Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

IEEE International Conference on Information and Automation (ICIA)

Optimal control of decoherence in the quantum circuit containing superconducting qubits

Yinghua Ji, Juju Hu

Published Jul 1, 2014• 0 citations
Publisher

Abstract

Utilizing the method of optimal control, we investigated the tactics of decoherence suppression in the open quantum circuit system containing superconducting qubits. We first discussed the modeling of the system under the optimal control. Then, we designed a control law by means of optimal control. The simulation results indicate that the flip time of qubits can be effectively manipulated through changing the weight coefficients of the cost function, which provides a new way for manipulating the decoherence.

DOI
10.1109/icinfa.2014.6932660

Related papers

Optimal Lyapunov-based states transfer for superconducting qubits

Yinghua Ji, Jianhua Huang, Juju Hu

Quantum control is responsible for many key problems in quantum information processing, such as decoherence suppression, quantum state engineering and quantum gate, etc. In recent years quantum control has become a major topic in the fields of quantum optics and quantum information. Fast control of the state of quantum system is effective for both decoherence suppression caused by the environment and information processing in quantum state transfer and tracking. Comparing the standard Lyapunov control function with bang-bang Lyapunov control function, we design an optimized quantum Lyapunov control function, and analyse the influence of control laws on population transfer probability and control time contrastively. The simulation results indicate that the optimized quantum Lyapunov control strategy effectively shortens the control time and avoids high-frequency oscillation that occurs in bang-bang Lyapunov control, therefore, strengthens the robustness against external interference.

IEEE International Conference on Information and Automation (ICIA)•Aug 1, 2016•2 citations

Circuit models for the co-simulation of superconducting quantum computing systems

Rohith Acharya, Fahd A. Mohiyaddin, Anton Potočnik +5 more

Quantum computers based on superconducting qubits have emerged as a leading candidate for a scalable quantum processor architecture. The core of a quantum processor consists of quantum devices that are manipulated using classical electronic circuits, which need to be co-designed for optimal performance and operation. As the principles governing the behavior of the classical circuits and the quantum devices are different, this presents a unique challenge in terms of the simulation, design and optimization of the joint system. A methodology is presented to transform the behavior of small-scale quantum processors to equivalent circuit models that are usable with classical circuits in a generic electrical simulator, enabling the detailed analysis of the impact of many important non-idealities. The methodology has specifically been employed to derive a circuit model of a superconducting qubit interacting with the quantized electromagnetic field of a superconducting resonator. Based on this technique, a comprehensive analysis of the qubit operation is performed, including the coherent control and readout of the qubit using electrical signals. Furthermore, the effect of several non-idealities in the system such as qubit relaxation, decoherence and leakage out of the computational subspace are captured, in contrast to previous works. As the presented method enables the co-simulation of the control electronics with the quantum system, it facilitates the design and optimization of near-term superconducting quantum processors.

Design, Automation, and Test in Europe•Feb 1, 2021•7 citations

Maximal suppression of decoherence in Markovian quantum systems

Jing Zhang, Chunwen Li, Re-Bing Wu +2 more

In this paper, we design an optimal control law to suppress decoherence effects in Markovian open quantum systems. The optimal control law is subject to the tracking precision of the trajectory governed by the free system, which is ideally free from decoherence. We observe from numerical simulation that the undesired decohering dynamics can be partially squeezed out in most systems. Moreover, we observe the existence of sinusoidally oscillating resonant modes that play dominant roles in the controlled trajectory, which can be easily realized by continuous wave pulses. These key features are strictly demonstrated in subsequent analysis under proper assumptions. For systems in which the coherent control does not work, we suggest a feedback control strategy to extend the applicability of control to wider class of systems.

Journal of Physics A Mathematical and General•Jul 6, 2005•42 citations

Robust and optimal control of open quantum systems

Zi-Jie Chen, Hongwei Huang, Lida Sun +9 more

Recent advancements in quantum technologies have highlighted the importance of mitigating system imperfections, including parameter uncertainties and decoherence effects, to improve the performance of experimental platforms. However, most of the previous efforts in quantum control are devoted to the realization of arbitrary unitary operations in a closed quantum system. Here, we improve the algorithm that suppresses system imperfections and noises, providing notably enhanced scalability for robust and optimal control of open quantum systems. Through experimental validation in a superconducting quantum circuit, we demonstrate that our approach outperforms its conventional counterpart for closed quantum systems with an ultra-low infidelity of about $0.60\%$, while the complexity of this algorithm exhibits the same scaling, with only a modest increase in the prefactor. This work represents a notable advancement in quantum optimal control techniques, paving the way for realizing quantum-enhanced technologies in practical applications.

quant-pharXiv:2603.05249•Science Advances•Mar 6, 2026•14 citations

Optimal quantum control based on Lyapunov stability theorem

Shuang Cong

By means of the design method for bilinear systems in the macroscopic field in association with the characteristic that the mathematical model of pure state quantum system is bilinear,and of selecting the performance index of the controlled system,the optimal control strategy in quantum systems was proposed based on the Lyapunov stability theorem.The detailed design process of optimal control law was derived.Some simulation experiments were performed on a spin-1/2 particle system.Experimental results demonstrate the effectiveness of the method proposed.At the same time,the influence of different parameters on the system control effects is analyzed.

