SciML / SciML/ModelOrderReduction.jl
Balanced Truncation Variants (LQG, Stochastic, Positive-/Bounded-Real, Time-/Frequency-Limited)
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- Dominant language
- Julia
- Stars
- 43
- Forks
- 8
- Avg merge
- 11h 47m
- Merged PRs (30d)
- 14
Description
From the catch-all tracking issue https://github.com/SciML/ModelOrderReduction.jl/issues/78
Extend beyond classical balanced truncation (#4) with the common BT variants from the LTI MOR checklist: LQG-BT, balanced stochastic truncation (BST), positive-real / bounded-real / H∞ BT, and time-/frequency-limited BT.
Reference list (pyMOR LTI MOR checklist): https://github.com/pymor/pymor/issues/388#issuecomment-892486556
Julia notes on classical BT limitations (stable systems only): https://github.com/SciML/ModelOrderReduction.jl/issues/78#issuecomment-1189978688
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start with the catch-all tracking issue #78 and the existing classical balanced truncation issue #4, then review the linked pyMOR checklist and Julia notes. Determine the project’s intended scope and entry points for LQG-BT, BST, positive-/bounded-real or H∞ BT, and time-/frequency-limited BT. Done means the agreed variants are implemented with appropriate validation, though this issue does not name specific files or tests.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- hpc
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Active
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100