin(\varphi)$ harmonic, however its precise kn

H. Ernandes, D. Feuillet, S. Feltzing, Á. Skúladóttir

The Gaia-Sausage-Enceladus merger was a major event in the history of the Milky Way. Studies on Milky Way satellite dwarf galaxies show that key elemental abundance patterns, which probe different nucleosynthetic channels, reflect the host galaxy's star formation history. We gather Mg, Fe, Ba, and Eu abundance measurements for Gaia-Sausage-Enceladus stars fr

Ying Ma, Owen Burns, Mingqiu Wang, Gang Li

Reinforcement learning (RL) is an effective method of finding reasoning pathways in incomplete knowledge graphs (KGs). To overcome the challenges of a large action space, a self-supervised pre-training method is proposed to warm up the policy network before the RL training stage. To alleviate the distributional mismatch issue in general self-supervised RL (S

Lingyun Yao, Martin Trapp, Jelin Leslin, Gaurav Singh

Probabilistic circuits (PCs) offer a promising avenue to perform embedded reasoning under uncertainty. They support efficient and exact computation of various probabilistic inference tasks by design. Hence, hardware-efficient computation of PCs is highly interesting for edge computing applications. As computations in PCs are based on arithmetic with probabil

Diogo Boito, Cristiane Y. London, Pere Masjuan, Camilo Rojas

The MUonE experiment is designed to extract the hadronic contribution to the electromagnetic coupling in the space-like region, $\Delta \alpha_{\rm had}(t)$, from elastic $e\mu$ scattering. The leading order hadronic vacuum polarization contribution to the muon $g-2$, $a_\mu^{\mathrm{HVP, \,LO}}$, can then be obtained from a weighted integral over $\Delta \a

Florinel-Alin Croitoru, Vlad Hondru, Radu Tudor Ionescu, Nicu Sebe

Direct Preference Optimization (DPO) has been proposed as an effective and efficient alternative to reinforcement learning from human feedback (RLHF). In this paper, we propose a novel and enhanced version of DPO based on curriculum learning for text-to-image generation. Our method is divided into two training stages. First, a ranking of the examples generat

Jiaju Lin, Haoxuan Hu

Audio tagging is an important task of mapping audio samples to their corresponding categories. Recently endeavours that exploit transformer models in this field have achieved great success. However, the quadratic self-attention cost limits the scaling of audio transformer models and further constrains the development of more universal audio models. In this p

Lukas Cvitkovich, Franz Fehringer, Christoph Wilhelmer, Diego Milardovich

Looking back at seven decades of highly extensive application in the semiconductor industry, silicon and its native oxide SiO$_2$ are still at the heart of several technological developments. Recently, the fabrication of ultra-thin oxide layers has become essential for keeping up with trends in down-scaling of nanoelectronic devices and for the realization o

Zixiang Ren, Siyao Zhang, Xinmin Li, Ling Qiu

This paper investigates secure communications in a near-field multi-functional integrated sensing, communication, and powering (ISCAP) system with an extremely large-scale antenna arrays (ELAA) equipped at the base station (BS). In this system, the BS sends confidential messages to a single communication user (CU), and at the same time wirelessly senses a po

Oscar D. H. Pardo, R. R. Rey-González

The design and development of new photonic devices for technological applications requires a deep understanding of the effect of structural properties on the resulting band gap size and its position. Here, we perform a theoretical study of behavior of the photonic band gap sizes, positions and percentages under variations of the parameters characterizing bin

Santtu Keskinen

Most of the dominant approaches to continual learning are based on either memory replay, parameter isolation, or regularization techniques that require task boundaries to calculate task statistics. We propose a static architecture-based method that doesn't use any of these. We show that we can improve the continual learning performance by replacing the final

Yeongtae Jang, Seokwoo Kim, Eunho Kim, Junsuk Rho

Band topology has emerged as a novel tool for material design across various domains, including photonic and phononic systems, and metamaterials. A prominent model for band topology is the Su-Schrieffer-Heeger (SSH) chain, which reveals topological in-gap states within Bragg-type gaps (BG) formed by periodic modification. Apart from classical BGs, another me

E. Quintin, N. A. Webb, I. Georgantopoulos, M. Gupta

Over recent decades, astronomy has entered the era of massive data and real-time surveys. This is improving the study of transient objects - although they still contain some of the most poorly understood phenomena in astrophysics, as it is inherently more difficult to obtain data on them. In order to help detect these objects in their brightest state, we hav

Chen-Hao Chao, Chien Feng, Wei-Fang Sun, Cheng-Kuang Lee

Existing Maximum-Entropy (MaxEnt) Reinforcement Learning (RL) methods for continuous action spaces are typically formulated based on actor-critic frameworks and optimized through alternating steps of policy evaluation and policy improvement. In the policy evaluation steps, the critic is updated to capture the soft Q-function. In the policy improvement steps,

