October 2023 arXiv papers — page 90

Marcele O. K. Mendonca, Flor G. Ortiz-Gomez, Jorge Querol, Eva Lagunas

Satellite communications, essential for modern connectivity, extend access to maritime, aeronautical, and remote areas where terrestrial networks are unfeasible. Current GEO systems distribute power and bandwidth uniformly across beams using multi-beam footprints with fractional frequency reuse. However, recent research reveals the limitations of this approa

Loic De Langhe, Orphée De Clercq, Veronique Hoste

We introduce a novel and efficient method for Event Coreference Resolution (ECR) applied to a lower-resourced language domain. By framing ECR as a graph reconstruction task, we are able to combine deep semantic embeddings with structural coreference chain knowledge to create a parameter-efficient family of Graph Autoencoder models (GAE). Our method significa

Chao Lou, Kewei Tu

Translation-based AMR parsers have recently gained popularity due to their simplicity and effectiveness. They predict linearized graphs as free texts, avoiding explicit structure modeling. However, this simplicity neglects structural locality in AMR graphs and introduces unnecessary tokens to represent coreferences. In this paper, we introduce new target for

Saraswathi Kalyani Subramanian, Sridharan Rengaswamy

Adaptive Optics (AO) systems have become integral for ground-based astronomy. Based on the scientific case, there are various flavours of AO systems. Measuring the turbulence strength profile ($C_N^2(h)$) and other site characteristics is essential before selecting a site or implementing certain types of AO systems. We used an iterative deconvolution procedu

Julia Hatamyar, Noemi Kreif, Rudi Rocha, Martin Huber

We combine two recently proposed nonparametric difference-in-differences methods, extending them to enable the examination of treatment effect heterogeneity in the staggered adoption setting using machine learning. The proposed method, machine learning difference-in-differences (MLDID), allows for estimation of time-varying conditional average treatment effe

Florentine Fleißner

The mathematical theory of a novel variational approximation scheme for general second and fourth order partial differential equations \begin{equation}\label{eq: A} \partial_t u - \nabla\cdot\Big(u\nabla\frac{\delta\phi}{\delta u}(u)\Big|\nabla\frac{\delta\phi}{\delta u}(u)\Big|^{q-2}\Big) \ = \ 0, \quad\quad u\geq0, \end{equation} $q\in(1, +\infty)$, is dev

Yanming Kang, Giang Tran, Hans De Sterck

While Transformer networks benefit from a global receptive field, their quadratic cost relative to sequence length restricts their application to long sequences and high-resolution inputs. We introduce Fast Multipole Attention (FMA), a divide-and-conquer mechanism for self-attention inspired by the Fast Multipole Method from n-body physics. FMA reduces the t

Shuhan Zhong, Sizhe Song, Weipeng Zhuo, Guanyao Li

Time series data, including univariate and multivariate ones, are characterized by unique composition and complex multi-scale temporal variations. They often require special consideration of decomposition and multi-scale modeling to analyze. Existing deep learning methods on this best fit to univariate time series only, and have not sufficiently considered s

Yuval Pinter, Michael Elhadad

We call into question the recently popularized method of direct model editing as a means of correcting factual errors in LLM generations. We contrast model editing with three similar but distinct approaches that pursue better defined objectives: (1) retrieval-based architectures, which decouple factual memory from inference and linguistic capabilities embodi

Malte Janßen, Tobias Pfandzelter, Minghe Wang, David Bermbach

Over the last years, Unmanned Aerial Vehicles (UAVs) have seen significant advancements in sensor capabilities and computational abilities, allowing for efficient autonomous navigation and visual tracking applications. However, the demand for computationally complex tasks has increased faster than advances in battery technology. This opens up possibilities f

Gustav Eriksson, Vidar Stiernström

A gradient-based method for shape optimization problems constrained by the acoustic wave equation is presented. The method makes use of high-order accurate finite differences with summation-by-parts properties on multiblock curvilinear grids to discretize in space. Representing the design domain through a coordinate mapping from a reference domain, the desig

Dongming Mei

The direct detection of MeV-scale dark matter (DM) particles hinges on achieving an exceptionally low energy detection threshold. Germanium (Ge) detectors, meticulously tailored with precise impurity compositions, hold the potential to enhance sensitivity to energy levels below the sub-electronvolt (sub-eV) range. This study explores the behavior of residual

Dingyao Yu, Kaitao Song, Peiling Lu, Tianyu He

AI-empowered music processing is a diverse field that encompasses dozens of tasks, ranging from generation tasks (e.g., timbre synthesis) to comprehension tasks (e.g., music classification). For developers and amateurs, it is very difficult to grasp all of these task to satisfy their requirements in music processing, especially considering the huge differenc

