Comments (3)
One of the issues I'm hitting right now is the deterministic aspect. Currently, if two pairs of nodes have the same cost, then the order of which they get contracted is not deterministic.
I think the best way around this is to add a "signature" to the nodes. This value will come from the node_increment
we already are using. This will add another parameter to the Node
constructor, but I think that will be ok.
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Hey @Thenerdstation, I'd be interested to help with this. Do you have a particular contraction algorithm for the full contraction in your mind already? There is a paper describing some optimized0 BF or DF search algorithms that we could implement
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I will likely have this one done today, but I would love to have a backtracking algorithm using BF or DF search. Feel free to make another issue and assign yourself to it.
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Related Issues (20)
- Flaky Test when seed not used HOT 5
- Flaky test (always fails) when seeds are removed HOT 1
- Test `test_gmres_on_larger_random_problem` fails without seeds
- symmetric backend very slow for PEPS tensors HOT 4
- Home Network
- lack sqrt operation in tensornetwork/matrixproductstates/infinite_mps.py
- TensorNetwork backend for QuTiP. HOT 2
- Bug for numpy backend ``sum`` method HOT 3
- SVD on jax backend and thus ``split_node`` cannot be jitted when ``max_truncation_err`` is set
- Bug of setting `center_position` in `apply_two_site_gate` when there's no truncation
- Quantum hardware system integration with TensorNetwork
- Missing code for TensorNetwork Machine Learning HOT 1
- `backend.item` in MPS calculation is incompatible with autograd in jax HOT 2
- The lack of tensor-train RNNs for latest tf/keras HOT 1
- Parallelism Contractors HOT 1
- Question: Vector to FiniteMPS?
- Is there a simple way to multiply a scalar to the tensor values of a node that is part of a network of tensors? HOT 2
- Maintenance of this repository HOT 3
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- Pf
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