December 2023 arXiv papers — page 102

Tomasz Linowski, Łukasz Rudnicki

The Glauber-Sudarshan, Wigner and Husimi quasiprobability distributions are indispensable tools in quantum optics. However, although mathematical relations between them are well established, not much is known about their operational connection. In this paper, we prove that a single composition of finite-strength quantum limited amplifier and attenuator chann

Kristin Courtney, Wilhelm Winter

We give sufficient conditions allowing one to build a C*-algebraic structure on a self-adjoint linear subspace of a C*-algebra in such a way that the subspace is naturally identified with the resulting C*-algebra via a completely positive order zero map. This leads to necessary and sufficient conditions to realize a self-adjoint linear subspace of a C*-algeb

Mahmoud Atashbar, Hamed Alizadeh Ghazijahani, Yong Liang Guan, Zhaojie Yang

In this paper, we study a multi-user visible light communication (VLC) system assisted with optical reflecting intelligent surface (ORIS). Joint precoding and alignment matrices are designed to maximize the average signal-to-interference plus noise ratio (SINR) criteria. Considering the constraints of the constant mean transmission power of LEDs and the powe

Andrew C. Freeman, Ketan Mayer-Patel, Montek Singh

The strong temporal consistency of surveillance video enables compelling compression performance with traditional methods, but downstream vision applications operate on decoded image frames with a high data rate. Since it is not straightforward for applications to extract information on temporal redundancy from the compressed video representations, we propos

Jingsheng Gao, Jiacheng Ruan, Suncheng Xiang, Zefang Yu

With the success of pre-trained visual-language (VL) models such as CLIP in visual representation tasks, transferring pre-trained models to downstream tasks has become a crucial paradigm. Recently, the prompt tuning paradigm, which draws inspiration from natural language processing (NLP), has made significant progress in VL field. However, preceding methods

E. Mornacchi, P. Pedroni, F. Afzal, Y. Wunderlich

A new data set for the helicity-dependent differential cross section of the single-meson photoproduction reaction $\gamma p \to p \pi^{0}$ was obtained for the photon energy interval 150-400 MeV. The experiment was performed at the A2 tagged photon facility of the Mainz Microtron MAMI using a circularly polarized photon beam and a longitudinally polarized pr

Yuqing Li, Yusheng Zhao, Xinyue Zhang, Hui Zhong

Quantum computing has been widely applied in various fields, such as quantum physics simulations, quantum machine learning, and big data analysis. However, in the domains of data-driven paradigm, how to ensure the privacy of the database is becoming a vital problem. For classical computing, we can incorporate the concept of differential privacy (DP) to meet

Jonathan Buchanan, Stephen McKean

A classic result of Anderson, Brown, and Peterson states that the cobordism spectrum MSpin (respectively, MSpin$^c$) splits as a sum of Eilenberg--Mac Lane spectra and connective covers of real K-theory (respectively, complex K-theory) at 2. We develop a theory of symplectic K-theory classes and use these to build an explicit splitting for MSpin$^h$ in terms

Tingfeng Song, Veniero Lenzi, José P. B. Silva, Luís Marques

Ferroelectric HfO2 films are usually polycrystalline and contain a mixture of polar and nonpolar phases. This challenges the understanding and control of polar phase stabilization and ferroelectric properties. Several factors such as dopants, oxygen vacancies, or stress, among others, have been investigated and shown to have a crucial role on optimizing the

Yan Pang, Tianhao Wang

With the rapid advancement of diffusion-based image-generative models, the quality of generated images has become increasingly photorealistic. Moreover, with the release of high-quality pre-trained image-generative models, a growing number of users are downloading these pre-trained models to fine-tune them with downstream datasets for various image-generatio

Juan Miguel Carceller, Frank Gaede, Gerardo Ganis, Benedikt Hegner

A performant and easy-to-use event data model (EDM) is a key component of any HEP software stack. The podio EDM toolkit provides a user friendly way of generating such a performant implementation in C++ from a high level description in yaml format. Finalizing a few important developments, we are in the final stretches for release v1.0 of podio, a stable rele

Lukas Bengel

We analyze the spectral and dynamical stability of solitary wave solutions to the Lugiato-Lefever equation (LLE) on $\mathbb{R}$. Our interest lies in solutions that arise through bifurcations from the phase-shifted bright soliton of the nonlinear Schr\"odinger equation (NLS). These solutions are highly nonlinear, localized, far-from-equilibrium waves, and a

S. Abe, J. H. Adams, D. Allard, P. Alldredge

This is a collection of papers presented by the JEM-EUSO Collaboration at the 38th International Cosmic Ray Conference (Nagoya, Japan, July 26-August 3, 2023)

Mohd. Gayas Ansari, Pragya Shukla

We numerically analyze the spectral statistics of the multiparametric Gaussian ensembles of complex matrices with zero mean and variances with different decay routes away from the diagonals. As the latter mimics different degree of effective sparsity among the matrix elements, such ensembles can serve as good models for a wide range of phase transitions e.g.

