April 2023 arXiv papers — page 22

Xiaomei Li, Aaron D. Ratschow, Steffen Hardt, Hans-Jürgen Butt

Slide electrification - the spontaneous charge separation by sliding water drops - can lead to an electrostatic potential of 1 kV and change drop motion substantially. To find out, how slide electrification influences the contact angles of moving drops, we analyzed the dynamic contact angles of aqueous drops sliding down tilted plates with insulated surfaces

Robin Ferede, Guido C. H. E. de Croon, Christophe De Wagter, Dario Izzo

Developing optimal controllers for aggressive high-speed quadcopter flight poses significant challenges in robotics. Recent trends in the field involve utilizing neural network controllers trained through supervised or reinforcement learning. However, the sim-to-real transfer introduces a reality gap, requiring the use of robust inner loop controllers during

Felix Mann, Helen M. Chrzanowski, Felipe Gewers, Marlon Placke

Interfacing the different building blocks of a future large scale quantum network will demand efficient and noiseless frequency conversion of quantum light. Nitrogen-vacancy (NV) centers in diamond are a leading candidate to form the nodes of such a network. However, the performance of a suitable converter remains a bottleneck, with existing demonstrations s

Rodothea Myrsini Tsoupidi, Elena Troubitsyna, Panagiotis Papadimitratos

Embedded devices are increasingly present in our everyday life. They often process critical information, and hence, rely on cryptographic protocols to achieve security. However, embedded devices remain vulnerable to attackers seeking to hijack their operation and extract sensitive information by exploiting side channels and code reuse. Code-Reuse Attacks (CR

C. A. Lindley, M. R. Jones, T. J. Rogers, E. J. Cross

It has been demonstrated that acoustic-emission (AE), inspection of structures can offer advantages over other types of monitoring techniques in the detection of damage; namely, an increased sensitivity to damage, as well as an ability to localise its source. There are, however, numerous challenges associated with the analysis of AE data. One issue is the hi

Maxim Krivenkov, Maryam Sajedi, Dmitry Marchenko, Evangelos Golias

Phosphorene, a 2D allotrope of phosphorus, is technologically very appealing because of its semiconducting properties and narrow band gap. Further reduction of the phosphorene dimensionality may spawn exotic properties of its electronic structure, including lateral quantum confinement and topological edge states. Phosphorene atomic chains self-assembled on A

Nikola Zubić, Daniel Gehrig, Mathias Gehrig, Davide Scaramuzza

Today, state-of-the-art deep neural networks that process events first convert them into dense, grid-like input representations before using an off-the-shelf network. However, selecting the appropriate representation for the task traditionally requires training a neural network for each representation and selecting the best one based on the validation score,

Giovanni Bellettini, Shokhrukh Yu. Kholmatov

We consider the geometric evolution of a network in the plane, flowing by anisotropic curvature. We discuss local existence of a classical solution in the presence of several smooth anisotropies. Next, we discuss some aspects of the polycrystalline case.

Michael Groom, Ben Thornber

This paper investigates the Reynolds number dependence of a turbulent mixing layer evolving from the Richtmyer-Meshkov instability using a series of direct numerical simulations of a well-defined narrowband initial condition for a range of different Reynolds numbers. The growth rate exponent of the integral width and mixed mass is shown to marginally depend

Jishnu Ray

In this short note, we work in the general framework of supersingular abelian varieties defined over $\mathbb{Q}$. Using Coleman maps constructed by B\"uy\"ukboduk--Lei, we define some objects called ``the multi-signed Mordell-Weil groups" for supersingular abelian varieties, make comments on the structure of the dual of these groups as an Iwasawa module and

Hieke Keuning, Johan Jeuring, Bastiaan Heeren

While functionality and correctness of code has traditionally been the main focus of computing educators, quality aspects of code are getting increasingly more attention. High-quality code contributes to the maintainability of software systems, and should therefore be a central aspect of computing education. We have conducted a systematic mapping study to gi

Yiyu Tang

A solution is given to a conjecture proposed by Y. Wigderson and A. Wigderson concerning a "Heisenberg-like" uncertainty principle. This is an old article already published in 2022.