Debasish Borah, Satyabrata Mahapatra, Partha Kumar Paul, Narendra Sahu

We study a scotogenic extension of the minimal gauged $L_{\mu}-L_{\tau}$ model, including three right-handed singlet fermions and a scalar doublet all odd under an in-built $Z_2$ symmetry to explain the anomalous magnetic moments of the muon, CDF-II W-mass anomaly, and the 95 GeV excess reported by the CMS collaboration. While the minimal model can successfu

Soochan Lee, Jaehyeon Son, Gunhee Kim

In this work, we aim to establish a strong connection between two significant bodies of machine learning research: continual learning and sequence modeling. That is, we propose to formulate continual learning as a sequence modeling problem, allowing advanced sequence models to be utilized for continual learning. Under this formulation, the continual learning

Yumeng Zeng, Bozhen Zhou, Shu Chen

The fidelity is widely used to detect quantum phase transitions, which is characterized by either a sharp change of fidelity or the divergence of fidelity susceptibility in the thermodynamical limit when the phase-driving parameter is across the transition point. In this work, we unveil that the occurrence of exact zeros of fidelity in finite-size systems ca

Andrés Tello, Victoria Degeler, Alexander Lazovik

Today, there are standard and well established procedures within the Human Activity Recognition (HAR) pipeline. However, some of these conventional approaches lead to accuracy overestimation. In particular, sliding windows for data segmentation followed by standard random k-fold cross validation, produce biased results. An analysis of previous literature and

N. N. Kovaleva

Magnetic properties of Mott-Hubbard insulators are determined by superexchange interactions mediated by the high-spin (HS) and low-spin (LS) intersite d-d charge excitations, which can be associated with the HS- and LS-Hubbard subbands in optical experiments. To explore the Mott-Hubbard physics in orthorhombic LaTiO_3 crystal exhibiting the G-type antiferrom

B. J. Alexander, J. J. Bollinger, M. S. Tame

Projected squeezed (PS) states are multipartite entangled states generated by unitary spin squeezing, followed by a collective quantum measurement and post-selection. They can lead to an appreciable decrease in the state preparation time of the maximally entangled N-qubit Greenberger-Horne-Zeilinger (GHZ) state when compared to deterministic preparation by u

Bojan Žunkovič, Antonio Zegarra

We investigate the dynamical properties of the XY spin 1/2 chain with infinite-range transverse interactions and find a dynamical phase transition with a chaotic dynamical phase. In the latter, we find non-vanishing finite-time Lyapunov exponents and intermittent behavior signaled by fast and slow entropy growth periods. Further, we study the XY chain with a

Huan Cao, Simon Morelli, Lee A. Rozema, Chao Zhang

Standard procedures for entanglement detection assume that experimenters can exactly implement specific quantum measurements. Here, we depart from such idealizations and investigate, in both theory and experiment, the detection of genuine multipartite entanglement when measurements are subject to small imperfections. For arbitrary qubits number $n$, we const

Mohamad Abed El Rahman Hammoud, Edriss S. Titi, Ibrahim Hoteit, Omar Knio

Efficient downscaling of large ensembles of coarse-scale information is crucial in several applications, such as oceanic and atmospheric modeling. The determining form map is a theoretical lifting function from the low-resolution solution trajectories of a dissipative dynamical system to their corresponding fine-scale counterparts. Recently, a physics-inform

Alexander Medvedev, Anton V. Proskurnikov, Zhanybai T. Zhusubaliyev

In the Impulsive Goodwin's oscillator (IGO), a continuous positive linear time-invariant (LTI) plant is controlled by an amplitude- and frequency-modulated feedback into an oscillating solution. Self-sustained oscillations in the IGO model have been extensively used to portray periodic rhythms in endocrine systems, whereas the potential of the concept as a c

Gang Chen, Laurentiu Rodina, Congkao Wen

Recently it has been shown that Bern-Carrasco-Johansson (BCJ) numerators of colour-kinematic duality for tree-level scattering amplitudes in Yang-Mills theory (coupled with scalars) can be determined using a quasi-shuffle Hopf algebra. In this paper we consider the same theory, but with higher-derivative corrections of the forms $\alpha' F^3$ and $\alpha'^2

T. Nosek

T2K is a neutrino oscillation experiment with a 295 km long baseline between the far detector, Super-Kamiokande, and a suite of near detectors to study $\nu_\mu/\bar{\nu}_\mu$ disappearance and $\nu_e/\bar{\nu}_e$ appearance in a $\nu_\mu/\bar{\nu}_\mu$ neutrino beam produced at J-PARC. The experiment has excluded CP conservation in the three-neutrino oscill

