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Curated by: Qiskit (180 videos)
Talk 1: Dephasing Robust Quantum Noise Spectroscopy Talk 2: Provably Optimal Control for Multiplicative Amplitude Control Noise Abstract: The path to demonstrations of quantum algorithms that impact the broader scientific community involves the construction of scalable devices and methods that are not swamped by the native noise of the hardware. To achieve that task, protocols must be developed to both mitigate and correct noisy components that can sufficiently target the specific noisy aspects of a given quantum hardware. In two talks, we will discuss aspects of such a protocol where we present both a method of reliably characterizing multiple noisy aspects of the quantum hardware and a method of utilizing such characterization methods to mitigate the characterized noise to engineer accurate quantum gates that are successful in spite of the existence of the characterized noise. For the first talk, we will discuss characterization of the strengths and spectra of the various noise processes affecting the quantum system, which is achieved through quantum noise spectroscopy. These characterization protocols have been applied to describe the dominant source of error on quantum systems, but have limited use when the system experiences multiple significant sources of noise. We will present some of our recent results on characterizing temporally correlated control noise in the presence of strong dephasing and detuning noise. We will then present our recent work on the use of quantum control for suppressing temporally correlated control noise. Through the use of filter design methods, we will show that one can tailor the spectral response of a quantum system to avoid regimes where the noise is dominant. For the second talk, we demonstrate an approach for engineering quantum control that optimally mitigates the influence of temporally-correlated control noise. Our approach takes the characterization of the control noise as an input and utilizes model-based descriptions of the noisy dynamics which allows for us to frame the search for control solutions as a gate-based circuit optimization which is convex. In this talk, we will discuss this model-based approach to constructing these provably optimal control sequences as well as provide demonstrations of the utility of our method. Finally, we can show that we can obtain near-optimal solutions in the presence of multiple noise sources which we show by the addition of time-correlated dephasing as long as the control noise is strong relative to the dephasing noise during the application of the gate.