Elahe Khalili Samani, Marco Radeschi

We prove that if a compact, simply connected Riemannian $G$-manifold $M$ has orbit space $M/G$ isometric to some other quotient $N/H$ with $N$ having zero topological entropy, then $M$ is rationally elliptic. This result, which generalizes most conditions on rational ellipticity, is a particular case of a more general result involving manifold submetries.

Davide Palitta, Zoran Tomljanović, Ivica Nakić, Jens Saak

Sequences of parametrized Lyapunov equations can be encountered in many application settings. Moreover, solutions of such equations are often intermediate steps of an overall procedure whose main goal is the computation of $\text{trace}(EX)$ where $X$ denotes the solution of a Lyapunov equation and $E$ is a given matrix. We are interested in addressing probl

Yunchen Li, Zhou Yu, Gaoqi He, Yunhang Shen

Symmetric positive definite~(SPD) matrices have shown important value and applications in statistics and machine learning, such as FMRI analysis and traffic prediction. Previous works on SPD matrices mostly focus on discriminative models, where predictions are made directly on $E(X|y)$, where $y$ is a vector and $X$ is an SPD matrix. However, these methods a

Placido Fernandez Declara, Frank Gaede, Gerardo Ganis, Benedikt Hegner

The podio event data model (EDM) toolkit provides an easy way to generate a performant implementation of an EDM from a high level description in yaml format. We present the most recent developments in podio, most importantly the inclusion of a schema evolution mechanism for generated EDMs as well as the "Frame", a thread safe, generalized event data containe

Kamil Kanclerz, Julita Bielaniewicz, Marcin Gruza, Jan Kocon

Data annotated by humans is a source of knowledge by describing the peculiarities of the problem and therefore fueling the decision process of the trained model. Unfortunately, the annotation process for subjective natural language processing (NLP) problems like offensiveness or emotion detection is often very expensive and time-consuming. One of the inevita

N. Lagarde, R. Minkeviciute, A. Drazdauskas, G. Tautvaisiene

Despite a rich observational background, few spectroscopic studies have dealt with the measurement of the carbon isotopic ratio in giant stars. However, it is a key element in understanding the mixing mechanisms that occur in the interiors of giant stars. We present the CNO and $^{12}$C/$^{13}$C abundances derived for 71 giant field stars. Then, using this n

Michel Bergère, Bertrand Eynard, Emmanuel Guitter, Soufiane Oukassi

Mobiles are a particular class of decorated plane trees which serve as codings for planar maps. Here we address the question of enumerating mobiles in their most general flavor, in correspondence with planar Eulerian (i.e., bicolored) maps. We show that the generating functions for such mobiles satisfy a number of recursive equations which lie in the field o

Pu Cao, Feng Zhou, Lu Yang, Tianrui Huang

In-domain generation aims to perform a variety of tasks within a specific domain, such as unconditional generation, text-to-image, image editing, 3D generation, and more. Early research typically required training specialized generators for each unique task and domain, often relying on fully-labeled data. Motivated by the powerful generative capabilities and

Mojtaba Najafi Khatounabad, Hacer Yalim Keles, Selma Kadioglu

This study presents a deep learning-based approach to seismic velocity inversion problem, focusing on both noisy and noiseless training datasets of varying sizes. Our Seismic Velocity Inversion Network (SVInvNet) introduces a novel architecture that contains a multi-connection encoder-decoder structure enhanced with dense blocks. This design is specifically

Samrat Mukherjee, Dibyanayan Bandyopadhyay, Baban Gain, Asif Ekbal

Diabetic Retinopathy (DR) is a prevalent illness associated with Diabetes which, if left untreated, can result in irreversible blindness. Deep Learning based systems are gradually being introduced as automated support for clinical diagnosis. Since healthcare has always been an extremely important domain demanding error-free performance, any adversaries could

Tao Zhang, Kun Ding, Jinyong Wen, Yu Xiong

Self-supervised learning (SSL) for RGB images has achieved significant success, yet there is still limited research on SSL for infrared images, primarily due to three prominent challenges: 1) the lack of a suitable large-scale infrared pre-training dataset, 2) the distinctiveness of non-iconic infrared images rendering common pre-training tasks like masked i

