Sample-based quantum diagonalization (SQD) release notes

Upcoming release

Bug Fixes

pyscf is no longer considered a dependency on Windows, where it fails to install. However, Windows remains an unsupported platform.

0.8.0

New Features

$Added support for Python 3.9.$
$All functions which take a rand_seed argument now also accept a numpy.random.Generator instance as the rand_seed .$

Upgrade Notes

The ground state returned by qiskit_addon_sqd.fermion.solve_fermion() will now be an instance of qiskit_addon_sqd.fermion.SCIState, rather than a PySCF SCIVector instance.

0.7.0

Bug Fixes

$Fixed a bug in qiskit_addon_sqd.fermion.solve_fermion() and qiskit_addon_sqd.fermion.optimize_orbitals() which causes the determinants for spin-up and spin-down to be incorrectly flipped before solving.$
$Fixed a bug in open-shell workflows which would cause qiskit_addon_sqd.fermion.optimize_orbitals() to crash with a malloc error.$

0.6.0

Upgrade Notes

Specifying addresses as a keyword argument to qiskit_addon_sqd.fermion.solve_fermion() and qiskit_addon_sqd.fermion.optimize_orbitals() is no longer supported. Users may still pass addresses as the first positional argument; however, this usage is deprecated. Users are encouraged to pass the bitstring matrix defining the subspace as the first positional arguments to these functions, as shown below.

To upgrade, change this code

# DEPRECATED CODE
from qiskit_addon_sqd.fermion import (
    bitstring_matrix_to_sorted_addresses,
    solve_fermion,
    optimize_orbitals,
)
 
bitstring_matrix = ...
addresses = bitstring_matrix_to_sorted_addresses(bitstring_matrix, open_shell=open_shell)
energy, coeffs, occs, spin = solve_fermion(
                                 addresses=addresses,
                                 hcore=hcore,
                                 eri=eri,
                             )
...
e_oo, rotation, occs_oo = optimize_orbitals(
                              addresses=addresses,
                              hcore=hcore,
                              eri=eri,
                          )
 
### SHOULD BECOME ###
 
# NEW CODE
from qiskit_addon_sqd.fermion import solve_fermion, optimize_orbitals
 
bitstring_matrix = ...
energy, coeffs, occs, spin = solve_fermion(
                                 bitstring_matrix,
                                 hcore=hcore,
                                 eri=eri,
                             )
...
e_oo, rotation, occs_oo = optimize_orbitals(
                              bitstring_matrix,
                              hcore=hcore,
                              eri=eri,
                          )

Deprecation Notes

The qiskit_addon_sqd.fermion.bitstring_matrix_to_sorted_addresses() function has been deprecated in favor of qiskit_addon_sqd.fermion.bitstring_matrix_to_ci_strs(). These two functions behave the same with one key exception – qiskit_addon_sqd.fermion.bitstring_matrix_to_sorted_addresses() returns the configurations as tuple(spin_dn, spin_up); whereas, qiskit_addon_sqd.fermion.bitstring_matrix_to_ci_strs() returns the configurations as tuple(spin_up, spin_dn).

To migrate
```
from qiskit_addon_sqd.fermion import (
    bitstring_matrix_to_sorted_addresses,
    bitstring_matrix_to_ci_strs,
)
 
# DEPRECATED CODE
bs_matrix = ...
addr_dn, addr_up = bitstring_matrix_to_sorted_addresses(bs_matrix, open_shell=True)
 
### SHOULD BECOME ###
 
# NEW CODE
bs_matrix = ...
ci_strs_up, ci_strs_dn = bitstring_matrix_to_ci_strs(bs_matrix, open_shell=True)
```
$The addresses argument to qiskit_addon_sqd.fermion.solve_fermion() and qiskit_addon_sqd.fermion.optimize_orbitals() has been deprecated in favor of bitstring_matrix . Users are no longer required to convert their configurations to integers; instead, they should now pass in the bitstring matrix specifying the subspace onto which to project and diagonalize the Hamiltonian. The conversion to the integer representation of determinants will be done internally.$

