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Physical Review Applied

Scalable quantum metrology via recursive optimization

Jungeng Zhou, Jiahao Huang, Chaohong Lee

Published Oct 25, 2024• 3 citations
Publisher

Abstract

Achieving higher precision in quantum metrology demands the optimization of both entangled-state preparation and readout processes. However, direct machine optimization using variational dynamics becomes impractical and time consuming, particularly with a large particle number. Here, we develop a heuristic recursive screening-breeding algorithm designed to efficiently optimize variational dynamics for scalable quantum metrology. Leveraging the similarity between optimal variables for adjacent particle numbers, the algorithm recursively updates variables from few to many particles, significantly reducing computational overhead. This enables the identification of optimized dynamics for entangled state preparation and readout, even with a large particle number. As a proof of concept, we apply the algorithm to efficiently optimize twist-and-turn dynamics for spin cat state preparation, interaction-based readout, and time-reversal metrology. Notably, in well-recursive cases, optimized variables can be approximated via fitting without recursion. Our recursive optimization algorithm establishes an efficient framework for scalable quantum metrology protocols, providing a practical avenue for quantum sensing with many-body systems.

DOI
10.1103/physrevapplied.22.044066

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Achieving higher precision in quantum metrology demands the optimization of both entangled-state preparation and readout processes. However, direct machine optimization using variational dynamics becomes impractical and time consuming, particularly with a large particle number. Here, we develop a heuristic recursive screening-breeding algorithm designed to efficiently optimize variational dynamics for scalable quantum metrology. Leveraging the similarity between optimal variables for adjacent particle numbers, the algorithm recursively updates variables from few to many particles, significantly reducing computational overhead. This enables the identification of optimized dynamics for entangled state preparation and readout, even with a large particle number. As a proof of concept, we apply the algorithm to efficiently optimize twist-and-turn dynamics for spin cat state preparation, interaction-based readout, and time-reversal metrology. Notably, in well-recursive cases, optimized variables can be approximated via fitting without recursion. Our recursive optimization algorithm establishes an efficient framework for scalable quantum metrology protocols, providing a practical avenue for quantum sensing with many-body systems.
Abstract Entanglement is one of the key ingredients for enhancing the measurement precision of quantum sensors. Generally, there is a trade-off between state preparation and sensing within a limited coherence time. To fully exploit temporal resources, concurrent entanglement generation and sensing with designed sequence of rotations are proposed. Based on twist-and-turn dynamics, modulated rotations along only one axis may be sufficient to drive the state to the optimal one for tiny estimated parameter. However, when the estimated parameter is not tiny, it may impact the evolved state and hence degrade the final measurement precision. Here, we introduce another modulated rotations along different axis and find out the optimal control sequences by means of machine optimization. The optimal measurement precision bounds become independent on the estimated parameter, which improves the dynamic range of the machine designed sensors. Particularly, by optimizing the interaction strength for different particle number and the time-modulated rotations along two different axes via machine optimization, the Heisenberg-limited precision scaling can be attained. Our work points out a way for designing optimized quantum-enhanced metrology protocols, which is promising for developing practical quantum sensors.
By leveraging quantum effects, such as superposition and entanglement, quantum metrology promises higher precision than classical strategies. It is, however, a challenging task to achieve the higher precision on practical systems. This is mainly due to difficulties in engineering nonclassical states and performing nontrivial measurements on the system, especially when the number of particles is large. Here we propose a variational scheme with the Loschmidt echo for quantum metrology. By utilizing hardware-efficient ansatzes in the design of variational quantum circuits, the quantum Fisher information (QFI) of the probe state can be extracted from the experimentally measured Loschmidt echo in a scalable manner. This QFI is then used to guide the online optimization of the preparation of the probe state. We experimentally implement the scheme on an ensemble of 10-spin quantum processors and achieve a 12.4-dB enhancement of the measurement precision over the uncorrelated states, which is close to the theoretical limit. The scheme can also be employed on various other noisy intermediate-scale quantum devices, which provides a promising protocol to demonstrate quantum advantages.
Quantum metrology studies the use of quantum mechanical systems as measurement devices or sensors. Surprisingly, preparing a sensor in an entangled state can enhance measurement precision. The simplest protocols for entanglement enhancement sense only small changes in a quantity. The range of values over which a measurement protocol works is called its dynamic range. For many types of sensors we require end-to-end protocols that describe how to use entanglement to achieve enhanced precision over a large dynamic range. In this dissertation, we describe two approaches to achieving entanglement-enhanced sensing over a large dynamic range. The first approach uses entangling resources in a way that circumvents the dynamic-range limitation by numerically optimizing variational circuits. Our protocols show improved performance at fixed circuit depth compared to previous variational-circuit-based approaches, and the generality of our approach reveals several generic features of such protocols. The second approach uses adaptivity to first obtain a preliminary estimate of the quantity and then iteratively refines it. In particular, we describe the use of one-axis twisting dynamics at each stage of this protocol to minimize the expected estimation error.
Nature imposes fundamental limits on how precisely we can probe the physical world. Quantum metrology is the study of achieving higher precision and accuracy in estimating the physical parameters by harnessing quantum resources. It is considered one of the most promising quantum technologies, offering significant advantages over classical ones in both near‑term and long‑term applications. However, existing theoretical research in quantum metrology often falls short of providing a unified and rigorous understanding of the ultimate precision under realistic experimental limitations on available quantum resources. In this thesis, we conduct a systematic investigation of the optimal precision limits in quantum metrology and identify the metrological strategies that achieve optimality under specified resource constraints. We primarily focus on the single-parameter estimation of quantum processes, a cornerstone task in quantum metrology. We first establish a general framework of strictly optimal quantum metrology using semidefinite programming within the formalism of higher-order quantum operations. This framework reveals a strict hierarchy for the performance of different families of strategies---parallel, sequential, and indefinite-causal-order ones---each subject to specific causal constraints. Our results rigorously demonstrate a quantum metrological advantage of indefinite causal order in finite-dimensional systems, which has recently aroused rapidly growing interest. In realistic scenarios, a fully optimized quantum metrology protocol may be experimentally demanding due to the complexity of state preparation and control. Tailored to practical constraints on the allowed ancilla and control operations, we propose a highly efficient tensor network algorithm to optimize the probe state and a long sequence of control for quantum metrology. When the number of control steps tends to infinity, we develop an asymptotic theory of quantum metrology for achieving the ultimate precision limit---Heisenberg limit---without ancilla. This contrasts with the traditional approach using quantum error correction for metrology that typically requires noiseless and controllable ancilla. Our results pave the way for exploiting the full potential of quantum resources in metrology. In the near term, our methods enable high-precision estimation with limited interaction with the unknown process using experimentally feasible control techniques. In the long term, they lay the foundation for scalable and fault-tolerant quantum metrology.
Useful quantum metrology requires nonclassical states with a high particle number and (close to) the optimal exploitation of the state's quantum correlations. Unfortunately, the single-particle detection resolution demanded by conventional protocols, such as spin squeezing via one-axis twisting, places severe limits on the particle number. Additionally, the challenge of finding optimal measurements (that saturate the quantum Cramér-Rao bound) for an arbitrary nonclassical state limits most metrological protocols to only moderate levels of quantum enhancement. "Interaction-based readout" protocols have been shown to allow optimal interferometry or to provide robustness against detection noise at the expense of optimality. In this Letter, we prove that one has great flexibility in constructing an optimal protocol, thereby allowing it to also be robust to detection noise. This requires the full probability distribution of outcomes in an optimal measurement basis, which is typically easily accessible and can be determined from specific criteria we provide. Additionally, we quantify the robustness of several classes of interaction-based readouts under realistic experimental constraints. We determine that optimal and robust quantum metrology is achievable in current spin-squeezing experiments.
Spin cat states are promising candidates for achieving Heisenberg-limited quantum metrology. It is suggested that spin cat states can be generated by adiabatic evolution. However, due to the limited coherence time, the adiabatic process may be too slow to be practical. To speed up the state generation, we propose to use machine optimization to generate desired spin cat states. Our proposed scheme relies only on experimentally demonstrated one-axis twisting interactions with piecewise time-modulation of rotations designed via machine optimization. The required evolution time is much shorter than the one with adiabatic evolution and it does not make large modification to the existing experimental setups. Our protocol with machine optimization is efficient and easy to be implemented in state-of-the-art experiments.