Пример #1
0
def dual_basis_jellium_hamiltonian(grid_length, dimension=3,
                                   wigner_seitz_radius=10., n_particles=None,
                                   spinless=True):
    """Return the jellium Hamiltonian with the given parameters.

    Args:
        grid_length (int): The number of spatial orbitals per dimension.
        dimension (int): The dimension of the system.
        wigner_seitz_radius (float): The radius per particle in Bohr.
        n_particles (int): The number of particles in the system.
                           Defaults to half filling if not specified.
    """
    n_qubits = grid_length ** dimension
    if not spinless:
        n_qubits *= 2

    if n_particles is None:
        # Default to half filling fraction.
        n_particles = n_qubits // 2

    if not (0 <= n_particles <= n_qubits):
        raise ValueError('n_particles must be between 0 and the number of'
                         ' spin-orbitals.')

    # Compute appropriate length scale.
    length_scale = wigner_seitz_length_scale(
        wigner_seitz_radius, n_particles, dimension)

    grid = Grid(dimension, grid_length, length_scale)
    hamiltonian = jellium_model(grid, spinless=spinless, plane_wave=False)
    hamiltonian = normal_ordered(hamiltonian)
    hamiltonian.compress()
    return hamiltonian
Пример #2
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    def test_3d2_with_spin(self):
        dimension = 3
        grid_length = 2
        n_spatial_orbitals = grid_length**dimension
        wigner_seitz_radius = 9.3

        spinless = False
        n_qubits = n_spatial_orbitals
        if not spinless:
            n_qubits *= 2
        n_particles_big = 9

        length_scale = wigner_seitz_length_scale(wigner_seitz_radius,
                                                 n_particles_big, dimension)

        self.grid3 = Grid(dimension, grid_length, length_scale)
        # Get the occupied orbitals of the plane-wave basis Hartree-Fock state.
        hamiltonian = jellium_model(self.grid3, spinless, plane_wave=True)
        hamiltonian = normal_ordered(hamiltonian)
        hamiltonian.compress()

        occupied_states = numpy.array(
            lowest_single_particle_energy_states(hamiltonian, n_particles_big))
        self.hf_state_index3 = numpy.sum(2**occupied_states)

        self.hf_state3 = csc_matrix(([1.0], ([self.hf_state_index3], [0])),
                                    shape=(2**n_qubits, 1))

        self.orbital_occupations3 = [
            digit == '1' for digit in bin(self.hf_state_index3)[2:]
        ][::-1]
        self.occupied_orbitals3 = [
            index for index, occupied in enumerate(self.orbital_occupations3)
            if occupied
        ]

        self.reversed_occupied_orbitals3 = list(self.occupied_orbitals3)
        for i in range(len(self.reversed_occupied_orbitals3)):
            self.reversed_occupied_orbitals3[i] = -1 + int(
                numpy.log2(self.hf_state3.shape[0])
            ) - self.reversed_occupied_orbitals3[i]

        self.reversed_hf_state_index3 = sum(
            2**index for index in self.reversed_occupied_orbitals3)

        operator = (FermionOperator('4^ 2^ 3^ 5 5 4', 2) +
                    FermionOperator('7^ 6^ 7 4', -3.7j) +
                    FermionOperator('3^ 7', 2.1))
        operator = normal_ordered(operator)
        transformed_operator = normal_ordered(
            fourier_transform(operator, self.grid3, spinless))

        expected = -0.2625 - 0.578125j
        # Calculated from expected = expectation(get_sparse_operator(
        #    transformed_operator), self.hf_state3)
        actual = expectation_db_operator_with_pw_basis_state(
            operator, self.reversed_occupied_orbitals3, n_spatial_orbitals,
            self.grid3, spinless)

        self.assertAlmostEqual(expected, actual)
Пример #3
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    def test_hf_state_plane_wave_basis_lowest_single_determinant_state(self):
        grid_length = 7
        dimension = 1
        spinless = True
        n_particles = 4
        length_scale = 2.0

        grid = Grid(dimension, grid_length, length_scale)
        hamiltonian = jellium_model(grid, spinless)
        hamiltonian_sparse = get_sparse_operator(hamiltonian)

        hf_state = hartree_fock_state_jellium(grid,
                                              n_particles,
                                              spinless,
                                              plane_wave=True)

