May 2024 arXiv papers — page 79

Euclid Collaboration, F. Hormuth, K. Jahnke, M. Schirmer

The near-infrared calibration unit (NI-CU) on board Euclid's Near-Infrared Spectrometer and Photometer (NISP) is the first astronomical calibration lamp based on light-emitting diodes (LEDs) to be operated in space. Euclid is a mission in ESA's Cosmic Vision 2015-2025 framework, to explore the dark universe and provide a next-level characterisation of the na

Euclid Collaboration, K. Jahnke, W. Gillard, M. Schirmer

The Near-Infrared Spectrometer and Photometer (NISP) on board the Euclid satellite provides multiband photometry and R>=450 slitless grism spectroscopy in the 950-2020nm wavelength range. In this reference article we illuminate the background of NISP's functional and calibration requirements, describe the instrument's integral components, and provide all its

Euclid Collaboration, M. S. Cropper, A. Al-Bahlawan, J. Amiaux

This paper presents the specification, design, and development of the Visible Camera (VIS) on the ESA Euclid mission. VIS is a large optical-band imager with a field of view of 0.54 deg^2 sampled at 0.1" with an array of 609 Megapixels and spatial resolution of 0.18". It will be used to survey approximately 14,000 deg^2 of extragalactic sky to measure the di

Euclid Collaboration, Y. Mellier, Abdurro'uf, J. A. Acevedo Barroso

The current standard model of cosmology successfully describes a variety of measurements, but the nature of its main ingredients, dark matter and dark energy, remains unknown. Euclid is a medium-class mission in the Cosmic Vision 2015-2025 programme of the European Space Agency (ESA) that will provide high-resolution optical imaging, as well as near-infrared

Jingbang Liu, James E. Sprittles, Tobias Grafke

Thermally activated phenomena in physics and chemistry, such as conformational changes in biomolecules, liquid film rupture, or ferromagnetic field reversal, are often associated with exponentially long transition times described by Arrhenius' law. The associated subexponential prefactor, given by the Eyring-Kramers formula, has recently been rigorously deri

Jorge J. Garcés, Lei Li, Antonio M. Peralta, Shanshan Su

Let $\{C_i\}_{i\in \Gamma_1},$ and $\{D_j\}_{j\in \Gamma_2},$ be two families of Cartan factors such that all of them have dimension at least $2$, and consider the atomic JBW$^*$-triples $A=\bigoplus\limits_{i\in \Gamma_1}^{\ell_{\infty}} C_i$ and $B=\bigoplus\limits_{j\in \Gamma_2}^{\ell_{\infty}} D_j$. Let $\Delta :A \to B$ be a {\rm(}non-necessarily linea

Raven Beutner, Bernd Finkbeiner

Non-deterministic planning aims to find a policy that achieves a given objective in an environment where actions have uncertain effects, and the agent - potentially - only observes parts of the current state. Hyperproperties are properties that relate multiple paths of a system and can, e.g., capture security and information-flow policies. Popular logics for

Sergio Altares-López, José M. Bengochea-Guevara, Carlos Ranz, Héctor Montes

The effective integration of generative artificial intelligence in education is a fundamental aspect to prepare future generations. The objective of this study is to analyze from a quantitative and qualitative point of view the perception of controlled student-IA interaction within the classroom. This analysis includes assessing the ethical implications and

T. Matsuno, A. M. Amarsi, M. Carlos, P. E. Nissen

Magnesium is one of the important elements in stellar physics as an electron donor and in Galactic Archaeology as a discriminator of different stellar populations. However, previous studies of Mg I and Mg II lines in metal-poor benchmark stars have flagged problems with magnesium abundances inferred from one-dimensional (1D), hydrostatic models of stellar at

Claudio Bonati, Andrea Pelissetto, Ettore Vicari

We study the O($N$)$^*$ transitions that occur in the 3D $\mathbb{Z}_2$-gauge $N$-vector model, and the analogous Ising$^*$ transitions occurring in the 3D $\mathbb{Z}_2$-gauge Higgs model, corresponding to an $N$-vector model with $N=1$. At these transitions, gauge-invariant correlations behave as in the usual $N$-vector/Ising model. Instead, the nongauge i

Hossein Vahid, Alberto Scacchi, Maria Sammalkorpi, Tapio Ala-Nissila

We examine the interactions between polyelectrolytes (PEs) and uncharged substrates at conditions corresponding to a dielectric discontinuity between the aqueous solution and the substrate. To this end, we vary the relevant system characteristics, in particular the substrate dielectric constant $\varepsilon_{\rm s}$ under different salt conditions. We employ