A. Belayadi, N. A. Hadadi, P. Vasilopoulos, A. Abbout

Kelvin probe force microscopy (KPFM) has been employed to probe charge carriers in a graphene/hexagonal boron nitride (hBN) heterostructure [Nano Lett, 21, 5013 (2021)]. We propose an approach for operating valley filtering based on the KPFM-induced potential $U_0$ instead of using external or induced pseudo-magnetic fields in strained graphene. Employing a

Óscar Jiménez Rama, Fernando Moreno-Pino, David Ramírez, Pablo M. Olmos

The best encoding is the one that is interpretable in nature. In this work, we introduce a novel model that incorporates an interpretable bottleneck-termed the Filter Bank (FB)-at the outset of a Variational Autoencoder (VAE). This arrangement compels the VAE to attend on the most informative segments of the input signal, fostering the learning of a novel en

Spencer Wadsworth, Jarad Niemi, Nick Reich

Collaboration among multiple teams has played a major role in probabilistic forecasting events of influenza outbreaks, the COVID-19 pandemic, other disease outbreaks, and in many other fields. When collecting forecasts from individual teams, ensuring that each team's model represents forecast uncertainty according to the same format allows for direct compari

Timothee Mickus, Elaine Zosa, Denis Paperno

Grounding has been argued to be a crucial component towards the development of more complete and truly semantically competent artificial intelligence systems. Literature has divided into two camps: While some argue that grounding allows for qualitatively different generalizations, others believe it can be compensated by mono-modal data quantity. Limited empi

J. A. Worden, J. Biener, C. Hin

Bicontinuous nanoporous materials possess remarkable mechanical properties, such as higher specific strength and lower specific modulus compared to fully dense materials combined with low densities and high specific surface areas. Unfortunately, their practical application is hindered by inherent macroscopic brittleness, mainly due to cascading ligament fail

Felix Hoops, Alexander Mühle, Florian Matthes, Christoph Meinel

A core part of the new identity management paradigm of Self-Sovereign Identity (SSI) is the W3C Decentralized Identifiers (DIDs) standard. The diversity of interoperable implementations encouraged by the paradigm is key for a less centralized future, and it is made possible by the concept of DIDs. However, this leads to a kind of dilemma of choices, where pr

Pascal Dreher, David Janoschka, Harald Giessen, Ralf Schützhold

Quantum path interferences occur whenever multiple equivalent and coherent transitions result in a common final state. Such interferences strongly modify the probability of a particle to be found in that final state, a key concept of quantum coherent control. When multiple nonlinear and energy-degenerate transitions occur in a system, the multitude of possib

Sascha Eisenträger, Lars Radtke, Wadhah Garhuom, Stefan Löhnert

The application of immersed boundary methods in static analyses is often impeded by poorly cut elements (small cut elements problem), leading to ill-conditioned linear systems of equations and stability problems. While these concerns may not be paramount in explicit dynamics, a substantial reduction in the critical time step size based on the smallest volume

Zachary Jones, Mohammad Al-Saad, Ankush Vavishta

QWOP is a browser-based, 2-dimensional flash game in which the player controls an Olympic sprinter competing in a simulated 100-meter race. The goal of the game is to advance the runner to the end of the 100-meter race as quickly as possible using the Q, W, O, and P keys, which control the muscles in the sprinters legs. Despite the game simple controls and s

Jingxu Bai, Yuechun Jiao, Rong Song, Georg Raithel

Long-range $(n+2)D_{5/2} \, nF_J$ Rydberg macro-dimers are observed in an ultracold cesium Rydberg gas for $39\leq n\leq48$. Strong dipolar "flip" ($\langle D_{5/2} F_{5/2} \vert \hat{V}_{dd} \vert F_{5/2} D_{5/2} \rangle$, $\langle D_{5/2} F_{7/2} \vert \hat{V}_{dd} \vert F_{7/2} D_{5/2} \rangle$) and "cross" ($\langle D_{5/2} F_{7/2} \vert \hat{V}_{dd} \ve

L. Salmon, V. Schánilec, J. Coraux, B. Canals

Achieving thermal equilibrium in two-dimensional lattices of interacting nanomagnets has been a key issue on the route to study exotic phases in artificial frustrated magnets. We revisit this issue in artificial one-dimensional kagom\'e spin chains. Imaging arrested micro-states generated by a field demagnetization protocol and analyzing their pairwise spin

