pyTDGL: Time-dependent Ginzburg-Landau in Python
Journal Article
·
· Computer Physics Communications
- SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States). Stanford Institute for Materials and Energy Science (SIMES); Stanford Univ., CA (United States); Stanford Institute for Materials and Energy Sciences, SLAC National Accelerator Laboratory
Time-dependent Ginzburg-Landau (TDGL) theory is a phenomenological model for the dynamics of superconducting systems. Due to its simplicity in comparison to microscopic theories and its effectiveness in describing the observed properties of the superconducting state, TDGL is widely used to interpret or explain measurements of superconducting devices. Here, we introduce pyTDGL, a Python package that solves a generalized TDGL model for superconducting thin films of arbitrary geometry, enabling simulations of vortex and phase dynamics in mesoscopic superconducting devices. pyTDGL can model the nonlinear magnetic response and dynamics of multiply connected films, films with multiple current bias terminals, and films with a spatially inhomogeneous critical temperature. We demonstrate these capabilities by modeling quasi-equilibrium vortex distributions in irregularly shaped films, and the dynamics and current-voltage-field characteristics of nanoscale superconducting quantum interference devices (nanoSQUIDs).
- Research Organization:
- Stanford Institute for Materials and Energy Sciences, SLAC National Accelerator Laboratory
- Sponsoring Organization:
- USDOE Office of Science (SC), Basic Energy Sciences (BES); USDOE Office of Science (SC), Basic Energy Sciences (BES). Materials Sciences & Engineering Division (MSE)
- Grant/Contract Number:
- AC02-76SF00515
- OSTI ID:
- 1985292
- Alternate ID(s):
- OSTI ID: 2000222
- Journal Information:
- Computer Physics Communications, Journal Name: Computer Physics Communications Vol. 291; ISSN 0010-4655
- Publisher:
- ElsevierCopyright Statement
- Country of Publication:
- United States
- Language:
- English
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