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An implementation of the SRC algorithm introduced in [Camaño, Epperly and Tropp, *Quantum***10**, 2022 (2026)](https://doi.org/10.22331/q-2026-03-10-2022) ([arXiv:2504.06475](https://arxiv.org/abs/2504.06475)).
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An implementation of the SRC algorithm introduced in [Camaño, Epperly and Tropp, *Quantum***10**, 2022 (2026)](https://doi.org/10.22331/q-2026-03-10-2022) ([arXiv:2504.06475](https://arxiv.org/abs/2504.06475)), extending the idea to other kinds of tensor networks.
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### Features
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@@ -23,15 +23,15 @@ from src_method import apply, compress
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The `apply` function covers cases 1 and 2 above, while the `compress` function covers cases 3 and 4. Both functions are pure, meaning no in-place modification ever happens. The user should
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manage the assignment of the returned objects, possibly overwriting the input variables.
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See the [reference documentation](https://docs.algorithmiq.fi/src_method/) for details, and the [tests](tests/) or [benchmarks](benches/) folders for usage examples.
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See the [reference documentation](algorithmiq.github.io/src_method/) for details, and the [tests](tests/) or [benchmarks](benches/) folders for usage examples.
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Whether a train is an MPS or an MPO is inferred from the rank of its first site tensor, so no wrapper type is needed.
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**NOTE**: the current implementation targets tensor networks with 3 or more sites. For smaller networks, an exact SVD-based fallback is dispatched, with a warning.
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### Tensor Indexing Conventions
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The array layout follows the default `quimb` tensor indexing conventions, so results round-trip through [Quimb](https://quimb.readthedocs.io/en/latest/autoapi/quimb/tensor/index.html) without any extra reshaping.
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The array layout follows the default `quimb` tensor indexing conventions, so results round-trip through [Quimb](https://quimb.readthedocs.io/en/latest/autoapi/quimb/tensor/index.html) without any permutation:
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