        HF_energy = expectation(hamiltonian_sparse, hf_state)

        for occupied_orbitals in permutations([1] * n_particles + [0] *
                                              (grid_length - n_particles)):
            state_index = numpy.sum(2**numpy.array(occupied_orbitals))
            HF_competitor = csr_matrix(([1.0], ([state_index], [0])),
                                       shape=(2**grid_length, 1))

            self.assertLessEqual(
                HF_energy, expectation(hamiltonian_sparse, HF_competitor))
Пример #4
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    def test_hf_state_energy_close_to_ground_energy_at_high_density(self):
        grid_length = 8
        dimension = 1
        spinless = True
        n_particles = grid_length**dimension // 2

        # High density -> small length_scale.
        length_scale = 0.25

        grid = Grid(dimension, grid_length, length_scale)
        hamiltonian = jellium_model(grid, spinless)
        hamiltonian_sparse = get_sparse_operator(hamiltonian)

        hf_state = hartree_fock_state_jellium(grid,
                                              n_particles,
                                              spinless,
                                              plane_wave=True)

        restricted_hamiltonian = jw_number_restrict_operator(
            hamiltonian_sparse, n_particles)

        E_g = get_ground_state(restricted_hamiltonian)[0]
        E_HF_plane_wave = expectation(hamiltonian_sparse, hf_state)

        self.assertAlmostEqual(E_g, E_HF_plane_wave, places=5)
Пример #5
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    def test_hf_state_energy_same_in_plane_wave_and_dual_basis(self):
        grid_length = 4
        dimension = 1
        wigner_seitz_radius = 10.0
        spinless = False

        n_orbitals = grid_length**dimension
        if not spinless:
            n_orbitals *= 2
        n_particles = n_orbitals // 2

        length_scale = wigner_seitz_length_scale(wigner_seitz_radius,
                                                 n_particles, dimension)

        grid = Grid(dimension, grid_length, length_scale)
        hamiltonian = jellium_model(grid, spinless)
        hamiltonian_dual_basis = jellium_model(grid,
                                               spinless,
                                               plane_wave=False)

        # Get the Hamiltonians as sparse operators.
        hamiltonian_sparse = get_sparse_operator(hamiltonian)
        hamiltonian_dual_sparse = get_sparse_operator(hamiltonian_dual_basis)

        hf_state = hartree_fock_state_jellium(grid,
                                              n_particles,
                                              spinless,
                                              plane_wave=True)
        hf_state_dual = hartree_fock_state_jellium(grid,
                                                   n_particles,
                                                   spinless,
                                                   plane_wave=False)

        E_HF_plane_wave = expectation(hamiltonian_sparse, hf_state)
        E_HF_dual = expectation(hamiltonian_dual_sparse, hf_state_dual)

        self.assertAlmostEqual(E_HF_dual, E_HF_plane_wave)
Пример #6
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    def test_ffft_2d_4x4_equal_expectation_values(self):
        system_size = 4
        n_qubits = 16
        grid = Grid(dimensions=2, length=system_size, scale=1.0)
        dual_basis = jellium_model(grid, spinless=True, plane_wave=False)
        ffft_result = operator_2d_fft_with_reordering(dual_basis, system_size)

        jw_dual_basis = jordan_wigner(dual_basis)
        jw_plane_wave = jordan_wigner(ffft_result)

        # Do plane wave and dual basis calculations together.
        pw_engine = MainEngine()
        pw_wavefunction = pw_engine.allocate_qureg(system_size**2)
        db_engine = MainEngine()
        db_wavefunction = db_engine.allocate_qureg(system_size**2)

        pw_engine.flush()
        db_engine.flush()