Bug Fixes

$Fixed a bug in qiskit_addon_sqd.configuration_recovery.recover_configurations() which would sometimes cause a divide-by-zero error when calculating individual bit-flip probability.$
$Fixes a bug that caused configuration recovery to fail on bitstrings of length greater than 72.$

0.5.0

Upgrade Notes

The qiskit_addon_sqd.counts.generate_counts_bipartite_hamming(), qiskit_addon_sqd.subsampling.postselect_and_subsample(), and qiskit_addon_sqd.configuration_recovery.post_select_by_hamming_weight() now require the hamming_right and hamming_left arguments to be specified as keyword arguments. Additionally, the samples_per_batch and n_batches arguments to qiskit_addon_sqd.subsampling.postselect_and_subsample() should now be passed as keyword arguments.

To upgrade

from qiskit_addon_sqd.configuration_recovery import post_select_by_hamming_weight
from qiskit_addon_sqd.subsampling import postselect_and_subsample
from qiskit_addon_sqd.counts import generate_counts_bipartite_hamming
 
counts = generate_counts_bipartite_hamming(num_samples, num_bits, num_elec_a, num_elec_b)
 
...
 
bs_mat = post_select_by_hamming_weight(bs_mat_full, num_elec_a, num_elec_b)    
 
...
 
batches = postselect_and_subsample(
    bs_mat,
    probs_arr,
    num_elec_a,
    num_elec_b,
    samples_per_batch,
    num_batches,
)

should be changed to

from qiskit_addon_sqd.configuration_recovery import post_select_by_hamming_weight
from qiskit_addon_sqd.subsampling import postselect_and_subsample
from qiskit_addon_sqd.counts import generate_counts_bipartite_hamming
 
counts = generate_counts_bipartite_hamming(num_samples, num_bits, hamming_right=num_elec_a, hamming_left=num_elec_b)
 
...
 
bs_mat = post_select_by_hamming_weight(bs_mat_full, hamming_right=num_elec_a, hamming_left=num_elec_b)
 
...
 
batches = postselect_and_subsample(
    bs_mat,
    probs_arr,
    hamming_right=num_elec_a,
    hamming_left=num_elec_b,
    samples_per_batch=samples_per_batch,
    num_batches=num_batches,
)

0.4.0

Prelude

This is a minor release which introduces a couple of small, but important, breaking changes to to the API. These changes allow for a more consistent pattern in specifying the number of alpha and beta electrons throughout both the chemistry and non-chemistry functions in the API.

Upgrade Notes

The qiskit_addon_sqd.counts.generate_counts_bipartite_hamming(), qiskit_addon_sqd.subsampling.postselect_and_subsample(), and qiskit_addon_sqd.configuration_recovery.post_select_by_hamming_weight() now take the hamming_right positional argument before the hamming_left argument to better match the rest of the workflow.

To upgrade

from qiskit_addon_sqd.configuration_recovery import post_select_by_hamming_weight
from qiskit_addon_sqd.subsampling import postselect_and_subsample
from qiskit_addon_sqd.counts import generate_counts_bipartite_hamming
 
counts = generate_counts_bipartite_hamming(num_samples, num_bits, num_elec_b, num_elec_a)
 
...
 
bs_mat = post_select_by_hamming_weight(bs_mat_full, num_elec_b, num_elec_a)    
 
...
 
batches = postselect_and_subsample(
    bs_mat,
    probs_arr,
    num_elec_b,
    num_elec_a,
    samples_per_batch,
    n_batches,
)

should be changed to

from qiskit_addon_sqd.configuration_recovery import post_select_by_hamming_weight
from qiskit_addon_sqd.subsampling import postselect_and_subsample
from qiskit_addon_sqd.counts import generate_counts_bipartite_hamming
 
counts = generate_counts_bipartite_hamming(num_samples, num_bits, num_elec_a, num_elec_b)
 
bs_mat = post_select_by_hamming_weight(bs_mat_full, num_elec_a, num_elec_b)
 
...
 
batches = postselect_and_subsample(
    bs_mat,
    probs_arr,
    num_elec_a,
    num_elec_b,
    samples_per_batch,
    n_batches,
)

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