Jiancheng Tang, Qianqian Yang, Deniz Gündüz

This paper studies a variant of the rate-distortion problem motivated by task-oriented semantic communication and distributed learning problems, where $M$ correlated sources are independently encoded for a central decoder. The decoder has access to a correlated side information in addition to the messages received from the encoders, and aims to recover a lat

Mohammad Areeb Qazi, Anees Ur Rehman Hashmi, Santosh Sanjeev, Ibrahim Almakky

Deep Learning has shown great success in reshaping medical imaging, yet it faces numerous challenges hindering widespread application. Issues like catastrophic forgetting and distribution shifts in the continuously evolving data stream increase the gap between research and applications. Continual Learning offers promise in addressing these hurdles by enablin

Yuheng Ma, Ke Jia, Hanfang Yang

We initiate the study of locally differentially private (LDP) learning with public features. We define semi-feature LDP, where some features are publicly available while the remaining ones, along with the label, require protection under local differential privacy. Under semi-feature LDP, we demonstrate that the mini-max convergence rate for non-parametric re

Ao Qu, Anirudh Valiveru, Catherine Tang, Vindula Jayawardana

Signalized intersections, arguably the most complicated type of traffic scenario, are essential to urban mobility systems. With recent advancements in intelligent transportation technologies, signalized intersections have great prospects for making transportation greener, safer, and faster. Several studies have been conducted focusing on intersection-level c

B. Vaia, F. Ursini, G. Matt, D. R. Ballantyne

The enigmatic and intriguing phenomenon of the "soft excess" observed in the X-ray spectra of luminous quasars continues to be a subject of considerable interest and debate in the field of high-energy astrophysics. This study focuses on the quasar HE 1029-1401 ($z=0.086$, $\log(L_{\rm{bol}}/[\rm{erg\,s^{-1}}])= 46.0 \pm 0.2$), with a particular emphasis on i

M. Sokolowski, G. Aniruddha, C. Di Pietrantonio, C. Harris

Fast Radio Bursts (FRBs) are millisecond dispersed radio pulses of predominately extra-galactic origin. Although originally discovered at GHz frequencies, most FRBs have been detected between 400 to 800 MHz. Nevertheless, only a handful of FRBs were detected below 400 MHz. Searching for FRBs at low frequencies is computationally challenging due to increased

Yue Li, Florian A. Kunneman, Koen V. Hindriks

With current state-of-the-art automatic speech recognition (ASR) systems, it is not possible to transcribe overlapping speech audio streams separately. Consequently, when these ASR systems are used as part of a social robot like Pepper for interaction with a human, it is common practice to close the robot's microphone while it is talking itself. This prevent

Jiri Smetana, Amit Singh Ubhi, Emilia Chick, Leonid Prokhorov

We present a pair of seismometers capable of measurement in all six axes of rigid motion. The vacuum-compatible devices implement compact interferometric displacement sensors to surpass the sensitivity of typical electrical readout schemes. Together with the capability to subtract the sensitivity-limiting coupling of ground tilt into horizontal motion, our s

Clara Bove, Thibault Laugel, Marie-Jeanne Lesot, Charles Tijus

As Machine Learning models achieve unprecedented levels of performance, the XAI domain aims at making these models understandable by presenting end-users with intelligible explanations. Yet, some existing XAI approaches fail to meet expectations: several issues have been reported in the literature, generally pointing out either technical limitations or misin

Safouane El Ghazouali, Arnaud Gucciardi, Umberto Michelucci

Self-rewarding have emerged recently as a powerful tool in the field of Natural Language Processing (NLP), allowing language models to generate high-quality relevant responses by providing their own rewards during training. This innovative technique addresses the limitations of other methods that rely on human preferences. In this paper, we build upon the co

Francesca Rizzo

EPW cubes form a locally complete family of smooth projective hyper-K\"ahler varieties of dimension 6, constructed by Iliev--Kapustka--Kapustka--Ranestad.\ Their construction and behavior share a lot of similarities with the double EPW sextics constructed by O'Grady.\ Adapting the methods of O'Grady, we construct a projective smooth small resolution of singu

G. Martínez-Solaeche, R. García-Benito, R. M. González Delgado, Luis Díaz-García

Contrastive learning (CL) has emerged as a potent tool for building meaningful latent representations of galaxy properties across a broad spectrum of wavelengths, ranging from optical and infrared to radio frequencies. These representations facilitate a variety of downstream tasks, including galaxy classification, similarity searches, and parameter estimatio

