Eigentools¶
Eigentools is a set of tools for studying linear eigenvalue problems. The underlying eigenproblems are solved using Dedalus, which provides a domain-specific language for partial differential equations. Each entry in the following list of features links to a Jupyter notebook giving an example of its use.
computation of pseudospectra for any Differential-Algebraic Equations with user-specifiable norms
tools to find critical parameters for linear stability analysis with user-specifiable definitions of growth and stability
ability to project eigenmode onto 2- or 3-D domain for visualization
Developers¶
The core development team consists of
Jeff Oishi (<jsoishi@gmail.com>)
Keaton Burns (<keaton.burns@gmail.com>)
Susan Clark (<susanclark19@gmail.com>)
Evan Anders (<evan.anders@northwestern.edu>)
Ben Brown (<bpbrown@gmail.com>)
Geoff Vasil (<geoffrey.m.vasil@gmail.com>)
Daniel Lecoanet (<daniel.lecoanet@northwestern.edu>)
Support¶
Eigentools was developed with support from the Research Corporation under award Scialog Collaborative Award (TDA) ID# 24231.