Nicolas Renaud, Pablo Rodríguez-Sánchez, Johan Hidding, P. Chris Broekema

The computational requirements of future large scale radio telescopes are expected to scale well beyond the capabilities of conventional digital resources. Current and planned telescopes are generally limited in their scientific potential by their ability to efficiently process the vast volumes of generated data. To mitigate this problem, we investigate the

Björn Engelmann, Timo Breuer, Philipp Schaer

Considering the multimodal signals of search items is beneficial for retrieval effectiveness. Especially in web table retrieval (WTR) experiments, accounting for multimodal properties of tables boosts effectiveness. However, it still remains an open question how the single modalities affect user experience in particular. Previous work analyzed WTR performanc

Tomasz Brzeziński

The affine space of traceless complex matrices in which the sum of all elements in every row and every column is equal to one is presented as an example of an affine space with a Lie bracket or a Lie affgebra.

Joao Magueijo

In theories where physics depends on a global foliation of space-time, a black hole's horizon is surrounded by an "eternity skin": a pile-up of space-like leaves that in the far-out region cover all times from the start of collapse to future eternity. Any future foliation-dependent change in the laws of physics would be enacted in this region and affect the

Yongshuai Gao, Shuai Li, Peiye Zhong

This paper is concerned with the existence and mass concentration behavior of minimizers for rotating Bose-Einstein condensations (BECs) with attractive interactions in a bounded domain $\mathcal{D}\subset \mathbb{R}^2$. It is shown that, there exists a finite constant $a^*$, denoting mainly the critical number of bosons in the system, such that the least en

Abdelhakim Amer, Olaya Álvarez-Tuñón, Halil Ibrahim Ugurlu, Jonas le Fevre Sejersen

Underwater robotic surveys can be costly due to the complex working environment and the need for various sensor modalities. While underwater simulators are essential, many existing simulators lack sufficient rendering quality, restricting their ability to transfer algorithms from simulation to real-world applications. To address this limitation, we introduce

Andreas Björklund, Petteri Kaski

Strassen's asymptotic rank conjecture [Progr. Math. 120 (1994)] claims a strong submultiplicative upper bound on the rank of a three-tensor obtained as an iterated Kronecker product of a constant-size base tensor. The conjecture, if true, most notably would put square matrix multiplication in quadratic time. We note here that some more-or-less unexpected alg

Hongzhen Chen, Lingna Wang, Haidong Yuan

How well can multiple incompatible observables be implemented by a single measurement? This is a fundamental problem in quantum mechanics with wide implications for the performance optimization of numerous tasks in quantum information science. While existing studies have been mostly focusing on the approximation of two observables with a single measurement,

Onur Salan, Ferhat Bayar, Hacı Ilhan, Erdogan Aydin

The reconfigurable intelligent surface (RIS) is considered a crucial technology for the future of wireless communication. Recently, there has been significant interest in combining RIS with spatial modulation (SM) or space shift keying (SSK) to achieve a balance between spectral and energy efficiency. In this paper, we have investigated the use of deep learn

Dmitry Nikolaev, Sebastian Padó

The question of what kinds of linguistic information are encoded in different layers of Transformer-based language models is of considerable interest for the NLP community. Existing work, however, has overwhelmingly focused on word-level representations and encoder-only language models with the masked-token training objective. In this paper, we present exper

Hiroshi Ando, Michal Doucha

We revisit a well-known "surjectivity onto quotient" type lemma of Kirchberg on the central sequence algebra of a separable unital ${\rm C}^*$-algebra, and use it to prove a "surjectivity onto quotient" result on approximately inner automorphisms of a separable unital ${\rm C}^*$-algebra of stable rank one, which we can partially upgrade also to the non-sepa

Martin Karafiát, Karel Veselý, Igor Szöke, Ladislav Mošner

This paper describes the joint effort of Brno University of Technology (BUT), AGH University of Krakow and University of Buenos Aires on the development of Automatic Speech Recognition systems for the CHiME-7 Challenge. We train and evaluate various end-to-end models with several toolkits. We heavily relied on Guided Source Separation (GSS) to convert multi-

Petteri Harjulehto, Peter Hästö, Andrea Torricelli

We study minimizers of non-autonomous energies with minimal growth and coercivity assumptions on the energy. We show that the minimizer is nevertheless the solution of the relevant Euler--Lagrange equation or inequality. The main tool is an extension result for convex $C^1$-energies.

