HI-VQE Qiskit Function Utilities

This package is intended to provide some utilities to help users of Qunova's HI-VQE Qiskit Function.

Current Features

Helps licensed users submit their license token to the function with encryption.

The below example shows how this package can be used to wrap the HI-VQE Qiskit Function retrieved from the Qiskit IBM Catalog to properly submit your token:

import math
import h5py
from qiskit_ibm_catalog import QiskitFunctionsCatalog, QiskitServerless
from hivqe_qiskit_function_utils import FunctionWrapper


catalog = QiskitFunctionsCatalog(token="your_qiskit_functions_catalog_token", 
                                 channel="ibm_quantum_platform", 
                                 instance="your_ibm_instance")

serverless = QiskitServerless(token="your_qiskit_functions_catalog_token", 
                              channel="ibm_quantum_platform", 
                              instance="your_ibm_instance")

molecule_geometry = f"""
O 0 0 0;
H {-0.957*math.sin(math.radians(104.5)/2.0)} {0.957*math.cos(math.radians(104.5)/2.0)} 0;
H {0.957*math.sin(math.radians(104.5)/2.0)} {0.957*math.cos(math.radians(104.5)/2.0)} 0
"""

hivqe = FunctionWrapper(token="your_hivqe_license_token", 
                        function=catalog.load("qunova/hivqe-chemistry"))

job = hivqe.run(
    geometry=molecule_geometry,
    backend_name="ibm_torino",
    max_states=10000,
    max_expansion_states=1000,
    hivqe_options={"ansatz": "epa", "max_iter": 10},
)

result = job.result()

# Extract the results
energy = result["energy"]
results_file_name = result["results_file_name"]
energy_variance = result["energy_variance"]
total_energy_history = result["energy_history"]

# Download the h5 results file to the current directory
serverless.file_download(results_file_name, 
                         catalog.load("qunova/hivqe-chemistry"))

# Read all data from the results file
with h5py.File(results_file_name, "r") as f:
    states = f["states"][:]
    eigenvector = f["eigenvector"][:]
    energy_history = f["energy_history"][:]
    final_energy = f["final_energy"][0]
    final_energy_variance = f["final_energy_variance"][0]

# Check the logs
logs = job.logs()