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https://github.com/KMU-quantum-classroom/qiskit-classroom-converter

qiskit classroom's quantum circuit / bra-ket notation / matrix converter package
https://github.com/KMU-quantum-classroom/qiskit-classroom-converter

converter qiskit

Last synced: 17 days ago
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qiskit classroom's quantum circuit / bra-ket notation / matrix converter package

Host: GitHub
URL: https://github.com/KMU-quantum-classroom/qiskit-classroom-converter
Owner: KMU-quantum-classroom
License: apache-2.0
Created: 2023-05-05T07:13:26.000Z (about 1 year ago)
Default Branch: main
Last Pushed: 2024-06-03T06:29:31.000Z (27 days ago)
Last Synced: 2024-06-04T02:47:07.801Z (26 days ago)
Topics: converter, qiskit
Language: Python
Homepage: https://pypi.org/project/qiskit-classroom-converter/
Size: 295 KB
Stars: 2
Watchers: 0
Forks: 0
Open Issues: 3
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
- Security: SECURITY.md

Lists

awesome-qiskit - qiskit-classroom-converter - Convert quantum circuits, matrices, and bra-ket strings. this converter includes the following conversion functions: quantum circuit to bra-ket notation, quantum circuit to matrix, matrix to quantum circuit, bra-ket notation to matrix. (Community)

README

        # 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}                               |

```python

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

```python

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

```bash

pip install qiskit-classroom-converter

```

## Docker Pull & Run

Alternative installation with docker image.

```shell

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

```python

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](example.py)

## How to test the software

```shell

python -m unittest -v

```

or 

```shell

tox

```

## ARM Platform

Mac ARM chips users may have issues running this package.

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

```shell

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)