qiskit-classroom-converter

Qiskit classroom Converter

0.5.0 (2024-03-06) : The Version has been updated to be compatible with Qiskit 1.0.0 and Python 3.12.

Documents

https://kmu-quantum-classroom.github.io/qiskit-classroom-converter/qiskit_class_converter.html

Official USER Guide

https://kmu-quantum-classroom.github.io/documents/overview.html

Support convert method

• quantum circuit to bra-ket notation
• quantum circuit to matrix
• matrix to quantum circuit
• string to bra-ket notation

---

Options

convert method	option
QC_TO_BRA_KET	expression{simplify, expand}, print{raw}
QC_TO_MATRIX	print{raw}
MATRIX_TO_QC	label{str}
STR_TO_BRA_KET	print{raw}

from qiskit_class_converter import ConversionService

ConversionService(conversion_type="QC_TO_BRA_KET", option={"expression": "simplify"})

Required data

• MATRIX_TO_QC
  • User's QuantumCircuit object

from qiskit import QuantumCircuit
from qiskit_class_converter import ConversionService

input_value = [
    [1, 0, 0, 0],
    [0, 0, 0, 1],
    [0, 0, 1, 0],
    [0, 1, 0, 0]
]
sample_converter = ConversionService(conversion_type="MATRIX_TO_QC")
result = sample_converter.convert(input_value=input_value)
# using user's QuantumCircuit object
quantum_circuit = QuantumCircuit(2, 2)
quantum_circuit.append(result, [0, 1])

How to Install

pip install qiskit-classroom-converter

Docker Pull & Run

Alternative installation with docker image.

docker pull ghcr.io/kmu-quantum-classroom/qiskit-classroom-converter
docker run -p 8888:8888 ghcr.io/kmu-quantum-classroom/qiskit-classroom-converter

Dependencies

• qiskit

Usage

from qiskit import QuantumCircuit
from qiskit_class_converter import ConversionService
# quantum circuit to matrix
quantum_circuit = QuantumCircuit(2, 2)
quantum_circuit.x(0)
quantum_circuit.cx(0, 1)
sample_converter = ConversionService(conversion_type="QC_TO_MATRIX")
result = sample_converter.convert(input_value=quantum_circuit)

code : example.py

How to test the software

python -m unittest -v

or

tox

ARM Platform

Mac ARM chips users may have issues running this package.

We have provided a Dockerfile, which can be used docker-compose.

docker-compose up --build

Acknowledgement

• 국문 : "본 연구는 2022년 과학기술정보통신부 및 정보통신기획평가원의 SW중심대학사업의 연구결과로 수행되었음"(2022-0-00964)
• English : "This research was supported by the MIST(Ministry of Science, ICT), Korea, under the National Program for Excellence in SW), supervised by the IITP(Institute of Information & communications Technology Planning & Evaluation) in 2022"(2022-0-00964)