Related papers: Optimization of a Superconducting Magnetic Energy …
The ever-increasing size and computational complexity of today's machine-learning algorithms pose an increasing strain on the underlying hardware. In this light, novel and dedicated architectural solutions are required to optimize energy…
This paper presents a classification of generator excitation waveforms using principal component analysis (PCA) and machine learning models, including logistic regression, random forest, and gradient boosting decision trees (GBDT). Building…
We propose a superconducting diode device comprising a central superconducting film flanked by two wires carrying an applied DC bias, suitably chosen so as to generate different asymmetric field profiles. Through numerical simulations of…
The rapidity and low power consumption of superconducting electronics makes them an ideal substrate for physical reservoir computing, which commandeers the computational power inherent to the evolution of a dynamical system for the purposes…
This project introduces a groundbreaking approach to address the challenge of periodic signal compression. By proposing a novel adaptive coding method, coupled with hardware-assisted data compression, we have developed a new architecture…
We describe a dynamic programming algorithm for predicting optimal RNA secondary structure, including pseudoknots. The algorithm has a worst case complexity of ${\cal O}(N^6)$ in time and ${\cal O}(N^4)$ in storage. The description of the…
Microwave quantum memory promises advanced capabilities for noisy intermediate-scale superconducting quantum computers. Existing approaches to microwave quantum memory lack complete combination of high efficiency, long storage time,…
Utilizing the intrinsic history-dependence and nonlinearity of hardware, physical reservoir computing is a promising neuromorphic approach to encode time-series data for in-sensor computing. The accuracy of this encoding critically depends…
A stand-alone App has been developed, focused on obtaining information about relevant engineering properties of magnetic levitation systems. Our modelling toolkit provides real time simulations of 2D magneto-mechanical quantities for…
Reservoir computing is a highly efficient machine learning framework for processing temporal data by extracting features from the input signal and mapping them into higher dimensional spaces. Physical reservoir layers have been realized…
Developing ultra-low-energy superconducting computing and fault-tolerant quantum computing will require scalable superconducting memory. While conventional superconducting logic-based memory cells have facilitated early demonstrations,…
Magnetocaloric materials can be useful in magnetic refrigeration applications, but to be practical the magneto-refrigerant needs to have a very large magnetocaloric effect (MCE) near room temperature for modest applied fields (<2 Tesla)…
We report the data on magnetization losses and critical current of multifilament copper stabilized coated conductors. Eight centimeters long samples of copper stabilized YBa2Cu3O7-x (YBCO) coated conductors manufactured commercially were…
Abstract: Solid state sensors having timing capabilities are becoming an absolute need in particle tracking techniques of future experiments at colliders. In this sense, silicon sensors having 3D structure are becoming an interesting…
The exponential growth of edge artificial intelligence demands material-focused solutions to overcome energy consumption and latency limitations when processing real-time temporal data. Physical reservoir computing (PRC) offers an…
A new method for implementing the kinetic energy operator for real-space, grid-based electronic structure codes is developed. It is based on multi-order Adaptive Finite Differencing (AFD) and uses atomic pseudo orbitals produced by the…
Magnetic traps for cold atoms have become a powerful tool of cold atom physics and condense matter research. The traps on superconducting chips allow one to increase the trapped atom life- and coherence time by decreasing the thermal noise…
High temperature superconducting materials are being considered to generate the magnetic fields required for the confinement of plasma in fusion reactors. The present study aims to assess the microstructural degradation resulting from ion…
We report on the depression of the superconducting critical temperature of ultra thin YBa2Cu3O7 (YBCO) layers, when their thickness is reduced in presence of La0.7Ca0.3MnO3 (LCMO) magnetic layers in [LCMO (15 u.c.)/ YBCO(N u.c.)]…
A 2D electromagnetic-thermal coupled numerical model has been developed using the finite element method and validated against experimental data to investigate a superconducting machine featuring high-temperature superconducting (HTS) tape…