Athanasios Bakopoulos, Christos Charmousis, Panagiota Kanti, Nicolas Lecoeur

We present explicit black holes endowed with primary scalar hair within the shift-symmetric subclass of Beyond Horndeski theories. These solutions depend, in addition to the conventional mass parameter, on a second free parameter encoding primary scalar hair. The properties and characteristics of the solutions at hand are analyzed with varying scalar charge.

Dmitri B. Horoshko, Mikhail I. Kolobov

We propose a device consisting of $m$ Mach-Zehnder interferometers and realizing sorting of first $2^m$ temporal Hermite-Gauss modes of light passing though it by adjusting the accumulated temporal Gouy phase acquired by every mode. This mode-order-dependent phase shift is achieved by a fractional Fourier transform realized by a time lens in one of interfero

Adrian Kochsiek, Rainer Gemulla

Semi-inductive link prediction (LP) in knowledge graphs (KG) is the task of predicting facts for new, previously unseen entities based on context information. Although new entities can be integrated by retraining the model from scratch in principle, such an approach is infeasible for large-scale KGs, where retraining is expensive and new entities may arise f

Ferdinand Verhulst

The evolution of a rotating axisymmetric galaxy from an asymmetric state to a state of mirror symmetry with respect to the galactic plane has as basic result that in the asymmetric initial state the perpendicular $z$ normal mode is unstable for the $1:1$ and $1:2$ resonances. Dynamically this results in a transfer of mass and momenta towards the galactic pla

Ling Chen, Yiyi Peng, Kai Qian, Hongyu Shi

Predicting user click behavior and making relevant recommendations based on the user's historical click behavior are critical to simplifying operations and improving user experience. Modeling UI elements is essential to user click behavior prediction, while the complexity and variety of the UI make it difficult to adequately capture the information of differ

Nicolas Chopin, Francesca R. Crucinio, Anna Korba

This paper explores the connections between tempering (for Sequential Monte Carlo; SMC) and entropic mirror descent to sample from a target probability distribution whose unnormalized density is known. We establish that tempering SMC corresponds to entropic mirror descent applied to the reverse Kullback-Leibler (KL) divergence and obtain convergence rates fo

Nick Fischer

How fast can you test whether a constellation of stars appears in the night sky? This question can be modeled as the computational problem of testing whether a set of points $P$ can be moved into (or close to) another set $Q$ under some prescribed group of transformations. Consider, as a simple representative, the following problem: Given two sets of at most

Rainer Schoedel, Steve Longmore, Jonny Henshaw, Adam Ginsburg

The inner hundred parsecs of the Milky Way hosts the nearest supermassive black hole, largest reservoir of dense gas, greatest stellar density, hundreds of massive main and post main sequence stars, and the highest volume density of supernovae in the Galaxy. As the nearest environment in which it is possible to simultaneously observe many of the extreme proc

Jacob Tyge Goker Swambo

The broad topic of this thesis is the design and analysis of Bitcoin custody systems. Both the technology and threat landscape are evolving constantly. Therefore, custody systems, defence strategies, and risk models should be adaptive too. We introduce Bitcoin custody by describing the different types, design principles, phases and functions of custody syste

Manisha Das, Deep Gupta, Petia Radeva, Ashwini M Bakde

Medical image fusion integrates the complementary diagnostic information of the source image modalities for improved visualization and analysis of underlying anomalies. Recently, deep learning-based models have excelled the conventional fusion methods by executing feature extraction, feature selection, and feature fusion tasks, simultaneously. However, most

Hampus Renberg Nilsson, Daryoush Shiri, Robert Rehammar, Anita Fadavi Roudsari

We investigate the required peripheral circuits to enable ideal performance for a high-gain travelling-wave parametric amplifier (TWPA) based on three-wave mixing (3WM). By embedding the TWPA in a network of superconducting diplexers, hybrid couplers and impedance matching networks, the amplifier can deliver a high stable gain with near-quantum-limited noise

Gennaro Auricchio, Qun Ma, Jie Zhang

In this paper, we explore the Mechanism Design aspects of the Maximum Vertex-weighted $b$-Matching (MVbM) problem on bipartite graphs $(A\cup T, E)$. The set $A$ comprises agents, while $T$ represents tasks. The set $E$ is the private information of either agents or tasks. In this framework, we investigate three mechanisms - $\MB$, $\MD$, and $\MG$ - that, g

Satyam Guragain, Ravi Srivastava

This paper explores interlacing inequalities in the Laplacian spectrum of signed cycles and investigates interlacing relationship between the spectrum of the net-Laplacian of a signed graph and its subgraph formed by removing a vertex together with its incident edges. Additionally, an inequality is derived between the net-Laplacian spectrum of a complete co-

