Search

We investigate the Emery model on several ladder-like lattices including two legs of copper d-orbitals and various numbers of oxygen p-orbitals. Pair binding energy, pair spatial structure, density distribution, and pairing correlation functions are calculated using the density matrix renormalization group (DMRG). We show that a Luther-Emery phase with enhanced pairing correlations can be found for hole doping as well as for electron doping with realistic model parameters. Ladder properties depend sensitively on model parameters, the oxygen p-orbitals taken into account, and boundary conditions. The pair binding energy is a more reliable quantity than correlation functions for studying pairing in ladders. Overall, our results for two-leg Emery ladders support the possibility of superconductivity in the hole-doped 2D model. The issue is rather to determine which of the various ladder structures and model parameters are appropriate to approximate the two-dimensional cuprates.

In the evolving landscape of autonomous vehicles, ensuring robust in-vehicle network (IVN) security is paramount. This paper introduces an advanced intrusion detection system (IDS) called KD-XVAE that uses a Variational Autoencoder (VAE)-based knowledge distillation approach to enhance both performance and efficiency. Our model significantly reduces complexity, operating with just 1669 parameters and achieving an inference time of 0.3 ms per batch, making it highly suitable for resource-constrained automotive environments. Evaluations in the HCRL Car-Hacking dataset demonstrate exceptional capabilities, attaining perfect scores (Recall, Precision, F1 Score of 100%, and FNR of 0%) under multiple attack types, including DoS, Fuzzing, Gear Spoofing, and RPM Spoofing. Comparative analysis on the CICIoV2024 dataset further underscores its superiority over traditional machine learning models, achieving perfect detection metrics. We furthermore integrate Explainable AI (XAI) techniques to ensure transparency in the model's decisions. The VAE compresses the original feature space into a latent space, on which the distilled model is trained. SHAP(SHapley Additive exPlanations) values provide insights into the importance of each latent dimension, mapped back to original features for intuitive understanding. Our paper advances the field by integrating state-of-the-art techniques, addressing critical challenges in the deployment of efficient, trustworthy, and reliable IDSes for autonomous vehicles, ensuring enhanced protection against emerging cyber threats.

Recommender systems play an important role in supporting the achievement of the United Nations sustainable development goals (SDGs). In recommender systems, explanations can support different goals, such as increasing a user's trust in a recommendation, persuading a user to purchase specific items, or increasing the understanding of the reasons behind a recommendation. In this paper, we discuss the concept of "sustainability-aware persuasive explanations" which we regard as a major concept to support the achievement of the mentioned SDGs. Such explanations are orthogonal to most existing explanation approaches since they focus on a "less is more" principle, which per se is not included in existing e-commerce platforms. Based on a user study in three item domains, we analyze the potential impacts of sustainability-aware persuasive explanations. The study results are promising regarding user acceptance and the potential impacts of such explanations., Comment: The paper was accepted for publication and will be presented in the LBR track of RecSys 2024, 14.- 18. October 2024, Bari, Italy

Coherent Diffraction Imaging (CDI) is an experimental technique to get images of isolated structures by recording the light scattered off the sample. Thanks to the extremely bright and short coherent light pulses provided by X-ray Free Electron Lasers, CDI makes it possible to study nanostructures in the gas phase and get time-resolved snapshots of their ultrafast dynamics with unprecedented resolution. In principle, the sample density can be recovered from the scattered light field through a straightforward Fourier Transform operation. However, only the amplitude of the field is recorded, while the phase is lost during the measurement process and has to be retrieved by means of suitable, well-established, phase retrieval algorithms. We present the Memetic Phase Retrieval (MPR) method, an improved approach to the phase retrieval problem, which makes use of a combination of existing phase retrieval algorithms and evolutionary algorithms to mitigate the shortcomings of conventional approaches. We benchmark the method on experimental data acquired in two experimental campaigns at SwissFEL and European XFEL. Imaging results on isolated nanostructures reveal considerable stability of the algorithm's behavior on the input parameters, as well as the capability of identifying the solution in challenging conditions. A user-friendly implementation of the MPR method is released as open-source software, aiming at being a reference tool for the FEL imaging community., Comment: 37 pages, 13 figures. Software not yet released as open source. Software documentation under construction. Authors list up to date

Successful software projects depend on the quality of software requirements. Creating high-quality requirements is a crucial step toward successful software development. Effective support in this area can significantly reduce development costs and enhance the software quality. In this paper, we introduce and assess the capabilities of a Large Language Model (LLM) to evaluate the quality characteristics of software requirements according to the ISO 29148 standard. We aim to further improve the support of stakeholders engaged in requirements engineering (RE). We show how an LLM can assess requirements, explain its decision-making process, and examine its capacity to propose improved versions of requirements. We conduct a study with software engineers to validate our approach. Our findings emphasize the potential of LLMs for improving the quality of software requirements., Comment: Accepted for publication at the RE@Next! track of RE 2024

ZnS is a brittle material but shows extraordinary plasticity during mechanical tests performed in complete darkness. This phenomenon is known as the photoplastic effect, whose underlying mechanisms have long been unclear. We study the impact of light, via photoexcited charge carriers, on the dislocation core structure and mobility using first-principles calculations. We calculate the core structure and the charge-dependent Peierls barriers of the glide set of Shockley partial dislocations in ZnS. Our findings reveal that locally charged dislocations capture excess carriers in the system, leading to core reconstructions that alter the Peierls barrier, resulting in higher barriers and lower mobility for these dislocations. This altered and asymmetric mobility, depending on dislocation character (edge or mixed) and local stoichiometry (Zn or S rich), is responsible for the brittle behavior of ZnS under light exposure and will be reversed in complete darkness.