Fiona McCarthy

The cosmic infrared background (CIB) traces star-forming galaxies throughout cosmic history, with emission peaking at $z\sim1-2$. CIB anisotropies are present at the far-infrared frequencies observed by cosmic microwave background (CMB) experiments such as $\textit{Planck}$. These contain a lot of astrophysical and cosmological information, but are hard to s

Emily O. Garvin, Markus J. Bonse, Jean Hayoz, Gabriele Cugno

The new generation of observatories and instruments (VLT/ERIS, JWST, ELT) motivate the development of robust methods to detect and characterise faint and close-in exoplanets. Molecular mapping and cross-correlation for spectroscopy use molecular templates to isolate a planet's spectrum from its host star. However, reliance on signal-to-noise ratio (S/N) metr

Rakesh Nath-Ranga, Olivier Absil, Valentin Christiaens, Emily O. Garvin

The advent of high-contrast imaging instruments combined with medium-resolution spectrographs allows spectral and temporal dimensions to be combined with spatial dimensions to detect and potentially characterize exoplanets with higher sensitivity. We develop a new method to effectively leverage the spectral and spatial dimensions in integral-field spectrosco

I. V. Anikin

In this review, we outline the main features of the non-local gauge, named the contour gauge. The contour gauge belongs to the axial type of gauges and extends the local gauge used in the most of approaches. The geometry of gluon fields and the path-dependent formalism are the essential tools for the description of non-local gauges. The principle feature of

Di Qiu, Xinyang Lin, Kaiye Wang, Xiangxiang Chu

With the growing attention on data privacy and communication security in face recognition applications, federated learning has been introduced to learn a face recognition model with decentralized datasets in a privacy-preserving manner. However, existing works still face challenges such as unsatisfying performance and additional communication costs, limiting

Mengyue Peng, Faxiang Qin

Substantial efforts have been devoted to the elaborate component and microstructure design of absorbents (inclusions) in microwave absorbing (MA) composite materials. However, mesoscopic architectures of composites also play significant roles in prescribing their electromagnetic properties, which are rarely explored in studies of MA materials. Herein, a comp

Hüseyin Uğur Genç

The quality of social interaction is crucial for psychological and physiological health. Previous research shows that smartphones can negatively impact face-to-face social interactions. Many HCI studies have addressed this by limiting smartphone use during social interactions. While these studies show a decrease in smartphone use, restrictive approaches have

Sadataka Furui, Serge Dos Santos

We propose a method to obtain the optimal weight function of 9 paths in (3+1)D space-time whose length is less than or equal to $2\times (6+2)$ lattice units. The factor 2 comes from inclusion of opposite direction path or time reversed paths. There are $2\times 2$ time shifts, which we assume that they can be regarded as stochastic Markov processes. We prep

Nitesh Kumar, Anupam Bhardwaj, Harinder P. Singh, Marina Rejkuba

We present a comprehensive photometric study of RR Lyrae stars in the M3 globular cluster, utilising a vast dataset of 3140 optical ($UBVRI$) CCD images spanning 35 years from astronomical data archives. We have successfully identified previously known 238 RR Lyrae stars from the photometric data, comprising 178 RRab, 49 RRc, and 11 RRd stars. Multi-band per

Ryan Luis Acosta Babb

Normed spaces appear to have very little going for them: aside from the hackneyed linear structure, you get a norm whose only virtue, aside from separating points, is the Triangle Inequality. What could you possibly prove with that? As it turns out, quite a lot. In this article we will start by considering basic convexity properties of normed spaces, and gra

Leon Witt, Armando Teles Fortes, Kentaroh Toyoda, Wojciech Samek

Blockchain technology and Artificial Intelligence (AI) have emerged as transformative forces in their respective domains. This paper explores synergies and challenges between these two technologies. Our research analyses the biggest projects combining blockchain and AI, based on market capitalization, and derives a novel framework to categorize contemporary

Christian Antić

Analogical reasoning is the ability to detect parallels between two seemingly distant objects or situations, a fundamental human capacity used for example in commonsense reasoning, learning, and creativity which is believed by many researchers to be at the core of human and artificial general intelligence. Analogical proportions are expressions of the form `

Cai-Chang Li, Jun-Nan Lu, Gui-Jun Ding

We perform a comprehensive analysis of the minimal eclectic flavor group $Q_{8}\rtimes S_3$ which is isomorphic to $GL(2,3)$, and all its irreducible representations are induced from the irreducible representations of $Q_{8}$ and $S_{3}$. The consistency conditions between EFG and generalized CP (gCP) symmetry are revisited, and we find the gCP symmetry comp

