journal article·2017-01-17Open access

Mesoscopic fluctuations in biharmonically driven flux qubits

Alejandro Ferrón, Daniel Domínguez, María José Sánchez

Physical Review B· Volume 95· Issue 4

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 of as an effective transmittance, 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 by Gustavsson et al. [Phys. Rev. Lett. 110, 016603 (2013)] and its sensitivity with both the phase lag and the dc flux detuning explored. In this way, signatures of universal conductance fluctuationslike effects have been analyzed and compared with predictions from a phenomenological model that only accounts for decoherence, as a classical noise. Here we go beyond the classical noise model and solve the full dynamics of the driven flux qubit in contact with a quantum bath employing the Floquet-Born-Markov master equation. Within this formalism, the computed relaxation and decoherence rates turn out to be 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 localizationlike effect in the average values of the relaxation rate. Our predictions can be tested for accessible but longer time scales than the current experimental times.
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Research context

OpenAlex topics: Quantum and electron transport phenomena · Quantum Information and Cryptography · Spectroscopy and Quantum Chemical Studies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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