A novel method to reconstruct the energy of hadronic showers in the CMS High Granularity Calorimeter (HGCAL) is presented. The HGCAL is a sampling calorimeter with very fine transverse and longitudinal granularity. The active media are silicon sensors and scintillator tiles readout by SiPMs and the absorbers are a combination of lead and Cu/CuW in the electromagnetic section, and steel in the hadronic section. The shower reconstruction method is based on graph neural networks and it makes use of a dynamic reduction network architecture. It is shown that the algorithm is able to capture and mitigate the main effects that normally hinder the reconstruction of hadronic showers using classical reconstruction methods, by compensating for fluctuations in the multiplicity, energy, and spatial distributions of the shower's constituents. The performance of the algorithm is evaluated using test beam data collected in 2018 prototype of the CMS HGCAL accompanied by a section of the CALICE AHCAL prototype. The capability of the method to mitigate the impact of energy leakage from the calorimeter is also demonstrated., Comment: Prepared for submission to JINST

The main purpose and motivation of this article is to create a linear transformation on the polynomial ring of rational numbers. A matrix representation of this linear transformation based on standard fundamentals will be given. For some special cases of this matrix, matrix equations including inverse matrices, the Bell polynomials will be given. With the help of these equations, new formulas containing different polynomials, especially the Bernoulli polynomials, will be given. Finally, by applying the Laplace transform to the generating function for the Bernoulli polynomials, we derive some novel formulas involving the Hurwitz zeta function and infinite series., Comment: 17 pages

This study introduces a novel framework that brings together two main Quantum Programming methodologies, gate-based Quantum Computing and Quantum Annealing, by applying the Model-Driven Engineering principles. This aims to enhance the adaptability, design and scalability of quantum programs, facilitating their design and operation across diverse computing platforms. A notable achievement of this research is the development of a mapping method for programs between gate-based quantum computers and quantum annealers which can lead to the automatic transformation of these programs. Specifically, this method is applied to the Variational Quantum Eigensolver Algorithm and Quantum Anneling Ising Model, targeting ground state solutions. Finding ground-state solutions is crucial for a wide range of scientific applications, ranging from simulating chemistry lab experiments to medical applications, such as vaccine development. The success of this application demonstrates Model-Driven Engineering for Quantum Programming frameworks's practical viability and sets a clear path for quantum Computing's broader use in solving intricate problems.

Creating new interfacial magnetic states with desired functionalities is attractive for fundamental studies and spintronics applications. The emergence of interfacial magnetic phases demands the fabrication of pristine interfaces and the characterization and understanding of atomic structure as well as electronic, magnetic, and orbital degrees of freedom at the interface. Here, we report a novel interfacial insulating ferromagnetic order in antiferromagnetic LaFeO3 grown on SrTiO3, characterized by a combination of electron microscopy and spectroscopy, magnetometry, and density functional theory. The epitaxial strain drives a spin-state disproportionation in the interfacial layer of LaFeO3, which leads to a checkerboard arrangement of low- and high-spin Fe3+ ions inside smaller and larger FeO6 octahedra, respectively. Ferromagnetism at the interface arises from superexchange interactions between the low- and high-spin Fe3+. The detailed understanding of creation of emergent magnetism illustrates the potential of designing and controlling orbital degrees of freedom at the interface to realize novel phases and functionalities for future spin-electronic applications.

The BABAR experiment participates to the global endeavor for a precise prediction of the anomalous magnetic moment of the muon by evaluating the contribution of hadronic processes to the vacuum polarization. After its last result published in 2009 and 2012, BABAR is preparing a new independent measurement of the $e^+e^- \rightarrow \pi^+\pi^-(\gamma)$ cross section via initial state radiation, with full data statistics and improved uncertainties. A first milestone was reached with the recent study of additional radiations in $e^+e^- \rightarrow \pi^+\pi^-(\gamma)$ and $e^+e^- \rightarrow \mu^+\mu^-(\gamma)$, which uncovered shortcomings of the Phokhara Monte Carlo generator in one-photon rates and angular distributions. This has practically no effect on the previous BABAR measurement, but could explain longstanding discrepancies with other experiments., Comment: 6 pages, 6 figures, Contribution to the 2024 Electroweak session of the 58th Rencontres de Moriond