Xiaoyu Yang, Jie Lu, En Yu

Multi-modal Large Language Models (MLLMs) frequently face challenges from concept drift when dealing with real-world streaming data, wherein distributions change unpredictably. This mainly includes gradual drift due to long-tailed data and sudden drift from Out-Of-Distribution (OOD) data, both of which have increasingly drawn the attention of the research co

Youngmi Hur, Hyojae Lim

Tight wavelet frames (TWFs) in \(L^2(\mathbb{R}^n)\) are versatile, and are practically useful due to their perfect reconstruction property. Nevertheless, existing TWF construction methods exhibit limitations, including a lack of specific methods for generating mother wavelets in extension-based construction, and the necessity to address the sum of squares (

Grigory Garkusha

The Ziegler spectrum for categories enriched in closed symmetric monoidal Grothendieck categories is defined and studied in this paper. It recovers the classical Ziegler spectrum of a ring. As an application, the Ziegler spectrum as well as the category of generalised quasi-coherent sheaves of a reasonable scheme is introduced and studied. It is shown that t

Pierre Marion, Lénaïc Chizat

The largest eigenvalue of the Hessian, or sharpness, of neural networks is a key quantity to understand their optimization dynamics. In this paper, we study the sharpness of deep linear networks for univariate regression. Minimizers can have arbitrarily large sharpness, but not an arbitrarily small one. Indeed, we show a lower bound on the sharpness of minim

Hong Rae Cho, Hyungwoon Koo, Young Joo Lee, Atte Pennanen

For $0<p<\infty$, $\Psi:[0,\infty)\to(0,\infty)$ and a finite positive Borel measure $\mu$ on the unit disc $\mathbb{D}$, the Lebesgue--Zygmund space $L^p_{\mu,\Psi}$ consists of all measurable functions $f$ such that $\lVert f \rVert_{L_{\mu, \Psi}^{p}}^p =\int_{\mathbb{D}}|f|^p\Psi(|f|)\,d\mu< \infty$. For an integrable radial function $\omega$ on $\mathbb

Martijn Gösgens, Lukas Lüchtrath, Elena Magnanini, Marc Noy

Motivated by an application in community detection, we consider an \ER random graph conditioned on the rare event that all connected components are fully connected. Such graphs can be considered as partitions of vertices into cliques. Hence, this conditional distribution defines a distribution over partitions. We show that a popular community detection metho

Puning Zhao, Lifeng Lai, Li Shen, Qingming Li

Privacy protection of users' entire contribution of samples is important in distributed systems. The most effective approach is the two-stage scheme, which finds a small interval first and then gets a refined estimate by clipping samples into the interval. However, the clipping operation induces bias, which is serious if the sample distribution is heavy-tail

Bingfang Yang, Zejun Li, Xinglong Jia, Stefano Moretti

In this paper, we study the discovery potential of a Vector-Like $B$ quark (VLB) via the process $pp \to B(\to bZ)j\to b(Z \to \nu_l\bar{\nu_l})j$ at the Large Hadron Collider (LHC) with $\sqrt{s}=14$ TeV. In the framework of a simplified model, we perform a scan over its parameter space and test its viability following a Monte Carlo analysis developed to in

Tom Burgert, Kai Norman Clasen, Jonas Klotz, Tim Siebert

The development of supervised deep learning-based methods for multi-label scene classification (MLC) is one of the prominent research directions in remote sensing (RS). However, collecting annotations for large RS image archives is time-consuming and costly. To address this issue, several data augmentation methods have been introduced in RS. Among others, th

Mahdi Moeini, Daniel Schermer, Oliver Wendt

In operations research, the Knapsack Problem (KP) is one of the classical optimization problems that has been widely studied. The KP has several variants and, in this paper, we address the binary KP, where for a given knapsack (with limited capacity) as well as a number of items, each of them has its own weight (volume or cost) and value, the objective consi

Prasun Dutta, Rajat K. De

Referring back to the original text in the course of hierarchical learning is a common human trait that ensures the right direction of learning. The models developed based on the concept of Non-negative Matrix Factorization (NMF), in this paper are inspired by this idea. They aim to deal with high-dimensional data by discovering its low rank approximation by

I. V. Anikin, Xurong Chen

We study the influence of analytical regularization used in the generalized function (distribution) space to the Tikhonov regularization procedure utilized in the different versions of Moore-Penrose's inversion. By introducing a new analytical term to the Tikhonov regularization of Moore-Penrose's inversion procedure, we derive new optimization conditions th

