Sub state vector#8077
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The current implementation appears to be exponential in space and time. The present change, due originally to jamieas@google.com, replaces python loops with numpy functions motivated by standard methods for computing partial traces. The change is runnable in Colab, including tests and a performance benchmark, at https://colab.sandbox.google.com/drive/1qWJTnlT6hPXI8cQsTwyqQveEtn7fGhNc?resourcekey=0-67OmbvgwTlf9fnKp3ppbrw
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## main #8077 +/- ##
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CLA check is fixed. |
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NoureldinYosri
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overall LGTM%nits
| num_qubits_out = len(keep_indices)#.shape[0] | ||
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| # The permutation moves the specified qubits to the start of the qubit order. | ||
| keeps = set(keep_indices) |
| if protocols.approx_eq(coherence_measure, 1, atol=atol): | ||
| return np.exp(2j * np.pi * np.random.random()) * best_candidate.reshape(ret_shape) | ||
| # The number of output qubits. | ||
| # keep_indices = np.array(keep_indices) |
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| # keep_indices = np.array(keep_indices) |
| return np.exp(2j * np.pi * np.random.random()) * best_candidate.reshape(ret_shape) | ||
| # The number of output qubits. | ||
| # keep_indices = np.array(keep_indices) | ||
| num_qubits_out = len(keep_indices)#.shape[0] |
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| num_qubits_out = len(keep_indices)#.shape[0] | |
| num_qubits_out = len(keep_indices) |
NoureldinYosri
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May 15, 2026
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thanks @AntonKast
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- Verify the maximum eigenvalue is indeed close to 1. - Enable arbitrary order of `keep_indices` as before. - Use the same tolerance check as before quantumlib#8077 with rtol=0. This allows to restore previous tests instead of having to do them with larger state vector deviation. - Put back RaiseValueErrorIfNotProvided as a default for `sub_state_vector`. This allows using `None` for the fallback return value. - Add check for negative values in `keep_indices`. Follow-up to quantumlib#8077
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The current implementation appears to be exponential in space and time. The present change, due originally to jamieas@google.com, replaces python loops with numpy functions motivated by standard methods for computing partial traces. The change is runnable in Colab, including tests and a performance benchmark, at
https://colab.sandbox.google.com/drive/1qWJTnlT6hPXI8cQsTwyqQveEtn7fGhNc?resourcekey=0-67OmbvgwTlf9fnKp3ppbrw