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Related papers: SuperConga: an open-source framework for mesoscopi…

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Quantitative understanding of the spatial distribution of magnetic fields and Meissner screening currents in two-dimensional (2D) superconductors and mesoscopic thin film superconducting devices is critical to interpreting the results of…

Superconductivity · Physics 2022-07-28 Logan Bishop-Van Horn , Kathryn A. Moler

We present the W-SLDA Toolkit, a general-purpose software package for simulating ultracold Fermi gases within the framework of density functional theory and its time-dependent extensions. The toolkit enables fully microscopic studies of…

Quantum Gases · Physics 2026-02-10 Gabriel Wlazłowski , Piotr Magierski , Michael McNeil Forbes , Aurel Bulgac

Superconducting quantum hardware architectures have been designed by considering the physical constraints of the underlying physics. These general-purpose architectures leave room for customization and optimization that can be exploited…

Quantum Physics · Physics 2024-05-06 Jagatheesan Kunasaikaran , Kevin Mato , Robert Wille

Deep learning has achieved great success in a wide spectrum of multimedia applications such as image classification, natural language processing and multimodal data analysis. Recent years have seen the development of many deep learning…

Machine Learning · Computer Science 2021-08-06 Naili Xing , Sai Ho Yeung , Chenghao Cai , Teck Khim Ng , Wei Wang , Kaiyuan Yang , Nan Yang , Meihui Zhang , Gang Chen , Beng Chin Ooi

One significant advantage of superconducting processors is their extensive design flexibility, which encompasses various types of qubits and interactions. Given the large number of tunable parameters of a processor, the ability to perform…

Quantum Physics · Physics 2025-04-25 Ziang Wang , Feng Wu , Hui-Hai Zhao , Xin Wan , Xiaotong Ni

Two-dimensional semiconductor-superconductor heterostructures form the foundation of numerous nanoscale physical systems. However, measuring the properties of such heterostructures, and characterizing the semiconductor in-situ is…

Superconductivity · Physics 2024-05-01 Serafim S. Babkin , Andrew P. Higginbotham , Maksym Serbyn

With the appearance of the heterogeneous platform OpenPower,many-core accelerator devices have been coupled with Power host processors for the first time. Towards utilizing their full potential, it is worth investigating performance…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-11-07 Erik Zenker , René Widera , Axel Huebl , Guido Juckeland , Andreas Knüpfer , Wolfgang E. Nagel , Michael Bussmann

An advanced theoretical framework is introduced and examined. Its main idea is to extract properties of the superconducting pairing gap function $\Delta(\omega)$ in the conventional, nearly localized superconductors. To test the approach,…

Superconductivity · Physics 2023-01-11 František Herman

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…

The discovery of high-$T_c$ conventional superconductivity in high-pressure hydrides has helped establish computational methods as a formidable tool to guide material discoveries in a field traditionally dominated by serendipitous…

We present a GPU-friendly framework for real-time implicit simulation of elastic material in the presence of frictional contacts. The integration of hyperelasticity, non-interpenetration contact, and friction in real-time simulations…

Graphics · Computer Science 2025-03-20 Ziqiu Zeng , Siyuan Luo , Fan Shi , Zhongkai Zhang

We describe an open source GPU implementation of a hybrid symplectic N-body integrator, GENGA (Gravitational ENcounters with Gpu Acceleration), designed to integrate planet and planetesimal dynamics in the late stage of planet formation and…

Earth and Planetary Astrophysics · Physics 2014-11-06 Simon L. Grimm , Joachim G. Stadel

Topological superconductivity in quasi-one-dimensional systems is a novel phase of matter with possible implications for quantum computation. Despite years of effort, a definitive signature of this phase in experiments is still debated. A…

Mesoscale and Nanoscale Physics · Physics 2021-07-12 Omri Lesser , Andrew Saydjari , Marie Wesson , Amir Yacoby , Yuval Oreg

We propose a semi-automatic staging area for efficiently building an accurate database of experimental physical properties of superconductors from literature, called SuperCon2, to enrich the existing manually-built superconductor database…

Superconducting quantum circuits are a promising hardware platform for realizing a fault-tolerant quantum computer. Accelerating progress in this field of research demands general approaches and computational tools to analyze and design…

Quantum Physics · Physics 2023-09-27 Taha Rajabzadeh , Zhaoyou Wang , Nathan Lee , Takuma Makihara , Yudan Guo , Amir H. Safavi-Naeini

We present a theoretical study of the compressibility, $\kappa$, in a Fermi gas with attractive contact interactions, providing predictions for the strongly-attractive regime and the superfluid phase. Our work emphasizes the compressibility…

Quantum Gases · Physics 2015-06-16 Hao Guo , Yan He , Chih-Chun Chien , K. Levin

The prospect of coupling a two-dimensional (2D) semiconductor heterostructure to a superconductor opens new research and technology opportunities, including fundamental problems in mesoscopic superconductivity, scalable superconducting…

Superconductivity is a fascinating quantum phenomenon characterized by zero electrical resistance and the Meissner effect. To date, several distinct families of superconductors (SCs) have been discovered. These include three-dimensional…

Materials Science · Physics 2017-11-27 Xiaoming Zhang , Yinong Zhou , Bin Cui , Mingwen Zhao , Feng Liu

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…

Physics Education · Physics 2016-12-30 J. Peña-Roche , A. Badia-Majos

Learning high-quality, robust, efficient, and disentangled representations is a central challenge in artificial intelligence (AI). Deep metric learning frameworks tackle this challenge primarily using architectural and optimization…

Machine Learning · Computer Science 2025-09-30 Shreyas Gokhale
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