Sean R. Bowerfind, Ehsan Taheri

The reachable set of controlled dynamical systems consist of the set of all possible reachable states from an initial condition, over a certain period of time under various control and operation constraints and exogenous disturbances. For space applications, determination of reachable sets is invaluable for trajectory planning, collision avoidance, ensuring

Virginie Debauche, Alec Edwards, Raphael M. Jungers, Alessandro Abate

Neural-based, data-driven analysis and control of dynamical systems have been recently investigated and have shown great promise, e.g. for safety verification or stability analysis. Indeed, not only do neural networks allow for an entirely model-free, data-driven approach, but also for handling arbitrary complex functions via their power of representation (a

Mrigank Pawagi, Viraj Kumar

Before implementing a function, programmers are encouraged to write a purpose statement i.e., a short, natural-language explanation of what the function computes. A purpose statement may be ambiguous i.e., it may fail to specify the intended behaviour when two or more inequivalent computations are plausible on certain inputs. Our paper makes four contributio

Ezequiel Zubieta, Santiago del Palacio, Federico García, Susana Beatriz Araujo Furlan

Pulsars are known for their exceptionally stable rotation. However, this stability can be disrupted by glitches, sudden increases in rotation frequency whose cause is poorly understood. In this study, we present some preliminary results from the pulsar monitoring campaign conducted at the IAR since 2019. We present measurements from timing solution fits of t

Florian van der Steen, Fré Vink, Heysem Kaya

The protection of sensitive data becomes more vital, as data increases in value and potency. Furthermore, the pressure increases from regulators and society on model developers to make their Artificial Intelligence (AI) models non-discriminatory. To boot, there is a need for interpretable, transparent AI models for high-stakes tasks. In general, measuring th

Markus Brill, Jannik Peters

When selecting committees based on preferences of voters, a variety of different criteria can be considered. Two natural objectives are maximizing the utilitarian welfare (the sum of voters' utilities) and coverage (the number of represented voters) of the selected committee. Previous work has studied the impact on utilitarian welfare and coverage when requi

Jaeryeong Chang, Sungjun Lee, Yoonsoo Kim, Younghoon Lim

We report the creation of dual-species Bose-Einstein condensates (BECs) of $^{23}$Na and $^{41}$K. Favorable background scattering lengths enable efficient sympathetic cooling of $^{41}$K via forced evaporative cooling of $^{23}$Na in a plugged magnetic trap and an optical dipole trap. The $1/e$ lifetime of the thermal mixture in the stretched hyperfine stat

Daniel Ciganda, Nicolas Todd

Macro-level modeling is still the dominant approach in many demographic applications because of its simplicity. Individual-level models, on the other hand, provide a more comprehensive understanding of observed patterns; however, their estimation using real data has remained a challenge. The approach we introduce in this article attempts to overcome this lim

Evgeny Skvortsov, Mirian Tsulaia

Scattering of two Kerr Black Holes emitting gravitational waves can be captured by an effective theory of a massive higher-spin field interacting with the gravitational field. While other compact objects should activate a multitude of non-minimal interactions it is the black holes that should be captured by the simplest minimal interaction. Implementing mass

Jonas Knoerr

It is shown that Alesker's solution of McMullen's conjecture implies the following stronger version of the conjecture: Every continuous, translation invariant, $k$-homogeneous valuation on convex bodies in $\mathbb{R}^n$ can be approximated uniformly on compact subsets by finite linear combinations of mixed volumes involving at most $N_{n,k}$ summands, where

Mobina Zibandepour, Akram Shojaei, Arash Abbasi Larki, Mehdi Delrobaei

Advancements in neurosurgical robotics have improved medical procedures, particularly deep brain stimulation, where robots combine human and machine intelligence to precisely implant electrodes in the brain. While effective, this procedure carries risks and side effects. Noninvasive deep brain stimulation (NIDBS) offers promise by making brain stimulation sa

Yuanyou Xu, Zongxin Yang, Yi Yang

Powered by large-scale text-to-image generation models, text-to-3D avatar generation has made promising progress. However, most methods fail to produce photorealistic results, limited by imprecise geometry and low-quality appearance. Towards more practical avatar generation, we present SEEAvatar, a method for generating photorealistic 3D avatars from text wi