Daniel Barragan-Yani, Ludger Wirtz

Although point defects in solids are one of the most promising physical systems to build functioning qubits, it remains challenging to position them in a deterministic array and to integrate them into large networks. By means of advanced ab initio calculations we show that undissociated screw dislocations in cubic 3C-SiC, and their associated strain fields,

Alfons Van Daele

Let $(A,\Delta)$ be a finite-dimensional Hopf algebra. The linear dual $B$ of $A$ is again a finite-dimensional Hopf algebra. The duality is given by an element $V\in B\otimes A$, defined by $\langle V,a\otimes b\rangle=\langle a,b\rangle$ where $a\in A$ and $b\in B$. We use $\langle\,\cdot\, , \,\cdot\,\rangle$ for the pairings. In the introduction of this

Elena Bunina

In this paper we prove that every automorphism of a Chevalley group (or its elementary subgroup) with root system of rank >1 over a commutative ring (with 1/2 for the systems A_2, F_4, B_l, C_l; with 1/2 and 1/3 for the system G_2) is standard, i.e., it is a composition of ring, inner, central and graph automorphisms. This result finalizes description of aut

Qisi Wang, Zipu Yan, Honghua Dai

Quasi-periodic responses composed of multiple base frequencies widely exist in science and engineering problems. The multiple harmonic balance (MHB) method is one of the most commonly used approaches for such problems. However, it is limited by low-order estimations due to complex symbolic operations in practical uses. Many variants have been developed to im

Cheng Sun, Guangyan Cai, Zhengqin Li, Kai Yan

Reconstructing the shape and spatially varying surface appearances of a physical-world object as well as its surrounding illumination based on 2D images (e.g., photographs) of the object has been a long-standing problem in computer vision and graphics. In this paper, we introduce an accurate and highly efficient object reconstruction pipeline combining neura

Duo-Lun Chen, Zong-Quan Zhou, Chuan-Feng Li, Guang-Can Guo

The Duan-Lukin-Cirac-Zoller (DLCZ) scheme is a potential method to establish remote entanglements and realize large-scale quantum networks. Here we propose a DLCZ-like scheme based on the noiseless photon echo in rare-earth ion-doped crystals. Correlated photon pairs with a controllable delay can be created by the direct optical rephasing. Theoretical analys

Haiqin Xie, Cheng Wang, Shicheng Li, Yue Zhang

In the realm of urban transportation, metro systems serve as crucial and sustainable means of public transit. However, their substantial energy consumption poses a challenge to the goal of sustainability. Disturbances such as delays and passenger flow changes can further exacerbate this issue by negatively affecting energy efficiency in metro systems. To tac

Felix-Ekkehard von Horstig, David J. Ibberson, Giovanni A. Oakes, Laurence Cochrane

Fast measurements of quantum devices is important in areas such as quantum sensing, quantum computing and nanodevice quality analysis. Here, we develop a superconductor-semiconductor multi-module microwave assembly to demonstrate charge state readout at the state-of-the-art. The assembly consist of a superconducting readout resonator interfaced to a silicon-

Simon Jantač, Jarmila Pelcová, Jana Sklenářová, Marek Drápela

The triboelectric charging of particles depends on the contact area of the particle and the contacting surface. Even though the surface topology determines the real contact area, particle charging models do not account for surface roughness. In this paper, we combine contact mechanics and triboelectrification models to predict the charging of rough particles

Marinko Jablan

Plasma echo is a dramatic manifestation of plasma damping process reversibility. In this paper we calculate temporal and spatial plasma echoes in graphene in the acoustic plasmon regime when echoes dominate over plasmon emission. We show an extremely strong spatial echo response and discuss how electron collisions reduce the echo. We also discuss differences

Xinmeng Xu, Weiping Tu, Chang Han, Yuhong Yang

Monaural speech enhancement (SE) is an ill-posed problem due to the irreversible degradation process. Recent methods to achieve SE tasks rely solely on positive information, e.g., ground-truth speech and speech-relevant features. Different from the above, we observe that the negative information, such as original speech mixture and speech-irrelevant features

Jun Yamamoto, Kousuke Yakubo

The presence of large-scale real-world networks with various architectures has motivated an active research towards a unified understanding of diverse topologies of networks. Such studies have revealed that many networks with the scale-free and fractal properties exhibit the structural multifractality, some of which are actually bifractal. Bifractality is a

Nitu, Rushikesh R Fopase, Lalit Mohan Pandey, Papori Seal

Magnetic bioactive glass ceramic (MGC) powders have been synthesized by sol gel route by systematically substituting silicon dioxide with iron oxide in the 45S5 glass composition. Powder x-ray diffraction studies revealed a variation in the percentage of combeite (Ca$_2$Na$_2$Si$_3$O$_9$), magnetite (Fe$_3$O$_4$), and hematite (Fe$_2$O$_3$) nanocrystalline p

