QPanda-Lite. A python-native version for pyqpanda. Simple, easy, and transparent.
Project description
QPanda-lite
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 >= 3.7
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++)
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
Examples
There are several ways to use QPanda-lite now.
- Circuit building (not supported now)
- Circuit simulation (not supported now)
- Run circuit on several backends
Circuit run on OriginQ Device
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 cwd.
- Now you can submit task to the online chip!
- (Note: if you fail to submit task, replace the token with the newest in json or this template and rerun.)
Step 2. Create the circuit and run
Refer to test/verify_real_chip_bitsequence_origin
- Step 0: Create the online config and import the originq module like this: from qpandalite.task.originq import *
- Step 1.1: Prepare circuits written in OriginIR format (as List[str])
- Step 1.2: Call submit_task_group and you will find the taskid is recorded to the savepath (Note: the upper limit count for quantum circuits is default_task_group_size)
- Step 2.1: Use load_all_online_info to load all taskids (as well as your taskname)
- Step 2.2: Use query_all_task to fetch the data from the platform. If not finished, it will not be fetched and return without waiting.
- Step 2.3: Use query_by_taskid is also available for fetching a single task result. It will return without waiting if the task is not finished.
- Step 3: Delete / move the online_info(savepath) folder to restore everything.
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
Refer to test/verify_real_chip_bitsequence_quafu
Circuit build (unfinished)
Refer to test/draft_test/circuit_builder_test.py
from qpandalite import Circuit
c = Circuit('hello')
c.rx(1, angle = 0.1)
print(c)
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]
Note: Have ImportError? ImportError:qpandalite is not install with QPandaLiteCpp.
You should install with QPandaLiteCpp before importing qpandalite.simulator
Documentation
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