cond-mat.mes-hall

arXiv:2412.17926v1 Announce Type: new Abstract: The extensive development of the field of spiking neural networks has led to many areas of research that have a direct impact on people's lives. As the most bio-similar of all neural networks, spiking neural networks not only allow the solution of recognition and clustering problems (including dynamics), but also contribute to the growing knowledge of the human nervous system. Our analysis has shown that the hardware implementation is of great importance, since the specifics of the physical processes in the network cells affect their ability to simulate the neural activity of living neural tissue, the efficiency of certain stages of information processing, storage and transmission. This survey reviews existing hardware neuromorphic implementations of bio-inspired spiking networks in the "semiconductor", "superconductor" and "optical" domains. Special attention is given to the possibility of effective "hybrids" of different approaches

arXiv:2412.18067v1 Announce Type: cross Abstract: Combinatorial libraries are a powerful approach for exploring the evolution of physical properties across binary and ternary cross-sections in multicomponent phase diagrams. Although the synthesis of these libraries has been developed since the 1960s and expedited with advanced laboratory automation, the broader application of combinatorial libraries relies on fast, reliable measurements of concentration-dependent structures and functionalities. Scanning Probe Microscopies (SPM), including piezoresponse force microscopy (PFM), offer significant potential for quantitative, functionally relevant combi-library readouts. Here we demonstrate the implementation of fully automated SPM to explore the evolution of ferroelectric properties in combinatorial libraries, focusing on Sm-doped BiFeO3 and ZnxMg1-xO systems. We also present and compare Gaussian Process-based Bayesian Optimization models for fully automated exploration, emphasizing local reproducibility (effective noise) as an essential factor in optimal experiment workflows. Automated SPM, when coupled with upstream synthesis controls, plays a pivotal role in bridging materials synthesis and characterization.

arXiv:2403.10990v3 Announce Type: replace-cross Abstract: Quantum noise plays a pivotal role in understanding quantum transport phenomena, including current correlations and wave-particle duality. A recent focus in this domain is $\Delta_T$ noise, which arises due to a finite temperature difference in the absence of charge current at zero voltage bias. This paper investigates $\Delta_T$ noise in mesoscopic hybrid junctions with insulators, where the average charge current is zero at zero voltage bias, through the measurement of quantum shot noise, i.e., $\Delta_T$ noise. Notably, we find that the $\Delta_T$ noise in metal-insulator-superconductor junctions is significantly larger than in metal-insulator-metal junctions. Furthermore, our results reveal that $\Delta_T$ noise initially increases with barrier strength, peaks, and then decreases, while it shows a steady increase with temperature bias, highlighting the nuanced interplay between barrier characteristics and thermal gradients.

arXiv:2412.07676v2 Announce Type: replace-cross Abstract: Semiconductor quantum dot (QD) devices have become central to advancements in spin-based quantum computing. As the complexity of QD devices grows, manual tuning becomes increasingly infeasible, necessitating robust and scalable autotuning solutions. Tuning large arrays of QD qubits depends on efficient choices of automated protocols. Here, we introduce a bootstrapping, autonomous testing, and initialization system (BATIS) designed to streamline QD device evaluation and calibration. BATIS navigates high-dimensional gate voltage spaces, automating essential steps such as leakage testing and gate characterization. For forming the current channels, BATIS follows a non-standard approach that requires a single measurement regardless of the number of channels. Demonstrated at 1.3 K on a quad-QD Si/Si$_x$Ge$_{1-x}$ device, BATIS eliminates the need for deep cryogenic environments during initial device diagnostics, significantly enhancing scalability and reducing setup times. By requiring only minimal prior knowledge of the device architecture, BATIS represents a platform-agnostic solution, adaptable to various QD systems, which bridges a critical gap in QD autotuning.