N. Li, A. Brassington, M. F. Shu, Y. Y. Wang

Identifying the elusive spinon excitations in quantum spin liquid (QSL) materials is what scientists have long sought for. Recently, thermal conductivity ($\kappa$) has emerged to be a decisive probe because the fermionic nature of spinons leads to a characteristic nonzero linear $\kappa_0/T$ term while approaching zero Kelvin. So far, only a few systems hav

Resmi M, Elaganuru Bashaiah, Ramachandrarao Yalla

We demonstrate the fabrication of an optical nanofiber tip (ONFT) using a two-step chemical etching technique. This technique employs 30% and 24% hydrofluoric (HF) acid for the first and second steps, respectively. In the first step, a silica single-mode fiber with clad diameter of 125 um and core diameter of 10 um is immersed in the HF acid for 90 minutes.

Michael R. Clark, Syed A. Shah, Andrei Piryatinski, Maxim Sukharev

We conduct systematic studies of the optical characteristics of plasmonic nanoparticles that exhibit C2v symmetry. We analyze three distinct geometric configurations: an L-type shape, a crescent, and a split-ring resonator. Optical properties are examined using the FDTD method. It is demonstrated that all three shapes exhibit two prominent plasmon bands asso

Vladimir Kolmogorov, Simone Naldi, Jeferson Zapata

This paper deals with the algorithmic aspects of solving feasibility problems of semidefinite programming (SDP), aka linear matrix inequalities (LMI). Since in some SDP instances all feasible solutions have irrational entries, numerical solvers that work with rational numbers can only find an approximate solution. We study the following question: is it possi

Lei Du, Juliette Monsel, Witlef Wieczorek, Janine Splettstoesser

Ground-state cooling of mechanical resonators is a prerequisite for the observation of various quantum effects in optomechanical systems and thus has always been a crucial task in quantum optomechanics. In this paper, we study how to realize ground-state cooling of the mechanical mode in a Fano-mirror optomechanical setup, which allows for enhanced effective

Gui-Lei Zhu, Chang-Sheng Hu, Hui Wang, Wei Qin

We demonstrate the emergence of nonreciprocal superradiant phase transitions and novel multicriticality in a cavity quantum electrodynamics (QED) system, where a two-level atom interacts with two counter-propagating modes of a whispering-gallery-mode (WGM) microcavity. The cavity rotates at a certain angular velocity, and is directionally squeezed by a unidi

Gauthier Guinet, Behrooz Omidvar-Tehrani, Anoop Deoras, Laurent Callot

We propose a new method to measure the task-specific accuracy of Retrieval-Augmented Large Language Models (RAG). Evaluation is performed by scoring the RAG on an automatically-generated synthetic exam composed of multiple choice questions based on the corpus of documents associated with the task. Our method is an automated, cost-efficient, interpretable, an

Marco Doretti, Elena Stanghellini

With reference to a binary outcome and a binary mediator, we derive identification bounds for natural effects under a reduced set of assumptions. Specifically, no assumptions about confounding are made that involve the outcome; we only assume no unobserved exposure-mediator confounding as well as a condition termed partially constant cross-world dependence (

Iván Alfonso, Aaron Conrardy, Armen Sulejmani, Atefeh Nirumand

Low-code platforms (latest reincarnation of the long tradition of model-driven engineering approaches) have the potential of saving us countless hours of repetitive boilerplate coding tasks. However, as software systems grow in complexity, low-code platforms need to adapt as well. Notably, nowadays this implies adapting to the modeling and generation of smar

Suman Mahakal, Avijit Jana, Diptasikha Das, Nabakumar Rana

A drastic variation (~47%) in thermal conductivity (\k{appa}) for synthesized samples (TiCoSb1+x, x=0.0, 0.01, 0.02, 0.03, 0.04, and 0.06) is observed. The lowest \k{appa} is reported for the TiCoSb1.02 sample. Thermal variation of \k{appa} is estimated from the temperature and power-dependent Raman spectroscopy data. Embedded phases and Co vacancy are analy

Victor Reijgwart, Michael Pantic, Roland Siegwart, Lionel Ott

Fast and reliable obstacle avoidance is an important task for mobile robots. In this work, we propose an efficient reactive system that provides high-quality obstacle avoidance while running at hundreds of hertz with minimal resource usage. Our approach combines wavemap, a hierarchical volumetric map representation, with a novel hierarchical and parallelizab

Huseyin Er, Aykut Özdönmez, Ilham Nasiroglu, Muhammet Emir Kenger

To detect additional bodies in binary systems, we performed a potent approach of orbital period variation analysis. In this work, we present 90 new mid-eclipse times of a short-period eclipsing binary system. Observations were made using two telescopes from 2014 to 2024, extending the time span of the O-C diagram to 24 years. The data obtained in the last se

Sahar Badri, Serafino Cicerone, Alessia Di Fonso, Gabriele Di Stefano

For a set of robots (or agents) moving in a graph, two properties are highly desirable: confidentiality (i.e., a message between two agents must not pass through any intermediate agent) and efficiency (i.e., messages are delivered through shortest paths). These properties can be obtained if the \textsc{Geodesic Mutual Visibility} (GMV, for short) problem is

Andreas Čap, Zhangwen Guo, Michał Andrzej Wasilewicz

This article contributes to the relative BGG-machinery for parabolic geometries. Starting from a relative tractor bundle, this machinery constructs a sequence of differential operators that are naturally associated to the geometry in question. In many situations of interest, it is known that this sequence provides a resolution of a sheaf that can locally be

Alessio Conte, Roberto Grossi, Yasuaki Kobayashi, Kazuhiro Kurita

Graphlets of order $k$ in a graph $G$ are connected subgraphs induced by $k$ nodes (called $k$-graphlets) or by $k$ edges (called edge $k$-graphlets). They are among the interesting subgraphs in network analysis to get insights on both the local and global structure of a network. While several algorithms exist for discovering and enumerating graphlets, the c

Pelin Guven Geredeli

In this work, the dynamics of a multilayered structure-fluid interaction (FSI) PDE system is considered. Here, the coupling of 3D Stokes and 3D elastic dynamics is realized via an additional 2D elastic equation on the boundary interface. Such modeling PDE systems appear in the mathematical modeling of eukaryotic cells and vascular blood flow in mammalian art

Cian O'Brien, Rachel Quinlan

We investigate multiplicative groups consisting entirely of singular alternating sign matrices (ASMs), and present several constructions of such groups. It is shown that every finite group is isomorphic to a group of singular ASMs, with a singular idempotent ASM as its identity element. The relationship between the size, the rank, and the possible multiplica

Bartomeu Pou, Jeffrey Smith, Eduardo Quinones, Mario Martin

We propose a novel control approach that combines offline supervised learning to address the challenges posed by non-linear phase reconstruction using unmodulated pyramid wavefront sensors (P-WFS) and online reinforcement learning for predictive control. The control approach uses a high-order P-WFS to drive a tip-tilt stage and a high-dimensional mirror conc

Maximilian Nägele, Jan Olle, Thomas Fösel, Remmy Zen

Markov decision processes (MDPs) are used to model a wide variety of applications ranging from game playing over robotics to finance. Their optimal policy typically maximizes the expected sum of rewards given at each step of the decision process. However, a large class of problems does not fit straightforwardly into this framework: Non-cumulative Markov deci

Marec W. Heger, Daniel M. Reich

In photoelectron circular dichroism (PECD) it is generally difficult to trace how and when the chirality of the molecule is imprinted onto the photoelectron. We present simulations of PECD in a simple model and employ chirality measures to establish a quantitative connection between the chirality of the potential, the electronic wave function's chirality, an

Yu. G. Ignat'ev, I. A. Kokh

A mathematical model of the Universe evolution, based on asymmetric doublet of classical and phantom dcalar Higgs fields with a kinetic connection between the components, has been constructed and studied. A detailed qualitative analysis was carried out, the properties of the model's symmetry and invarience with respect to the similariry transformations of fu

Anastasija Nikiforova, Martin Lnenicka, Petar Milić, Mariusz Luterek

Public data ecosystems (PDEs) represent complex socio-technical systems crucial for optimizing data use in the public sector and outside it. Recognizing their multifaceted nature, previous research pro-posed a six-generation Evolutionary Model of Public Data Ecosystems (EMPDE). Designed as a result of a systematic literature review on the topic spanning thre

Rohit Sarma Sarkar, Sabyasachi Chakraborty, Bibhas Adhikari

In this paper, we design quantum circuits for the exponential of scaled $n$-qubit Pauli strings using single-qubit rotation gates, Hadamard gate, and CNOT gates. A key result we derive is that any two Pauli-string operators composed of identity and $X$ gates are permutation similar, and the corresponding permutation matrices are product of CNOT gates, with t

Aleksandr Sidorenko, Achim Wagner, Martin Ruskowski

While the benefits of reconfigurable manufacturing systems (RMS) are well-known, there are still challenges to their development, including, among others, a modular software architecture that enables rapid reconfiguration without much reprogramming effort. Skill-based engineering improves software modularity and increases the reconfiguration potential of RMS

