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Over recent decades, astronomy has entered the era of massive data and real-time surveys. This is improving the study of transient objects - although they still contain some of the most poorly understood phenomena in astrophysics, as it is inherently more difficult to obtain data on them. In order to help detect these objects in their brightest state, we have built a quasi-real time transient detection system for the XMM-Newton pipeline: the Search for Transient Objects in New detections using Known Sources (STONKS) pipeline. STONKS detects long-term X-ray transients by automatically comparing new XMM-Newton detections to any available archival X-ray data at this position, sending out an alert if the amplitude of variability between observations is over 5. This required an initial careful cross-correlation and flux calibration of various X-ray catalogs from different observatories (XMM-Newton, Chandra, Swift, ROSAT, and eROSITA). We also systematically computed the XMM-Newton upper limits at the position of any X-ray source covered by the XMM-Newton observational footprint, even without any XMM-Newton counterpart. The behavior of STONKS was then tested on all 483 observations performed with imaging mode in 2021. Over the 2021 testing run, STONKS provided $0.7^{+0.7}_{-0.5}$ alerts per day, about 80% of them being serendipitous. STONKS also detected targeted tidal disruption events, ensuring its ability to detect other serendipitous events. As a byproduct of our method, the archival multi-instrument catalog contains about one million X-ray sources, with 15% of them involving several catalogs and 60% of them having XMM-Newton upper limits. STONKS demonstrates a great potential for revealing future serendipitous transient X-ray sources, providing the community with the ability to follow-up on these objects a few days after their detection., Comment: 30 pages, 30 figures, accepted in A&A

A new digital twin (DT) framework with optimal sensor placement (OSP) is proposed to accurately calculate the modal responses and identify the damage ratios of the offshore jacket platforms. The proposed damage identification framework consists of two models (namely one OSP model and one damage identification model). The OSP model adopts the multi-objective Lichtenberg algorithm (MOLA) to perform the sensor number/location optimization to make a good balance between the sensor cost and the modal calculation accuracy. In the damage identification model, the Markov Chain Monte Carlo (MCMC)-Bayesian method is developed to calculate the structural damage ratios based on the modal information obtained from the sensory measurements, where the uncertainties of the structural parameters are quantified. The proposed method is validated using an offshore jacket platform, and the analysis results demonstrate efficient identification of the structural damage location and severity.

Exploring the topology of electronic bands is a way to realize new states of matter with possible implications for information technology. Because bands cannot always be observed directly, a central question is how to tell that a topological regime has been achieved. Experiments are often guided by a prediction of a unique signal or a pattern, called "the smoking gun". Examples include peaks in conductivity, microwave resonances, and shifts in interference fringes. However, many condensed matter experiments are performed on relatively small, micron or nanometer-scale, specimens. These structures are in the so-called mesoscopic regime, between atomic and macroscopic physics, where phenomenology is particularly rich. In this paper, we demonstrate that the trivial effects of quantum confinement, quantum interference and charge dynamics in nanostructures can reproduce accepted smoking gun signatures of triplet supercurrents, Majorana modes, topological Josephson junctions and fractionalized particles. The examples we use correspond to milestones of topological quantum computing: qubit spectroscopy, fusion and braiding. None of the samples we use are in the topological regime. The smoking gun patterns are achieved by fine-tuning during data acquisition and by subsequent data selection to pick non-representative examples out of a fluid multitude of similar patterns that do not generally fit the "smoking gun" designation. Building on this insight, we discuss ways that experimentalists can rigorously delineate between topological and non-topological effects, and the effects of fine-tuning by deeper analysis of larger volumes of data., Comment: Data are available through Zenodo at DOI: 10.5281/zenodo.8349309

Many recipes for realizing topological superconductivity rely on broken time-reversal symmetry, which is often attained by applying a substantial external magnetic field. Alternatively, using magnetic materials can offer advantages through low-field operation and design flexibility on the nanoscale. Mechanisms for lifting spin degeneracy include exchange coupling, spin-dependent scattering, spin injection-all requiring direct contact between the bulk or induced superconductor and a magnetic material. Here, we implement locally broken time-reversal symmetry through dipolar coupling from nearby micromagnets to superconductor-semiconductor hybrid nanowire devices. Josephson supercurrent is hysteretic due to micromangets switching. At or around zero external magnetic field, we observe an extended presence of Andreev bound states near zero voltage bias. We also show a zero-bias peak plateau of a non-quantized value. Our findings largely reproduce earlier results where similar effects were presented in the context of topological superconductivity in a homogeneous wire, and attributed to more exotic time-reversal breaking mechanisms [1]. In contrast, our stray field profiles are not designed to create Majorana modes, and our data are compatible with a straightforward interpretation in terms of trivial states in quantum dots. At the same time, the use of micromagnets in hybrid superconductor-semiconductor devices shows promise for future experiments on topological superconductivity.

This paper addresses the question: Can spintronic circuits based on Magnetic Tunnel Junction (MTJ) transducers outperform their state-of-the-art CMOS counterparts? To this end, we use the EPFL combinational benchmark sets, synthesize them in 7 nm CMOS and in MTJ-based spintronic technologies, and compare the two implementation methods in terms of Energy-Delay-Product (EDP). To fully utilize the technologies potential, CMOS and spintronic implementations are built upon standard Boolean and Majority Gates, respectively. For the spintronic circuits, we assumed that domain conversion (electric/magnetic to magnetic/electric) is performed by means of MTJs and the computation is accomplished by domain wall based majority gates, and considered two EDP estimation scenarios: (i) Uniform Benchmarking, which ignores the circuit's internal structure and only includes domain transducers power and delay contributions into the calculations, and (ii) Majority-Inverter-Graph Benchmarking, which also embeds the circuit structure, the associated critical path delay and energy consumption by DW propagation. Our results indicate that for the uniform case, the spintronic route is better suited for the implementation of complex circuits with few inputs and outputs. On the other hand, when the circuit structure is also considered via majority and inverter synthesis, our analysis clearly indicates that in order to match and eventually outperform CMOS performance, MTJ efficiency has to be improved by 3-4 orders of magnitude. While it is clear that for the time being the MTJ-based-spintronic way cannot compete with CMOS, further transducer developments may tip the balance, which, when combined with information non-volatility, may make spintronic implementation for certain applications that require a large number of calculations and have a rather limited amount of interaction with the environment., Comment: This work was supported by imec Industrial Affiliation Program on Exploratory Logic Devices. It has also received funding from the European Union Horizon Europe research and innovation programme within the project SPIDER under grant agreement No 101070417

The sensitivity of ferroelectric domain walls to external stimuli makes them functional entities in nanoelectronic devices. Specifically, optically driven domain reconfiguration with in-plane polarization is advantageous and thus highly sought. Here, we show the existence of in-plane polarized sub-domains imitating a single domain state and reversible optical control of its domain wall movement in a single-crystal of ferroelectric BaTiO3. Similar optical control in the domain configuration of non-polar ferroelastic material indicates long-range ferroelectric polarization is not essential for the optical control of domain wall movement. Instead, flexoelectricity is found to be an essential ingredient for the optical control of the domain configuration and hence, ferroelastic materials would be another possible candidate for nanoelectronic device applications.