Compressed Optimization of Device Architectures (CODA) for semiconductor quantum devices

Abstract

Recent advances in nanotechnology have enabled researchers to manipulate small collections of quantum mechanical objects with unprecedented accuracy. In semiconductor quantum dot qubits, this manipulation requires controlling the dot orbital energies, tunnel couplings, and the electron occupations. These properties all depend on the voltages placed on the metallic electrodes that define the device, whose positions are fixed once the device is fabricated. While there has been much success with small numbers of dots, as the number of dots grows, it will be increasingly useful to control these systems with as few electrode voltage changes as possible. Here, we introduce a protocol, which we call the Compressed Optimization of Device Architectures (CODA), in order to both efficiently identify sparse sets of voltage changes that control quantum systems, and to introduce a metric which can be used to compare device designs. As an example of the former, we apply this method to simulated devices with up to 100 quantum dots and show that CODA automatically tunes devices more efficiently than other common nonlinear optimizers. To demonstrate the latter, we determine the optimal lateral scale for a triple quantum dot, yielding a simulated device that can be tuned with small voltage changes on a limited number of electrodes.

arXiv comment10 pages, 4 figures

References in corpus (33)

• Quantum Computation with Quantum Dots
• Spins in few-electron quantum dots
• Silicon Quantum Electronics
• A Two Qubit Logic Gate in Silicon
• A >99.9%-fidelity quantum-dot spin qubit with coherence limited by charge noise
• A single-atom electron spin qubit in silicon
• A programmable two-qubit quantum processor in silicon
• Quantum CNOT Gate for Spins in Silicon
• High-fidelity readout and control of a nuclear spin qubit in silicon
• Electrical control of a long-lived spin qubit in a Si/SiGe quantum dot
• A Coherent Spin-Photon Interface in Silicon
• Strong spin-photon coupling in silicon
• Quantum Coherence in a One-Electron Semiconductor Charge Qubit
• Electrometry Using Coherent Exchange Oscillations in a Singlet-Triplet-Qubit
• Reduced sensitivity to charge noise in semiconductor spin qubits via symmetric operation
• Quantum control and process tomography of a semiconductor quantum dot hybrid qubit
• Noise suppression using symmetric exchange gates in spin qubits
• Two-axis control of a singlet-triplet qubit with an integrated micromagnet
• Silicon quantum processor with robust long-distance qubit couplings
• Quantum dot self consistent electronic structure and the Coulomb blockade
• Gate fidelity and coherence of an electron spin in a Si/SiGe quantum dot with micromagnet
• Microwave-driven coherent operations of a semiconductor quantum dot charge qubit
• Electrical spin driving by $g$-matrix modulation in spin-orbit qubits
• Probing low noise at the MOS interface with a spin-orbit qubit
• A Dressed Spin Qubit in Silicon
• Extending the coherence of a quantum dot hybrid qubit
• Tunable Hybrid Qubit in a GaAs Double Quantum Dot
• Two-Electron Spin Correlations in Precision Placed Donors in Silicon
• Automated tuning of inter-dot tunnel couplings in quantum dot arrays
• Computer-automated tuning of semiconductor double quantum dots into the single-electron regime
• State-conditional coherent charge qubit oscillations in a Si/SiGe quadruple quantum dot
• QFlow lite dataset: A machine-learning approach to the charge states in quantum dot experiments
• Transport through an impurity tunnel coupled to a Si/SiGe quantum dot

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