All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
- Further reduced the number of matrix products by around 30% for high orders and down to a guaranteed minimum for 3rd order.
- Improved the efficiency of the MUMPS solver on real Hamiltonians.
- Fix incorrect shape of {autolink}
~pymablock.BlockSeriesblocks if$H_0$ has a zero block (#127).
- Switched to the
python-mumpswrapper for the direct solver, which is available on all platforms and is more feature-complete. - The implicit KPM solver now guarantees reaching a requested accuracy.
- A new algorithm that has optimal scaling while avoiding multiplication by
$H_0$ , and supports implicit data. This combines advantages of all previous algorithms, and therefore supersedes them. - Sped up {autolink}
~pymablock.series.cauchy_dot_productwhen there are more than 3 series by reusing intermediate results. - Optimized memory usage of
~pymablock.block_diagonalizeby deleting intermediate results when they are no longer needed.
- A complete description of the algorithm to the documentation, see documentation.
- String representation of {autolink}
~pymablock.BlockSeriesfor readability.
expanded,symbolic,implicit, andgeneralfunctions and algorithms (functionality taken over by the new general algorithm, with {autolink}~pymablock.block_diagonalizethe main interface).- the
algorithmargument from {autolink}~pymablock.block_diagonalize(there is only one algorithm now). exclude_lastargument of {autolink}~pymablock.series.cauchy_dot_product(instead we check whtether other terms lack 0th order).
- First release of Pymablock.