Oliver Eberle, Ilias Chalkidis, Laura Cabello, Stephanie Brandl

Contrastive explanations, where one decision is explained in contrast to another, are supposed to be closer to how humans explain a decision than non-contrastive explanations, where the decision is not necessarily referenced to an alternative. This claim has never been empirically validated. We analyze four English text-classification datasets (SST2, DynaSen

Cornel Marius Murea, Dan Tiba

We indicate a new approach to the optimization of the clamped plates with holes. It is based on the use of Hamiltonian systems and the penalization of the performance index. The alternative technique employing the penalization of the state system, cannot be applied in this case due to the (two) Dirichlet boundary conditions. We also include numerical tests e

Naif Hadadi, Adel Belayadi, Ahmed AlRabiah, Ousmane Ly

The extremely high pseudo-magnetic field emerging in strained graphene suggests that an oscillating nano-deformation will induce a very high current even without electric bias. In this paper, we demonstrate the sub-terahertz (THz) dynamics of a valley-current and the corresponding charge pumping with a periodically excited nano-bubble. We discuss the amplitu

Ferdinand Claude, Maxime J. Jacquet, Michiel Wouters, Elisabeth Giacobino

Second-order phase transitions are governed by spontaneous symmetry breaking, which yield collective excitations with a gapless spectrum called Nambu-Goldstone (NG) modes. While NG modes in conservative systems are propagating excitations, non-equilibrium phase transitions have been predicted to feature a diffusive NG mode. We present the first experimental

MEG II Collaboration, K. Afanaciev, A. M. Baldini, S. Ban

The MEG II experiment, located at the Paul Scherrer Institut (PSI) in Switzerland, is the successor to the MEG experiment, which completed data taking in 2013. MEG II started fully operational data taking in 2021, with the goal of improving the sensitivity of the mu+ -> e+ gamma decay down to 6e-14 almost an order of magnitude better than the current limit.

Yangheng Zhao, Zhen Xiang, Sheng Yin, Xianghe Pang

Recently, multi-agent collaborative (MAC) perception has been proposed and outperformed the traditional single-agent perception in many applications, such as autonomous driving. However, MAC perception is more vulnerable to adversarial attacks than single-agent perception due to the information exchange. The attacker can easily degrade the performance of a v

LuÍs E. E. De Araujo, Zhifan Zhou, Matt Dimario, B. E. Anderson

We present a study of homodyne measurements of two-mode, vacuum-seeded, quadrature-squeezed light generated by four-wave mixing in warm rubidium vapor. Our results reveal that the vacuum squeezing can extend down to measurement frequencies of less than 1 Hz, and the squeezing bandwidth, similar to the seeded intensity-difference squeezing measured in this sy

Florian Hornung, Ulrich Pfister, Stephanie Bauer, Dee Rocking Cyrlyson's

The integration of on-demand quantum emitters into photonic integrated circuits (PICs) has drawn much of attention in recent years, as it promises a scalable implementation of quantum information schemes. A central property for several applications is the indistinguishability of the emitted photons. In this regard, GaAs quantum dots (QDs) obtained by droplet

Gavin A. L. Coleman, Richard P. Nelson, Amaury H. M. J. Triaud, Matthew R. Standing

The recent discovery of multiple planets in the circumbinary system TOI-1338/BEBOP-1 raises questions about how such a system formed. The formation of the system was briefly explored in the discovery paper, but only to answer the question do current pebble accretion models have the potential to explain the origin of the system? We use a global model of circu

Yen-Ju Chen, Nai-Chieh Huang, Ching-Pei Lee, Ping-Chun Hsieh

Various acceleration approaches for Policy Gradient (PG) have been analyzed within the realm of Reinforcement Learning (RL). However, the theoretical understanding of the widely used momentum-based acceleration method on PG remains largely open. In response to this gap, we adapt the celebrated Nesterov's accelerated gradient (NAG) method to policy optimizati

Payal Wankhede, Manisha Das, Deep Gupta, Petia Radeva

Medical image fusion combines the complementary information of multimodal medical images to assist medical professionals in the clinical diagnosis of patients' disorders and provide guidance during preoperative and intra-operative procedures. Deep learning (DL) models have achieved end-to-end image fusion with highly robust and accurate fusion performance. H

Giorgos Polychronis, Spyros Lalis

An ever increasing number of applications can employ aerial unmanned vehicles, or so-called drones, to perform different sensing and possibly also actuation tasks from the air. In some cases, the data that is captured at a given point has to be processed before moving to the next one. Drones can exploit nearby edge servers to offload the computation instead

