Speaker
Description
Quantum devices are subject to noise detrimental to their qubits' fidelity and coherence times. In spin qubits, one of the dominant noise sources is charge noise arising from device defects that form charge traps. Dynamical decoupling (DD) can refocus qubits, cancelling noise fluctuations well below or well above the DD pulse repetition rate. However, it acts as a narrow filter, leaving noise near its passband largely uncorrected and continuing to degrade qubit performance. Characterising the structure of this residual noise is therefore essential for designing more effective filters. With this in mind, we simulate temporal correlations present in random telegraph noise (RTN) and study their effect on a qubit. To evaluate whether these correlations are captured by conventional tools, we compare against power spectral density (PSD), which fully describes only Gaussian processes and discards higher-order temporal structure in non-Gaussian processes like RTN. We investigate whether the entropy of a correlated joint trap system is sensitive to correlations that PSD misses, as it captures the nonlinear mutual information between temporally separated samples. Our research aims to inform the design of improved DD filters that account for temporally cross-correlated noise.
| I am the presenting author | Yes |
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