VarQRTE
class VarQRTE(ansatz, initial_parameters, variational_principle=None, estimator=None, ode_solver=<class 'qiskit.algorithms.time_evolvers.variational.solvers.ode.forward_euler_solver.ForwardEulerSolver'>, lse_solver=None, num_timesteps=None, imag_part_tol=1e-07, num_instability_tol=1e-07)
Bases: qiskit.algorithms.time_evolvers.variational.var_qte.VarQTE
, qiskit.algorithms.time_evolvers.real_time_evolver.RealTimeEvolver
Variational Quantum Real Time Evolution algorithm.
Parameters
- ansatz – Ansatz to be used for variational time evolution.
- initial_parameters – Initial parameter values for an ansatz.
- variational_principle – Variational Principle to be used. Defaults to
RealMcLachlanPrinciple
. - estimator – An estimator primitive used for calculating expectation values of TimeEvolutionProblem.aux_operators.
- ode_solver – ODE solver callable that implements a SciPy
OdeSolver
interface or a string indicating a valid method offered by SciPy. - lse_solver – Linear system of equations solver callable. It accepts
A
andb
to solveAx=b
and returnsx
. IfNone
, the defaultnp.linalg.lstsq
solver is used. - num_timesteps – The number of timesteps to take. If
None
, it is automatically selected to achieve a timestep of approximately 0.01. Only relevant in case of theForwardEulerSolver
. - imag_part_tol – Allowed value of an imaginary part that can be neglected if no imaginary part is expected.
- num_instability_tol – The amount of negative value that is allowed to be rounded up to 0 for quantities that are expected to be non-negative.
Methods
evolve
VarQRTE.evolve(evolution_problem)
Apply Variational Quantum Time Evolution to the given operator.
Parameters
evolution_problem (TimeEvolutionProblem
) – Instance defining an evolution problem.
Return type
VarQTEResult
Returns
Result of the evolution which includes a quantum circuit with bound parameters as an evolved state and, if provided, observables evaluated on the evolved state.
Raises
ValueError – If initial_state
is included in the evolution_problem
.