Yuanhao Yue, Chengyu Wang, Jun Huang, Peng Wang

Instruction tuning aims to align large language models (LLMs) with open-domain instructions and human-preferred responses. While several studies have explored autonomous approaches to distilling and annotating instructions from powerful proprietary LLMs, such as ChatGPT, they often neglect the impact of the distributions and characteristics of tasks, togethe

Hans Triebel

The paper deals with the distribution of eigenvalues of the compact fractal pseudodifferential operator $T^\mu_\tau$, \[ \big( T^\mu_\tau f\big)(x) = \int_{\mathbb{R}^n} e^{-ix\xi} \, \tau(x,\xi) \, \big( f\mu \big)^\vee (\xi) \, \mathrm{d} \xi, \qquad x\in \mathbb{R}^n, \] in suitable special Besov spaces $B^s_p (\mathbb{R}^n) = B^s_{p,p} (\mathbb{R}^n)$, $

Wenbo Niu, Jinhyung Park

In 1986, Green-Lazarsfeld raised the gonality conjecture asserting that the gonality $\operatorname{gon}(C)$ of a smooth projective curve $C$ of genus $g\geq 2$ can be read off from weight-one syzygies of a sufficiently positive line bundle $L$ on $C$, and also proposed possible least degree of such a line bundle. In 2015, Ein-Lazarsfeld proved the conjectur

Zhiyuan Wang, Bokui Chen, Xiaoyang Qu, Zhenhou Hong

With the rapid advancements in artificial intelligence, the development of knowledgeable and personalized agents has become increasingly prevalent. However, the inherent variability in state variables and action spaces among personalized agents poses significant aggregation challenges for traditional federated learning algorithms. To tackle these challenges,

Matteo Casarosa, Alessandro Codenotti, Martino Lupini

In this paper, we initiate the study of pro-Lie Polish abelian groups from the perspective of homological algebra. We extend to this context the type-decomposition of locally compact Polish abelian groups of Hoffmann and Spitzweck, and prove that the category $\mathbf{proLiePAb}$ of pro-Lie Polish abelian groups is a thick subcategory of the category of Poli

Louis Duval, Emily Lamour, Stéphane Macé, Jorge Machado

We have measured several 2p $\rightarrow$ 1s transition energies in core-excited boron-like ions of sulfur and argon. The measurements are reference-free, with an accuracy of a few parts per million. The x-rays were produced by the plasma of a an electron-cyclotron resonance ion source and were measured by a double-crystal x-ray spectrometer. The precision o

Lorenzo Brevi, Antonio Mandarino, Enrico Prati

The use of deep learning in physical sciences has recently boosted the ability of researchers to tackle physical systems where little or no analytical insight is available. Recently, the Physics-Informed Neural Networks (PINNs) have been introduced as one of the most promising tools to solve systems of differential equations guided by some physically grounde

Walter Boscheri, Saray Busto, Michael Dumbser

We present a novel high order semi-implicit hybrid finite volume/virtual element numerical scheme for the solution of compressible flows on Voronoi tessellations. The method relies on the flux splitting of the compressible Navier-Stokes equations into three sub-systems: a convective sub-system solved explicitly using a finite volume (FV) scheme, and the visc

Maria Isabel Rivas Ginel, Sarah Theroine

Video game localisation, a field highly impacted by the lack of visual environment and text linearity, forces translators to create inclusive solutions in terms of gender to overcome the hurdles created by variables. This paper will introduce the specificities of this sector and present an analysis of some of those techniques extracted from parallel corpora

Yufang Cui, Anders Lindquist

In this paper, we tackle the significant challenge of simultaneous stabilization in control systems engineering, where the aim is to employ a single controller to ensure stability across multiple systems. We delve into both scalar and multivariable scenarios. For the scalar case, we present the necessary and sufficient conditions for a single controller to s

Luis Fredes, Bernard Bercu, Michel Bonnefont, Adrien Richou

Chatteerjee and Diaconis have recently shown the asymptotic normality for the joint distribution of the number of descents and inverse descents in a random permutation. A noteworthy point of their results is that the asymptotic variance of the normal distribution is diagonal, which means that the number of descents and inverse descents are asymptotically unc

Moises Diaz, Miguel Angel Ferrer, Donato Impedovo, Giuseppe Pirlo

Computer aided diagnosis systems can provide non-invasive, low-cost tools to support clinicians. These systems have the potential to assist the diagnosis and monitoring of neurodegenerative disorders, in particular Parkinson's disease (PD). Handwriting plays a special role in the context of PD assessment. In this paper, the discriminating power of "dynamical

