def run_grape():
save_file_path = generate_save_file_path(EXPERIMENT_NAME, SAVE_PATH)
config = copy(GRAPE_CONFIG)
config.update({
"save_file_path": save_file_path
})
result = grape_schroedinger_discrete(**config)
def run_grape():
t_start = time.process_time()
save_file_path = generate_save_file_path(EXPERIMENT_NAME, SAVE_PATH)
config = copy(GRAPE_CONFIG)
config.update({"save_file_path": save_file_path})
result = grape_schroedinger_discrete(**config)
tot_time = time.process_time() - t_start
print("Total time (%s iterations): %d s, time/ieration: %.2f s" %
(ITERATION_COUNT, tot_time, tot_time / ITERATION_COUNT))
"".format(TRANSMON_ZERO))
print("TRANSMON_ONE:\n{}"
"".format(TRANSMON_ONE))
print("INITIAL_STATE_0:\n{}"
"".format(INITIAL_STATE_0))
print("TARGET_STATE_0:\n{}"
"".format(TARGET_STATE_0))
print("CONTROL_EVAL_TIMES:\n{}"
"".format(anp.linspace(0, EVOLUTION_TIME, CONTROL_EVAL_COUNT)))
print("SYSTEM_EVAL_TIMES:\n{}"
"".format(anp.linspace(0, EVOLUTION_TIME, SYSTEM_EVAL_COUNT)))
# qoc saves data in h5 format. You can parse h5 files using the `h5py` package [5].
EXPERIMENT_NAME = "tutorial_schroed_cavity01"
SAVE_PATH = "./out"
SCHROED_FILE_PATH = generate_save_file_path(EXPERIMENT_NAME, SAVE_PATH)
# Next, we use the GRAPE algorithm to find a set of time-dependent
# controls that accomplishes the state transfer that we desire.
result = grape_schroedinger_discrete(CONTROL_COUNT,
CONTROL_EVAL_COUNT,
COSTS, EVOLUTION_TIME,
hamiltonian, INITIAL_STATES,
SYSTEM_EVAL_COUNT,
complex_controls=COMPLEX_CONTROLS,
iteration_count=ITERATION_COUNT,
log_iteration_step=LOG_ITERATION_STEP,
optimizer=OPTIMIZER,
save_file_path=SCHROED_FILE_PATH,
save_intermediate_states=SAVE_INTERMEDIATE_STATES,
save_iteration_step=SAVE_ITERATION_STEP,)
# Define the optimization.
COMPLEX_CONTROLS = True
MAX_CONTROL_NORMS = anp.array((5, ))
CONTROL_COUNT = 1
EVOLUTION_TIME = 10 # nanoseconds
CONTROL_EVAL_COUNT = 11
SYSTEM_EVAL_COUNT = 2
ITERATION_COUNT = int(1e6)
OPTIMIZER = LBFGSB()
# Define output.
LOG_ITERATION_STEP = 1
SAVE_ITERATION_STEP = 1
SAVE_PATH = "./out"
SAVE_FILE_NAME = "transmon_pi_decoherence"
SAVE_FILE_PATH = generate_save_file_path(SAVE_FILE_NAME, SAVE_PATH)
def main():
result = grape_lindblad_discrete(
CONTROL_COUNT,
CONTROL_EVAL_COUNT,
COSTS,
EVOLUTION_TIME,
INITIAL_DENSITIES,
SYSTEM_EVAL_COUNT,
complex_controls=COMPLEX_CONTROLS,
hamiltonian=hamiltonian,
iteration_count=ITERATION_COUNT,
lindblad_data=lindblad_data,
log_iteration_step=LOG_ITERATION_STEP,
