2.2 Randomized Measurement

WaveFunction Overlap

This method is based on Probing Rényi entanglement entropy via randomized measurements with deplorizing error mitigation by Simple mitigation of global depolarizing errors in quantum simulations.

randomized_overlap_echo

Here, we assume you already have the calculated data. You can call the function randomized_overlap_echo from qurry.process.randomized_measure to calculate the entropy.

This function requires only three arguments: shots, counts, and selected_classical_registers. All other arguments are optional.

Note that selected_classical_registers expects a list of bitstring indices, NOT qubit indices, as these are distinct.

The following is the arguments of the function:


def randomized_overlap_echo(
    shots: int,
    first_counts: list[dict[str, int]],
    second_counts: list[dict[str, int]],
    selected_classical_registers: Optional[Iterable[int]] = None,
    backend: PostProcessingBackendLabel = DEFAULT_PROCESS_BACKEND,
    pbar: Optional[tqdm.tqdm] = None,
) -> WaveFuctionOverlapResult:
    """Calculate wavefunction overlap
    a.k.a. loschmidt echo when processes time evolution system.

    Args:
        shots (int):
            Shots of the experiment on quantum machine.
        first_counts (list[dict[str, int]]):
            Counts of the experiment on quantum machine.
        second_counts (list[dict[str, int]]):
            Counts of the experiment on quantum machine.
        selected_classical_registers (Optional[Iterable[int]], optional):
            The list of **the index of the selected_classical_registers**.
        backend (ExistingProcessBackendLabel, optional):
            Backend for the process. Defaults to DEFAULT_PROCESS_BACKEND.
        pbar (Optional[tqdm.tqdm], optional):
            The progress bar API, you can use put a :cls:`tqdm` object here.
            This function will update the progress bar description.
            Defaults to None.


    Returns:
        WaveFuctionOverlapResult: A dictionary contains purity, entropy,
            a list of each overlap, puritySD, degree, actual measure range, bitstring range.
    """

This function returns a dictionary that contains the echo, echoSD, and other relevant information. The returned dict contains the following information:

class WaveFuctionOverlapResult(TypedDict):
    """The return type of the post-processing for wavefunction overlap."""

    echo: np.float64
    """The overlap value."""
    echoSD: np.float64
    """The overlap standard deviation."""
    echoCells: dict[int, np.float64]
    """The overlap of each single count."""
    num_classical_registers: int
    """The number of classical registers."""
    classical_registers: Optional[list[int]]
    """The list of the index of the selected classical registers."""
    classical_registers_actually: list[int]
    """The list of the index of the selected classical registers which is actually used."""
    # refactored
    counts_num: int
    """The number of first counts and second counts."""
    taking_time: float
    """The calculation time."""

Dummy Data

from qurry.capsule import quickRead

easy_dummy: dict[str, dict[str, int]] = quickRead("../easy-dummy.json")
large_dummy_list = [easy_dummy["0"] for _ in range(100)]

Simple Example

from qurry.process.randomized_measure import randomized_overlap_echo

test_result_1_1_1 = randomized_overlap_echo(
    4096, large_dummy_list, large_dummy_list, list(range(6))
)
from pprint import pprint

print("| result of randomized_overlap_echo except for purityCells")
pprint({k: v for k, v in test_result_1_1_1.items() if k != "echoCells"})
# "echoCells" is too long we skip it here

print("| result of randomized_overlap_echo[purityCells]")
print(test_result_1_1_1["echoCells"][0])
print(test_result_1_1_1["echoCells"][1])
| result of randomized_overlap_echo except for purityCells
{'classical_registers': [0, 1, 2, 3, 4, 5],
 'classical_registers_actually': [0, 1, 2, 3, 4, 5],
 'counts_num': 100,
 'echo': np.float64(1.0627930164337158),
 'echoSD': np.float64(0.0),
 'num_classical_registers': 8,
 'taking_time': 0.003980862}
| result of randomized_overlap_echo[purityCells]
1.0627930164337158
1.0627930164337158

Integration with your own progress bar

from tqdm import tqdm
import time

all_counts_progress_01 = tqdm(
    [
        (4096, large_dummy_list, list(range(6))),
        (4096, large_dummy_list, list(range(2, 8))),
        (4096, large_dummy_list, list(range(7))),
        (4096, large_dummy_list, list(range(0, 7))),
        (4096, large_dummy_list, [0, 1, 2, 6, 7]),
        (4096, large_dummy_list, [3, 4, 5, 6, 7, 0, 1]),
    ],
    bar_format="| {desc} - {elapsed} < {remaining}",
)

test_result_1_1_2 = []
for tmp_shot, tmp_counts, tmp_partition in all_counts_progress_01:
    print(tmp_partition)
    test_result_1_1_2.append(
        randomized_overlap_echo(
            tmp_shot, tmp_counts, tmp_counts, tmp_partition, pbar=all_counts_progress_01
        )
    )
    time.sleep(0.5)
|  - 00:00 < ?
| Calculate selected classical registers: [0, 1, 2, 3, 4, 5]. - 00:00 < ?
[0, 1, 2, 3, 4, 5]
| Calculate selected classical registers: [0, 1, 2, 3, 4, 5]. - 00:00 < 00:02
| Calculate selected classical registers: [2, 3, 4, 5, 6, 7]. - 00:00 < 00:02
[2, 3, 4, 5, 6, 7]
| Calculate selected classical registers: [2, 3, 4, 5, 6, 7]. - 00:01 < 00:02
| Calculate selected classical registers: [0, 1, 2, 3, 4, 5, 6]. - 00:01 < 00:02
[0, 1, 2, 3, 4, 5, 6]
| Calculate selected classical registers: [0, 1, 2, 3, 4, 5, 6]. - 00:01 < 00:01
| Calculate selected classical registers: [0, 1, 2, 3, 4, 5, 6]. - 00:01 < 00:01
[0, 1, 2, 3, 4, 5, 6]
| Calculate selected classical registers: [0, 1, 2, 3, 4, 5, 6]. - 00:02 < 00:01
| Calculate selected classical registers: [0, 1, 2, 6, 7]. - 00:02 < 00:01      
[0, 1, 2, 6, 7]
| Calculate selected classical registers: [0, 1, 2, 6, 7]. - 00:02 < 00:00
| Calculate selected classical registers: [3, 4, 5, 6, 7, 0, 1]. - 00:02 < 00:00
[3, 4, 5, 6, 7, 0, 1]
| Calculate selected classical registers: [3, 4, 5, 6, 7, 0, 1]. - 00:03 < 00:00
| Calculate selected classical registers: [3, 4, 5, 6, 7, 0, 1]. - 00:03 < 00:00

