July 2023 arXiv papers — page 58

Hoi Ping Luk, Min Yan

We classify edge-to-edge tilings of the sphere by congruent almost equilateral pentagons, in which four edges have the same length. Together with our earlier classifications of edge-to-edge tilings of the sphere by congruent equilateral pentagons of other types, and our classification of edge-to-edge tilings of the sphere by congruent quadrilaterals or trian

Jieting Luo, Thomas Studer, Mehdi Dastani

The increasing applications of AI systems require personalized explanations for their behaviors to various stakeholders since the stakeholders may have various knowledge and backgrounds. In general, a conversation between explainers and explainees not only allows explainers to obtain the explainees' background, but also allows explainees to better understand

S. Di Marino, S. Murro, E. Radici

The goal of this paper is to derive the so-called five gradients inequality for optimal transport theory for general cost functions on two class of differentiable manifolds: locally compact Lie groups and compact Riemannian manifolds.

Dejan Porjazovski, Tamás Grósz, Mikko Kurimo

Traditional topic identification solutions from audio rely on an automatic speech recognition system (ASR) to produce transcripts used as input to a text-based model. These approaches work well in high-resource scenarios, where there are sufficient data to train both components of the pipeline. However, in low-resource situations, the ASR system, even if ava

Ye Ouyang, Yaqin Zhang, Xiaozhou Ye, Yunxin Liu

In the global craze of GPT, people have deeply realized that AI, as a transformative technology and key force in economic and social development, will bring great leaps and breakthroughs to the global industry and profoundly influence the future world competition pattern. As the builder and operator of information and communication infrastructure, the teleco

Annalena Mickel, Andreas Neuenkirch

We study the Euler scheme for scalar non-autonomous stochastic differential equations, whose diffusion coefficient is not globally Lipschitz but a fractional power of a globally Lipschitz function. We analyse the strong error and establish a criterion, which relates the convergence order of the Euler scheme to an inverse moment condition for the diffusion co

Jeongmi Kim, Luc Belloni, Benjamin Rotenberg

Molecular simulations in an open environment, involving ion exchange, are necessary to study various systems, from biosystems to confined electrolytes. However, grand-canonical simulations are often computationally demanding in condensed phases. A promising method (L. Belloni, J. Chem. Phys., 2019), one of the hybrid nonequilibrium molecular dynamics/Monte C

Khaldoon Ghanem, Erik Koch

We show that in the continuum limit, the average spectrum method (ASM) is equivalent to maximizing R\'enyi entropies of order $\eta$, of which Shannon entropy is the special case $\eta=1$. The order of R\'enyi entropy is determined by the way the spectra are sampled. Our derivation also suggests a modification of R\'enyi entropy, giving it a non-trivial $\et

Sujay Ghosh, Mohammad Kazem Bakhshizadeh, Guangya Yang, Łukasz Kocewiak

As the integration of renewable energy generation increases and as conventional generation is phased out, there is a gradual decline in the grid's strength and resilience at the connection point of wind turbines (WTs). Previous studies have shown that traditional grid-following controlled converters exhibit deteriorating dynamic characteristics and may resul

Tatiana Belova, Alexander S. Kulikov, Ivan Mihajlin, Olga Ratseeva

The field of fine-grained complexity aims at proving conditional lower bounds on the time complexity of computational problems. One of the most popular assumptions, Strong Exponential Time Hypothesis (SETH), implies that SAT cannot be solved in $2^{(1-\epsilon)n}$ time. In recent years, it has been proved that known algorithms for many problems are optimal u

Giacomo Ascione, Michele Bufalo, Giuseppe Orlando

This study introduces the CIR3 model, a three-factor model characterized by stochastic and correlated trends and volatilities. The paper focuses on establishing the Wasserstein ergodicity of this model, a task not achievable through conventional means such as the Dobrushin theorem. Instead, alternative mathematical approaches are employed, including consider

C. Swastik, Ravinder K. Banyal, Mayank Narang, Athira Unni

The GAIA space mission is impacting astronomy in many significant ways by providing a uniform, homogeneous and precise data set for over 1 billion stars and other celestial objects in the Milky Way and beyond. Exoplanet science has greatly benefited from the unprecedented accuracy of stellar parameters obtained from GAIA. In this study, we combine photometri

Fan-Yun Hung, Chia-Fu Yu

We present a formula for the class number of a multinorm one torus $T_{L/k}$ associated to any \'etale algebra $L$ over a global field $k$. This is deduced from a formula for analogues of invariants introduced by T.~Ono, which are interpreted as a generalization of Gauss genus theory. This paper includes the variants of Ono's invariant for arbitrary $S$-idea

Guowei Dai, Yong Zhang

In this paper, we prove the existence of $k$ families of smooth unbounded domains $\Omega_s\subset\mathbb{R}^{N+1}$ with $N\geq1$, where \begin{equation} \Omega_s=\left\{(x,t)\in \mathbb{R}^N\times \mathbb{R}:\vert x\vert<1+s\cos \left(\frac{2\pi}{T(s)}t\right)+s w_s\left(\frac{2\pi}{T(s)}t\right)\right\},\nonumber \end{equation} such that \begin{equation} -

Stéphane Dartois, Camille Male, Ion Nechita

The tensor flattenings appear naturally in quantum information when one produces a density matrix by partially tracing the degrees of freedom of a pure quantum state. In this paper, we study the joint $^*$-distribution of the flattenings of large random tensors under mild assumptions, in the sense of free probability theory. We show the convergence toward an

Decheng Liu, Tao Chen, Chunlei Peng, Nannan Wang

Due to the successful development of deep image generation technology, visual data forgery detection would play a more important role in social and economic security. Existing forgery detection methods suffer from unsatisfactory generalization ability to determine the authenticity in the unseen domain. In this paper, we propose a novel Attention Consistency

Zeinab Teimoori, Kazem Rezazadeh, Abasat Rostami

We study the inflationary scenario in the Tsallis entropy-based cosmology. The Friedmann equations in this setup can be derived by using the first law of thermodynamics. To derive the relations of the power spectra of the scalar and tensor perturbations in this setup, we reconstruct an $f(R)$ gravity model which is thermodynamically equivalent to our model i

Jie Qi, Jing Zhang, Miroslav Krstic

The recently introduced DeepONet operator-learning framework for PDE control is extended from the results for basic hyperbolic and parabolic PDEs to an advanced hyperbolic class that involves delays on both the state and the system output or input. The PDE backstepping design produces gain functions that are outputs of a nonlinear operator, mapping functions

Evgeny I. Buchbinder, Benjamin J. Stone

We analyse the general structure of the three-point functions involving conserved higher-spin currents $J_{s} := J_{\alpha(i) \dot{\alpha}(j)}$ belonging to any Lorentz representation in four-dimensional conformal field theory. Using the constraints of conformal symmetry and conservation equations, we computationally analyse the general structure of three-po

Tim Yarally, Luís Cruz, Daniel Feitosa, June Sallou

The batch size is an essential parameter to tune during the development of new neural networks. Amongst other quality indicators, it has a large degree of influence on the model's accuracy, generalisability, training times and parallelisability. This fact is generally known and commonly studied. However, during the application phase of a deep learning model,

Amit Bhunia, Pragya Joshi, Nitesh Singh, Biswanath Chakraborty

Development of stable room-temperature bright single-photon emitters using atomic defects in hexagonal-boron nitride flakes (h-BN) provides significant promises for quantum technologies. However, an outstanding challenge in h-BN is creating site-specific, stable, high emission rate single photon emitters with very low Huang-Rhys (HR) factor. Here, we discuss

Taoran Sheng, Manfred Huber

The embedded sensors in widely used smartphones and other wearable devices make the data of human activities more accessible. However, recognizing different human activities from the wearable sensor data remains a challenging research problem in ubiquitous computing. One of the reasons is that the majority of the acquired data has no labels. In this paper, w

Marwan Mousa, Damien van de Berg, Niki Kotecha, Ehecatl Antonio del Rio-Chanona

Most solutions to the inventory management problem assume a centralization of information that is incompatible with organisational constraints in real supply chain networks. The inventory management problem is a well-known planning problem in operations research, concerned with finding the optimal re-order policy for nodes in a supply chain. While many centr

Han He, Weitao Zhang, Haotong Zhang, Song Wang

The distribution of stellar $\mathrm{H}\alpha$ chromospheric activity with respect to stellar atmospheric parameters (effective temperature $T_\mathrm{eff}$, surface gravity $\log\,g$, and metallicity $\mathrm{[Fe/H]}$) and main-sequence/giant categories is investigated for the F-, G-, and K-type stars observed by the LAMOST Medium-Resolution Spectroscopic S

Albert Skegro, Changfu Zou, Torsten Wik

Growing demands for electrification result in increasingly larger battery packs. Due to factors such as cell position in the pack and variations in the manufacturing process, the packs exhibit variations in the performance of their constituent cells. Moreover, due to the fixed cell configuration, the weakest cell renders the pack highly susceptible to these

Yuanxi Yu, Sha Jin, Xue Fan, Mona Sarter

In the realm of nanoscience, the dynamic behaviors of liquids at scales beyond the conventional structural relaxation time, $\tau$, unfold a fascinating blend of solid-like characteristics, including the propagation of collective shear waves and the emergence of elasticity. However, in classical bulk liquids, where $\tau$ is typically of the order of 1 ps or

Alexandre Pacaud, Aurelien Bechler, Marceau Coupechoux

For decades, Simultaneous Ascending Auction (SAA) has been the most popular mechanism used for spectrum auctions. It has recently been employed by many countries for the allocation of 5G licences. Although SAA presents relatively simple rules, it induces a complex strategic game for which the optimal bidding strategy is unknown. Considering the fact that som

Yassir Fathullah, Chunyang Wu, Egor Lakomkin, Junteng Jia

Large language models have proven themselves highly flexible, able to solve a wide range of generative tasks, such as abstractive summarization and open-ended question answering. In this paper we extend the capabilities of LLMs by directly attaching a small audio encoder allowing it to perform speech recognition. By directly prepending a sequence of audial e

Xiang Liu, Mengwei Xu, Liwei Zhang

Second-order optimality conditions of the bilevel programming problems are dependent on the second-order directional derivatives of the value functions or the solution mappings of the lower level problems under some regular conditions, which can not be calculated or evaluated. To overcome this difficulty, we propose the notion of the bi-local solution. Under

Mahieddine Adim

In this article we consider the multi-layer shallow water system for the propagation of gravity waves in density-stratified flows, with additional terms introduced by the oceanographers Gent and McWilliams in order to take into account large-scale isopycnal diffusivity induced by small-scale unresolved eddies. We establish a bridge between the multi-layer sh

Vikram Singh, M. Bicky Singh, Sunil Nair

This study employs resonant ultrasound spectroscopy (RUS) to investigate the elastic properties of single crystalline KH$_{2}$PO$_{4}$ (KDP) through the paraelectric to ferroelectric phase transition. Noteworthy anomalies are observed in selected resonance modes and their corresponding mechanical quality factors ($Q$) around the transition temperature. The t

Jing Zhang, Jie Qi

A backstepping-based compensator design is developed for a system of $2\times2$ first-order linear hyperbolic partial differential equations (PDE) in the presence of an uncertain long input delay at boundary. We introduce a transport PDE to represent the delayed input, which leads to three coupled first-order hyperbolic PDEs. A novel backstepping transformat

Torsten Enßlin, Carolin Weidinger, Philipp Frank

The concept of attention, numerical weights that emphasize the importance of particular data, has proven to be very relevant in artificial intelligence. Relative entropy (RE, aka Kullback-Leibler divergence) plays a central role in communication theory. Here we combine these concepts, attention and RE. RE guides optimal encoding of messages in bandwidth-limi

Krishan Chand, Henrik Rosenberger, Benjamin Sanderse

The present work presents a stable POD-Galerkin based reduced-order model (ROM) for two-dimensional Rayleigh-B\'enard convection in a square geometry for three Rayleigh numbers: $10^4$ (steady state), $3\times 10^5$ (periodic), and $6 \times 10^6$ (chaotic). Stability is obtained through a particular (staggered-grid) full-order model (FOM) discretization tha

Andrey Saveliev, Rafael Alves Batista

Lorentz invariance violation (LIV) is a proposed phenomenon where Lorentz symmetry is violated at high energies, potentially affecting particle dynamics and interactions. We use numerical simulations with the CRPropa framework to investigate LIV in gamma-ray-induced electromagnetic cascades, specifically studying how it impacts cascading electrons and photon

Hikaru Kawai, Kiyoharu Kawana, Kin-ya Oda, Kei Yagyu

In ordinary thermodynamics, around first-order phase transitions, the intensive parameters such as temperature and pressure are automatically fixed to the phase transition point when one controls the extensive parameters such as total volume and total energy. From the microscopic point of view, the extensive parameters are more fundamental than the intensive

Cyrille Allery, Claudine Beghein, Claire Dubot, Fabien Dubot

This paper deals with the numerical modeling of flow around and through a porous obstacle by a reduced order model (ROM) obtained by Galerkin projection of the Navier-Stokes equations onto a Proper Orthogonal Decomposition (POD) reduced basis. In the few existing works dealing with model reduction techniques applied to flows in porous media, flows were descr

Sungwon Hwang, Junha Hyung, Daejin Kim, Min-Jung Kim

As recent advances in Neural Radiance Fields (NeRF) have enabled high-fidelity 3D face reconstruction and novel view synthesis, its manipulation also became an essential task in 3D vision. However, existing manipulation methods require extensive human labor, such as a user-provided semantic mask and manual attribute search unsuitable for non-expert users. In

Raphael Seidel, Nikolay Tcholtchev, Sebastian Bock, Manfred Hauswirth

Uncomputation is an essential part of reversible computing and plays a vital role in quantum computing. Using this technique, memory resources can be safely deallocated without performing a nonreversible deletion process. For the case of quantum computing, several algorithms depend on this as they require disentangled states in the course of their execution.

K. R. Arun, Rahuldev Ghorai, Mainak Kar

An asymptotic preserving and energy stable scheme for the Euler-Poisson system under the quasineutral scaling is designed and analysed. Correction terms are introduced in the convective fluxes and the electrostatic potential, which lead to the dissipation of mechanical energy and the entropy stability. The resolution of the semi-implicit in time finite volum

Zhenbo Wang, Yu Zhang, Li Wang, Shu Chen

We investigate the effect of an additional modulation parameter $\delta$ on the mobility properties of quasiperiodic lattices described by a generalized Ganeshan-Pixley-Das Sarma model with two on site modulation parameters. For the case with bounded quasiperiodic potential, we unveil the existence of self-duality relation, independent of $\delta$. By applyi

Javier Aguilar Martín, Constanze Roitzheim

Derived $A_\infty$-algebras have a wealth of theoretical advantages over regular $A_\infty$-algebras. However, due to their bigraded nature, in practice they are often unwieldy to work with. We develop a framework involving brace algebras on operads which allows us to study derived $A_\infty$ algebras in a new conceptual context. One particular advantage is

Reuben Moyo, Stanley Ndebvu, Michael Zimba, Jimmy Mbelwa

Examinations are a crucial part of the learning process, and academic institutions invest significant resources into maintaining their integrity by preventing cheating from students or facilitators. However, cheating has become rampant in examination setups, compromising their integrity. The traditional method of relying on invigilators to monitor every stud

Weiyu Zhang

This report first provides a brief review of various forms of dialogue-based participation, e.g., Citizen Assembly, Citizen Lottery, Citizen Jury, Deliberative Polling, and Participatory Budgeting. Challenges associated with these long-lasting practices are identified and hybrid deliberation is proposed as a concept to address the challenges. The report then

Qiaoyi Su, Yuhong Chou, Yifan Hu, Jianing Li

Spiking neural networks (SNNs) are brain-inspired energy-efficient models that encode information in spatiotemporal dynamics. Recently, deep SNNs trained directly have shown great success in achieving high performance on classification tasks with very few time steps. However, how to design a directly-trained SNN for the regression task of object detection st

Jian Ma, Junhao Liang, Chen Chen, Haonan Lu

Recent progress in personalized image generation using diffusion models has been significant. However, development in the area of open-domain and non-fine-tuning personalized image generation is proceeding rather slowly. In this paper, we propose Subject-Diffusion, a novel open-domain personalized image generation model that, in addition to not requiring tes

Yaniv Donath, Matthew Lewandowski, Leonardo Senatore

We show that it is possible to directly measure the formation time of galaxies using large-scale structure. In particular, we show that the large-scale distribution of galaxies is sensitive to whether galaxies form over a narrow period of time before their observed times, or are formed over a time scale on the order of the age of the Universe. Along the way,

Etienne Ménager, Tanguy Navez, Olivier Goury, Christian Duriez

The Finite Element Method (FEM) is a powerful modeling tool for predicting the behavior of soft robots. However, its use for control can be difficult for non-specialists of numerical computation: it requires an optimization of the computation to make it real-time. In this paper, we propose a learning-based approach to obtain a compact but sufficiently rich m

Takumi Shimasue, Ken Osato, Masamune Oguri, Rhythm Shimakawa

We perform the weak lensing mass mapping analysis to identify troughs, which are defined as local minima in the mass map. Since weak lensing probes projected matter along the line-of-sight, these troughs can be produced by single voids or multiple voids projected along the line-of-sight. To scrutinise the origins of the weak lensing troughs, we systematicall

Rui Wang, Ying D. Liu, Xiaowei Zhao, Huidong Hu

Small-scale eruptions could play an important role in coronal heating, generation of solar energetic particles (SEPs), and mass source of the solar wind. However, they are poorly observed, and their characteristics, distributions, and origins remain unclear. Here a mini coronal dimming was captured by the recently launched Solar Orbiter spacecraft. The obser

Ning Wang, Xin Zhang, Qing Mai

The expectation-maximization (EM) algorithm and its variants are widely used in statistics. In high-dimensional mixture linear regression, the model is assumed to be a finite mixture of linear regression and the number of predictors is much larger than the sample size. The standard EM algorithm, which attempts to find the maximum likelihood estimator, become

Isack Lee, Eungi Lee, Seok Bong Yoo

Most research on facial expression recognition (FER) is conducted in highly controlled environments, but its performance is often unacceptable when applied to real-world situations. This is because when unexpected objects occlude the face, the FER network faces difficulties extracting facial features and accurately predicting facial expressions. Therefore, o

Yonghui Chu, Zhiqiang Wei, Zai Yang, Derrick Wing Kwan Ng

Channel estimation (CE) plays a key role in reconfigurable intelligent surface (RIS)-aided multiple-input multiple-output (MIMO) communication systems, while it poses a challenging task due to the passive nature of RIS and the cascaded channel structures. In this paper, a partially decoupled atomic norm minimization (PDANM) framework is proposed for CE of RI

Antonin Coutant, Bruno Lombard

When semi-infinite phononic crystals (PCs) are in contact, localized modes may exist at their boundary. The central question is generally to predict their existence and to determine their stability. With the rapid expansion of the field of topological insulators, powerful tools have been developed to address these questions. In particular, when applied to on

Elliot H. Young, Rajen D. Shah

We study partially linear models in settings where observations are arranged in independent groups but may exhibit within-group dependence. Existing approaches estimate linear model parameters through weighted least squares, with optimal weights (given by the inverse covariance of the response, conditional on the covariates) typically estimated by maximising

Angelo Esposito, Davide Germani, Alfredo Glioti, Antonio D. Polosa

We determine the contribution of long-range pion interactions to the $X(3872)$ dynamics, assuming it is a loosely bound $D^0 \bar{D}^{*0}$ molecule. Our result is based on the distorted wave Born approximation in non-relativistic quantum mechanics. Despite their long-range nature, we find that pion interactions cannot produce a large and negative effective r

Wolfram Neutsch

Based on Kantor's geometry, we give a new Highly symmetric construction of Lyons' sporadic simple group $Ly$ via its minimal representation over $\mathbb F_5^{111}$, thus obtaining elementary existence proofs for both the group and the representation at one stroke.

Wei Liu, Jincheng Wang, Fangfang Wang, Kai Qi

In this paper, we investigate phase transitions in the Majority-Vote model coupled with noise layers of different structures. We examine the Square lattice and Random-regular networks, as well as their combinations, for both vote layers and noise layers. Our findings reveal the presence of independent third-order transitions in all cases and dependent third-

Arne Schmidt, Pablo Morales-Álvarez, Rafael Molina

Medical image segmentation is a challenging task, particularly due to inter- and intra-observer variability, even between medical experts. In this paper, we propose a novel model, called Probabilistic Inter-Observer and iNtra-Observer variation NetwOrk (Pionono). It captures the labeling behavior of each rater with a multidimensional probability distribution

Giacomo Canevari, Antonio Segatti

In this paper we discuss the behavior of the Oseen-Frank model for nematic liquid crystals in the limit of vanishing thickness. More precisely, in a thin slab~$\Omega\times (0,h)$ with~$\Omega\subset \mathbb{R}^2$ and $h>0$ we consider the one-constant approximation of the Oseen-Frank model for nematic liquid crystals. We impose Dirichlet boundary conditions

Debajyoti Bera, Tharrmashastha Sapv

Classical branching programs are studied to understand the space complexity of computational problems. Prior to this work, Nakanishi and Ablayev had separately defined two different quantum versions of branching programs that we refer to as NQBP and AQBP. However, none of them, to our satisfaction, captures the intuitive idea of being able to query different

Thilo von Neumann, Christoph Boeddeker, Marc Delcroix, Reinhold Haeb-Umbach

MeetEval is an open-source toolkit to evaluate all kinds of meeting transcription systems. It provides a unified interface for the computation of commonly used Word Error Rates (WERs), specifically cpWER, ORC-WER and MIMO-WER along other WER definitions. We extend the cpWER computation by a temporal constraint to ensure that only words are identified as corr

Lucia Illari, Nicholas J. Restrepo, Neil F. Johnson

Why is distrust (e.g. of medical expertise) now flourishing online despite the surge in mitigation schemes being implemented? We analyze the changing discourse in the Facebook ecosystem of approximately 100 million users who pre-pandemic were focused on (dis)trust of vaccines. We find that post-pandemic, their discourse strongly entangles multiple non-vaccin

Chenfeng Zhu, Dachun Yang, Wen Yuan

Let $\Omega\subset\mathbb{R}^n$ be a bounded $(\varepsilon,\infty)$-domain with $\varepsilon\in(0,1]$, $X(\mathbb{R}^n)$ a ball Banach function space satisfying some extra mild assumptions, and $\{\rho_\nu\}_{\nu\in(0,\nu_0)}$ with $\nu_0\in(0,\infty)$ a $\nu_0$-radial decreasing approximation of the identity on $\mathbb{R}^n$. In this article, the authors e

Shuai Feng, Bao-Min Gu, Fu-Wen Shu

It is believed that gravity can be considered as a quantum coherent mediator. In this study, we propose a plan to test the existence of extra dimensions using the Quantum Gravity Induced Entanglement of Masses (QGEM) experiment. This experiment involves two freely falling test masses passing through a Stern-Gerlach-like device. We investigate the entanglemen

Silius M. Vandeskog, Raphaël Huser, Oddbjørn Bruland, Sara Martino

Aiming to deliver improved precipitation simulations for hydrological impact assessment studies, we develop a methodology for modelling and simulating high-dimensional spatial precipitation extremes, focusing on both their marginal distributions and tail dependence structures. Tail dependence is crucial for assessing the consequences of extreme precipitation

Marlon Schäfer, Benjamin Kambs, Dennis Herrmann, Tobias Bauer

The silicon-vacancy center in diamond holds great promise as a qubit for quantum communication networks. However, since the optical transitions are located within the visible red spectral region, quantum frequency conversion to low-loss telecommunication wavelengths becomes a necessity for its use in long-range, fiber-linked networks. This work presents a hi

Shintaro Uchiyama, Kyoji Umemura, Yusuke Morita

This paper proposes a system that uses large language models to provide immediate feedback to students in flipped classroom preparation learning. This study aimed to solve challenges in the flipped classroom model, such as ensuring that students are emotionally engaged and motivated to learn. Students often have questions about the content of lecture videos

Joshua Aldrich Edbert, Sahrima Jannat Oishwee, Shubhashis Karmakar, Zadia Codabux

Background: Software security is crucial to ensure that the users are protected from undesirable consequences such as malware attacks which can result in loss of data and, subsequently, financial loss. Technical Debt (TD) is a metaphor incurred by suboptimal decisions resulting in long-term consequences such as increased defects and vulnerabilities if not ma

Yunhao Ge, Yuecheng Li, Shuo Ni, Jiaping Zhao

Continual learning aims to emulate the human ability to continually accumulate knowledge over sequential tasks. The main challenge is to maintain performance on previously learned tasks after learning new tasks, i.e., to avoid catastrophic forgetting. We propose a Channel-wise Lightweight Reprogramming (CLR) approach that helps convolutional neural networks

Luocheng Huang, Zheyi Han, Anna Wirth-Singh, Vishwanath Saragadam

Subwavelength diffractive optics known as meta-optics have demonstrated the potential to significantly miniaturize imaging systems. However, despite impressive demonstrations, most meta-optical imaging systems suffer from strong chromatic aberrations, limiting their utilities. Here, we employ inverse-design to create broadband meta-optics operating in the lo

Anna Jové, Núria Fagella

We study the behaviour of a transcendental entire map $ f\colon \mathbb{C}\to\mathbb{C} $ on an unbounded invariant Fatou component $ U $, assuming that infinity is accessible from $ U $. It is well-known that $ U $ is simply connected. Hence, by means of a Riemann map $ \varphi\colon\mathbb{D}\to U $ and the associated inner function, the boundary of $ U $

Samuel Grayson, Reed Milewicz, Joshua Teves, Daniel S. Katz

Those seeking to reproduce a computational experiment often need to manually look at the code to see how to build necessary libraries, configure parameters, find data, and invoke the experiment; it is not automatic. Automatic reproducibility is a more stringent goal, but working towards it would benefit the community. This work discusses a machine-readable l

Ryoto Yanagisawa, Sota Koike, Tomoki Nawae, Naohito Tsujii

Energy harvesting is essential for the internet-of-things networks where a tremendous number of sensors require power. Thermoelectric generators (TEGs), especially those based on silicon (Si), are a promising source of clean and sustainable energy for these sensors. However, the reported performance of planar-type Si TEGs never exceeded power factors of 0.1

Rami Ayoush, Dmitriy Stolyarov, Michał Wojciechowski

We prove that the polar decomposition of the singular part of a vector measure depends on its conditional expectations computed with respect to the $q$-regular filtration. This dependency is governed by a martingale analog of the so-called wave cone, which naturally corresponds to the result of De Philippis and Rindler about fine properties of PDE-constraine

Lingyi Yang, Feng Jiang, Haizhou Li

The remarkable capabilities of large-scale language models, such as ChatGPT, in text generation have impressed readers and spurred researchers to devise detectors to mitigate potential risks, including misinformation, phishing, and academic dishonesty. Despite this, most previous studies have been predominantly geared towards creating detectors that differen

Simiao Zhang, Jitao Bai, Menghong Guan, Yihao Huang

Machine learning is widely used to make decisions with societal impact such as bank loan approving, criminal sentencing, and resume filtering. How to ensure its fairness while maintaining utility is a challenging but crucial issue. Fairness is a complex and context-dependent concept with over 70 different measurement metrics. Since existing regulations are o

C. M. Wensrich, S. Holman, M. Courdurier, W. R. B. Lionheart

We examine the problem of Bragg-edge elastic strain tomography from energy resolved neutron transmission imaging. A new approach is developed for two-dimensional plane-stress and plane-strain systems whereby elastic strain can be reconstructed from its Longitudinal Ray Transform (LRT) as two parts of a Helmholtz decomposition based on the concept of an Airy

Athul Pradeepkumar Girija

The ability to launch small secondary payloads to Mars on future science missions present an exciting opportunity for demonstration of advanced technologies for planetary exploration such as aerocapture. Over the years, several aerocapture technology demonstration missions have been proposed but none could be realized, causing the technology to become dorman

Kh. Helensana Devi, K. Sashikanta Sngh, N. Nimai Singh

We discuss the stability of the neutrino oscillation parameters at low energy scale including self-complementarity (SC) relations among mixing angles under radiative corrections with the variation of SUSY breaking scale ($m_s$) in both normal and inverted hierarchical cases. We observe that the neutrino oscillation parameters including the SC relation mainta

Christof Geiß, Daniel Labardini-Fragoso

Let $(\Sigma,\mathbb{M},\mathbb{P})$ be a surface with marked points $\mathbb{M}\subseteq \partial\Sigma\neq\varnothing$ and punctures $\mathbb{P}\subseteq\Sigma\setminus\partial\Sigma$. In this paper we show that for every curve $\gamma$ on $\Sigma\setminus\mathbb{P}$, the curve obtained by resolving the kinks of $\gamma$ in any order is uniquely determined

Lorenzo Tronchin, Minh H. Vu, Paolo Soda, Tommy Löfstedt

Data Augmentation (DA) is a technique to increase the quantity and diversity of the training data, and by that alleviate overfitting and improve generalisation. However, standard DA produces synthetic data for augmentation with limited diversity. Generative Adversarial Networks (GANs) may unlock additional information in a dataset by generating synthetic sam

Pei Wang, Bing-Yu Su, Lei Zu, Yupeng Yang

Observations from the James Webb Space Telescope (JWST) have unveiled several galaxies with stellar masses $M_*\gtrsim10^{10} M_\odot$ at redshifts $7.4\lesssim z\lesssim 9.1$. These remarkable findings indicate an unexpectedly high stellar mass density, which contradicts the prediction of the $\Lambda \rm CDM$ model. Our study utilizes the Chevallier--Polar

Marin Vlastelica, Jin Cheng, Georg Martius, Pavel Kolev

There has been significant recent progress in the area of unsupervised skill discovery, utilizing various information-theoretic objectives as measures of diversity. Despite these advances, challenges remain: current methods require significant online interaction, fail to leverage vast amounts of available task-agnostic data and typically lack a quantitative

Fedor Sandomirskiy, Omer Tamuz

The family of Boltzmann distributions is used in statistical mechanics to describe the distribution of states in systems with a given temperature. We give a novel characterization of this family as the unique one satisfying independence for uncoupled systems. The theorem boils down to a statement about endomorphisms of the convolution semi-group of finitely

Chiranjib Bhattacharyya, Ravindran Kannan, Amit Kumar

The Separating Hyperplane theorem is a fundamental result in Convex Geometry with myriad applications. Our first result, Random Separating Hyperplane Theorem (RSH), is a strengthening of this for polytopes. $\rsh$ asserts that if the distance between $a$ and a polytope $K$ with $k$ vertices and unit diameter in $\Re^d$ is at least $\delta$, where $\delta$ is

Samed Keşir, M. Yaser Yağan, İbrahim Hökelek, Ali Emre Pusane

Reconfigurable Intelligent Surfaces (RISs) are becoming one of the fundamental building blocks of next-generation wireless communication systems. To that end, RIS phase configuration optimization is an important issue, where finding the most suitable configuration becomes a challenging and resource-consuming task, especially as the number of RIS elements inc

Zahra Torbatian, Dino Novko

$1T$-TiSe$_2$ is believed to posses a soft electronic mode, i.e., plasmon or exciton, that might be responsible for the exciton condensation and charge-density-wave (CDW) transition. Here, we explore collective electronic excitations in single-layer $1T$-TiSe$_2$ by using the ab-initio electromagnetic linear response and unveil intricate scattering pathways

Gabriela Lichtenstein, Michael A. Schmidt, German Valencia, Raymond R. Volkas

We analyse the potential of the proposed $\mu^+ \mu^+$ and $\mu^+ e^-$ collider $\mu$TRISTAN to complement the searches for charged-lepton flavour-violation (CLFV) that can be carried out by Belle II. $\mu$TRISTAN offers the possibility of directly producing and studying new resonances that could mediate CLFV for a certain range of masses. In addition, we fi

Bo-Lun Huang, Zhen-Zhao Tao, Tong-Jie Zhang

Narrowband radio search for extraterrestrial intelligence (SETI) in the 21st century suffers severely from radio frequency interference (RFI), resulting in a high number of false positives, and it could be the major reason why we have not yet received any messages from space. We thereby propose a novel observation strategy, called MultiBeam Point-source Scan

Xiaolei Zhang, Hwankoo Kim

In this note, we investigate the Baer splitting problem over commutative rings. In particular, we show that if a commutative ring $R$ is $\tau_q$-semisimple, then every Baer $R$-module is projective.

Théophile Buffière, Lionel Pournin

A $3$-dimensional polytope $P$ is $k$-equiprojective when the projection of $P$ along any line that is not parallel to a facet of $P$ is a polygon with $k$ vertices. In 1968, Geoffrey Shephard asked for a description of all equiprojective polytopes. It has been shown recently that the number of combinatorial types of $k$-equiprojective polytopes is at least

Sarah A. Vollert, Christopher Drovandi, Matthew P. Adams

The potential effects of conservation actions on threatened species can be predicted using ensemble ecosystem models by forecasting populations with and without intervention. These model ensembles commonly assume stable coexistence of species in the absence of available data. However, existing ensemble-generation methods become computationally inefficient as

Zhongping Ji, Feifei Che, Hanshuo Liu, Ziyi Zhao

In this paper, we propose a technique for making humans in photographs protrude like reliefs. Unlike previous methods which mostly focus on the face and head, our method aims to generate art works that describe the whole body activity of the character. One challenge is that there is no ground-truth for supervised deep learning. We introduce a sigmoid variant

Shu-Yung Liu, Mei-Heng Yueh

An area-preserving parameterization is a bijective mapping that maps a surface onto a specified domain and preserves the local area. This paper formulates the computation of disk area-preserving parameterization as an authalic energy minimization (AEM) problem and proposes a novel preconditioned nonlinear conjugate gradient method for the AEM with guaranteed

Eunsuk Yang, Eun Hwan Roh, Young Bae Jun

Recently Yang-Roh-Jun introduced the notion of ordered BCI-algebras as a generalization of BCI-algebras. They also introduced the notions of homomorphisms and kernels of ordered BCI-algebras and investigated related properties. Here we extend their investigation to ordered homomorphisms, i.e., order-preserving homomorphisms. To this end, the notions of order

Jian-Sheng Wang, Mauro Antezza

Based on a tight-binding model for the electron system, we investigate the transfer of energy, momentum, and angular momentum mediated by electromagnetic fields among buckminsterfullerene (C$_{60}$) and graphene nano-strips. Our nonequilibrium Green's function approach enables calculations away from local thermal equilibrium where the fluctuation-dissipation

Daria Reshetova, Guanhang Wu, Marcel Puyat, Chunhui Gu

Object detection is the key technique to a number of Computer Vision applications, but it often requires large amounts of annotated data to achieve decent results. Moreover, for pedestrian detection specifically, the collected data might contain some personally identifiable information (PII), which is highly restricted in many countries. This label intensive

Wenquan Xu, Zijian Zhang, Yong Feng, Haoyu Song

In-Network Computing (INC) has found many applications for performance boosts or cost reduction. However, given heterogeneous devices, diverse applications, and multi-path network typologies, it is cumbersome and error-prone for application developers to effectively utilize the available network resources and gain predictable benefits without impeding normal

Motomi Aoki, Yuefeng Yin, Simon Granville, Yao Zhang

Spin-orbit torque (SOT) is receiving tremendous attention from both fundamental and application-oriented aspects. Co2MnGa, a Weyl ferromagnet that is in a class of topological quantum materials, possesses cubic-based high structural symmetry, the L21 crystal ordering, which should be incapable of hosting anisotropic SOT in conventional understanding. Here we