Solvers

Python solver entry points.

openquantumsim.solvers.mesolve(H, rho0, tlist, *, c_ops=None, e_ops=None, state_observables=None, options=None)[source]

Solve a Lindblad master equation.

Supports time-independent Hamiltonians and TimeDependentHamiltonian objects with scalar coefficients.

Parameters:

  • H (Operator | TimeDependentHamiltonian)

  • rho0 (ndarray[tuple[Any, ...], dtype[complex128]])

  • tlist (Sequence[float])

  • c_ops (Sequence[Operator] | None)

  • e_ops (Sequence[Operator] | None)

  • state_observables (Mapping[str, Callable[[ndarray[tuple[Any, ...], dtype[complex128]]], Any]] | None)

  • options (Options | None)

Return type:

Result

openquantumsim.solvers.mcsolve(H, psi0, tlist, *, c_ops=None, e_ops=None, n_traj=None, state_observables=None, options=None)[source]

Run Monte Carlo wave-function trajectories.

Built-in state_observables created by openquantumsim.state_metrics() are aggregated by the backend when they can be represented as linear expectation values or pure-trajectory constants. Arbitrary Python callbacks remain available through single_trajectory() or deterministic mesolve() runs with saved state access.

Parameters:

  • H (Operator)

  • psi0 (ndarray[tuple[Any, ...], dtype[complex128]])

  • tlist (Sequence[float])

  • c_ops (Sequence[Operator] | None)

  • e_ops (Sequence[Operator] | None)

  • n_traj (int | None)

  • state_observables (Mapping[str, Callable[[ndarray[tuple[Any, ...], dtype[complex128]]], Any]] | None)

  • options (Options | None)

Return type:

Result

openquantumsim.solvers.single_trajectory(H, psi0, tlist, *, c_ops=None, e_ops=None, state_observables=None, options=None)[source]

Run one Monte Carlo wave-function trajectory.

Set Options(save_states=True) to return the ket at each requested time.

Parameters:

  • H (Operator)

  • psi0 (ndarray[tuple[Any, ...], dtype[complex128]])

  • tlist (Sequence[float])

  • c_ops (Sequence[Operator] | None)

  • e_ops (Sequence[Operator] | None)

  • state_observables (Mapping[str, Callable[[ndarray[tuple[Any, ...], dtype[complex128]]], Any]] | None)

  • options (Options | None)

Return type:

Result

openquantumsim.solvers.steadystate(H, c_ops, *, method='iterative-gmres', options=None)[source]

Compute a Lindblad steady state.

Parameters:
Return type:

ndarray[tuple[Any, …], dtype[complex128]]

openquantumsim.solvers.lindblad_superoperator(H, c_ops=None)[source]

Return the dense Lindblad superoperator matrix in column-stacked form.

The returned matrix L acts on vec(rho) (column-stacked, matching NumPy’s Fortran-order reshape) as vec(L(rho)) = L @ vec(rho).

Parameters:
Return type:

ndarray[tuple[Any, …], dtype[complex128]]

openquantumsim.solvers.apply_superoperator(superoperator, rho)[source]

Apply a column-stacked superoperator to a density matrix.

Parameters:

  • superoperator (ndarray[tuple[Any, ...], dtype[complex128]])

  • rho (ndarray[tuple[Any, ...], dtype[complex128]])

Return type:

ndarray[tuple[Any, …], dtype[complex128]]

openquantumsim.solvers.brmesolve(H, rho0, tlist, *, a_ops, e_ops=None, options=None)[source]

Solve the secular Bloch-Redfield master equation.

a_ops pairs each bath-coupling operator with a spectrum callable gamma(omega) giving the dissipator weight at Bohr frequency omega. A constant weight g is equivalent to a Lindblad collapse operator sqrt(g) * A; a zero-temperature bath returns g for omega > 0 and 0 for omega < 0.

Transitions sharing a Bohr frequency are treated as a single secular channel. The Hamiltonian must be Hermitian.

Parameters:

  • H (Operator)

  • rho0 (ndarray[tuple[Any, ...], dtype[complex128]])

  • tlist (Sequence[float])

  • a_ops (Sequence[tuple[Operator, Callable[[float], float]]])

  • e_ops (Sequence[Operator] | None)

  • options (Options | None)

Return type:

Result

openquantumsim.solvers.propagator(H, tlist, *, c_ops=None)[source]

Propagators for a time-independent system at each time in tlist.

Without collapse operators this returns the unitary propagators U(t) = exp(-i H t). With collapse operators it returns the propagator superoperators S(t) = exp(L t) built from the Lindblad generator (see lindblad_superoperator()); apply them to a density matrix with apply_superoperator().

Parameters:
Return type:

list[Operator]