O. P. Solovtsova, V. I. Lashkevich, L. P. Kaptari

We investigate the radiative quantum electrodynamic (QED) corrections to the lepton ($L=e, ~\mu $ and $\tau$) anomalous magnetic moment due to the contributions of diagrams with insertions of the photon vacuum polarisation operator consisting solely of four closed lepton ($l=e, ~\mu $ and $\tau$) loops. Moreover, we focus on specific operators with two loops

Pierre Germain, Joonhyun La, Katherine Zhiyuan Zhang

The MMT equation was proposed by Majda, McLaughlin and Tabak as a model to study wave turbulence. We focus on the kinetic equation associated to this Hamiltonian system, which is believed to give a way to predict turbulent spectra. We clarify the formulation of the problem, and we develop the local well-posedness theory for this equation. Our analysis uncove

Jimin Wang, Ji-Feng Zhang

Differentially private distributed stochastic optimization has become a hot topic due to the urgent need of privacy protection in distributed stochastic optimization. In this paper, two-time scale stochastic approximation-type algorithms for differentially private distributed stochastic optimization with time-varying sample sizes are proposed using gradient-

Sebastian Egginger, Alona Sakhnenko, Jeanette Miriam Lorenz

Quantum kernel methods are a promising method in quantum machine learning thanks to the guarantees connected to them. Their accessibility for analytic considerations also opens up the possibility of prescreening datasets based on their potential for a quantum advantage. To do so, earlier works developed the geometric difference, which can be understood as a

Yue Cao, Tianlin Li, Xiaofeng Cao, Ivor Tsang

We introduce a novel approach to counter adversarial attacks, namely, image resampling. Image resampling transforms a discrete image into a new one, simulating the process of scene recapturing or rerendering as specified by a geometrical transformation. The underlying rationale behind our idea is that image resampling can alleviate the influence of adversari

Carlos Güemes-Palau, Miquel Ferriol Galmés, Albert Cabellos-Aparicio, Pere Barlet-Ros

Currently the state of the art network models are based or depend on Discrete Event Simulation (DES). While DES is highly accurate, it is also computationally costly and cumbersome to parallelize, making it unpractical to simulate high performance networks. Additionally, simulated scenarios fail to capture all of the complexities present in real network scen

Ioannis Nasios

This paper presents an application of artificial intelligence on mass spectrometry data for detecting habitability potential of ancient Mars. Although data was collected for planet Mars the same approach can be replicated for any terrestrial object of our solar system. Furthermore, proposed methodology can be adapted to any domain that uses mass spectrometry

James Weng, Niklas B. Thompson, Christopher Folmar, James D. Martin

To obtain the best resolution for any measurement there is an ever-present challenge to achieve maximal differentiation between signal and noise over as fine of sampling dimensions as possible. In diffraction science these issues are particularly pervasive when analyzing small crystals, systems with diffuse scattering, or other systems in which the signal of

Jiaxi Pu, Yanhao Wang, Yuchen Li, Xuan Zhou

Temporal bipartite graphs are widely used to denote time-evolving relationships between two disjoint sets of nodes, such as customer-product interactions in E-commerce and user-group memberships in social networks. Temporal butterflies, $(2,2)$-bicliques that occur within a short period and in a prescribed order, are essential in modeling the structural and

Nicolas Strangmann

The ALICE experiment at the LHC investigates the properties of the hot and dense nuclear matter created in heavy-ion collisions. By comparing the particle production in pp and p-Pb collisions, possible nuclear initial state effects can be isolated. Measurements of the $\omega$ meson $p_\text{T}$-spectra in pp and p-Pb collisions not only allow for a determin

Jae Hee Lee, Sergio Lanza, Stefan Wermter

In this paper, we review recent approaches for explaining concepts in neural networks. Concepts can act as a natural link between learning and reasoning: once the concepts are identified that a neural learning system uses, one can integrate those concepts with a reasoning system for inference or use a reasoning system to act upon them to improve or enhance t

Edoardo Gramigna, Riccardo Lasagni Manghi, Marco Zannoni, Paolo Tortora

Hera represents the European Space Agency's inaugural planetary defense space mission and plays a pivotal role in the Asteroid Impact and Deflection Assessment international collaboration with NASA DART mission that performed the first asteroid deflection experiment using the kinetic impactor techniques. With the primary objective of conducting a detailed po

Hui Jiang, Jianling Fu, Ming Xu, Yuxin Deng

Reachability analysis plays a central role in system design and verification. The reachability problem, denoted $\Diamond^J\,\Phi$, asks whether the system will meet the property $\Phi$ after some time in a given time interval $J$. Recently, it has been considered on a novel kind of real-time systems -- quantum continuous-time Markov chains (QCTMCs), and emb

