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Related papers: Cluster-based Superconducting Tunneling Networks

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Tunneling spectroscopy between parallel two-dimensional (2D) electronic systems provides a powerful method to probe the underlying electronic properties by measuring tunneling conductance. In this work, we present a theoretical framework…

Mesoscale and Nanoscale Physics · Physics 2025-09-29 Modi Ke , Mahmoud M. Asmar , Wang-Kong Tse

Deep clustering uncovers hidden patterns and groups in complex time series data, yet its opaque decision-making limits use in safety-critical settings. This survey offers a structured overview of explainable deep clustering for time series,…

Machine Learning · Computer Science 2025-10-21 Udo Schlegel , Gabriel Marques Tavares , Thomas Seidl

We fabricate nanolayer alumina capacitor and apply high electric fields, close to 1 GV/m, to inject charges in the dielectric. Asymmetric charge distributions have been achieved due to the selectivity of the quantum tunneling process.…

Mesoscale and Nanoscale Physics · Physics 2021-02-01 Eduard Ilin , Irina Burkova , Eugene V. Colla , Michael Pak , Alexey Bezryadin

Effect of geometry on the superconductivity is considered. It is shown that the for nearly two dimensional BCS systems the critical temperature is rapidly increased with decreasing the thickness of the layer. The result is expected to be…

Condensed Matter · Physics 2007-05-23 N. M. Khue , Le Ngoc Minh , Tran Tri Lan , Do Huu Nha

Subspace clustering is an unsupervised clustering technique designed to cluster data that is supported on a union of linear subspaces, with each subspace defining a cluster with dimension lower than the ambient space. Many existing…

Machine Learning · Computer Science 2021-03-23 Benjamin D. Haeffele , Chong You , René Vidal

It is shown that nanoparticles made of low $T_c$ superconductors have large diamagnetic response at temperatures several orders of magnitude above $T_c$. Most features of the recently observed Giant diamagnetism of Au nanorods are explained…

Mesoscale and Nanoscale Physics · Physics 2015-06-23 Yoseph Imry

The development of multi-core processor systems is a demanded branch of science and technology. The appearance of processors with dozens and hundreds of cores poses to the developers the question of choosing the optimal topology capable to…

Hardware Architecture · Computer Science 2019-03-29 Shchegoleva M. A. , Romanov A. Yu. , Lezhnev E. V. , Amerikanov A. A

Single-electron circuits of the future, consisting of a network of quantum dots, will require a mechanism to transport electrons from one functional part to another. For example, in a quantum computer[1] decoherence and circuit complexity…

Mesoscale and Nanoscale Physics · Physics 2011-11-02 R. P. G. McNeil , M. Kataoka , C. J. B. Ford , C. H. W. Barnes , D. Anderson , G. A. C. Jones , I. Farrer , D. A. Ritchie

Deep neural networks (DNNs) offer a means of addressing the challenging task of clustering high-dimensional data. DNNs can extract useful features, and so produce a lower dimensional representation, which is more amenable to clustering…

Machine Learning · Computer Science 2021-07-23 Louis Mahon , Thomas Lukasiewicz

Contact resistance and current crowding are important to nanoscale electrical contacts. In this paper, we present a self-consistent model to characterize partially overlapped parallel contacts with varying specific contact resistivity along…

Applied Physics · Physics 2019-12-24 Sneha Banerjee , John Luginsland , Peng Zhang

We study the conductance of a junction between the normal and superconducting segments of a nanowire, both of which are subjected to spin-orbit coupling and an external magnetic field. We directly compare the transport properties of the…

Mesoscale and Nanoscale Physics · Physics 2017-06-01 Christopher Reeg , Dmitrii L. Maslov

Subspace clustering assumes that the data is sepa-rable into separate subspaces. Such a simple as-sumption, does not always hold. We assume that, even if the raw data is not separable into subspac-es, one can learn a representation…

Machine Learning · Computer Science 2019-12-11 Jyoti Maggu , Angshul Majumdar , Emilie Chouzenoux

We investigate the onset of the discontinuous percolation transition in small-world hyperbolic networks by studying the systems-size scaling of the typical largest cluster approaching the transition, $p\nearrow p_{c}$. To this end, we…

Statistical Mechanics · Physics 2014-08-01 Vijay Singh , Stefan Boettcher

Superconducting circuits and microwave signals are good candidates to realize quantum networks, which are the backbone of quantum computers. We have realized a quantum node based on a 3D microwave superconducting cavity parametrically…

Quantum Physics · Physics 2015-03-06 Emmanuel Flurin , Nicolas Roch , Jean-Damien Pillet , François Mallet , Benjamin Huard

We determine the shape, multiplicity, size, and radial structure of superclusters in the LambdaCDM concordance cosmology from z = 0 to z = 2. Superclusters are defined as clusters of clusters in our large-scale cosmological simulation. We…

Astrophysics · Physics 2008-11-26 James J. Wray , Neta A. Bahcall , Paul Bode , Carl Boettiger , Philip F. Hopkins

The growth of Fe nanoclusters on the Ge(001) surface has been studied using lowtemperature scanning tunnelling microscopy (STM) and density functional theory (DFT) calculations. STM results indicate that Fe nucleates on the Ge(001) surface,…

The superconducting properties of a two-dimensional superconducting wire network with a new geometry have been measured as a function of the external magnetic field. The extreme localization effect recently predicted for this periodic…

Mesoscale and Nanoscale Physics · Physics 2009-10-31 B. Pannetier , C. C. Abilio , E. Serret , Th. Fournier , P. Butaud , J. Vidal

Intrinsic c-axis tunnelling in the superconducting state has been measured in zero and finite fields in small mesa structures fabricated on the surface of 2212-BSCCO single crystals. The temperature dependence of the zero-field critical…

Superconductivity · Physics 2009-10-31 C. E. Gough , P. J. Thomas , J. C. Fenton , G. Yang

Superconducting properties of metallic nanowires can be entirely different from those of bulk superconductors because of the dominating role played by thermal and quantum fluctuations of the order parameter. For superconducting wires with…

Superconductivity · Physics 2009-12-16 K. Yu. Arutyunov , D. S. Golubev , A. D. Zaikin

Neural network-based clustering has recently gained popularity, and in particular a constrained clustering formulation has been proposed to perform transfer learning and image category discovery using deep learning. The core idea is to…

Computer Vision and Pattern Recognition · Computer Science 2018-06-29 Yen-Chang Hsu , Zhaoyang Lv , Joel Schlosser , Phillip Odom , Zsolt Kira