Anna Laura Suarez

We explore a pointfree approach to spaces which extends the category of $T_0$ spaces. Our pointfree objects are Raney extensions, pairs $(L,C)$ where $C$ is a coframe, $L\subseteq C$ is a frame which meet-generates it, and the inclusion $L\subseteq C$ preserves the frame operations as well as the strongly exact meets. We show that the category $\mathbf{Raney

Francis Filbet, François Golse

We propose a new approach to discretize the von Neumann equation, which is efficient in the semi-classical limit. This method is first based on the so called Weyl's variables to address the stiffness associated with the equation. Then, by applying a truncated Hermite expansion of the density operator, we successfully handle this stiffness. Additionally, we d

Xu Huang

We record a particularly simple construction on top of Lumsdaine's local universes that allows for a Coquand-style universe of propositions with propositional extensionality to be interpreted in a category with subobject classifiers.

Nicolas Fares, Maxime Lavaud, Zaicheng Zhang, Aditya Jha

Confined motions in complex environments are ubiquitous in microbiology. These situations invariably involve the intricate coupling between fluid flow, soft boundaries, surface forces and fluctuations. In the present study, such a coupling is investigated using a novel method combining holographic microscopy and advanced statistical inference. Specifically,

Kyriacos Mosphilis, Vassilis Vassiliades

This work is a preliminary study on using Exploratory Landscape Analysis (ELA) for Quality Diversity (QD) problems. We seek to understand whether ELA features can potentially be used to characterise QD problems paving the way for automating QD algorithm selection. Our results demonstrate that ELA features are affected by QD optimisation differently than rand

Tingchen Fu, Deng Cai, Lemao Liu, Shuming Shi

Supervised fine-tuning (SFT) on instruction-following corpus is a crucial approach toward the alignment of large language models (LLMs). However, the performance of LLMs on standard knowledge and reasoning benchmarks tends to suffer from deterioration at the latter stage of the SFT process, echoing the phenomenon of alignment tax. Through our pilot study, we

Benjamin Nill

We prove a sharp upper bound on the number of distinct columns of a totally unimodular matrix with column sums $1$ improving upon Heller's classical bound. The proof uses Seymour's decomposition theorem. Such matrices are closely related to unimodular polytopes: lattice polytopes where the vertices of every full-dimensional subsimplex form an affine lattice

Yulin Xie, Yifa Tang

High-dimensional Lagrange interpolation plays a pivotal role in finite element methods, where ensuring the unisolvence and symmetry of its interpolation space and nodes set is crucial. In this paper, we leverage group action and group representation theories to precisely delineate the conditions for unisolvence. We establish a necessary condition for unisolv

István Gaál

J. Harrington and L. Jones characterized monogenity of four new parametric families of quartic polynomials with various Galois groups. A short time later P. Voutier added a cyclic family. In this note we intend to describe all generators of power integral bases in the number fields generated by a root of the monogenic polynomials.

Yongyi Zang, Yifan Wang, Minglun Lee

Neural upmixing, the task of generating immersive music with an increased number of channels from fewer input channels, has been an active research area, with mono-to-stereo and stereo-to-surround upmixing treated as separate problems. In this paper, we propose a unified approach to neural upmixing by formulating it as spherical harmonics - more specifically

Qiang Chen, Weizhong Yu, Feiping Nie, Xuelong Li

Fuzzy clustering algorithms can be roughly categorized into two main groups: Fuzzy C-Means (FCM) based methods and mixture model based methods. However, for almost all existing FCM based methods, how to automatically selecting proper membership degree hyper-parameter values remains a challenging and unsolved problem. Mixture model based methods, while circum

Li Fan, Lee Ching-Hung, Han Su, Feng Shanshan

In recent years, the potential applications of Large Multimodal Models (LMMs) in fields such as healthcare, social psychology, and industrial design have attracted wide research attention, providing new directions for human factors research. For instance, LMM-based smart systems have become novel research subjects of human factors studies, and LMM introduces

Sudhakantha Girmohanta, Shota Nakagawa, Yuichiro Nakai, Junxuan Xu

There has been an attempt to revive the visible QCD axion at the 10 MeV scale assuming that it exclusively couples to the first-generation quarks and the electron. This variant of the QCD axion is claimed to remain phenomenologically viable, partly due to a clever model construction that induces tree-level pion-phobia and exploits uncertainties inherent in t

Krishnadev Narayanankutty, José Antonio Pereiro-Morejon, Arián Ferrero-Fernández, Valentina Onesto