Using Python backend

It will be slow. You’d better think twice before using it.

all_counts_progress_02 = tqdm(
    [
        (4096, large_dummy_list, list(range(6))),
        (4096, large_dummy_list, list(range(2, 8))),
        (4096, large_dummy_list, list(range(7))),
        (4096, large_dummy_list, list(range(0, 7))),
        (4096, large_dummy_list, [0, 1, 2, 6, 7]),
        (4096, large_dummy_list, [3, 4, 5, 6, 7, 0, 1]),
    ],
    bar_format="| {desc} - {elapsed} < {remaining}",
)


test_result_1_1_2 = []
for tmp_shot, tmp_counts, tmp_partition in all_counts_progress_02:
    print(tmp_partition)
    test_result_1_1_2.append(
        randomized_overlap_echo(
            tmp_shot,
            tmp_counts,
            tmp_counts,
            tmp_partition,
            pbar=all_counts_progress_02,
            backend="Python",
        )
    )
    time.sleep(0.5)
|  - 00:00 < ?
| Calculate selected classical registers: [0, 1, 2, 3, 4, 5]. - 00:00 < ?
[0, 1, 2, 3, 4, 5]
| Calculate selected classical registers: [0, 1, 2, 3, 4, 5]. - 00:05 < 00:29
| Calculate selected classical registers: [2, 3, 4, 5, 6, 7]. - 00:05 < 00:29
[2, 3, 4, 5, 6, 7]
| Calculate selected classical registers: [2, 3, 4, 5, 6, 7]. - 00:12 < 00:24
| Calculate selected classical registers: [0, 1, 2, 3, 4, 5, 6]. - 00:12 < 00:24
[0, 1, 2, 3, 4, 5, 6]
| Calculate selected classical registers: [0, 1, 2, 3, 4, 5, 6]. - 00:18 < 00:19
| Calculate selected classical registers: [0, 1, 2, 3, 4, 5, 6]. - 00:18 < 00:19
[0, 1, 2, 3, 4, 5, 6]
| Calculate selected classical registers: [0, 1, 2, 3, 4, 5, 6]. - 00:25 < 00:12
| Calculate selected classical registers: [0, 1, 2, 6, 7]. - 00:25 < 00:12      
[0, 1, 2, 6, 7]
| Calculate selected classical registers: [0, 1, 2, 6, 7]. - 00:31 < 00:06
| Calculate selected classical registers: [3, 4, 5, 6, 7, 0, 1]. - 00:31 < 00:06
[3, 4, 5, 6, 7, 0, 1]
| Calculate selected classical registers: [3, 4, 5, 6, 7, 0, 1]. - 00:37 < 00:00
| Calculate selected classical registers: [3, 4, 5, 6, 7, 0, 1]. - 00:37 < 00:00

Post-Process Availablities and Version Info

from qurry.process.status import AVAIBILITY_STATESHEET

AVAIBILITY_STATESHEET
 | Qurrium version: 0.13.0
---------------------------------------------------------------------------
 ### Qurrium Post-Processing
   - Backend Availability ................... Python Cython Rust   JAX   
 - randomized_measure
   - entangled_entropy.entropy_core_2 ....... Yes    Depr.  Yes    No    
   - entangle_entropy.purity_cell_2 ......... Yes    Depr.  Yes    No    
   - entangled_entropy_v1.entropy_core ...... Yes    Depr.  Yes    No    
   - entangle_entropy_v1.purity_cell ........ Yes    Depr.  Yes    No    
   - wavefunction_overlap.echo_core_2 ....... Yes    Depr.  Yes    No    
   - wavefunction_overlap.echo_cell_2 ....... Yes    Depr.  Yes    No    
   - wavefunction_overlap_v1.echo_core ...... Yes    Depr.  Yes    No    
   - wavefunction_overlap_v1.echo_cell ...... Yes    Depr.  Yes    No    
 - hadamard_test
   - purity_echo_core ....................... Yes    No     Yes    No    
 - magnet_square
   - magnsq_core ............................ Yes    No     Yes    No    
 - string_operator
   - strop_core ............................. Yes    No     Yes    No    
 - classical_shadow
   - rho_m_core ............................. Yes    No     No     Yes   
 - utils
   - randomized ............................. Yes    Depr.  Yes    No    
   - counts_process ......................... Yes    No     Yes    No    
   - bit_slice .............................. Yes    No     Yes    No    
   - dummy .................................. Yes    No     Yes    No    
   - test ................................... Yes    No     Yes    No    
---------------------------------------------------------------------------
   + Yes ...... Working normally.
   + Error .... Exception occurred.
   + No ....... Not supported.
   + Depr. .... Deprecated.
---------------------------------------------------------------------------
by <Hoshi>