**Content**This package contains the MATLAB code used in the paper “Subspace methods for computing the pseudospectral abscissa and the stability radius”.

**Authors**D. Kressner, EPF Lausanne

B. Vandereycken, EPF Lausanne

**Requirements**The code

*should*work on any reasonably recent version of MATLAB. It was tested with R2011b, R2013b (Mac OS X) and R2010b (Linux).

Although parts of the code is MEX, binary MEX files are provided so there is hopefully no need to compile them. If needed, you can try to compile them using`install_mex`.

**Installation**Download and unpack the package.

Run the`startup`file to adjust your MATLAB path.

Try out`example_dense`,`example_sparse`,`difficult_example_dense`,`difficult_example_sparse`. You should get something like the following output.

>> startup >> example_dense Iteration 1. Current = -7.816030706939740e-02. Absolute error = 1.34e-04. Relative error = 1.18e-06. Iteration 2. Current = -7.802629355658958e-02. Relative change = 1.34e-04. Absolute error = 3.49e-09. Relative error = 3.09e-11. Iteration 3. Current = -7.802629006654559e-02. Relative change = 3.49e-09. Absolute error = 2.08e-15. Relative error = 1.84e-17. Iteration 4. Current = -7.802629006654559e-02. Relative change = 0.00e+00. -- Tolerance on relative change satisfied at iteration 4. Current = -7.802629006654559e-02.

**License and use**The code is GPLv3 licensed. In addition, it is research code and not intended for production use. If you publish a paper using this code, a reference to the above paper would be appreciated.

The code contains parts of PROPACK, EigTool, the criss-cross algorithm, PSAPSR, and eigsplus all of which may have their own licenses.

**Contact**All comments, bugs and requests are most welcome at .

**Version history**

v0.2 (26 November 2013): bug fix for eigsplus.m in MATLAB versions R2013a and R2013b (thanks to Tim Mitchell, NYU).

v0.1 (14 March 2012): initial release.

**Obligatory marketing picture 1**The rectangular pseudospectra of the subspaces generated by

`subspace_pspa`for iterations (from left to right, top to bottom) applied to the Grcar matrix for . In addition, the thin lines show the square pseudospectra .

**Obligatory marketing picture 2**Iterates of

`subspace_pspa`using`options.tol_svd=-1`(blue discs, always eigenvalue computations) and`options.tol_svd=Inf`(red circles, no eigenvalue computations) for the Grcar (left figure) and the Orr-Sommerfeld (right figure) matrices of size . The default`options.tol_svd=0.1`only performs 2 to 3 eigenvalue computations (not shown).