        # Choose random state.
        state = numpy.zeros(2**n_qubits, dtype=complex)
        for i in range(len(state)):
            state[i] = (random.random() *
                        numpy.exp(1j * 2 * numpy.pi * random.random()))
        state /= numpy.linalg.norm(state)

        # Put randomly chosen state in the registers.
        pw_engine.backend.set_wavefunction(state, pw_wavefunction)
        db_engine.backend.set_wavefunction(state, db_wavefunction)

        # Apply the FFFT to the dual basis wave function.
        ffft_2d(db_engine, db_wavefunction, system_size)

        # Flush the engine and compute expectation values and eigenvalues.
        pw_engine.flush()
        db_engine.flush()

        plane_wave_expectation_value = (
            pw_engine.backend.get_expectation_value(jw_dual_basis,
                                                    pw_wavefunction))
        dual_basis_expectation_value = (
            db_engine.backend.get_expectation_value(jw_plane_wave,
                                                    db_wavefunction))

        All(Measure) | pw_wavefunction
        All(Measure) | db_wavefunction

        self.assertAlmostEqual(plane_wave_expectation_value,
                               dual_basis_expectation_value)
Пример #7
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    def test_jw_restrict_jellium_ground_state_integration(self):
        n_qubits = 4
        grid = Grid(dimensions=1, length=n_qubits, scale=1.0)
        jellium_hamiltonian = jordan_wigner_sparse(
            jellium_model(grid, spinless=False))

        #  2 * n_qubits because of spin
        number_sparse = jordan_wigner_sparse(number_operator(2 * n_qubits))

        restricted_number = jw_number_restrict_operator(number_sparse, 2)
        restricted_jellium_hamiltonian = jw_number_restrict_operator(
            jellium_hamiltonian, 2)

        energy, ground_state = get_ground_state(restricted_jellium_hamiltonian)

        number_expectation = expectation(restricted_number, ground_state)
        self.assertAlmostEqual(number_expectation, 2)
Пример #8
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    def setUp(self):
        grid_length = 4
        dimension = 1
        wigner_seitz_radius = 10.
        self.spinless = True
        self.n_spatial_orbitals = grid_length**dimension

        n_qubits = self.n_spatial_orbitals
        self.n_particles = 3

        # Compute appropriate length scale and the corresponding grid.
        length_scale = wigner_seitz_length_scale(wigner_seitz_radius,
                                                 self.n_particles, dimension)

        self.grid1 = Grid(dimension, grid_length, length_scale)
        # Get the occupied orbitals of the plane-wave basis Hartree-Fock state.
        hamiltonian = jellium_model(self.grid1, self.spinless, plane_wave=True)
        hamiltonian = normal_ordered(hamiltonian)
        hamiltonian.compress()

        occupied_states = numpy.array(
            lowest_single_particle_energy_states(hamiltonian,
                                                 self.n_particles))
        self.hf_state_index1 = numpy.sum(2**occupied_states)

        self.hf_state1 = csc_matrix(([1.0], ([self.hf_state_index1], [0])),
                                    shape=(2**n_qubits, 1))

        self.orbital_occupations1 = [
            digit == '1' for digit in bin(self.hf_state_index1)[2:]
        ][::-1]
        self.occupied_orbitals1 = [
            index for index, occupied in enumerate(self.orbital_occupations1)
            if occupied
        ]

        self.reversed_occupied_orbitals1 = list(self.occupied_orbitals1)
        for i in range(len(self.reversed_occupied_orbitals1)):
            self.reversed_occupied_orbitals1[i] = -1 + int(
                numpy.log2(self.hf_state1.shape[0])
            ) - self.reversed_occupied_orbitals1[i]