During overflow metabolism, cells excrete glycolytic byproducts when growing under aerobic conditions in a seemingly wasteful fashion. While potentially advantageous for microbes with finite oxidative capacity, its role in higher organisms is harder to assess. Recent single-cell experiments suggest overflow metabolism arises due to imbalances in inter-cellul

Shusheng Li, Qilong Zhai

In this paper, we propose a weak Galerkin (WG) finite element method for the Maxwell eigenvalue problem. By restricting subspaces, we transform the mixed form of Maxwell eigenvalue problem into simple elliptic equation. Then we give the WG numerical scheme for the Maxwell eigenvalue problem. Furthermore, we obtain the optimal error estimates of arbitrarily h

Álvaro Mozota Frauca

In this paper I offer an introduction to group field theory (GFT) and to some of the issues affecting the foundations of this approach to quantum gravity. I first introduce covariant GFT as the theory that one obtains by interpreting the amplitudes of certain spin foam models as Feynman amplitudes in a perturbative expansion. However, I argue that it is uncl

Kenan Huremović, Federico Nutarelli, Francesco Serti, Fernando Vega-Redondo

Using administrative data on the universe of inter-firm transactions in Spain, we show that firms learn to import from their domestic suppliers and customers. Our identification strategy exploits the panel structure of the data, the firm-time variation across import origins, and the network structure. We find evidence of both upstream and downstream network

Seyed Mohammad Rezaei Niya

The positivistic assumptions of determinism and objectivism in the realm of Newtonian mechanics are questioned in this paper. While objectivism is only challenged through proposing the mildest form of subjectivism, determinism is structurally disputed by proposing that the physical reality, at least in the examples discussed, is, in essence, probabilistic an

b collaboration, Giulio Aielli, Juliette Alimena, Saul Balcarcel-Salazar

The CODEX-$\beta$ apparatus is a demonstrator for the proposed future CODEX-b experiment, a long-lived-particle detector foreseen for operation at IP8 during HL-LHC data-taking. The demonstrator project, intended to collect data in 2025, is described, with a particular focus on the design, construction, and installation of the new apparatus.

Iu-Iong Ng, Yuichiro Toma

In 2016, Cramer, Ducas, Peikert and, Regev proposed an efficient algorithm for recovering short generators of principal ideals in $q$-th cyclotomic fields with $q$ being a prime power. In this paper, we improve their analysis of the dual basis of the log-cyclotomic-unit lattice under the Generalised Riemann Hypothesis and in the case that $q$ is a prime numb

Bo-Wei Tseng, Tsun-Hsu Chang

The intricate interplay between complex permittivity and permeability constitutes the cornerstone of electromagnetic (EM) applications, enabling precise customization for various uses. This study employed silver-epoxy nano-composites to exemplify a conductor-insulator composite, leveraging silver's exceptional attributes, such as high conductivity and low re

Mingxin Wang

In this paper we study a nonlinear infection viral propagation model with diffusion, in which, the left boundary is fixed and with homogeneous Dirichlet boundary conditions, while the right boundary is free. We find that the habitat always expands to the half line $[0, \infty)$, and that the virus and infected cells always die out when the {\it Basic Reprodu

Mazhar Ali

We have reexamined the moments of positive maps and the criterion based on these moments to detect entanglement. For two qubits, we observed that reduction map is equivalent to partial transpose map as the resulting matrices have the same set of eigenvalues although both matrices look different in same computational basis. Consequently, the detection power o

Chris Chen, Annabelle McIver, Carroll Morgan

We present a novel formal system for proving quantitative-leakage properties of programs. Based on a theory of Quantitative Information Flow (QIF) that models information leakage as a noisy communication channel, it uses "gain-functions" for the description and measurement of expected leaks. We use a small imperative programming language, augmented with leak

Rutger Duflou, Gautam Gaddemane, Michel Houssa, Aryan Afzalian

Self-heating effects can significantly degrade the performance in nanoscale devices. We investigate self-heating effects in such devices based on two-dimensional materials using ab-initio techniques. A new algorithm was developed to allow for efficient self-energy computations, achieving a $\sim$500 times speedup. It is found that for the simple case of free

Mentzelos Melistas

We study the reduction properties of low genus curves whose Jacobian has complex multiplication. In the elliptic curve case, we classify the possible Kodaira types of reduction that can occur. Moreover, we investigate the possible Namikawa Ueno types that can occur for genus $2$ curves whose Jacobian has complex multiplication which is defined over the base

Hee-Youl Kwak, Dae-Young Yun, Yongjune Kim, Sang-Hyo Kim

Ensuring extremely high reliability in channel coding is essential for 6G networks. The next-generation of ultra-reliable and low-latency communications (xURLLC) scenario within 6G networks requires frame error rate (FER) below $10^{-9}$. However, low-density parity-check (LDPC) codes, the standard in 5G new radio (NR), encounter a challenge known as the err