Ahmad Ghasemi, Ehsan Zeraatkar, Majid Moradikia, Seyed

This paper introduces adversarial attacks targeting a Graph Neural Network (GNN) based radio resource management system in point to point (P2P) communications. Our focus lies on perturbing the trained GNN model during the test phase, specifically targeting its vertices and edges. To achieve this, four distinct adversarial attacks are proposed, each accountin

Alexander Komech

We consider the Maxwell-Bloch system which is a finite-dimensional approximation of the coupled nonlinear Maxwell-Schr\"odinger equations. The approximation consists of one-mode Maxwell field coupled to two-level molecule. We construct time-periodic solutions to the factordynamics which is due to the symmetry gauge group. For the corresponding solutions to t

Bing-qing Zhang, Hong Wu, Wei Du, Pin-song Zhao

We present a study of low surface brightness galaxies (LSBGs) selected by fitting the images for all the galaxies in $\alpha$.40 SDSS DR7 sample with two kinds of single-component models and two kinds of two-component models (disk+bulge): single exponential, single s\'{e}rsic, exponential+deVaucular (exp+deV), and exponential+s\'{e}rsic (exp+ser). Under the

Rajrupa Banerjee, Kiran Sharma, Sudhanwa Patra, Prasanta K. Panigrahi

The geometrical representation of two-flavor neutrino oscillation represents the neutrino's flavor eigenstate as a magnetic moment-like vector that evolves around a magnetic field-like vector that depicts the Hamiltonian of the system. In the present work, we demonstrate the geometrical interpretation of neutrino in a vacuum in the presence of decay, which t

Peilin Cai

This paper investigates the application of advanced image segmentation techniques to analyze C-fos immediate early gene expression, a crucial marker for neural activity. Due to the complexity and high variability of neural circuits, accurate segmentation of C-fos images is paramount for the development of new insights into neural function. Amidst this backdr

Yuan Yao, Tian-Sheuan Chang

Deep-learning accelerators are increasingly in demand; however, their performance is constrained by the size of the feature map, leading to high bandwidth requirements and large buffer sizes. We propose an adaptive scale feature map compression technique leveraging the unique properties of the feature map. This technique adopts independent channel indexing g

Stefan Noll, John M. C. Plane, Wuhu Feng, Konstantinos S. Kalogerakis

The Earth's mesopause region between about 75 and 105 km is characterised by chemiluminescent emission from various lines of different molecules and atoms. This emission was and is important for the study of the chemistry and dynamics in this altitude region at nighttime. However, our understanding of molecular emissions with low intensities and high line de

Paul S. Clarke, Annalivia Polselli

Recent advances in causal inference have seen the development of methods which make use of the predictive power of machine learning algorithms. In this paper, we develop novel double machine learning (DML) procedures for panel data in which these algorithms are used to approximate high-dimensional and nonlinear nuisance functions of the covariates. Our new p

Richard Montgomery

The Kepler problem is the special case $\alpha = 1$ of the power law problem: to solve Newton's equations for a central force whose potential is of the form $-\mu/r^{\alpha}$ where $\mu$ is a coupling constant. Associated to such a problem is a two-dimensional cone with cone angle $2 \pi c$ with $c = 1 - \frac{\alpha}{2}$. We construct a transformation takin

Anna Sophie Schmidhuber

Dilation surfaces are geometric surfaces modelled after the complex plane whose structure group is generated by the groups of translations and dilations. For any dilation surface, for any direction $\theta$ in $S^1$, there exists a foliation on the surface called the directional foliation in direction $\theta$. In this Thesis, we prove a structure theorem fo

Kirill Boguslavski, Paul Hotzy, David I. Müller, Dénes Sexty

In this conference proceeding, we investigate the physical anisotropy in terms of the temporal and spatial lattice spacings in relation to the bare parameters of SU(2) pure gauge theory using Wilson gradient flow. Anisotropic lattices have a wide range of applications, from thermodynamic calculations in QCD to very recent real-time simulations using the comp

José Raimundo Carvalho, Diego de Maria André, Yuri Costa

We investigate the dynamics of the update of subjective homicide victimization risk after an informational shock by developing two econometric models able to accommodate both optimal decisions of changing prior expectations which enable us to rationalize skeptical Bayesian agents with their disregard to new information. We apply our models to a unique househ

Z. Gholami, Z. Noorinejad, M. Amini, E. Ghanbari-Adivi

A novel method has been devised to compute the Local Integrals of Motion (LIOMs) for a one-dimensional many-body localized system. In this approach, a class of optimal unitary transformations is deduced in a tensor-network formalism to diagonalize the Hamiltonian of the specified system. To construct the tensor network, we utilize the eigenstates of the subs

