class VarQITE(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)[source]#

Bases: VarQTE, ImaginaryTimeEvolver

Variational Quantum Imaginary Time Evolution algorithm.

  • ansatz (QuantumCircuit) – Ansatz to be used for variational time evolution.

  • initial_parameters (Mapping[Parameter, float] | Sequence[float]) – Initial parameter values for the ansatz.

  • variational_principle (ImaginaryVariationalPrinciple | None) – Variational Principle to be used. Defaults to ImaginaryMcLachlanPrinciple.

  • estimator (BaseEstimator | None) – An estimator primitive used for calculating expectation values of TimeEvolutionProblem.aux_operators.

  • ode_solver (Type[OdeSolver] | str) – ODE solver callable that implements a SciPy OdeSolver interface or a string indicating a valid method offered by SciPy.

  • lse_solver (Callable[[np.ndarray, np.ndarray], np.ndarray] | None) – Linear system of equations solver callable. It accepts A and b to solve Ax=b and returns x. If None, the default np.linalg.lstsq solver is used.

  • num_timesteps (int | None) – 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 the ForwardEulerSolver.

  • imag_part_tol (float) – Allowed value of an imaginary part that can be neglected if no imaginary part is expected.

  • num_instability_tol (float) – The amount of negative value that is allowed to be rounded up to 0 for quantities that are expected to be non-negative.



Apply Variational Quantum Time Evolution to the given operator.


evolution_problem (TimeEvolutionProblem) – Instance defining an evolution problem.


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.


ValueError – If initial_state is included in the evolution_problem.

Return type: