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A python-native version for pyqpanda. Simple, easy, and transparent.

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QPanda-lite

Documentation Status PyPI version Build and Test

QPanda: Quantum Programming Architecture for NISQ Device Application

QPanda-lite should be a simple, easy, and transparent python-native version for QPanda.

Status

Developing. Unstable.

Design principles

  • A clear, and tranparent way to assemble/execute a quantum program
  • Support sync/async modes for execution on a quantum hardware
  • Clear error hints
  • Full, and better documentations
  • Visualization of the quantum program
  • Be able to migrate to different quantum backends

Install

OS

  • Windows
  • Linux (not fully tested)
  • MacOS (not fully tested)

Requirements

  • Python >= 3.8

Optional for quafu execution

manually install via pip :

  • pyquafu (pip install pyquafu)

Optional for qiskit execution

manually install via pip :

  • qiskit (pip install qiskit) and
  • qiskit-ibm-provider (pip install qiskit-ibm-provider) and
  • qiskit-ibmq-provider (pip install qiskit-ibmq-provider)

Optional for C++ simulator

  • CMake >= 3.1
  • C++ compiler (with C++ 14 support), including MSVC, gcc, clang, etc...

Build from source

A minimum version

# Clone the code
git clone https://github.com/Agony5757/QPanda-lite.git
cd QPanda-lite

# install
python setup.py install --no-cpp

For development

git clone https://github.com/Agony5757/QPanda-lite.git
cd QPanda-lite

# install
python setup.py develop

With C++ enabled (quantum circuit simulator written in C++, ensure that CMAKE is included in your environment variables.)

git clone https://github.com/Agony5757/QPanda-lite.git
cd QPanda-lite

# install
python setup.py install

Build the docs

Will be released in the future.

pip

For python 3.8 to 3.10

pip install qpandalite

Tutorials

There are several ways to use QPanda-lite now.

  • Circuit building
  • Run circuit on several backends / dummies (classical-simulation backends)
  • Circuit simulation

1. Circuit build

Refer to test/demo

from qpandalite import Circuit

c = Circuit()
c.rx(1, 0.1)
c.cnot(1, 0)
measure(0, 1, 2, 3)
print(c.circuit)
Function Code sample Explanation
Circuit initialization c = qpandalite.Circuit()
Qubit/cbit initialization No need to specify the number
Gate (like CNOT) c.cnot(1,2) Directly use the qubit number
Measure c.measure(0,1,2) Directly use the qubit number (no support mid-circuit measurement)
Remap c = c.remapping({0:10, 1:11, 2:12}) Input a python dict to indicate the mapping. It creates a new Circuit object.
Output as str c.circuit / c.originir Return a python str

2. Circuit run on Quantum Devices / Dummies

Function Code sample Explanation
"Import" the platform import qpandalite.task.originq as originq This importing is independent from "import qpandalite". Available platforms are under qpandalite.task
Prepare the account See qcloud_config_template
Task submission taskid = originq.submit_task(circuits) Circuits is str or List[str]. Returned taskid can be either list or one str, depending on the number of inputting circuits. All returns are native python data structures. See Circuit build.
Query (synchronously) results = originq.query_by_taskid_sync(taskid) Inputting the taskid by the return of submit_task. The results are always a list (even if you only submit one circuit). All returns are native python data structures.
Query (asynchronously) status_and_result = originq.query_by_taskid(taskid) Inputting the taskid by the return of submit_task. This will immediately return without waiting. Use status_and_result['status'] to see if the computing is finished; use status_and_result['result'] to view results (the same with Query (synchronously), always being a list). All returns are native python data structures.
Handle measurement result results = originq.convert_originq_result(results, style = 'keyvalue', prob_or_shots = 'prob', key_style = 'bin') Convert the raw data to a more human-friendly format. Style includes "keyvalue" and "list", prob_or_shots includes "prob" and "shots". When inputting a list, the output is also a list corresponding to all inputs. All returns are native python data structures.
Calculate expectation exps = [calculate_expectation(result, ['ZII', 'IZI', 'IIZ']) for result in results] Calculate the Z/I expectations accroding to the measurement results. Note that it only accepts the diagonal Hamiltonians. The hamiltonians can be a list, where the output is also a list. However, the input "result" cannot be a list.

2.1 OriginQ

Step 1. Create online config

Refer to qcloud_config_template/originq_template.py

  • Input the necessary information (token, urls, group_size) to call create_originq_online_config
  • You will have the originq_online_config.json in your current working directory (cwd).
  • Now you can submit task to the online chip!

Step 1.1 (Optional). Use originq_dummy

Dummy server is used to emulate the behavior of an online-avaiable quantum computing server, without really accessing the system but with your local computer to simulate the quantum circuit.

  • Input the necessary information (available_qubits and available_topology) to call create_originq_dummy_config.

  • If you want both mode, use create_originq_config and inputting all needed information.

Step 2. Create the circuits and run

Refer to test/demo

2.2 Circuit run on Quafu Device

Step 1. Create online config

Refer to qcloud_config_template/quafu_template.py

  • Input the necessary information (token, urls, group_size) to call create_quafu_online_config
  • You will have the quafu_online_config.json in your cwd.
  • Now you can submit task to the online chip!

Step 2. Create the circuit and run

Todo.

2.3 Circuit run on IBM Device

Todo.

3. Circuit simulation

Refer to test/draft_test/originir_simulator_test.py

import qpandalite.simulator as qsim

sim = qsim.OriginIR_Simulator(reverse_key=False)

originir = '''
QINIT 72
CREG 2
RY q[45],(0.9424777960769379)
RY q[46],(0.9424777960769379)
CZ q[45],q[46]
RY q[45],(-0.25521154)
RY q[46],(0.26327053)
X q[46]
MEASURE q[45],c[0]
MEASURE q[46],c[2]
MEASURE q[52],c[1]
'''

res = sim.simulate(originir)
print(res)
print(sim.state)

# Expect output: 
# [0.23218757036469517, 0.04592184582945769, 0.0, 0.0, 0.6122094271102275, 0.10968115669561962, 0.0, 0.0]
# [(0.4818584546987789+0j), (-0.21429383059121812+0j), (0.7824381298928546+0j), (0.33118145584500897+0j), 0j, 0j, 0j, 0j]

Documentation (not finished)

Readthedocs

Readthedocs: https://qpanda-lite.readthedocs.io/

Build the docs

The doc is based on

cd docs
pip install -r requirements.txt
make html