•Jan 1, 2008•1 citation

Optimization Algorithms for Josephson Qubits

Robert Roloff, Markus Wenin, W. Pötz

Superconducting nanoelectrical circuits are promising candidates for the physical implementation of the basic building block of a quantum computer, the qubit. We investigate how optimal control theory can be applied to optimize the dynamics of Josephson qubits. For the example of the charge qubit, several numerical methods are employed to search for external control fields which, by current technology, are realistic and induce the desired unitary time evolution within the system (i.e. the desired gate operation) as faithfully as possible in presence of dissipation, decoherence and leakage. Associated calculations which model the environment microscopically are time-intensive so that parallel computing methods are beneficial in the sampling over control fields. In particular, we discuss the performance of differential-evolution-algorithm based optimizations on a cluster. Using a simpler Lindblad model for environmental effects, we compare the performance of a conjugate-gradient approach to that of a genetic algorithm.

International Workshop on Computational Electronics•May 1, 2009•0 citations
Utilizing the method of optimal control, we investigated the tactics of decoherence suppression in the open quantum circuit system containing superconducting qubits. We first discussed the modeling of the system under the optimal control. Then, we designed a control law by means of optimal control. The simulation results indicate that the flip time of qubits can be effectively manipulated through changing the weight coefficients of the cost function, which provides a new way for manipulating the decoherence.
Quantum control is responsible for many key problems in quantum information processing, such as decoherence suppression, quantum state engineering and quantum gate, etc. In recent years quantum control has become a major topic in the fields of quantum optics and quantum information. Fast control of the state of quantum system is effective for both decoherence suppression caused by the environment and information processing in quantum state transfer and tracking. Comparing the standard Lyapunov control function with bang-bang Lyapunov control function, we design an optimized quantum Lyapunov control function, and analyse the influence of control laws on population transfer probability and control time contrastively. The simulation results indicate that the optimized quantum Lyapunov control strategy effectively shortens the control time and avoids high-frequency oscillation that occurs in bang-bang Lyapunov control, therefore, strengthens the robustness against external interference.
Quantum computers based on superconducting qubits have emerged as a leading candidate for a scalable quantum processor architecture. The core of a quantum processor consists of quantum devices that are manipulated using classical electronic circuits, which need to be co-designed for optimal performance and operation. As the principles governing the behavior of the classical circuits and the quantum devices are different, this presents a unique challenge in terms of the simulation, design and optimization of the joint system. A methodology is presented to transform the behavior of small-scale quantum processors to equivalent circuit models that are usable with classical circuits in a generic electrical simulator, enabling the detailed analysis of the impact of many important non-idealities. The methodology has specifically been employed to derive a circuit model of a superconducting qubit interacting with the quantized electromagnetic field of a superconducting resonator. Based on this technique, a comprehensive analysis of the qubit operation is performed, including the coherent control and readout of the qubit using electrical signals. Furthermore, the effect of several non-idealities in the system such as qubit relaxation, decoherence and leakage out of the computational subspace are captured, in contrast to previous works. As the presented method enables the co-simulation of the control electronics with the quantum system, it facilitates the design and optimization of near-term superconducting quantum processors.
In this paper, we design an optimal control law to suppress decoherence effects in Markovian open quantum systems. The optimal control law is subject to the tracking precision of the trajectory governed by the free system, which is ideally free from decoherence. We observe from numerical simulation that the undesired decohering dynamics can be partially squeezed out in most systems. Moreover, we observe the existence of sinusoidally oscillating resonant modes that play dominant roles in the controlled trajectory, which can be easily realized by continuous wave pulses. These key features are strictly demonstrated in subsequent analysis under proper assumptions. For systems in which the coherent control does not work, we suggest a feedback control strategy to extend the applicability of control to wider class of systems.
Recent advancements in quantum technologies have highlighted the importance of mitigating system imperfections, including parameter uncertainties and decoherence effects, to improve the performance of experimental platforms. However, most of the previous efforts in quantum control are devoted to the realization of arbitrary unitary operations in a closed quantum system. Here, we improve the algorithm that suppresses system imperfections and noises, providing notably enhanced scalability for robust and optimal control of open quantum systems. Through experimental validation in a superconducting quantum circuit, we demonstrate that our approach outperforms its conventional counterpart for closed quantum systems with an ultra-low infidelity of about 0.60%0.60\%0.60%, while the complexity of this algorithm exhibits the same scaling, with only a modest increase in the prefactor. This work represents a notable advancement in quantum optimal control techniques, paving the way for realizing quantum-enhanced technologies in practical applications.
By means of the design method for bilinear systems in the macroscopic field in association with the characteristic that the mathematical model of pure state quantum system is bilinear,and of selecting the performance index of the controlled system,the optimal control strategy in quantum systems was proposed based on the Lyapunov stability theorem.The detailed design process of optimal control law was derived.Some simulation experiments were performed on a spin-1/2 particle system.Experimental results demonstrate the effectiveness of the method proposed.At the same time,the influence of different parameters on the system control effects is analyzed.
Superconducting nanoelectrical circuits are promising candidates for the physical implementation of the basic building block of a quantum computer, the qubit. We investigate how optimal control theory can be applied to optimize the dynamics of Josephson qubits. For the example of the charge qubit, several numerical methods are employed to search for external control fields which, by current technology, are realistic and induce the desired unitary time evolution within the system (i.e. the desired gate operation) as faithfully as possible in presence of dissipation, decoherence and leakage. Associated calculations which model the environment microscopically are time-intensive so that parallel computing methods are beneficial in the sampling over control fields. In particular, we discuss the performance of differential-evolution-algorithm based optimizations on a cluster. Using a simpler Lindblad model for environmental effects, we compare the performance of a conjugate-gradient approach to that of a genetic algorithm.