Skip to main content

Quingo Simulator Backend QuaLeSim

Project description

Start

The QuaLeSim(Quantum Lego Simulator) is an adapted version of DQCSim. For quantum circuit simulation, you can simulate QUIET-s and QCIS instruction by it. And what's more, now the QuaLeSim is integrated into the backend of Quingo, you can use it directly after installing quingoc and quingo-runtime. More inforemations is available in [[#Install]]

Install

The QuaLeSim now is only for Linux platform.

  1. 环境准备:
    • Linux platform with python>=3.7
    • Rust # if you don't have rust, make sure you have 'curl' to install rust in the setup.py .
  2. 安装说明:
    • 目前已经将 qualesim 及其相关插件上传至 PYPI,可以选择下面两种方式安装:
    1. 一键安装qualesim 及其相关插件:
      • pip install qualesim[TEQUILA]
      • 注:tequila目前尚未开源,tequila不会默认安装。
        • 若需要使用Tequila模拟器,可以在qualesim之后加[TEQUILA]来安装
    2. 单独安装各个模块插件:
      • pip install qualesim # 安装qualesim本体
      • pip install qualesim-tequila # 安装 tequila 后端,tequila尚未开源,需要单独安装

Quick Start

Quick Start is for users use the Simulator directly or use it with quingo-runtime. Some examples are available below.

  1. For independent users:
    • The Simulator can simulate QUIET-s and QCIS instructions, you can use it directly:
from qualesim.plugin import *
from qualesim.host import *
sim = Simulator(stderr_verbosity=Loglevel.INFO)

sim.with_frontend("<path-to-qcis-file>", verbosity=Loglevel.INFO)
# sim.with_frontend("<path-to-qi-file>", verbosity=Loglevel.INFO)
# Loglevel is for output information for DEBUG/INFO/OFF
# If you only want the simulation output, please set it OFF

sim.with_backend("quantumsim", verbosity=Loglevel.INFO)
# sim.with_backend("tequila", verbosity=Loglevel.INFO)
# now we have DQCsim-Tequila and DQCsim-QuantumSim backend for Simulator

sim.simulate()
res = sim.run(measure_mod="state_vector", num_shots=10)
# Start the simulation with different exe mod,
# measure_mod="one_shot" and num_shots=int /
#             "state_vector"
# the output should be

sim.stop()
final_state = dict()
final_state = res["res"]
print(final_state)
  • the output is :
measure_mod="state_vector":
res1(M Q1, M Q2) = {'classical': {'Q1': 1, 'Q2': 1}, 'quantum': (['Q3'], [0j, (1+0j)])}
# classical is qubit measured, quantum is qubit unmeasured with state vector.
res2() = {'classical': {}, 'quantum': (['Q1', 'Q2', 'Q3'], [(0.7071067811865472+0j), 0j, 0j, 0j, 0j, 0j, 0j, (0.7071067811865478+0j)])}

measure_mod="one_shot", num_shots=10:
# classical is classical value, quantum is qubit measured. and they are one to one correspondence
res(measure(q1)->c1, measure(q2)->c2) = {'quantum': [['q1', 'q2'], [[0, 0], [0, 0], [1, 1], [0, 0], [0, 0], [1, 1], [0, 0], [0, 0], [1, 1], [1, 1]]], 'classical': [{'c1': [0], 'c2': [0]}, {'c1': [0], 'c2': [0]}, {'c1': [1], 'c2': [1]}, {'c1': [0], 'c2': [0]}, {'c1': [0], 'c2': [0]}, {'c1': [1], 'c2': [1]}, {'c1': [0], 'c2': [0]}, {'c1': [0], 'c2': [0]}, {'c1': [1], 'c2': [1]}, {'c1': [1], 'c2': [1]}]}
  1. For Quingo Users
    • You should follow the [[#Install|extern: quingoc & quingo-runtime installation]] to install it.
from quingo import *
import qututor.global_config as gc
from quingo.backend.qisa import Qisa

# input quingo file and simulate qu func
qu_file = gc.quingo_dir / "ghz.qu"
circ_name = "GHZ_state"

# set the qisa, and it is the output instructions QUIET,
# you can change to Qisa.QCIS or others.
task = Quingo_task(
    qu_file,
    circ_name,
    qisa=Qisa.QUIET,
)

num_shots = 10
cfg = ExeConfig(ExeMode.SimFinalResult, num_shots)
num_qubits = 3

# now backend BackendType.QUANTUM_SIM, BackendType.DQCSIM_TEQUILA
# BackendType.DQCSIM_QUANTUMSIM, BackendType.SYMQC is available.
# method 1
qasm_fn = compile(task, params=(num_qubits,))
res = execute(qasm_fn, BackendType.QUANTUM_SIM, cfg)

# method 2
# res = call(task, (num_qubits,), BackendType.DQCSIM_TEQUILA, cfg)

print("res: ", res)
  • the output is :
measure_mod="state_vector":
res1(M Q1, M Q2) = {'classical': {'Q1': 1, 'Q2': 1}, 'quantum': (['Q3'], [0j, (1+0j)])}
# classical is qubit measured, quantum is qubit unmeasured with state vector.
res2() = {'classical': {}, 'quantum': (['Q1', 'Q2', 'Q3'], [(0.7071067811865472+0j), 0j, 0j, 0j, 0j, 0j, 0j, (0.7071067811865478+0j)])}

measure_mod="one_shot", num_shots=10:
# quingo-runtime only have quantum values.
res(measure(q1)->c1, measure(q2)->c2) =(['q1', 'q2'], [[0, 0], [0, 0], [1, 1], [0, 0], [0, 0], [1, 1], [0, 0], [0, 0], [1, 1], [1, 1]])

FAQ

  1. for install
    1. your environment donot have rust?
    2. if you have llvm in your platform, the setup install maybe very slow.
      • the problem is to be solved.
    3. install about quingoc
  2. for use
    1. when you first use it, there would be a problem 核心已转储
      • it is the dqcsim's problem and is to be solved.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

qualesim-1.0.2-cp312-cp312-manylinux2014_x86_64.whl (11.7 MB view hashes)

Uploaded CPython 3.12

qualesim-1.0.2-cp311-cp311-manylinux2014_x86_64.whl (11.7 MB view hashes)

Uploaded CPython 3.11

qualesim-1.0.2-cp310-cp310-manylinux2014_x86_64.whl (11.7 MB view hashes)

Uploaded CPython 3.10

qualesim-1.0.2-cp39-cp39-manylinux2014_x86_64.whl (11.7 MB view hashes)

Uploaded CPython 3.9

qualesim-1.0.2-cp38-cp38-manylinux2014_x86_64.whl (11.7 MB view hashes)

Uploaded CPython 3.8

qualesim-1.0.2-cp37-cp37m-manylinux2014_x86_64.whl (11.7 MB view hashes)

Uploaded CPython 3.7m

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page