Convergence parameters
- class qtealeaves.convergence_parameters.TNConvergenceParametersFiniteT(t_grid, statics_method=4, dt_max=0.1, measure_obs_every_n_iter=20, k_b=1, **kwargs)[source]
Convergence parameters for finite temperature. Based on the input temperature grid, the time grid for imaginary time evolution is created. The largest value of time step is limited with the input dt_max.
Parameters
- t_gridlist or np.ndarray
Temperature grid, we want to take measurements for each point in the grid. The temperature grid must be sorted in descending order.
- statics_methodint, optional
Only imaginary time evolution methods are enabled, i.e., 3 (two-tensor), 4 (single-tensor link-expansion), or 5 (single-tensor). Default to 4 (single-tensor link-expansion)
- dt_maxfloat, optional
Maximal time step for imaginary time evolution. Default is 0.1.
- measure_obs_every_n_iterint, optional
The measurements are done every measure_obs_every_n_iter iterations. The target tempertures will fall on multiples of measure_obs_every_n_iter Default is 20.
- k_bfloat, optional
Value for Boltzmann constant.
**kwargs : other
TNConvergenceParametersparametersAttributes
- self.sim_params[‘imag_evo_dt’]np.ndarray
Time step grid.
- self.measure_obs_every_n_iterint
See Parameters above.
- self.n_gridnp.ndarray of int
The number of iterations/measure_obs_every_n_iter needed to reach each of the temperatures from t_grid, starting from the infinite temperature.
- property temperature
Returns the grid of temperatures at which the measurements are made. To check if the grid corresponds to the input temperature grid, use self.temperature[self.n_grid].