Critical currents in superconductors with quasiperiodic pinning arrays: One-dimensional chains and two-dimensional Penrose lattices
V. R. Misko (1,2), Sergey Savel'ev (1), and Franco Nori (1,2) ((1), Frontier Research System, Institute of Physical, Chemical Research, (RIKEN), Wako-shi, Saitama, Japan; (2) Center for Theoretical Physics, CSCS,, Department of Physics, University of Michigan, Ann Arbor, USA)

TL;DR
This paper investigates how quasiperiodic pinning arrays, including 1D chains and 2D Penrose lattices, influence the critical depinning current in superconductors, revealing self-similar structures and broadening the range of high critical currents.
Contribution
It provides a detailed analysis of critical currents in quasiperiodic pinning arrays, highlighting the role of Fibonacci sequences and self-similarity, and compares their effectiveness to periodic and random arrays.
Findings
Peaks in J_c(Phi) follow Fibonacci harmonics in 1D chains.
Self-similarity observed in J_c(Phi) for QP lattices.
QP lattices yield broader high J_c(Phi) ranges than periodic or random arrays.
Abstract
We study the critical depinning current J_c, as a function of the applied magnetic flux Phi, for quasiperiodic (QP) pinning arrays, including one-dimensional (1D) chains and two-dimensional (2D) arrays of pinning centers placed on the nodes of a five-fold Penrose lattice. In 1D QP chains of pinning sites, the peaks in J_c(Phi) are shown to be determined by a sequence of harmonics of long and short periods of the chain. This sequence includes as a subset the sequence of successive Fibonacci numbers. We also analyze the evolution of J_c(Phi) while a continuous transition occurs from a periodic lattice of pinning centers to a QP one; the continuous transition is achieved by varying the ratio gamma = a_S/a_L of lengths of the short a_S and the long a_L segments, starting from gamma = 1 for a periodic sequence. We find that the peaks related to the Fibonacci sequence are most pronounced when…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
