Mesoscopic fluctuations in biharmonically driven flux qubits
Authors: Alejandro Ferrón (Instituto de Modelado e Innovación Tecnológica), Daniel Domínguez (Centro Atómico Bariloche and Instituto Balseiro, 8400 San Carlos de Bariloche, Argentina), María José Sánchez (Centro Atómico Bariloche and Instituto Balseiro, 8400 San Carlos de Bariloche, Argentina)
Abstract: We investigate flux qubits driven by a biharmonic magnetic signal, with a phase lag that acts as an effective time reversal broken parameter. The driving induced transition rate between the ground and the excited state of the flux qubit can be thought as an effective transmitance, profiting from a direct analogy between interference effects at avoided level crossings and scattering events in disordered electronic systems. For time scales prior to full relaxation but large compared to the decoherence time, this characteristic rate has been accessed experimentally and its sensitivity with both the phase lag and the dc flux detuning explored. In this way signatures of Universal Conductance Fluctuations-like effects have recently been analized in flux qubits and compared with a phenomenological model that only accounts for decoherence, as a classical noise. We here solve the full dynamics of the driven flux qubit in contact with a quantum bath employing the Floquet Markov Master equation. Within this formalism relaxation and decoherence rates result strongly dependent on both the phase lag and the dc flux detuning. Consequently, the associated pattern of fluctuations in the characteristic rates display important differences with those obtained within the mentioned phenomenological model. In particular we demonstrate the Weak Localization-like effect in the averages values of the relaxation rate. Our predictions can be tested for accessible, but longer time scales than the current experimental times.
Explore the paper tree
Click on the tree nodes to be redirected to a given paper and access their summaries and virtual assistant
Look for similar papers (in beta version)
By clicking on the button above, our algorithm will scan all papers in our database to find the closest based on the contents of the full papers and not just on metadata. Please note that it only works for papers that we have generated summaries for and you can rerun it from time to time to get a more accurate result while our database grows.