Research data supporting "Digital quantum simulation of many-body localization transition in a disordered kicked Ising model"

Expeimental data are saved as Python numpy arrays. For example, type otoc=numpy.load("otoc.npy", allow_pickle=True).item() in Python code. Then, we get the raw experimental data of OTOCs as a Python dictionary. Similarly, the measurement errors of OTOCs, the experimental data of fidelities used for rescaling of OTOCs in error mitigation, and the measurement errors of fidelities are save in otoc_err.npy, fidelity.npy and fidelity_err.npy, respectively. The keys of the dictionaries are the strengths of disorder w=[0.05, 0.08, 0.1, 0.12, 0.14, 0.16, 0.18, 0.2, 0.25, 0.3, 0.4, 0.5, 1.0]. For example, OTOCs with the strength of disorder w=0.05 are saved in otoc[0.05] as a numpy array, whose shape is (number of noise factor=2, number of disorder=25, number of Trotter step=11, number of qubits=60). The physical qubits of ibm_fez used in our experiments are [101, 83, 65, 121, 103, 85, 67, 123, 105, 87, 69, 143, 125, 107, 89, 145, 127, 109, 91, 147, 129, 111, 116, 102, 100, 96, 84, 82, 77, 66, 64, 122, 120, 104, 86, 68, 57, 136, 124, 117, 106, 97, 88, 78, 70, 144, 142, 126, 108, 90, 146, 137, 128, 118, 110, 98, 92, 148, 130, 112]. Note also that the butterfly operator acts on the 106th qubit. We get OTOCs e.g., at 5 Trotter step, 101th physical qubit and 20th realization of disorder with noise factor=1.0 as otoc[0.05][0,19,5,0], and that of noise factor=1.5 as otoc[0.05][1,19,5,0].