Feature/hamiltonian generation #22
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| """ | ||
| Test properties of a larger lattice (2x2 square) without full matrix comparison. | ||
| """ | ||
| lattice = SquareLattice(size=(2, 2), pbc=True) # 4 sites, 8 bonds with PBC |
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2*2 with PBC is subtle, as you can see, there will be two bonds between the same two lattice points
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over all looks good, a nice work, only some minor details require fix or explanantion |
This commit refactors the hamiltonian generation functions to be more robust, flexible, and aligned with the project's backend-agnostic architecture, based on feedback from the recent code review. Key changes include: - **Backend Agnosticism:** The `PauliStringSum2COO` call now uses `numpy=False`, ensuring the returned sparse matrix is a native tensor of the currently active backend (TensorFlow, JAX, etc.). The return type hints have been updated to `Any` to reflect this. - **Anisotropic Heisenberg Model:** The `heisenberg_hamiltonian` function now accepts a list or tuple for `j_coupling`, allowing for the definition of anisotropic models with different Jx, Jy, and Jz values. - **Test Suite Enhancement:** Tests have been updated to use `tc.backend.to_dense` for backend-agnostic validation. A new test case for the anisotropic Heisenberg model has also been added to ensure its correctness. - **Code Cleanup:** A redundant `float()` cast was removed from the Rydberg hamiltonian logic.
| from typing import Any, List, Tuple, Union | ||
| import numpy as np | ||
| from tensorcircuit.cons import dtypestr, backend | ||
| import tensorcircuit as tc |
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dont directly use tensorcircuit internally, use from .cons import dtypestr, backend and use backend.blah in the code instead of tc.backend
Internal API Usage: I've switched to importing backend and dtypestr from .cons and PauliStringSum2COO from ..quantum as you suggested, avoiding direct calls to the top-level tc package. Error Handling: For both heisenberg_hamiltonian and rydberg_hamiltonian, I've added a check to raise a ValueError if num_sites is 0, which is indeed more explicit.
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Hi @refraction-ray, Internal API Usage: I've updated the code to use backend from .cons and relative imports for internal modules, instead of calling the top-level tensorcircuit package. Error Handling: I've added a ValueError check for num_sites = 0 in both Hamiltonian functions, as you suggested. Rydberg Hamiltonian Sign: Regarding your question on the Z-term sign (why -v_ij/4?), I've double-checked the derivation and I thought the implementation is correct. The single-body Z coefficient comes from two sources: To make this clearer for future reference, I've also added a comment inside the function explaining this derivation. I believe this addresses all your feedback. The PR should be ready for another look. Thanks again |
| import typing | ||
| from typing import Any, List, Tuple, Union | ||
| import numpy as np | ||
| from tensorcircuit.cons import dtypestr, backend |
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should also be from ..cons ?
| @@ -0,0 +1,154 @@ | |||
| import typing | |||
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should merge with the following line? import all types you will use
This commit addresses code review feedback on the new hamiltonians module. - Switched from absolute to relative imports for internal modules (`..cons`, `..quantum`) to improve modularity. - Cleaned up and unified `typing` imports for better code style and consistency.
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Thanks for the review, @refraction-ray! I've updated the PR according to your suggestions. It should be ready for another look now. |
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great! LGTM. will merge if CI finished successfully. |
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This pull request implements Task 1 of the follow-up plan, introducing utility functions to generate common spin Hamiltonians from
Latticeobjects.Key Contributions:
generate_heisenberg_hamiltonian: Creates a sparse Heisenberg Hamiltonian based on the nearest-neighbor pairs provided by the lattice.generate_rydberg_hamiltonian: Creates a sparse Rydberg Hamiltonian, utilizing the lattice's distance matrix to calculate long-range interactions.tests/templates/test_hamiltonians.py) with unit tests that verify: