Universal qubit control through FPGA-accelerated qubit classification, Hamiltonian estimation and real-time feedback [Part 1]
ORAL
Abstract
Gate-controlled spin qubits are a promising platform for implementing quantum processors [1,2] and now operate near the error-correctable threshold [3]. To correct errors, however, fast real-time feedback based on qubit measurements must be executed within the coherence time of the qubits. Moreover, continuous real-time feedback is also useful to tune and calibrate the qubit environment in order to maintain high fidelity gates and long coherence times.
Here, we read out singlet-triplet qubits in GaAs double quantum dots by radio-frequency reflectometry without analog demodulation/thresholding. Instead, qubit classification is performed in real-time on an FPGA-based pulse processor (Quantum Machines’ OPX+ [4]) using the raw reflectometry signal of the cryostat, opening the door to on-the-fly adaptive control sequences such as Hamiltonian estimation and qubit stabilization. To this end, we show how the co-integration of an OPX+ and QDevil’s QDAC [5] can be used to optimize qubit tuning voltages in real time, based on single-shot outcomes of qubit manipulations.
[1] A.M.J. Zwerver et al., Nat. Electron. 5, 184-190 (2022)
[2] S.G.J. Philips et al., Nature 609, 919-924 (2022)
[3] A. Noiri et al., Nature 601, 338–342 (2022)
[4] https://www.quantum-machines.co/opx+/
[5] https://qdevil.com/
Here, we read out singlet-triplet qubits in GaAs double quantum dots by radio-frequency reflectometry without analog demodulation/thresholding. Instead, qubit classification is performed in real-time on an FPGA-based pulse processor (Quantum Machines’ OPX+ [4]) using the raw reflectometry signal of the cryostat, opening the door to on-the-fly adaptive control sequences such as Hamiltonian estimation and qubit stabilization. To this end, we show how the co-integration of an OPX+ and QDevil’s QDAC [5] can be used to optimize qubit tuning voltages in real time, based on single-shot outcomes of qubit manipulations.
[1] A.M.J. Zwerver et al., Nat. Electron. 5, 184-190 (2022)
[2] S.G.J. Philips et al., Nature 609, 919-924 (2022)
[3] A. Noiri et al., Nature 601, 338–342 (2022)
[4] https://www.quantum-machines.co/opx+/
[5] https://qdevil.com/
*This project was funded within the QuantERA II Programme that has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No 101017733.
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Presenters
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Joost van der Heijden
- Quantum Machines, QDevil