Neural-network-designed three-qubit gates robust against charge noise and crosstalk in silicon

Abstract

Spin qubits in semiconductor quantum dots are a promising platform for quantum computing, however scaling to large systems is hampered by crosstalk and charge noise. Crosstalk here refers to the unwanted off-resonant rotation of idle qubits during the resonant rotation of the target qubit. For a three-qubit system with crosstalk and charge noise, it is difficult to analytically create gate protocols that produce three-qubit gates, such as the Toffoli gate, directly in a single shot instead of through the composition of two-qubit gates. Therefore, we numerically optimize a physics-informed neural network to produce theoretically robust shaped pulses that generate a Toffoli-equivalent gate. Additionally, robust $\frac{\pi }{2}$ $X$ and CZ gates are also presented in this work to create a universal set of gates robust against charge noise. The robust pulses maintain an infidelity of $10^{-3}$ for average quasistatic fluctuations in the voltage of up to a few mV instead of tenths of mV for non-robust pulses.

arXiv comment7 pages, 7 figures

References in corpus (34)

• Quantum Computation with Quantum Dots
• Surface codes: Towards practical large-scale quantum computation
• A >99.9%-fidelity quantum-dot spin qubit with coherence limited by charge noise
• Simple pulses for elimination of leakage in weakly nonlinear qubits
• A programmable two-qubit quantum processor in silicon
• Efficient Z-Gates for Quantum Computing
• Computing with spin qubits at the surface code error threshold
• Fast universal quantum control above the fault-tolerance threshold in silicon
• Fidelity benchmarks for two-qubit gates in silicon
• Two-qubit silicon quantum processor with operation fidelity exceeding 99%
• Universal quantum logic in hot silicon qubits
• CMOS-based cryogenic control of silicon quantum circuits
• Introduction to the Pontryagin Maximum Principle for Quantum Optimal Control
• Silicon qubit fidelities approaching incoherent noise limits via pulse engineering
• On the advantages of using relative phase Toffolis with an application to multiple control Toffoli optimization
• Quantum error correction with silicon spin qubits
• Low-frequency charge noise in Si/SiGe quantum dots
• Arbitrary quantum control of qubits in the presence of universal noise
• The impact of classical control electronics on qubit fidelity
• Efficient C-Phase gate for single-spin qubits in quantum dots
• Reducing charge noise in quantum dots by using thin silicon quantum wells
• On-demand electrical control of spin qubits
• Electron g-factor of valley states in realistic silicon quantum dots
• Crosstalk analysis for single-qubit and two-qubit gates in spin qubit arrays
• The SMART protocol -- Pulse engineering of a global field for robust and universal quantum computation
• Flopping-mode electric dipole spin resonance
• Quantum Computation Protocol for Dressed Spins in a Global Field
• Protocol for a resonantly-driven three-qubit Toffoli gate with silicon spin qubits
• Spatial Noise Correlations in a Si/SiGe Two-Qubit Device from Bell State Coherences
• Robust quantum gates using smooth pulses and physics-informed neural networks
• Spin decoherence in a two-qubit CPHASE gate: the critical role of tunneling noise
• Robust implementation of quantum gates despite always-on exchange coupling in silicon double quantum dots
• Two-qubit CZ gates robust against charge noise in silicon while compensating for crosstalk using neural network
• Neural-network-designed three-qubit gates robust against charge noise and crosstalk in silicon

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• Efficient learning and optimizing non-Gaussian correlated noise in digitally controlled qubit systems