Ainayya Almira, Anisah Rachmawati, Insi Norma Jelita, Yoan Nurlaili

The aim of this research is to provide insight to chemistry education teachers and researchers regarding the effectiveness of the guided inquiry learning model and provide direction for further research in this field. The research method used in this article is Systematic Literature Review (SLR), to help compile and evaluate various research related to the g

Elham Yousefi, Mohamed Gewily, Franz König, Günter Höglinger

Measuring disease progression in clinical trials for testing novel treatments for multifaceted diseases as Progressive Supranuclear Palsy (PSP), remains challenging. In this study we assess a range of statistical approaches to compare outcomes measured by the items of the Progressive Supranuclear Palsy Rating Scale (PSPRS). We consider several statistical ap

Haifeng Huang, Yilun Chen, Zehan Wang, Rongjie Huang

Recent advancements in 3D Large Language Models (LLMs) have demonstrated promising capabilities for 3D scene understanding. However, previous methods exhibit deficiencies in general referencing and grounding capabilities for intricate scene comprehension. In this paper, we introduce the use of object identifiers and object-centric representations to interact

Anders Tranberg, Gerhard Ungersbäck

In certain models of inflation, the postinflationary reheating of the Universe is not primarily due to perturbative decay of the inflaton field into particles, but proceeds through a tachyonic instability. In the process, long-wavelength modes of an unstable field, which is often distinct from the inflaton itself, acquire very large occupation numbers, which

Jiquan Wang, Sha Zhao, Haiteng Jiang, Shijian Li

Automatic sleep staging is essential for sleep assessment and disorder diagnosis. Most existing methods depend on one specific dataset and are limited to be generalized to other unseen datasets, for which the training data and testing data are from the same dataset. In this paper, we introduce domain generalization into automatic sleep staging and propose th

J. DiMarco, P. Akella, G. Ambrosio, M. Baldini

MQXFA production series quadrupole magnets are being built for the Hi-Lumi (HL) LHC upgrade by the US Accelerator Upgrade Project (US-HL-LHC AUP). These magnets are being placed in pairs, as a cold mass, within cryostats at Fermilab, and are being tested to assess alignment and magnetic performance at Fermilab's horizontal test stand facility. The ~10 m - lo

Efstathia Bougioukli, Michael A. Zazanis

We examine hitting probability problems for Ornstein-Uhlenbeck (OU) processes and Geometric Brownian motions (GBM) with respect to exponential boundaries related to problems arising in risk theory and asset and liability models in pension funds. In Section 2 we consider the OU process described by the Stochastic Differential Equation (SDE) $dX_t = \mu X_t dt

Jia-Hao Lü, Pei-Rong Han, Wen Ning, Xin Zhu

We study the quantum metric in a driven Tavis-Cummings model, comprised of multiple qubits interacting with a quantized photonic field. The parametrical driving of the photonic field breaks the system's U(1) symmetry down to a ${\rm Z}_2$ symmetry, whose spontaneous breaking initiates a superradiant phase transition. We analytically solved the eigenenergies

Erfan Keshavarz, S. Habib Mazharimousavi

In this research, we present a Python-based solution designed to simulate a one-dimensional quantum system that incorporates multiple Dirac $\delta -$% potentials. The primary aim of this research is to investigate the scattering problem within such a system. By developing this program, we can generate wave functions throughout the system and compute transmi

Jan Pich, Rahul Santhanam

We prove that if conditions I-II (below) hold and there is a sequence of Boolean functions $f_n$ hard to approximate by p-size circuits such that p-size circuit lower bounds for $f_n$ do not have p-size proofs in Extended Frege system EF, then $P\ne NP$. I. $S^1_2$ proves that a concrete function in ${\sf E}$ is hard to approximate by subexponential-size cir

Marion Dubois-Sage, Baptiste Jacquet, Frank Jamet, Jean Baratgin

Our aim is to analyze the relevance of the mentor-child paradigm with a robot for individuals with Autism Spectrum Disorders, and the adaptations required. This method could allow a more reliable evaluation of the socio-cognitive abilities of individuals with autism, which may have been underestimated due to pragmatic factors.