Marco Barbieri, Pablo Spiga

Given a finite connected graph ${\Gamma}$ and a group $G$ acting transitively on the vertices of ${\Gamma}$, we prove that the number of vertices of ${\Gamma}$ and the cardinality of $G$ are bounded above by a function depending only on the cardinality of ${\Gamma}$ and on the exponent of $G$. We also prove that the number of generators of a group $G$ acting

Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang, Ru Li

Knowledge graph entity typing (KGET) aims to infer missing entity type instances in knowledge graphs. Previous research has predominantly centered around leveraging contextual information associated with entities, which provides valuable clues for inference. However, they have long ignored the dual nature of information inherent in entities, encompassing bot

J. P. Lorenz, J. F. Linnartz, A. Kool, M. R. van Delft

ZrSiS has been identified as an exemplary Dirac nodal-line semimetal, in which the Dirac band crossings extend along a closed loop in momentum space. Recently, the topology of the Fermi surface of ZrSiS was uncovered in great detail by quantum oscillation studies. For a magnetic field along the tetragonal $c$ axis, a rich frequency spectrum was observed stem

Jefferson Sousa, Jorge Noronha, Matthew Luzum

The evolution of a relativistic heavy-ion collision is typically understood as a process that transmutes the initial geometry of the system into the final momentum distribution of observed hadrons, which can be described via a cumulant expansion of the initial distribution of energy density and is represented at leading order as the well-known eccentricity s

Thorsten Wittkopp, Philipp Wiesner, Odej Kao

To assist IT service developers and operators in managing their increasingly complex service landscapes, there is a growing effort to leverage artificial intelligence in operations. To speed up troubleshooting, log anomaly detection has received much attention in particular, dealing with the identification of log events that indicate the reasons for a system

Vincent Knibbeler, Sara Lombardo, Casper Oelen

We classify the automorphic Lie algebras of equivariant maps from a complex torus to $\mathfrak{sl}_2(\mathbb{C})$. For each case we compute a basis in a normal form. The automorphic Lie algebras correspond precisely to two disjoint families of Lie algebras parametrised by the modular curve of $\mathrm{PSL}_2(\mathbb{Z})$, apart from four cases, which are al

Th. K. Mavrogordatos

We explore the statistical behavior of the light emanating from a coherently driven Jaynes-Cummings (JC) oscillator operating in the regime of multiphoton blockade with two monitored output channels causing the loss of coherence at equal rates. We do so by adopting an operational approach which draws the particle and wave aspects of the forwards scattered ra

T. Moore, J. H. Gillanders, M. Nicholl, M. E. Huber

Most stripped-envelope supernova progenitors are thought to be formed through binary interaction, losing hydrogen and/or helium from their outer layers. Ultra-stripped supernovae are an emerging class of transient which are expected to be produced through envelope-stripping by a NS companion. However, relatively few examples are known and the outcomes of suc

Sumit Panganti, Siba Prasad Das

General relativity (GR) predicts the existence of black hole (BH). The rotating BH called as a Kerr Black hole and GR implies that there is an upper limit on the angular momentum per mass squared of black holes $\leq 1$, above which the event horizon of the Kerr BH is not exist. We find the radial equation for equatorial motion for Kerr BH in terms of the ef

Natalie Carl, Trever Schirmer, Tobias Pfandzelter, David Bermbach

Function-as-a-Service (FaaS) is a popular cloud computing model in which applications are implemented as work flows of multiple independent functions. While cloud providers usually offer composition services for such workflows, they do not support cross-platform workflows forcing developers to hardcode the composition logic. Furthermore, FaaS workflows tend

T. Celora, M. J. Hatton, I. Hawke, N. Andersson

We present a proof-of-principle implementation of the first fully covariant filtering scheme applied to relativistic fluid turbulence. The filtering is performed with respect to special observers, identified dynamically as moving with the "bulk of the flow". This means that filtering does not depend on foliations of spacetime but rather on the intrinsic fibr

Simon Weissmann, Sara Klein, Waïss Azizian, Leif Döring

Stochastic gradient methods are among the most important algorithms in training machine learning problems. While classical assumptions such as strong convexity allow a simple analysis they are rarely satisfied in applications. In recent years, global and local gradient domination properties have shown to be a more realistic replacement of strong convexity. T

Benjamin Hivert, Denis Agniel, Rodolphe Thiébaut, Boris P. Hejblum

Post-clustering inference in single-cell RNA sequencing (scRNA-seq) analysis presents significant challenges in controlling Type I error during differential expression analysis. Data fission, a promising approach that aims to split data into two independent parts, relies on strong parametric assumptions of non-mixture distributions that are inherently violat

George Biswas

The Gottesman-Knill theorem asserts that quantum circuits composed solely of Clifford gates can be efficiently simulated classically. This theorem hinges on the fact that Clifford gates map Pauli strings to other Pauli strings, thereby allowing for a structured simulation process using classical computations. In this work, we break down the step-by-step proc