Vu Nguyen Ha, Juan Carlos Merlano Duncan, Eva Lagunas, Jorge Querol

This paper proposes a joint optimization framework for energy-efficient linear precoding and feeder-link-beam matching design in a multi-gateway multi-beam bent-pipe satellite communication system. The proposed scheme jointly optimizes the precoding vectors at the gateway antennas and amplifying-and-matching mechanism at the satellite to maximize the system-

Andrei V. Zaitsevskii, Alexander V. Oleynichenko, Ephraim Eliav

The tiny-core generalized (Gatchina) relativistic pseudopotential (GRPP) model provides an accurate approximation for many-electron Hamiltonians of molecules containing heavy atoms, ensuring a proper description of the effects of non-Coulombian electron-electron interactions, electronic self-energy and vacuum polarization. Combining this model with electron

Loris Zanotto, Marco Boldrin, Giuseppe Chitarin, Mattia Dan

The Acceleration Grid Power Supply of the MITICA test facility in Padova (Italy) is currently under commissioning. The power conversion system, the DC generator, and the High Voltage equipment have been individually commissioned, whereas the integration tests are ongoing. It is a challenging process due to the unconventional application, to the variety of di

Marek Fila, Petra Macková

We focus on open questions regarding the uniqueness of distributional solutions of the fast diffusion equation (FDE) with a given source term. When the source is sufficiently smooth, the uniqueness follows from standard results. Assuming that the source term is a measure, the existence of different classes of solutions is known, but in many cases, their uniq

Enes Pasalic, Alexandr Polujan, Sadmir Kudin, Fengrong Zhang

In this article, we provide the first systematic analysis of bent functions $f$ on $\mathbb{F}_2^{n}$ in the Maiorana-McFarland class $\mathcal{MM}$ regarding the origin and cardinality of their $\mathcal{M}$-subspaces, i.e., vector subspaces on which the second-order derivatives of $f$ vanish. By imposing restrictions on permutations $\pi$ of $\mathbb{F}_2^

Xiaoling Zhou, Ou Wu, Michael K. Ng

Machine learning models are prone to capturing the spurious correlations between non-causal attributes and classes, with counterfactual data augmentation being a promising direction for breaking these spurious associations. However, generating counterfactual data explicitly poses a challenge, and incorporating augmented data into the training process decreas

Marc Denecker, David S. Warren

Our position is that logic programming is not programming in the Horn clause sublogic of classical logic, but programming in a logic of (inductive) definitions. Thus, the similarity between prototypical Prolog programs (e.g., member, append, ...) and how inductive definitions are expressed in mathematical text, is not coincidental but essential. We argue her

Michael Bidollahkhani, Ferhat Atasoy, Elnaz Abedini, Ali Davar

In recent years, the field of medicine has been increasingly adopting artificial intelligence (AI) technologies to provide faster and more accurate disease detection, prediction, and assessment. In this study, we propose an interpretable AI approach to diagnose patients with neurofibromatosis using blood tests and pathogenic variables. We evaluated the propo

Timo Kaiser, Christoph Reinders, Bodo Rosenhahn

Label noise and ambiguities between similar classes are challenging problems in developing new models and annotating new data for semantic segmentation. In this paper, we propose Compensation Learning in Semantic Segmentation, a framework to identify and compensate ambiguities as well as label noise. More specifically, we add a ground truth depending and glo

Jiafeng Mao, Xueting Wang

Current large-scale generative models have impressive efficiency in generating high-quality images based on text prompts. However, they lack the ability to precisely control the size and position of objects in the generated image. In this study, we analyze the generative mechanism of the stable diffusion model and propose a new interactive generation paradig

Matthieu Blanke, Marc Lelarge

Model-based reinforcement learning is a powerful tool, but collecting data to fit an accurate model of the system can be costly. Exploring an unknown environment in a sample-efficient manner is hence of great importance. However, the complexity of dynamics and the computational limitations of real systems make this task challenging. In this work, we introduc

Zhongxi Qiu, Yan Hu, Heng Li, Jiang Liu

Segmentation is vital for ophthalmology image analysis. But its various modal images hinder most of the existing segmentation algorithms applications, as they rely on training based on a large number of labels or hold weak generalization ability. Based on Segment Anything (SAM), we propose a simple but effective learnable prompt layer suitable for multiple t

Li-Cheng Lan, Huan Zhang, Cho-Jui Hsieh

In this paper, we define, evaluate, and improve the ``relay-generalization'' performance of reinforcement learning (RL) agents on the out-of-distribution ``controllable'' states. Ideally, an RL agent that generally masters a task should reach its goal starting from any controllable state of the environment instead of memorizing a small set of trajectories. F

Abdullatif Albaseer, Mohamed Abdallah, Ala Al-Fuqaha, Abegaz Mohammed

Clustered federated Multitask learning is introduced as an efficient technique when data is unbalanced and distributed amongst clients in a non-independent and identically distributed manner. While a similarity metric can provide client groups with specialized models according to their data distribution, this process can be time-consuming because the server

Ruizhe Zheng, Jun Li, Yi Wang, Tian Luo

Patient-independent detection of epileptic activities based on visual spectral representation of continuous EEG (cEEG) has been widely used for diagnosing epilepsy. However, precise detection remains a considerable challenge due to subtle variabilities across subjects, channels and time points. Thus, capturing fine-grained, discriminative features of EEG pat

Alexander Felfernig, Viet-Man Le, Sebastian Lubos

Feature model configuration can be supported on the basis of various types of reasoning approaches. Examples thereof are SAT solving, constraint solving, and answer set programming (ASP). Using these approaches requires technical expertise of how to define and solve the underlying configuration problem. In this paper, we show how to apply conjunctive queries

Yuya Tanaka

This paper is concerned with the two-species chemotaxis-competition model with degenerate diffusion, \[\begin{cases} u_t = \Delta u^{m_1} - \chi_1 \nabla\cdot(u\nabla w) + \mu_1 u (1-u-a_1v), &x\in\Omega,\ t>0,\\% v_t = \Delta v^{m_2} - \chi_2 \nabla\cdot(v\nabla w) + \mu_2 v (1-a_2u-v), &x\in\Omega,\ t>0,\\% 0 = \Delta w +u+v-\overline{M}(t), &x\in\Omega,\

Samiran Mandal, Sk Irsad Ali, Subhamay Pramanik, Atis Chandra Mandal

Nanocrystalline samples of pristine capped and uncapped zinc sulphide were synthesized via the sol-gel technique. The nanocrystallinity of the samples were confirmed by the X-ray diffraction technique, where size of the particle size decreases with the increasing of mol. concentration (x = 0.00, 0.02, 0.03, 0.04 Mol). of capping agent sodium dodecyle sulphat

Marco Huber, Meiling Fang, Fadi Boutros, Naser Damer

Face recognition (FR) systems continue to spread in our daily lives with an increasing demand for higher explainability and interpretability of FR systems that are mainly based on deep learning. While bias across demographic groups in FR systems has already been studied, the bias of explainability tools has not yet been investigated. As such tools aim at ste

Kirill Mokrov, Alexander Smirnov, Mao Zeng

We present FUEL (Fractional Universal Evaluation Library), a C++ library for performing rational function arithmetic with a flexible choice of third-party computer algebra systems as simplifiers. FUEL is an outgrowth of a C++ interface to Fermat which was originally part of the FIRE code for integration-by-parts (IBP) reduction for Feynman integrals, now pro

Petra van den Bos, Marielle Stoelinga

This paper coins the notion of Joker games, a variant of concurrent games where the players are not strictly adversarial. Instead, Player 1 can get help from Player 2 by playing a Joker move. We formalize these games as cost games and develop strategies that minimize the use of Jokers - viewed as costs - to secure a win with the least possible help. Our inve

Shitong Shao, Xiaohan Yuan, Zhen Huang, Ziming Qiu

Dataset expansion can effectively alleviate the problem of data scarcity for medical image segmentation, due to privacy concerns and labeling difficulties. However, existing expansion algorithms still face great challenges due to their inability of guaranteeing the diversity of synthesized images with paired segmentation masks. In recent years, Diffusion Pro

Takayuki Katsuki, Takayuki Osogami

This paper addresses a regression problem in which output label values are the results of sensing the magnitude of a phenomenon. A low value of such labels can mean either that the actual magnitude of the phenomenon was low or that the sensor made an incomplete observation. This leads to a bias toward lower values in labels and the resultant learning because

G. Bourdarot, J-P. Berger, G. Lesur, K. Perraut

Context: FUors outbursts are a crucial stage of accretion in young stars. However a complete mechanism at the origin of the outburst still remains missing. Aims: We aim at constraining the instability mechanism in FU Orionis star itself, by directly probing the size and the evolution in time of the outburst region with near-infrared interferometry, and to co

Dev Gurung, Shiva Raj Pokhrel, Gang Li

We design a model of Post Quantum Cryptography (PQC) Quantum Federated Learning (QFL). We develop a framework with a dynamic server selection and study convergence and security conditions. The implementation and results are publicly available1.