Yas Vaseghi, Behnaz Behara, Mehdi Delrobaei

The Internet of Medical Things (IoMT) offers a promising solution to improve patient health and reduce human error. Wearable smart infusion pumps that accurately administer medication and integrate with electronic health records are an example of technology that can improve healthcare. They can even alert healthcare professionals or remote servers during ope

Chenguang Liang, Yu Zhang, Shu Chen

Systems of interacting bosons in double-well potentials, modeled by two-site Bose-Hubbard models, are of significant theoretical and experimental interest and attracted intensive studies in contexts ranging from many-body physics and quantum dynamics to the onset of quantum chaos. In this work we systematically study a kicked two-site Bose-Hubbard model (Bos

Anthony D'Onofrio, Amir Hossain, Lesther Santana, Naseem Machlovi

The rapid advancement of quantum computing has pushed classical designs into the quantum domain, breaking physical boundaries for computing-intensive and data-hungry applications. Given its immense potential, quantum-based computing systems have attracted increasing attention with the hope that some systems may provide a quantum speedup. For example, variati

Qian Chen, Taolin Zhang, Dongyang Li, Xiaofeng He

The minimal feature removal problem in the post-hoc explanation area aims to identify the minimal feature set (MFS). Prior studies using the greedy algorithm to calculate the minimal feature set lack the exploration of feature interactions under a monotonic assumption which cannot be satisfied in general scenarios. In order to address the above limitations,

Philipp Schmitz, Tobias Jauch, Alex Wezel, Mohammad R. Fadiheh

This paper introduces Okapi, a new hardware/software cross-layer architecture designed to mitigate Transient Execution Side Channel attacks, including Spectre variants, in modern computing systems. Okapi provides a hardware basis for secure speculation in sandboxed environments and can replace expensive speculation barriers in software. At its core, it allow

Mateusz Kula, Piotr Nowakowski

We examine properties of achievement sets of series in $\mathbb{R}^2$. We show several examples of unusual sets of subsums on the plane. We prove that we can obtain any set of P-sums as a cut of an achievement set in $\mathbb{R}^2.$ We introduce a notion of the spectre of a set in an Abelian group, which generalizes the notion of the center of distances. We

Lucas Benoit--Maréchal, Marco Salvalaglio

The Swift-Hohenberg (SH) and Phase-Field Crystal (PFC) models are minimal yet powerful approaches for studying phenomena such as pattern formation, collective order, and defects via smooth order parameters. They are based on a free-energy functional that inherently includes elasticity effects. This study addresses how gradient elasticity (GE), a theory that

Maxwell X. Cai, Kin Long Kelvin Lee

In physics, density $\rho(\cdot)$ is a fundamentally important scalar function to model, since it describes a scalar field or a probability density function that governs a physical process. Modeling $\rho(\cdot)$ typically scales poorly with parameter space, however, and quickly becomes prohibitively difficult and computationally expensive. One promising ave

Erica Brondolin, Juan Miguel Carceller, Wouter Deconinck, Wenxing Fang

Detector studies for future experiments rely on advanced software tools to estimate performance and optimize their design and technology choices. The Key4hep project provides a flexible turnkey solution for the full experiment life-cycle based on established community tools such as ROOT, Geant4, DD4hep, Gaudi, podio and spack. Members of the CEPC, CLIC, EIC,

Andre Sailer, Benedikt Hegner, Clement Helsens, Erica Brondolin

The Key4hep project aims to provide a turnkey software solution for the full experiment lifecycle, based on established community tools. Several future collider communities (CEPC, CLIC, EIC, FCC, and ILC) have joined to develop and adapt their workflows to use the common data model EDM4hep and common framework. Besides sharing of existing experiment workflow

Thomas Robinson, Niek Tax, Richard Mudd, Ido Guy

Active learning can improve the efficiency of training prediction models by identifying the most informative new labels to acquire. However, non-response to label requests can impact active learning's effectiveness in real-world contexts. We conceptualise this degradation by considering the type of non-response present in the data, demonstrating that biased

Scott Armstrong, Raghavendra Venkatraman

We prove optimal convergence rates for eigenvalues and eigenvectors of the graph Laplacian on Poisson point clouds. Our results are valid down to the critical percolation threshold, yielding error estimates for relatively sparse graphs.

Guillermo Perna, Esteban Calzetta

A quantum measurement involves energy exchanges between the system to be measured and the measuring apparatus. Some of them involve energy losses, for example because energy is dissipated into the environment or is spent in recording the measurement outcome. Moreover, these processes take time. For this reason, these exchanges must be taken into account in t

Mario Fuest, Shahin Heydari

For the gang territoriality model \begin{align*} \begin{cases} u_t = D_u \Delta u + \chi_u \nabla \cdot (u \nabla w), \\ v_t = D_v \Delta v + \chi_v \nabla \cdot (v \nabla z), \\ w_t = -w + \frac{v}{1+v}, \\ z_t = -z + \frac{u}{1+u}, \end{cases} \end{align*} where $u$ and $v$ denote the densities of two rivaling gangs which spray graffiti (with densities $z$

