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arXiv:1903.12651 · Physical Review A

Adiabatic population transfer of dressed spin states with quantum optimal control

Shu-Hao Wu, Mayra Amezcua, Hailin Wang

Published Jun 10, 2019• 14 citations
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Abstract

We report theoretical studies of adiabatic population transfer using dressed spin states. Quantum optimal control using the chopped random basis (CRAB) algorithm has been implemented in a negatively charged diamond nitrogen vacancy center that is coupled to a strong and resonant microwave field. We show that the dressed spin states are highly effective in suppressing effects of spin dephasing on adiabatic population transfer. The numerical simulation also demonstrates that CRAB-based quantum optimal control can enable an efficient and robust adiabatic population transfer.

DOI
10.1103/physreva.99.063812

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We report theoretical studies of adiabatic population transfer using dressed spin states. Quantum optimal control using the chopped random basis (CRAB) algorithm has been implemented in a negatively charged diamond nitrogen vacancy center that is coupled to a strong and resonant microwave field. We show that the dressed spin states are highly effective in suppressing effects of spin dephasing on adiabatic population transfer. The numerical simulation also demonstrates that CRAB-based quantum optimal control can enable an efficient and robust adiabatic population transfer.
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Optimal control of quantum system is significant for information science and technology. Here, an efficient scheme is proposed for implementing fast population transfer in a spin qutrit of nitrogen-vacancy center via shortcuts to adiabaticity (STA) with simplified drivings. At two-photon resonance, a Λ\Lambda Λ -configuration interaction between the spin qutrit and driving fields can be obtained effectively. By the invariant-based STA, the reversible population transfer can be realized using the Rabi pulses with sine and cosine waveforms. Compared with the superadiabatic transitionless driving, the present pulses in our strategy become simplified technically, contributing to reduce the error effect of control parameter deviations. Moreover, the high-fidelity quantum operations can be performed with the accessible decoherence rates. The protocol could offer an optimized avenue towards the STA-based quantum control of spin qutrit experimentally.
This work is devoted to the study and the application of the Chopped RAndomBasis (CRAB) control algorithm as an efficient, versatile optimal control techniqueto be used for the purpose of enhancing the quality of quantum processes. In orderto show its principal aspects, the method is here applied to different systems, inparticular one-qubit and two-qubit system. Finally, the dressed CRAB algorithmis presented as a valid alternative to the standard method, as it comes with theadditional property of guaranteed convergence to the global optimum
Integer factorization remains a significant challenge for classical computers and is fundamental to the security of RSA encryption. Adiabatic quantum algorithms present a promising solution, yet their practical implementation is limited by the short coherence times of current noisy intermediate-scale quantum devices and quantum simulators. In this work, we apply the chopped random-basis (CRAB) optimization technique to enhance adiabatic quantum factorization algorithms. We demonstrate the effectiveness of CRAB by applying it to factor the integers ranging from 21 to 2479, achieving significantly improved fidelity of the target state when the evolution time exceeds the quantum speed limit. Notably, this performance improvement shows resilience in the presence of dephasing noise, highlighting CRAB's practical utility in noisy quantum systems. Our findings suggest that CRAB optimization can serve as a powerful tool for advancing adiabatic quantum algorithms, with broader implications for quantum information processing tasks.
In this work, we describe in detail the chopped random basis (CRAB) optimal control technique recently introduced to optimize time-dependent density matrix renormalization group simulations [P. Doria, T. Calarco, and S. Montangero, Phys. Rev. Lett. 106, 190501 (2011)]. Here, we study the efficiency of this control technique in optimizing different quantum processes and we show that in the considered cases we obtain results equivalent to those obtained via different optimal control methods while using less resources. We propose the CRAB optimization as a general and versatile optimal control technique.
The chopped random basis (CRAB) ansatz for quantum optimal control has been proven to be a versatile tool to enable quantum technology applications such as quantum computing, quantum simulation, quantum sensing, and quantum communication. Its capability to encompass experimental constraints-while maintaining an access to the usually trap-free control landscape-and to switch from open-loop to closed-loop optimization (including with remote access-or RedCRAB) is contributing to the development of quantum technology on many different physical platforms. In this review article we present the development, the theoretical basis and the toolbox for this optimization algorithm, as well as an overview of the broad range of different theoretical and experimental applications that exploit this powerful technique.