Xiangyu Chen, Zheyuan Li, Yuandong Pu, Yihao Liu

Despite the significant progress made by deep models in various image restoration tasks, existing image restoration networks still face challenges in terms of task generality. An intuitive manifestation is that networks which excel in certain tasks often fail to deliver satisfactory results in others. To illustrate this point, we select five representative n

Spandan Senapati, Rahul Vaze

We consider the online convex optimization (OCO) problem with quadratic and linear switching cost in the limited information setting, where an online algorithm can choose its action using only gradient information about the previous objective function. For $L$-smooth and $\mu$-strongly convex objective functions, we propose an online multiple gradient descen

Emanuele Lucrezia, Laura Sacerdote, Cristina Zucca

We consider a Lindley process with Laplace distributed space increments. We obtain closed form recursive expressions for the density function of the position of the process and for its first exit time distribution from the domain $[0,h]$. We illustrate the results in terms of the parameters of the process. The work is completed by an open source version of t

Shanshan Xu, T. Y. S. S Santosh, Oana Ichim, Isabella Risini

In legal NLP, Case Outcome Classification (COC) must not only be accurate but also trustworthy and explainable. Existing work in explainable COC has been limited to annotations by a single expert. However, it is well-known that lawyers may disagree in their assessment of case facts. We hence collect a novel dataset RAVE: Rationale Variation in ECHR1, which i

Aviv Slobodkin, Omer Goldman, Avi Caciularu, Ido Dagan

Large language models (LLMs) have been shown to possess impressive capabilities, while also raising crucial concerns about the faithfulness of their responses. A primary issue arising in this context is the management of (un)answerable queries by LLMs, which often results in hallucinatory behavior due to overconfidence. In this paper, we explore the behavior

Ilias Diakonikolas, Daniel M. Kane, Yuxin Sun

We study the problem of learning mixtures of linear classifiers under Gaussian covariates. Given sample access to a mixture of $r$ distributions on $\mathbb{R}^n$ of the form $(\mathbf{x},y_{\ell})$, $\ell\in [r]$, where $\mathbf{x}\sim\mathcal{N}(0,\mathbf{I}_n)$ and $y_\ell=\mathrm{sign}(\langle\mathbf{v}_\ell,\mathbf{x}\rangle)$ for an unknown unit vector

Zahra Alijani, Vojtech Molek

Designing effective neural networks requires tuning architectural elements. This study integrates fractional calculus into neural networks by introducing fractional order derivatives (FDO) as tunable parameters in activation functions, allowing diverse activation functions by adjusting the FDO. We evaluate these fractional activation functions on various dat

V. Janaki, S. Madhan, T. C. Vijayaraghavan

In this paper we show derivations among logarithmic space bounded counting classes based on closure properties of $\#L$ that leads us to the result that $NL=C_=L\subseteq PL$.

Chao Liu, Dabin Zheng, Wei Lu, Xiaoqiang Wang

The study of the generalized Hamming weight of linear codes is a significant research topic in coding theory as it conveys the structural information of the codes and determines their performance in various applications. However, determining the generalized Hamming weights of linear codes, especially the weight hierarchy, is generally challenging. In this pa

Junais, P. M. Weilbacher, B. Epinat, S. Boissier

Giant low-surface brightness (GLSB) galaxies are an extreme class of objects with very faint and extended gas-rich disks. Malin 1 is the largest GLSB galaxy known to date, but its formation is still poorly understood. We use VLT/MUSE IFU spectroscopic observations of Malin 1 to reveal, for the first time, the presence of H$\alpha$ emission distributed across

Naomichi Nakajima

Information geometry of Markov chains has been studied using the dually flat structure of the space of transition probabilities. Although applications of this structure have been investigated, few attempts have examined its statistical meaning. In this paper, we construct a foundation for investigating the statistical meaning based on Amari's theory of posit

Yuqian Sun, Yuying Tang, Ze Gao, Zhijun Pan

This paper presents "AI Nushu," an emerging language system inspired by Nushu (women's scripts), the unique language created and used exclusively by ancient Chinese women who were thought to be illiterate under a patriarchal society. In this interactive installation, two artificial intelligence (AI) agents are trained in the Chinese dictionary and the Nushu

Aritra Das

In this paper, a theoretical calculation of thermal di-lepton production rate (DPR) is reported from a hot and dense, unbounded rotating quark gluon plasma in the presence of very strong uniform background magnetic field typically generated at heavy-ion collision experiments. In this extreme magnetic field, the quarks as well as anti-quarks are approximated