Fabio Ornati, Gianfranco Di Domenico, Paolo Panicucci, Francesco Topputo

Air-bearing platforms for simulating the rotational dynamics of satellites require highly precise ground truth systems. Unfortunately, commercial motion capture systems used for this scope are complex and expensive. This paper shows a novel and versatile method to compute the attitude of rotational air-bearing platforms using a monocular camera and sets of f

Laura Cossu

As highlighted in a series of recent papers by Tringali and the author, fundamental aspects of the classical theory of factorization can be significantly generalized by blending the languages of monoids and preorders. Specifically, the definition of a suitable preorder on a monoid allows for the exploration of decompositions of its elements into (more or les

Sebastian O. Jordan, Qiongxiu Li, Richard Heusdens

Privacy-preserving distributed processing has received considerable attention recently. The main purpose of these algorithms is to solve certain signal processing tasks over a network in a decentralised fashion without revealing private/secret data to the outside world. Because of the iterative nature of these distributed algorithms, computationally complex

Tanya Akumu, Celia Cintas, Girmaw Abebe Tadesse, Adebayo Oshingbesan

The representations of the activation space of deep neural networks (DNNs) are widely utilized for tasks like natural language processing, anomaly detection and speech recognition. Due to the diverse nature of these tasks and the large size of DNNs, an efficient and task-independent representation of activations becomes crucial. Empirical p-values have been

Varpu Ahlberg, Juri Poutanen, Tuomo Salmi

The hotspot emission of accreting millisecond pulsars (AMPs) undergoes scattering in the accretion flow between the disk inner radius and the neutron star surface. The scattering optical depth of the flow depends on the photon emission angle, which is a function of the pulse phase, and reaches its maximum when the hotspot is closest to the observer. At suffi

László Sipos, Kolos Csaba Ágoston, Péter Biró, Sándor Bozóki

Standard methods, standard test conditions and the use of good sensory practices are key elements of sensory testing. However, while compliance assessment by trained and expert assessors is well developed, few information is available on testing consumer consistency. Therefore, we aim to answer the following research questions: What type of metrics can be us

Subhajit Sahu

Community detection is the problem of identifying natural divisions in networks. Efficient parallel algorithms for this purpose are crucial in various applications, particularly as datasets grow to substantial scales. This technical report presents an optimized parallel implementation of the Label Propagation Algorithm (LPA), a high speed community detection

Graziâni Candiotto, Fernanda R. Silva, Deyse G. Costa, Rodrigo B. Capaz

Linear carbon chains (LCCs) are the ultimate 1D molecular system and they show unique mechanical, optical and electronic properties that can be tuned by altering the number of carbon atoms, strain, encapsulation, and other external parameters. In this work, we probe the effects of quantum anharmonicity, strain and finite size on the structural and vibrationa

Sam Staton, Christina Vasilakopoulou

The Sixth International Conference on Applied Category Theory took place at the University of Maryland, 31 July -- 4 August 2023. This conference follows the previous meetings at Leiden (2018), Oxford (2019), MIT (2020, fully online), Cambridge (2021) and Glasgow (2022). The conference comprised contributed talks, a poster session, an industry showcase sessi

Tomas T. Osterholt, Pieter M. Gunnink, Rembert A. Duine

Due to their robustness, the implementation of geometric phases provides a reliable and controllable way to manipulate the phase of a spin wave, thereby paving the way towards functional magnonics-based data processing devices. Moreover, geometric phases in spin waves are interesting from a fundamental perspective as they contain information about spin wave

Juan Luis Gonzalez Bello, Minh-Quan Viet Bui, Munchurl Kim

Recent advances in neural rendering have shown that, albeit slow, implicit compact models can learn a scene's geometries and view-dependent appearances from multiple views. To maintain such a small memory footprint but achieve faster inference times, recent works have adopted `sampler' networks that adaptively sample a small subset of points along each ray i

Nicolas Garcia Trillos, Bodhisattva Sen

In the standard formulation of the denoising problem, one is given a probabilistic model relating a latent variable $\Theta \in \Omega \subset \mathbb{R}^m \; (m\ge 1)$ and an observation $Z \in \mathbb{R}^d$ according to: $Z \mid \Theta \sim p(\cdot\mid \Theta)$ and $\Theta \sim G^*$, and the goal is to construct a map to recover the latent variable from th