We describe the University of Amsterdam Intelligent Data Engineering Lab team's entry for the SemEval-2024 Task 6 competition. The SHROOM-INDElab system builds on previous work on using prompt programming and in-context learning with large language models (LLMs) to build classifiers for hallucination detection, and extends that work through the incorporation of context-specific definition of task, role, and target concept, and automated generation of examples for use in a few-shot prompting approach. The resulting system achieved fourth-best and sixth-best performance in the model-agnostic track and model-aware tracks for Task 6, respectively, and evaluation using the validation sets showed that the system's classification decisions were consistent with those of the crowd-sourced human labellers. We further found that a zero-shot approach provided better accuracy than a few-shot approach using automatically generated examples. Code for the system described in this paper is available on Github., Comment: 6 pages, 6 figures, 4 tables, camera-ready copy, accepted to the 18th International Workshop on Semantic Evaluation (SemEval-2024), for associated code and data see https://github.com/bradleypallen/shroom

Image sensors hold a pivotal role in society due to their ability to capture vast amounts of information. Traditionally, image sensors are opaque due to light absorption in both the pixels and the read-out electronics that are stacked on top of each other. Making image sensors visibly transparent would have a far-reaching impact in numerous areas such as human-computer interfaces, smart displays, and both augmented and virtual reality. In this paper, we present the development and analysis of the first semi-transparent image sensor and its applicability as an eye-tracking device. The device consists of an 8x8 array of semi-transparent photodetectors and electrodes disposed on a fully transparent substrate. Each pixel of the array has a size of 60 x 140 {\mu}m and an optical transparency of 85-95%. Pixels have a high sensitivity, with more than 90% of them showing a noise equivalent irradiance < 10-4 W/m2 for wavelengths of 637 nm. As the semi-transparent photodetectors have a large amount of built-in gain, the opaque read-out electronics can be placed far away from the detector array to ensure maximum transparency and fill factor. Indeed, the operation and appearance of transparent image sensors present a fundamental shift in how we think about cameras and imaging, as these devices can be concealed in plain sight.

We present SpaceHopper, a three-legged, small-scale robot designed for future mobile exploration of asteroids and moons. The robot weighs 5.2kg and has a body size of 245mm while using space-qualifiable components. Furthermore, SpaceHopper's design and controls make it well-adapted for investigating dynamic locomotion modes with extended flight-phases. Instead of gyroscopes or fly-wheels, the system uses its three legs to reorient the body during flight in preparation for landing. We control the leg motion for reorientation using Deep Reinforcement Learning policies. In a simulation of Ceres' gravity (0.029g), the robot can reliably jump to commanded positions up to 6m away. Our real-world experiments show that SpaceHopper can successfully reorient to a safe landing orientation within 9.7 degree inside a rotational gimbal and jump in a counterweight setup in Earth's gravity. Overall, we consider SpaceHopper an important step towards controlled jumping locomotion in low-gravity environments., Comment: To be published in the 2024 IEEE International Conference on Robotics and Automation

The silicon vertex detector (SVD) is installed at the heart of the Belle II experiment, taking data at the high-luminosity $B$-Factory SuperKEKB since 2019. The detector has shown a stable and above-99\% hit efficiency, with a large signal-to-noise in all sensors since the beginning of data taking. Cluster position and time resolution have been measured with 2020 and 2022 data and show excellent performance and stability. The effect of radiation damage is visible, but not affecting the performance. As the luminosity increases, higher machine backgrounds are expected and the excellent hit-time information in SVD can be exploited for background rejection. In particular, we have recently developed a novel procedure to select hits by grouping them event-by-event based on their time. This new procedure allows a significant reduction of the fake rate, while preserving the tracking efficiency, and it has therefore replaced the previous cut-based procedure. We have developed a method that uses the SVD hits to estimate the track time (previously unavailable) and the collision time. It has a similar precision to the estimate based on the drift chamber but its execution time is three orders of magnitude smaller, allowing a faster online reconstruction that is crucial in a high luminosity regime. The track time is a powerful information provided to analysis that allows, together with the above-mention grouping selection, to raise the occupancy limit above that expected at nominal luminosity, leaving room for a safety factor. Finally, in June 2022 the data taking of the Belle II experiment was stopped to install a new two-layer DEPFET detector (PXD) and upgrade components of the accelerator. The whole silicon tracker (PXD+SVD) has been extracted from Belle II, the new PXD installed, the detector closed and commissioned. We briefly describe the SVD results of this upgrade., Comment: 16$^{\text{th}}$ Topical Seminar on Innovative Particle and Radiation Detectors (IPRD23) 25--29 September 2023 Siena, Italy

Sports recommender systems receive an increasing attention due to their potential of fostering healthy living, improving personal well-being, and increasing performances in sport. These systems support people in sports, for example, by the recommendation of healthy and performance boosting food items, the recommendation of training practices, talent and team recommendation, and the recommendation of specific tactics in competitions. With applications in the virtual world, for example, the recommendation of maps or opponents in e-sports, these systems already transcend conventional sports scenarios where physical presence is needed. On the basis of different working examples, we present an overview of sports recommender systems applications and techniques. Overall, we analyze the related state-of-the-art and discuss open research issues., Comment: Article under review in the Journal of Intelligent Information Systems (Springer JIIS)