Piotr Białas, Piotr Korcyl, Tomasz Stebel

We describe a new direct method to estimate bipartite mutual information of a classical spin system based on Monte Carlo sampling enhanced by autoregressive neural networks. It allows studying arbitrary geometries of subsystems and can be generalized to classical field theories. We demonstrate it on the Ising model for four partitionings, including a multipl

Oisín Flynn-Connolly, José M. Moreno-Fernández

We introduce higher-order Massey products for algebras over algebraic operads. This extends the work of Fernando Muro on secondary ones. We study their basic properties and behavior with respect to morphisms of algebras and operads and give some connections to formality. We prove that these higher-order operations represent the differentials in a naturally a

Qizhang Li, Yiwen Guo, Wangmeng Zuo, Hao Chen

Intermediate-level attacks that attempt to perturb feature representations following an adversarial direction drastically have shown favorable performance in crafting transferable adversarial examples. Existing methods in this category are normally formulated with two separate stages, where a directional guide is required to be determined at first and the sc

Marco Huber, Anh Thi Luu, Philipp Terhörst, Naser Damer

Explainable Face Recognition is gaining growing attention as the use of the technology is gaining ground in security-critical applications. Understanding why two faces images are matched or not matched by a given face recognition system is important to operators, users, anddevelopers to increase trust, accountability, develop better systems, and highlight un

Takanori Sugimoto

Topological states of matter are promising resources for composing fault-tolerant quantum computers, advancing beyond the limitations of current noisy intermediate-scale quantum devices. To enable this progress, a deep understanding of topological phenomena within actual quantum computing platforms is essential. However, existing quantum-circuit algorithms t

Songze Li, Duanyi Yao, Jin Liu

In a vertical federated learning (VFL) system consisting of a central server and many distributed clients, the training data are vertically partitioned such that different features are privately stored on different clients. The problem of split VFL is to train a model split between the server and the clients. This paper aims to address two major challenges i

Iven Van Mechelen, Christian Hennig, Henk A. L. Kiers

The domain of cluster analysis is a meeting point for a very rich multidisciplinary encounter, with cluster-analytic methods being studied and developed in discrete mathematics, numerical analysis, statistics, data analysis, data science, and computer science (including machine learning, data mining, and knowledge discovery), to name but a few. The other sid

Shengwei Zhou, Rufan Bai, Xiaowei Wu

We consider the problem of fairly allocating a sequence of indivisible items that arrive online in an arbitrary order to a group of n agents with additive normalized valuation functions. We consider both the allocation of goods and chores and propose algorithms for approximating maximin share (MMS) allocations. When agents have identical valuation functions

Lei Hao

We study the exciton states in the symmetrically biased dice model, the electronic structures of which have an isolated flat band between two dispersive bands. At 1/3 or 2/3 filling, the model describes a two-dimensional semiconductor with the band edge at two degenerate valleys. Because of qualitative changes in the eigenvectors resulting from the bias term

Paweł Foszner, Agnieszka Szczęsna, Luca Ciampi, Nicola Messina

Generally, crowd datasets can be collected or generated from real or synthetic sources. Real data is generated by using infrastructure-based sensors (such as static cameras or other sensors). The use of simulation tools can significantly reduce the time required to generate scenario-specific crowd datasets, facilitate data-driven research, and next build fun

David García-Lorite, Raul Merino

In this paper, we develop a novel method based on Malliavin calculus to find an approximation for the convexity adjustment for various classical interest rate products. Malliavin calculus provides a simple way to get a template for the convexity adjustment. We find the approximation for Futures, OIS Futures, FRAs, and CMSs under a general family of the one-f

Tomislav Piskor, Florian G. Eich, Michael Marthaler, Frank K. Wilhelm

We propose and analyze a method for improving quantum chemical energy calculations on a quantum computer impaired by decoherence and shot noise. The error mitigation approach relies on the fact that the one- and two-particle reduced density matrices (1- and 2-RDM) of a chemical system need to obey so-called N-representability constraints. We post-process the

Chi Fang, Caihua Wan, Xiaoyue Zhang, Satoshi Okamoto

The spin Hall effect (SHE) can generate a pure spin current by an electric current, which is promisingly used to electrically control magnetization. To reduce power consumption of this control, a giant spin Hall angle (SHA) in the SHE is desired in low-resistivity systems for practical applications. Here, critical spin fluctuation near the antiferromagnetic

