Diverse methods and practical aspects in controlling single semiconductor qubits: a review

Jia-Ao Peng; Chu-Dan Qiu; Wen-Long Ma; Jun-Wei Luo

doi:10.1088/1674-4926/24120040

J. Semicond. > In Press

REVIEWS

Diverse methods and practical aspects in controlling single semiconductor qubits: a review

Jia-Ao Peng^{1, 2, §}, Chu-Dan Qiu^{1, 2, §}, Wen-Long Ma^{1, 2,} and Jun-Wei Luo^{1, 2,}

+ Author Affiliations

1. State Key Laboratory of Superlattices and Microstructures, Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China
2. College of Materials Science and Opto-Electronic Technology, University of Chinese Academy of Sciences, Beijing 100049, China
^§Jia-Ao Peng and Chu-Dan Qiu contributed equally to this work and should be considered as co-first authors.

Author Bio:

Jia-ao Peng got his bachelor’s degree in 2020 from University of Science and Technology of China. Now he is a doctoral student at Institute of Semiconductors (IOS) under the supervision of Prof. Wen-long Ma and Prof. Jun-wei Luo. His research focuses on quantum information and quantum control.

Chu-Dan Qiu, graduated from Southern University of Science and Technology with a M.Sc. degree (2019) and is currently a PhD candidate at Technical University of Denmark. Her research focuses on quantum information theory, including quantum measurement, quantum metrology and their applications in NV centers in diamond.

Wen-Long Ma is currently a professor at Institute of Semiconductors (IOS), Chinese Academy of Sciences (CAS) and University of Chinese Academy of Sciences (UCAS). He got his Ph.D. degree from IOS, CAS (2015) and his B.S. degree from University of Science and Technology Beijing (2010). He was a postdoctoral fellow at the Chinese University of Hong Kong (2015–2017), Yale University (2017–2019) and University of Chicago (2019–2020). His research interests include various issues in quantum technologies, such as quantum dissipation and decoherence, quantum measurement and control, quantum error-correction and fault-tolerant control, quantum sensing and quantum algorithms.

Jun-Wei Luo received his Bachelor’s and Master’s degrees from Zhejiang University in 2000 and 2003, respectively, and his Ph.D in condensed matter physics from the Institute of Semiconductors, Chinese Academy of Sciences in 2007. He is currently the director of the State Key Laboratory of Semiconductor Physics and Chip Technologies, Institute of Semiconductors, CAS. He focuses mainly on semiconductor physics of Silicon-based devices for post-Moore’s law technologies and discovered hidden spin polarization in inversion-symmetric bulk crystals.

Corresponding author: Wen-Long Ma, wenlongma@semi.ac.cn; Jun-Wei Luo, jwluo@semi.ac.cn

DOI: 10.1088/1674-4926/24120040CSTR: 32376.14.1674-4926.24120040

Abstract: Quantum control allows a wide range of quantum operations employed in molecular physics, nuclear magnetic resonance and quantum information processing. Thanks to the existing microelectronics industry, semiconducting qubits, where quantum information is encoded in spin or charge degree freedom of electrons or nuclei in semiconductor quantum dots, constitute a highly competitive candidate for scalable solid-state quantum technologies. In quantum information processing, advanced control techniques are needed to realize quantum manipulations with both high precision and noise resilience. In this review, we first introduce the basics of various widely-used control methods, including resonant excitation, adabatic passage, shortcuts to adiabaticity, composite pulses, and quantum optimal control. Then we review the practical aspects in applying these methods to realize accurate and robust quantum gates for single semiconductor qubits, such as Loss–DiVincenzo spin qubit, spinglet-triplet qubit, exchange-only qubit and charge qubit.

Key words: quantum information with solid state qubits, quantum control, quantum dots, quantum gate

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Fig. 1. (Color online) Diverse methods of quantum control with their characteristics and typical control processes. (a) Rabi oscillations at three different values of the perpendicular magnetic field (left) (adapted from Ref. [42]). A typical nutation of a qubit subject to a resonant transversal field illustrated on a Bloch sphere observed in the rotating frame (middle) and in the lab frame (right) (adapted from Ref. [43]). (b) The $ \Lambda $-linkage pattern and the ladder pattern of energy levels in STIRAP (left) (Adapted from Ref. [134]). Typical surfaces of eigenenergies of a two-level system for RAP (middle) and STIRAP (right) (Adapted from Ref. [52]). (c) Schematic of adiabatic, diabatic, and STA processes (left), where along the STA path (green dots), the system evolves to the target state in a shorter time without necessarily traveling along the same level. Different strategies for STA in three-level systems, including the counterdiabatic STA (middle) with initial couplings (red, solid lines) and additional required STA coupling (blue, dotted line), and invariant-based inverse engineering STA (right) with modified STA couplings (green, solid lines) (adapted from Ref. [18]). (d) A diagram depicting the time dependence of the Rabi frequency and phase in CPs (left) (adapted from Ref. [75]). A typical illustration of the evolution for composite pulses sequence on a pseudo Bloch sphere with left (L) (middle) and right (R) (right) handedness (Adapted from Ref. [76]). (e) A typical control structure for QOP (left), and the illustration of the gradients for amplitudes in the strongly modulating pulses direct search method (middle) and the GRAPE algorithm (right) (Adapted from Ref. [19]). For strongly modulating pulses direct search method, every time each segment is split into two equal parts, after searching the optimal control to minimize the cost functional.