Yanchi Li, Wenyin Gong, Tingyu Zhang, Fei Ming

Evolutionary multitasking (EMT) has emerged as a popular topic of evolutionary computation over the past decade. It aims to concurrently address multiple optimization tasks within limited computing resources, leveraging inter-task knowledge transfer techniques. Despite the abundance of multitask evolutionary algorithms (MTEAs) proposed for multitask optimiza

Hayet Dahmri, Salim Bouamama

Minimum connected dominating set problem is an NP-hard combinatorial optimization problem in graph theory. Finding connected dominating set is of high interest in various domains such as wireless sensor networks, optical networks, and systems biology. Its weighted variant named minimum weight connected dominating set is also useful in such applications. In t

Santiago Toro Oquendo

This article presents a novel approach to construct a model category structure designed to model the homotopy theory of spaces equipped with an action by the group $C_2$, where morphisms are considered to be isovariant. Our methodology centers on simplicial techniques. We replace the conventional simplex category $\Delta$ with a modified category $C_2 \Delta

Shrishti Saha Shetu, Soumitro Chakrabarty, Oliver Thiergart, Edwin Mabande

This paper introduces an innovative method for reducing the computational complexity of deep neural networks in real-time speech enhancement on resource-constrained devices. The proposed approach utilizes a two-stage processing framework, employing channelwise feature reorientation to reduce the computational load of convolutional operations. By combining th

F. Febres Cordero, G. Figueiredo, M. Kraus, B. Page

We compute the two-loop master integrals for leading-color QCD scattering amplitudes including a closed light-quark loop in $t\bar{t}H$ production at hadron colliders. Exploiting numerical evaluations in modular arithmetic, we construct a basis of master integrals satisfying a system of differential equations in $\epsilon$-factorized form. We present the ana

Raphael Fortulan, Noushin Raeisi Kheirabadi, Panagiotis Mougkogiannis, Alessandro Chiolerio

Liquid computers use incompressible fluids for computational processes. Here we present experimental laboratory prototypes of liquid computers using colloids composed of zinc oxide (ZnO) nanoparticles and microspheres containing thermal proteins (proteinoids). The choice of proteinoids is based on their distinctive neuron-like electrical behaviour and their

Sujan Pal

The notion of abundance of certain type of configuration in certain large sets was first proved by Furstenberg and Glazner in 1998. After that many author investigate abundance of different types of configurations in different types of large sets. Hindman, Hosseini, Strauss and Tootkaboni recently introduced another notion of large sets called $CR$ sets. The

Amirhossein Habibian, Amir Ghodrati, Noor Fathima, Guillaume Sautiere

This work aims to improve the efficiency of text-to-image diffusion models. While diffusion models use computationally expensive UNet-based denoising operations in every generation step, we identify that not all operations are equally relevant for the final output quality. In particular, we observe that UNet layers operating on high-res feature maps are rela

Aravindkumaran S, D. Saraswady

Cognitive Radio Network (CRN) provides effective capabilities for resource allocation with the valuable spectrum resources in the network. It provides the effective allocation of resources to the unlicensed users or Secondary Users (SUs) to access the spectrum those are unused by the licensed users or Primary Users (Pus). This paper develops an Optimal Relay

Margarita Castaneda-Salazar, Margarida Mendes Lopes, Alexis Zamora

Let X be a non singular projective surface. Given a semistable non isotrivial fibration f over a smooth rational curve with general fiber non hyperelliptic of genus g bigger than 3, we show that if the number s of singular fibers is 5, then the genus is less or equal to 11, thus improving the previously known bound (g lesser or equal to 17). Furthermore we s

Jacek Kubica, Piotr Zgliczyński, Piotr Kalita

We present a method for the complete analysis of the dynamics of dissipative Partial Differential Equations (PDEs) undergoing a pitchfork bifurcation. We apply our technique to the Kuramoto--Sivashinsky PDE on the line to obtain a computer-assisted proof of the creation of two symmetric branches of non-symmetric fixed points and heteroclinic connections betw

Feng Ji, Xingchao Jian, Wee Peng Tay

Graphons are limit objects of sequences of graphs and are used to analyze the behavior of large graphs. Recently, graphon signal processing has been developed to study signal processing on large graphs. A major limitation of this approach is that any sparse sequence of graphs inevitably converges to the zero graphon, rendering the resulting signal processing

Mikko Salo

This work gives an expository account of certain applications of microlocal analysis in three geometric inverse problems. We will discuss the geodesic X-ray transform inverse problem, the Gelfand problem for the wave equation on a Riemannian manifold, and the Calder\'on problem for the Laplace equation on a Riemannian manifold.