        self.reversed_hf_state_index1 = sum(
            2**index for index in self.reversed_occupied_orbitals1)
 def test_jordan_wigner_dual_basis_hamiltonian_default_to_jellium(self):
     grid = Grid(dimensions=1, scale=1.0, length=4)
     self.assertTrue(
         jordan_wigner_dual_basis_hamiltonian(grid).isclose(
             jordan_wigner(jellium_model(grid, plane_wave=False))))
 def test_plane_wave_hamiltonian_default_to_jellium_with_no_geometry(self):
     grid = Grid(dimensions=1, scale=1.0, length=4)
     self.assertTrue(
         plane_wave_hamiltonian(grid).isclose(jellium_model(grid)))
Пример #11
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    def test_8mode_ffft_with_external_swaps_equal_expectation_values(self):
        n_qubits = 8

        grid = Grid(dimensions=1, length=n_qubits, scale=1.0)
        dual_basis = jellium_model(grid, spinless=True, plane_wave=False)
        ffft_result = normal_ordered(dual_basis)

        # Swap 01234567 to 45670123 for fourier_transform. Additionally,
        # the FFFT's ordering is 04261537, so swap 04261537 to 01234567,
        # and then 01234567 to 45670123.
        swap_mode_list = ([1, 3, 5, 2, 4, 1, 3, 5] +
                          [3, 2, 4, 1, 3, 5, 0, 2, 4, 6, 1, 3, 5, 2, 4, 3])
        for mode in swap_mode_list:
            ffft_result = swap_adjacent_fermionic_modes(ffft_result, mode)
            ffft_result = normal_ordered(ffft_result)

        ffft_result = fourier_transform(ffft_result, grid, spinless=True)
        ffft_result = normal_ordered(ffft_result)

        # After the FFFT, swap 45670123 -> 01234567.
        swap_mode_list = [3, 2, 4, 1, 3, 5, 0, 2, 4, 6, 1, 3, 5, 2, 4, 3]
        for mode in swap_mode_list:
            ffft_result = swap_adjacent_fermionic_modes(ffft_result, mode)
            ffft_result = normal_ordered(ffft_result)

        jw_dual_basis = jordan_wigner(dual_basis)
        jw_plane_wave = jordan_wigner(ffft_result)

        # Do plane wave and dual basis calculations simultaneously.
        pw_engine = MainEngine()
        pw_wavefunction = pw_engine.allocate_qureg(n_qubits)
        db_engine = MainEngine()
        db_wavefunction = db_engine.allocate_qureg(n_qubits)

        pw_engine.flush()
        db_engine.flush()

        # Choose random state.
        state = numpy.zeros(2**n_qubits, dtype=complex)
        for i in range(len(state)):
            state[i] = (random.random() *
                        numpy.exp(1j * 2 * numpy.pi * random.random()))
        state /= numpy.linalg.norm(state)

        # Put randomly chosen state in the registers.
        pw_engine.backend.set_wavefunction(state, pw_wavefunction)
        db_engine.backend.set_wavefunction(state, db_wavefunction)

        prepare_logical_state(pw_wavefunction, i)
        prepare_logical_state(db_wavefunction, i)

        All(H) | [pw_wavefunction[1], pw_wavefunction[3]]
        All(H) | [db_wavefunction[1], db_wavefunction[3]]

        ffft(db_engine, db_wavefunction, n_qubits)
        Ph(3 * numpy.pi / 4) | db_wavefunction[0]

        # Flush the engine and compute expectation values and eigenvalues.
        pw_engine.flush()
        db_engine.flush()

        plane_wave_expectation_value = (
            pw_engine.backend.get_expectation_value(jw_dual_basis,
                                                    pw_wavefunction))
        dual_basis_expectation_value = (
            db_engine.backend.get_expectation_value(jw_plane_wave,
                                                    db_wavefunction))

        All(Measure) | pw_wavefunction
        All(Measure) | db_wavefunction

        self.assertAlmostEqual(plane_wave_expectation_value,
                               dual_basis_expectation_value)