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Fig. 2. (Color online) The four major qubit types covered in this review, with typical device images and energy-level diagrams. (a) The device layout of a quantum-dot electron spin-1/2 qubit (adapted from Ref. [114]), and a typical image about energy levels of a silicon quantum dot in a magnetic field B (adapted from Ref. [115]). (b) Scanning electron micrograph of a two-qubit device in GaAs quantum dots, and an energy level diagram showing the two-electron spin states of the double quantum dot and energy splitting (adapted from Ref. [116]). (c) False color micrograph of a quantum-dot-based resonant exchange qubit and the corresponding energy level diagram (adapted from Ref. [117]). (d) Schematic diagram of a triple-dot device for a charge quadrupole qubit and spectrum of the Hamiltonian for equal tunnel couplings as a function of detuning $ \delta $ (adapted from Ref. [118]).

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Fig. 3. (Color online) Applications of diverse control methods to semiconductor qubits: device diagrams, control pulses, and gates fidelity (or population dynamics). (a) False-color scanning electron microscope image of a spin-based two-qubit silicon quantum processor (left). Comparison of a common control square pulse and a smoothed pulse to simulate the actual environmental conditions. Spin-up probabilities as a function of drive frequency $ f $ and microwave burst length $ \tau_{{\rm{R}}} $ when driven on resonance for each qubit (right) (adapted from Ref. [124]). (b) False-color scanning electron micrograph of a quadruple quantum-dot device for adiabatic quantum-state transfer of both single-spin eigenstates and two-spin singlet states (left); Change in exchange-coupling strengths between qubits for the adiabatic quantum-state transfer step (middle). Singlet return probabilities of the left and right pairs as a function of interpolation time $ T $ (right) (adapted from Ref. [131]). (c) Direct transfer of one electron in an array of 2n + 1 QDs (left). Typical STA pulse shape (middle) with $ \Omega _{12} $ (solid, blue), $ \Omega _{23} $ (dashed, red). Fidelity $ F $ versus dephasing rate $ \gamma $ (in units of $ 5 \times 10^{7} s^{-1} $) and the operation time $ t_{f} $ for a triple QD by inverse engineering STA (right) (adapted from Ref. [150]). (d) Schematic diagram of a triple-dot device depicting the gate layout and the resulting electrostatic control of the potential landscape (left). The control composite pulses within all-electrical operation to measure charge noise dynamics in the system (middle). Sveraged double-dot singlet–triplet oscillations at a magnetic field of 0.1 $ T $ (right) (adapted from Ref. [167]). (e) Scanning electron micrograph image of a SiMOS qubit device (left). Microwave modulation $ \Omega _{x} $ (blue), $ \Omega _{y} $ (red) for the basic 7 types of Clifford gate through GRAPE iteration (middle). The infidelity ($ r=1-F $) and incoherence ($ \omega $) for sequences using square pulses (scheme S) and GRAPE optimised pulses (scheme O) in the randomised benchmarking result (right) (adapted from Ref. [177]).

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Table 1. An overview of the five quantum control methods discussed in the review.

Method	Pros and cons	Practical aspects in semiconductor qubits
Resonant excitation	Pros: simple, widely used Cons: strict resonant condition	Manipulation: ESR by engineered magnetic fields^[102–104] EDSR via natural spin–orbit fields^[106–108] 　　　synthetic spin–orbit fields^{[109, 110]}
Adiabatic passage	Pros: insensitive to variations of control parameters Cons: slow	Experimental advances: RAP: realization of spin states transfer via electron spin shuttling^{[128, 129]} spin states transfer in multi-level systems through spin chain^[130] two-spin singlet states transfer in a GaAs quantum-dot device^[131]
Adiabatic passage		STIRAP: demonstration of certain steps^[133] excitons in two coupled QDs^[135] cavity-assisted STIRAP^[138]
Shortcuts to adiabaticity	Pros: flexible; faster than adiabatic passage Cons: relatively high control complexity	Several protocols: Fast and robust control of electron spins^{[127, 148–150]} Arbitrary four-dimensional qubit rotation^[152] Non-Abelian geometric gates^[153]
Composite pulses	Pros: robust with high fidelity; general and universal Cons: fast increasing complexity with extension of sequence lengths	Potential applications: Perform dynamically corrected gates^[161–163] Construct robust quantum gates^[165] Measuring noise dynamics^[166]
Quantum optimal control	Pros: precise and fast Cons: only numerical solutions; high control complexity	Experimental advances: Open-loop optimization in SiMOS qubits^[177] Close-loop optimization in GaAs-based singlet–triplet qubits^[179]

