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| # (C) Copyright IBM 2024. | ||
| # | ||
| # This code is licensed under the Apache License, Version 2.0. You may | ||
| # obtain a copy of this license in the LICENSE.txt file in the root directory | ||
| # of this source tree or at http://www.apache.org/licenses/LICENSE-2.0. | ||
| # | ||
| # Any modifications or derivative works of this code must retain this | ||
| # copyright notice, and modified files need to carry a notice indicating | ||
| # that they have been altered from the originals. | ||
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| """Tests for sampling Slater determinants.""" | ||
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| from __future__ import annotations | ||
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| import itertools | ||
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| import numpy as np | ||
| import pytest | ||
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| import ffsim | ||
| from ffsim.states.bitstring import BitstringType | ||
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| @pytest.mark.parametrize( | ||
| "norb, nelec, bitstring_type", | ||
| [ | ||
| (norb, nelec, bitstring_type) | ||
| for (norb, nelec), bitstring_type in itertools.product( | ||
| ffsim.testing.generate_norb_nelec(range(1, 5)), BitstringType | ||
| ) | ||
| ], | ||
| ) | ||
| def test_sample_slater_determinant_spinful( | ||
| norb: int, nelec: tuple[int, int], bitstring_type: BitstringType | ||
| ): | ||
| """Test sample Slater determinant, spinful.""" | ||
| rng = np.random.default_rng(1234) | ||
| shots = 1000 | ||
| for _ in range(min(2, ffsim.dim(norb, nelec))): | ||
| rotation_a = ffsim.random.random_unitary(norb, seed=rng) | ||
| rotation_b = ffsim.random.random_unitary(norb, seed=rng) | ||
| occupied_orbitals = ffsim.testing.random_occupied_orbitals( | ||
| norb, nelec, seed=rng | ||
| ) | ||
| rdm_a, rdm_b = ffsim.slater_determinant_rdms( | ||
| norb, occupied_orbitals, (rotation_a, rotation_b) | ||
| ) | ||
| vec = ffsim.slater_determinant( | ||
| norb, occupied_orbitals, (rotation_a, rotation_b) | ||
| ) | ||
| test_distribution = np.abs(vec) ** 2 | ||
| samples = ffsim.sample_slater_determinant( | ||
| (rdm_a, rdm_b), | ||
| norb, | ||
| nelec, | ||
| shots=shots, | ||
| bitstring_type=bitstring_type, | ||
| seed=rng, | ||
| ) | ||
| addresses = ffsim.strings_to_addresses(samples, norb, nelec) | ||
| indices, counts = np.unique(addresses, return_counts=True) | ||
| assert np.sum(counts) == shots | ||
| empirical_distribution = np.zeros(ffsim.dim(norb, nelec), dtype=float) | ||
| empirical_distribution[indices] = counts / shots | ||
| assert np.sum(np.sqrt(test_distribution * empirical_distribution)) > 0.99 | ||
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| @pytest.mark.parametrize( | ||
| "norb, nelec, bitstring_type", | ||
| [ | ||
| (norb, nelec, bitstring_type) | ||
| for (norb, nelec), bitstring_type in itertools.product( | ||
| ffsim.testing.generate_norb_nocc(range(1, 5)), BitstringType | ||
| ) | ||
| ], | ||
| ) | ||
| def test_sample_slater_determinant_spinless( | ||
| norb: int, nelec: int, bitstring_type: BitstringType | ||
| ): | ||
| """Test sample Slater determinant, spinless.""" | ||
| rng = np.random.default_rng(1234) | ||
| shots = 1000 | ||
| rotation = ffsim.random.random_unitary(norb, seed=rng) | ||
| for occupied_orbitals in itertools.combinations(range(norb), nelec): | ||
| rdm = ffsim.slater_determinant_rdms(norb, occupied_orbitals, rotation, rank=1) | ||
| vec = ffsim.slater_determinant(norb, occupied_orbitals, rotation) | ||
| test_distribution = np.abs(vec) ** 2 | ||
| samples = ffsim.sample_slater_determinant( | ||
| rdm, norb, nelec, shots=shots, bitstring_type=bitstring_type, seed=rng | ||
| ) | ||
| addresses = ffsim.strings_to_addresses(samples, norb, nelec) | ||
| indices, counts = np.unique(addresses, return_counts=True) | ||
| assert np.sum(counts) == shots | ||
| empirical_distribution = np.zeros(ffsim.dim(norb, nelec), dtype=float) | ||
| empirical_distribution[indices] = counts / shots | ||
| assert np.sum(np.sqrt(test_distribution * empirical_distribution)) > 0.99 | ||
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| def test_sample_slater_determinant_large(): | ||
| """Test sample Slater determinant for a larger number of orbitals.""" | ||
| norb = 6 | ||
| nelec = (3, 2) | ||
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| rng = np.random.default_rng(1234) | ||
| shots = 5000 | ||
| rotation_a = ffsim.random.random_unitary(norb, seed=rng) | ||
| rotation_b = ffsim.random.random_unitary(norb, seed=rng) | ||
| occupied_orbitals = ((0, 2, 3), (2, 4)) | ||
| rdm_a, rdm_b = ffsim.slater_determinant_rdms( | ||
| norb, occupied_orbitals, (rotation_a, rotation_b) | ||
| ) | ||
| vec = ffsim.slater_determinant(norb, occupied_orbitals, (rotation_a, rotation_b)) | ||
| test_distribution = np.abs(vec) ** 2 | ||
| samples = ffsim.sample_slater_determinant( | ||
| (rdm_a, rdm_b), norb, nelec, shots=shots, seed=rng | ||
| ) | ||
| addresses = ffsim.strings_to_addresses(samples, norb, nelec) | ||
| indices, counts = np.unique(addresses, return_counts=True) | ||
| assert np.sum(counts) == shots | ||
| empirical_distribution = np.zeros(ffsim.dim(norb, nelec), dtype=float) | ||
| empirical_distribution[indices] = counts / shots | ||
| assert np.sum(np.sqrt(test_distribution * empirical_distribution)) > 0.99 | ||
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| def test_sample_slater_determinant_restrict(): | ||
| """Test sample Slater determinant with subset of orbitals.""" | ||
| norb = 8 | ||
| nelec = (4, 3) | ||
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| shots = 10 | ||
| occupied_orbitals = ((0, 2, 3, 5), (2, 3, 4)) | ||
| rdm_a, rdm_b = ffsim.slater_determinant_rdms(norb, occupied_orbitals) | ||
| samples = ffsim.sample_slater_determinant( | ||
| (rdm_a, rdm_b), norb, nelec, orbs=([1, 2, 5], [3, 4, 5]), shots=shots | ||
| ) | ||
| assert samples == ["011110"] * 10 |
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