Ye Liu, Yang Liu, Chang-Sheng Hu, Yun-Kun Jiang

In this paper, we study static bistability and mechanical cooling of a dissipative optomechanical cavity filled with a Kerr medium. The system exhibits optical bistability for a wide input-power range with the power threshold being greatly reduced, in contrast to the case of purely dissipative coupling. At the bistable regime, the membrane can be effectively

Weijie Fang, Yanggeng Fu, Jiaquan Gao, Longkun Guo

Witnessing the advancing scale and complexity of chip design and benefiting from high-performance computation technologies, the simulation of Very Large Scale Integration (VLSI) Circuits imposes an increasing requirement for acceleration through parallel computing with GPU devices. However, the conventional parallel strategies do not fully align with modern

Xiaorui Wang, Jun Wang, Xin Tang, Peng Gao

Filter pruning is widely adopted to compress and accelerate the Convolutional Neural Networks (CNNs), but most previous works ignore the relationship between filters and channels in different layers. Processing each layer independently fails to utilize the collaborative relationship across layers. In this paper, we intuitively propose a novel pruning method

Takashi Nakatsukasa, Nobuo Hinohara

The local alpha strength is proposed to quantify the possibility to form an alpha particle at a specific location inside the nucleus. It also provides the strength of ground and excited states in the residual nuclei after the removal of the alpha particle. We use the Hartree-Fock-plus-BCS (HF+BCS) method in the calculation of the local alpha strengths for Sn

G. Catarina, Bruno Murta

The physical properties of a quantum many-body system can, in principle, be determined by diagonalizing the respective Hamiltonian, but the dimensions of its matrix representation scale exponentially with the number of degrees of freedom. Hence, only small systems that are described through simple models can be tackled via exact diagonalization. To overcome

Håkan Runvik, Alexander Medvedev

The paper deals with the estimation of a signal model in the form of the output of a continuous linear time-invariant system driven by a sequence of instantaneous impulses, i.e. an impulsive time series. This modeling concept arises in, e.g., endocrinology when episodic hormone secretion events and elimination rates are simultaneously estimated from sampled

Aleksei Shabanov, Aleksei Tarasov, Sergey Nikolenko

Current metric learning approaches for image retrieval are usually based on learning a space of informative latent representations where simple approaches such as the cosine distance will work well. Recent state of the art methods such as HypViT move to more complex embedding spaces that may yield better results but are harder to scale to production environm

Giacomo Lucertini, Stefano Pagliarani, Andrea Pascucci

We prove global Schauder estimates for kinetic Kolmogorov equations with coefficients that are H\"older continuous in the spatial variables but only measurable in time. Compared to other available results in the literature, our estimates are optimal in the sense that the inherent H\"older spaces are the strongest possible under the given assumptions: in part

Marek Pfützner, Ivan Mukha, Simin Wang

One of characteristic phenomena for nuclei beyond the proton dripline is the simultaneous emission of two protons (2\emph{p}). The current status of our knowledge of this most recently observed and the least known decay mode is presented. First, different approaches to theoretical description of this process, ranging from effective approximations to advanced

Hongwei Liu, Jian Yang, Jianfeng Zhang, Dongheng Shao

Recently, 3D object detection has attracted significant attention and achieved continuous improvement in real road scenarios. The environmental information is collected from a single sensor or multi-sensor fusion to detect interested objects. However, most of the current 3D object detection approaches focus on developing advanced network architectures to imp

Y. Nakai, W. M. C. Sameera, K. Furuya, H. Hidaka

We have performed experimental investigations of methanol formation via the reactions of low energy $CH_{3}^{+}$ ions with an amorphous solid water (ASW) surface around 10 K. A newly developed experimental apparatus enabled irradiation of the ASW surface by several eV ions and detection of trace amounts of reaction products on the surface. It was found that

Leonardo Zambrano, Andrés Damián Muñoz-Moller, Mario Muñoz, Luciano Pereira

The barren plateau phenomenon is one of the main obstacles to implementing variational quantum algorithms in the current generation of quantum processors. Here, we introduce a method capable of avoiding the barren plateau phenomenon in the variational determination of the geometric measure of entanglement for a large number of qubits. The method is based on

Ruyi Zhang, Ting Lin, Shaoqin Peng, Jiachang Bi

The fabrication of flexible single-crystalline plasmonic or photonic components in a scalable way is fundamentally important to flexible electronic and photonic devices with high speed, high energy efficiency, and high reliability. However, it remains to be a big challenge so far. Here, we have successfully synthesized flexible single-crystalline optical hyp

Jiakai Sun, Zhanjie Zhang, Jiafu Chen, Guangyuan Li

Neural Radiance Fields (NeRF) has shown great success in novel view synthesis due to its state-of-the-art quality and flexibility. However, NeRF requires dense input views (tens to hundreds) and a long training time (hours to days) for a single scene to generate high-fidelity images. Although using the voxel grids to represent the radiance field can signific

Hongxiang Lin, Matteo Figini, Felice D'Arco, Godwin Ogbole

Low-field (<1T) magnetic resonance imaging (MRI) scanners remain in widespread use in low- and middle-income countries (LMICs) and are commonly used for some applications in higher income countries e.g. for small child patients with obesity, claustrophobia, implants, or tattoos. However, low-field MR images commonly have lower resolution and poorer contrast

Pablo D. Carrasco, Federico Rodriguez-Hertz

In this paper we prove that for topologically mixing metric Anosov flows their equilibrium states corresponding to H\"older potentials satisfy a strong rigidity property: they are determined only by their disintegrations on (strong) stable or unstable leaves. As a consequence we deduce: the corresponding horocyclic foliations of such systems are uniquely qua

Zichuan Liu, Yuanyang Zhu, Chunlin Chen

Value decomposition is widely used in cooperative multi-agent reinforcement learning, however, its implicit credit assignment mechanism is not yet fully understood due to black-box networks. In this work, we study an interpretable value decomposition framework via the family of generalized additive models. We present a novel method, named Neural Attention Ad

L. Dunn, A. Melatos, C. M. Espinoza, D. Antonopoulou

A striking feature of the Vela pulsar (PSR J0835$-$4510) is that it undergoes sudden increases in its spin frequency, known as glitches, with a fractional amplitude on the order of $10^{-6}$ approximately every 900 days. Glitches of smaller magnitudes are also known to occur in Vela. Their distribution in both time and amplitude is less well constrained but

Stephan Stock, Jonas Kemmer, Diana Kossakowski, Silvia Sabotta

In this study we present an analysis of the performance and properties of the quasi-periodic (QP) GP kernel, which is the multiplication of the squared-exponential kernel by the exponential-sine-squared kernel, based on an extensive set of synthetic RVs, into which the signature of activity was injected. We find that while the QP-GP rotation parameter matche

Zhe Wang, Zhiyuan Zhang, Jianfeng Lu, Yingzhou Li

An efficient excited state method, named xCDFCI, in the configuration interaction framework, is proposed. xCDFCI extends the unconstrained nonconvex optimization problem in coordinate descent full configuration interaction~(CDFCI) to a multicolumn version, for low-lying excited states computation. The optimization problem is addressed via a tailored coordina

Aditya Pribadi Kalapaaking, Ibrahim Khalil, Mohammad Saidur Rahman, Abdelaziz Bouras

Smart manufacturing systems involve a large number of interconnected devices resulting in massive data generation. Cloud computing technology has recently gained increasing attention in smart manufacturing systems for facilitating cost-effective service provisioning and massive data management. In a cloud-based manufacturing system, ensuring authorized acces

Willian M. H. Natori, Hui-Ke Jin, Johannes Knolle

The $S=3/2$ Kitaev honeycomb model (KHM) is unique among the spin-$S$ Kitaev models due to a massive ground state quasi-degeneracy that hampered previous numerical and analytical studies. In a recent work~\cite{jin2022unveiling}, we showed how an SO(6) Majorana parton mean-field theory of the $S=3/2$ isotropic KHM explains the anomalous features of this Kita

Kagan Akcay, MohammadJavad Salehi, Giuseppe Caire

Coded caching (CC) schemes exploit the cumulative cache memory of the users and simple linear coding to turn unicast traffic (individual file requests) into a multicast transmission. For the originally proposed $K$-user single-server/single shared link network model, CC yields an $O(K)$ gain with respect to conventional uncoded caching with the same per-user

Jeonghun J. Lee, Xinran Jin

We develop mixed finite element methods for nonlinear reaction-diffusion equations with interfaces which have Robin-type interface conditions. We introduce the velocity of chemicals as new variables and reformulate the governing equations. The stability of semidiscrete solutions, existence and the a priori error estimates of fully discrete solutions are prov

Bilel Benjdira, Anas M. Ali, Anis Koubaa

Image Dehazing aims to remove atmospheric fog or haze from an image. Although the Dehazing models have evolved a lot in recent years, few have precisely tackled the problem of High-Resolution hazy images. For this kind of image, the model needs to work on a downscaled version of the image or on cropped patches from it. In both cases, the accuracy will drop.