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Received: 31 December 2024 Revised: 30 March 2025 Online: Accepted Manuscript: 01 September 2025Uncorrected proof: 04 September 2025

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Jia-Ao Peng, Chu-Dan Qiu, Wen-Long Ma, Jun-Wei Luo. Diverse methods and practical aspects in controlling single semiconductor qubits: a review[J]. Journal of Semiconductors, 2025, In Press. doi: 10.1088/1674-4926/24120040 ****J-A Peng, C-D Qiu, W-L Ma, and J-W Luo, Diverse methods and practical aspects in controlling single semiconductor qubits: a review[J]. J. Semicond., 2025, accepted doi: 10.1088/1674-4926/24120040

Citation:

Jia-Ao Peng, Chu-Dan Qiu, Wen-Long Ma, Jun-Wei Luo. Diverse methods and practical aspects in controlling single semiconductor qubits: a review[J]. Journal of Semiconductors, 2025, In Press. doi: 10.1088/1674-4926/24120040 ****

J-A Peng, C-D Qiu, W-L Ma, and J-W Luo, Diverse methods and practical aspects in controlling single semiconductor qubits: a review[J]. J. Semicond., 2025, accepted doi: 10.1088/1674-4926/24120040

Citation:

J-A Peng, C-D Qiu, W-L Ma, and J-W Luo, Diverse methods and practical aspects in controlling single semiconductor qubits: a review[J]. J. Semicond., 2025, accepted doi: 10.1088/1674-4926/24120040

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Diverse methods and practical aspects in controlling single semiconductor qubits: a review

DOI: 10.1088/1674-4926/24120040

CSTR: 32376.14.1674-4926.24120040

Jia-Ao Peng^{1, 2, §},
Chu-Dan Qiu^{1, 2, §},
Wen-Long Ma^{1, 2,},
Jun-Wei Luo^{1, 2,}

1.
State Key Laboratory of Superlattices and Microstructures, Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China
2.
College of Materials Science and Opto-Electronic Technology, University of Chinese Academy of Sciences, Beijing 100049, China

More Information

Jia-ao Peng got his bachelor’s degree in 2020 from University of Science and Technology of China. Now he is a doctoral student at Institute of Semiconductors (IOS) under the supervision of Prof. Wen-long Ma and Prof. Jun-wei Luo. His research focuses on quantum information and quantum control
Chu-Dan Qiu, graduated from Southern University of Science and Technology with a M.Sc. degree (2019) and is currently a PhD candidate at Technical University of Denmark. Her research focuses on quantum information theory, including quantum measurement, quantum metrology and their applications in NV centers in diamond
Wen-Long Ma is currently a professor at Institute of Semiconductors (IOS), Chinese Academy of Sciences (CAS) and University of Chinese Academy of Sciences (UCAS). He got his Ph.D. degree from IOS, CAS (2015) and his B.S. degree from University of Science and Technology Beijing (2010). He was a postdoctoral fellow at the Chinese University of Hong Kong (2015–2017), Yale University (2017–2019) and University of Chicago (2019–2020). His research interests include various issues in quantum technologies, such as quantum dissipation and decoherence, quantum measurement and control, quantum error-correction and fault-tolerant control, quantum sensing and quantum algorithms
Jun-Wei Luo received his Bachelor’s and Master’s degrees from Zhejiang University in 2000 and 2003, respectively, and his Ph.D in condensed matter physics from the Institute of Semiconductors, Chinese Academy of Sciences in 2007. He is currently the director of the State Key Laboratory of Semiconductor Physics and Chip Technologies, Institute of Semiconductors, CAS. He focuses mainly on semiconductor physics of Silicon-based devices for post-Moore’s law technologies and discovered hidden spin polarization in inversion-symmetric bulk crystals
Corresponding author: wenlongma@semi.ac.cn; jwluo@semi.ac.cn
Received Date: 2024-12-31
Revised Date: 2025-03-30

Available Online: 2025-09-01

Abstract

Abstract

Quantum control allows a wide range of quantum operations employed in molecular physics, nuclear magnetic resonance and quantum information processing. Thanks to the existing microelectronics industry, semiconducting qubits, where quantum information is encoded in spin or charge degree freedom of electrons or nuclei in semiconductor quantum dots, constitute a highly competitive candidate for scalable solid-state quantum technologies. In quantum information processing, advanced control techniques are needed to realize quantum manipulations with both high precision and noise resilience. In this review, we first introduce the basics of various widely-used control methods, including resonant excitation, adabatic passage, shortcuts to adiabaticity, composite pulses, and quantum optimal control. Then we review the practical aspects in applying these methods to realize accurate and robust quantum gates for single semiconductor qubits, such as Loss–DiVincenzo spin qubit, spinglet-triplet qubit, exchange-only qubit and charge qubit.
- quantum information with solid state qubits,
- quantum control,
- quantum dots,
- quantum gate

^§Jia-Ao Peng and Chu-Dan Qiu contributed equally to this work and should be considered as co-first authors.

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