Mazhar Ali

We investigate entanglement dynamics of bipartite as well multipartite systems beyond Markov approximation. We study two pairs of cavity-reservoir systems, modeled as four qubits and track the change of entanglement among cavity-cavity qubits, reservoir-reservoir qubits, and also for genuine entanglement of all four qubits. For cavity-cavity qubits, we find

Jasna Prezelj, Fabio Vlacci

We present solutions to additive and multiplicative Cousin problems formulated on an axially symmetric domain $\Omega \subset \mathbb H$ for slice--regular functions starting from the solutions for subclasses, namely slice--regular slice--preserving functions and functions in a given vectorial class. Consequently, we prove the vanishing of the corresponding

di Blasio Giuseppina, Maria Michaela Porzio

In this paper we study a class of nonlinear anisotropic parabolic problems in bounded domains. In detail, we study the influences of the initial data and the forcing term f on the behavior of the solutions. We prove existence and uniqueness results. We indagate on the behavior in time of the solutions with a particular attention to the autonomous case f(x, t

Zhimin Fan, Jie Guo, Yiming Wang, Tianyu Xiao

Finding valid light paths that involve specular vertices in Monte Carlo rendering requires solving many non-linear, transcendental equations in high-dimensional space. Existing approaches heavily rely on Newton iterations in path space, which are limited to obtaining at most a single solution each time and easily diverge when initialized with improper seeds.

Herivelto Borges, João Paulo Guardieiro, Cecília Salgado, Jaap Top

The aim of this paper is to present elliptic curves defined over function fields of even characteristic having arbitrarily large Mordell-Weil rank. More precisely, we study elliptic curves arising as quartic twist of a supersingular elliptic curve defined over $\mathbb{F}_2$ using the function field of a maximal curve $C$ that admits an order 4 automorphism.

Sahil Rajesh Dhayalkar

Transformers have revolutionized various domains of artificial intelligence due to their unique ability to model long-range dependencies in data. However, they lack in nuanced, context-dependent modulation of features and information flow. This paper introduces two significant enhancements to the transformer architecture - the Evaluator Adjuster Unit (EAU) a

Alberto Rodríguez-Arenas, Jochen Wengenroth

We give streamlined proofs of theorems of S.\ Smirnov about the decomposition of vector fields of measures into curves.

Zhangkai Cao, Jiahao Su, Jianyu Li, Tao Ying

The study of non-Fermi liquids sheds light on unconventional phenomena in condensed matter systems that lie beyond the scope of Landau Fermi liquid theory. One intriguing example is the Bose metal, characterized by an uncondensed bosonic ground state. However, constructing a Bose metal phase in two dimensions (2D) remains a significant challenge.} Utilizing

Martin Bohnert

A half-integral polygon with quasi-period collapse behaves similarly to a lattice polygon in the sense that the number of lattice points in its integer dilates can be calculated as values of a polynomial, its Ehrhart polynomial. As a main result, we classify the Ehrhart polynomials of all half-integral non-lattice polygons with quasi-period collapse. In part

Jiarun Ding, Peiwen Jiang, Chao-Kai Wen, Shi Jin

Semantic communication has undergone considerable evolution due to the recent rapid development of artificial intelligence (AI), significantly enhancing both communication robustness and efficiency. Despite these advancements, most current semantic communication methods for image transmission pay little attention to the differing importance of objects and ba

Kunio Kaneta, Kin-ya Oda, Motohiko Yoshimura

We propose a scenario that can explain the early-time inflation and the late-time dark energy within a unified framework. A scalar potential combining power-law and exponential type in a context of extended Jordan-Brans-Dicke gravity is critically important for this realization. A realistic scenario can be achieved in a two-field model in which one direction

Pengzhou Cheng, Yidong Ding, Tianjie Ju, Zongru Wu

Large language models (LLMs) have raised concerns about potential security threats despite performing significantly in Natural Language Processing (NLP). Backdoor attacks initially verified that LLM is doing substantial harm at all stages, but the cost and robustness have been criticized. Attacking LLMs is inherently risky in security review, while prohibiti

Martin Leutbecher, Sándor Baran

Multivariate probabilistic verification is concerned with the evaluation of joint probability distributions of vector quantities such as a weather variable at multiple locations or a wind vector for instance. The logarithmic score is a proper score that is useful in this context. In order to apply this score to ensemble forecasts, a choice for the density is