Zhiquan Tan, Zihao Wang, Yifan Zhang

Label hierarchy is an important source of external knowledge that can enhance classification performance. However, most existing methods rely on predefined label hierarchies that may not match the data distribution. To address this issue, we propose Simultaneous label hierarchy Exploration And Learning (SEAL), a new framework that explores the label hierarch

Marie Fialová

The Aharonov-Casher theorem is a result on the number of the so-called zero modes of a system described by the magnetic Pauli operator in $\mathbb{R}^2$. In this paper we address the same question for the Dirac operator on a flat two-dimensional manifold with boundary and Atiyah-Patodi-Singer boundary condition. More concretely we are interested in the plane

Katharina Flügel, Daniel Coquelin, Marie Weiel, Charlotte Debus

Backpropagation has long been criticized for being biologically implausible due to its reliance on concepts that are not viable in natural learning processes. Two core issues are the weight transport and update locking problems caused by the forward-backward dependencies, which limit biological plausibility, computational efficiency, and parallelization. Alt

Berndt Gensel, Theophilus Agama

In this paper, we further develop the theory of circles of partition by introducing the notion of complex circles of partition. This work generalizes the classical framework, extending from subsets of the natural numbers as base sets to partitions defined within the complex plane, which now serves as both the base and bearing set. We employ the squeeze princ

Johannes J. Buck

In this paper, we generalize results of Bruinier on automorphic Green functions on Hilbert modular surfaces to arbitrary ideals. For instance, we compute the Fourier expansion of the unregularized Green functions, use it to regularize them, obtain the Fourier expansion of the regularized Green functions and evaluate integrals of unregularized and regularized

B. Li, D. Vretenar, T. Nikšić, P. W. Zhao

An implementation of the generalized time-dependent generator coordinated method (TD-GCM) is developed, that can be applied to the dynamics of small- and large-amplitude collective motion of atomic nuclei. Both the generator states and weight functions of the GCM correlated wave function depend on time. The initial generator states are obtained as solutions

Nicolas Burq, Robert Schippa

We consider Maxwell equations on a smooth domain with perfectly conducting boundary conditions in isotropic media in two and three dimensions. In the charge-free case we recover Strichartz estimates due to Blair--Smith--Sogge for wave equations on domains up to endpoints. For the proof we suitably extend Maxwell equations over the boundary, which introduces

Boris I. Ivanov, Jinmyeong Kim, Çağlar Kutlu, Arjan F. van Loo

The axion search experiments based on haloscopes at the Center for Axion and Precision Physics Research (CAPP) of the Institute for Basic Science (IBS) in South Korea are performed in the frequency range from 1 GHz to 6 GHz. In order to perform the experiments in a strong magnetic field of 12 T and a large-volume cavity of close to 40 liters, we use He wet d

Eslam Eldeeb, Hirley Alves

IoT has a significant role in the smart campus. This paper presents a detailed description of the Smart Campus dataset based on LoRaWAN. LoRaWAN is an emerging technology that enables serving hundreds of IoT devices. First, we describe the LoRa network that connects the devices to the server. Afterward, we analyze the missing transmissions and propose a k-ne

Jeonghun J. Lee, Jacob Moore

In this paper we propose a new finite element discretization for the two-field formulation of poroelasticity which uses the elastic displacement and the pore pressure as primary variables. The main goal is to develop a numerical method with small problem sizes which still achieve key features such as parameter-robustness, local mass conservation, and robust

Fanny Augeri, Anirban Basak

Consider a random symmetric matrix with i.i.d.~entries on and above its diagonal that are products of Bernoulli random variables and random variables with sub-Gaussian tails. Such a matrix will be called a sparse Wigner matrix and can be viewed as the adjacency matrix of a random network with sub-Gaussian weights on its edges. In the regime where the mean de

Yao-Wen Chang

We propose a continuum model for the theoretical study of hybridized moir\'e excitons in transition metal dichalcogenides heterobilayers, and we use a variational method to solve the exciton wavefunction and calculate the optical absorption spectrum. The exciton continuum model is built by the charge continuum model for electrons and holes in moir\'e superla