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Optimal Control at the Quantum Speed Limit (0902.4193v2)

Published 24 Feb 2009 in quant-ph and cond-mat.other

Abstract: Optimal control theory is a promising candidate for a drastic improvement of the performance of quantum information tasks. We explore its ultimate limit in paradigmatic cases, and demonstrate that it coincides with the maximum speed limit allowed by quantum evolution (the quantum speed limit).

Citations (336)

Summary

  • The paper demonstrates that the Krotov algorithm achieves optimal quantum transitions at the fundamental Quantum Speed Limit for fault-tolerant quantum systems.
  • Numerical investigations show that in the Landau-Zener model, infidelities decay exponentially with iterations once the critical transition time is met.
  • In spin chain models, optimal control performance scales linearly with system size, significantly enhancing quantum state transfer speeds.

Optimal Control at the Quantum Speed Limit

The paper "Optimal Control at the Quantum Speed Limit" by Caneva et al. addresses a fundamental challenge in quantum information science: efficiently controlling quantum systems within the stringent requirements of fault tolerance. It focuses on leveraging optimal control (OC) theory to achieve the highest permitted speed for quantum state transitions, known as the Quantum Speed Limit (QSL).

Quantum information tasks, such as the implementation of quantum gates, necessitate accurate control of quantum systems. Optimal control techniques offer a means to design control pulses that achieve desired state transformations. The Krotov algorithm, a well-known OC method, is explored in this work. This algorithm iteratively optimizes a set of control functions to minimize the infidelity between the achieved and target quantum states.

The authors investigate the limits of the Krotov algorithm in achieving the QSL imposed by quantum mechanics. They perform their analysis on two paradigmatic models: the Landau-Zener (LZ) model and quantum state transfer in spin chains. These models serve as test cases for evaluating the efficacy of OC strategies against established quantum dynamical bounds.

Numerical Investigations and Results

For the Landau-Zener model, the paper explores the minimal transition time required to traverse an avoided level crossing using the Krotov algorithm. It is shown that for times below a critical threshold, denoted as $T_{\mathrm{QSL}$, the algorithm fails to converge to an optimal solution, highlighting the fundamental speed constraints in quantum transitions. For $T \geq T_{\mathrm{QSL}$, infidelities are shown to exponentially decay with the number of iterations, indicating successful control achieving QSL. The numerical findings are corroborated by theoretical estimates based on time-independent quantum mechanical bounds.

In the context of quantum state transfer, the analysis shifts to a model system of a spin chain with Heisenberg interactions. The task here is to transfer quantum information across the chain. Through the use of the Krotov method, the paper demonstrates a substantial increase in transfer speed beyond the limits of adiabatic evolution. Numerical results illustrate that the performance of OC is closely tied to the QSL, adhering to a linear dependency on system size.

Theoretical Implications and Practical Impact

The implications of this research are significant both theoretically and practically. Theoretically, it provides insights into the interplay between OC methods and the dynamical constraints of quantum systems, offering a deeper understanding of how close practical control can get to fundamental quantum limits. Practically, achieving control at the QSL can potentially enhance the performance of quantum devices, paving the way for more efficient quantum computation and communication.

Furthermore, the paper suggests that optimal control strategies focusing on QSLs can serve as effective means of characterizing the operational limits of complex quantum systems.

Future Directions

Future research could build on these findings by exploring the scalability of these OC methods for larger, more complex quantum systems. Additionally, further studies could investigate the extension of these optimal control strategies to other quantum models, potentially incorporating noise and decoherence effects. Understanding and optimizing control in realistic environments will be crucial for the advancement of practical quantum technologies.

In conclusion, this paper by Caneva et al. highlights optimal control as a powerful tool for achieving Quantum Speed Limits, providing crucial insights into the ultimate efficiency boundaries of quantum state evolutions.

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