Quick Start

Install OpenQuantumSim from PyPI:

python -m pip install openquantumsim

OpenQuantumSim uses JuliaCall to load the packaged Julia backend. The first solver call on a new machine may spend a few minutes resolving and precompiling Julia packages.

Backend Setup and Startup Speed

Run the backend setup once after installing OpenQuantumSim:

oqs setup-julia

This moves Julia package resolution and precompilation out of the first solver call. For repeated simulation sessions, build a local Julia sysimage:

oqs build-sysimage

The sysimage build can take several minutes, but future solver calls automatically reuse it through JuliaCall. Rebuild it after upgrading Julia or OpenQuantumSim. Set OPENQUANTUMSIM_USE_SYSIMAGE=0 to disable automatic sysimage use for a process, or set OPENQUANTUMSIM_JULIA_SYSIMAGE to point at a custom sysimage.

Spontaneous Emission

This example solves spontaneous emission for a two-level system and compares the excited-state population with the analytic result.

import numpy as np
import openquantumsim as oqs

atom = oqs.SpinSpace(0.5, label="atom")
excited = oqs.basis(atom, "up")

gamma = 0.2
H = 0.0 * oqs.sigmaz(atom)
rho0 = oqs.ket2dm(excited)
collapse = np.sqrt(gamma) * oqs.sigmam(atom)
projector = oqs.Operator(oqs.ket2dm(excited), atom, "P_excited")
times = np.linspace(0.0, 0.2, 3)

result = oqs.mesolve(
    H,
    rho0,
    times,
    c_ops=[collapse],
    e_ops=[projector],
    options=oqs.Options(rtol=1e-8, atol=1e-10),
)

expected = np.exp(-gamma * times)
assert np.allclose(result.expect[0].real, expected, atol=2e-7)
print(result.expect[0].real)

Beyond the Basics

Weak system-bath coupling with the secular Bloch-Redfield equation, where each bath coupling pairs an operator with a spectrum callable:

kappa = 0.4
zero_temperature = lambda omega: kappa if omega < 0 else 0.0

br = oqs.brmesolve(
    H,
    rho0,
    times,
    a_ops=[(oqs.sigmam(atom), zero_temperature)],
    e_ops=[projector],
)

A constant spectrum gamma = g is equivalent to a Lindblad collapse operator sqrt(g) * A, which makes BR results easy to check against mesolve.

Entanglement and correlation diagnostics work on plain NumPy states, so they can be applied to any saved density matrix:

conc = oqs.concurrence(rho)                      # two-qubit states
neg = oqs.negativity(rho, (2, 2), 0, 1)          # any bipartite cut
taus = np.linspace(0.0, 10.0, 201)
wlist, spectrum = oqs.spectrum_2op_1t(
    H, rho0, taus, oqs.sigmap(atom), oqs.sigmam(atom), c_ops=[collapse],
)

Development Install

For local development from source:

git clone https://github.com/mohammadjafariph/OpenQuantumSimulation.git
cd OpenQuantumSimulation
python -m pip install -e ".[dev]"
oqs setup-julia

Run the Python and Julia tests with:

python -m pytest
julia --project=src/OpenQuantumSimJL -e 'using Pkg; Pkg.test()'