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arXiv:1405.0485 · Nature Communications

Suppressing qubit dephasing using real-time Hamiltonian estimation

Michael Shulman, Shannon P. Harvey, John M. Nichol, Stephen D. Bartlett, Andrew C. Doherty, V. Umansky, Amir Yacoby

Published Oct 8, 2014• 199 citations
arXivHTMLPDF

Abstract

Unwanted interaction between a quantum system and its fluctuating environment leads to decoherence and is the primary obstacle to establishing a scalable quantum information processing architecture. Strategies such as environmental and materials engineering, quantum error correction and dynamical decoupling can mitigate decoherence, but generally increase experimental complexity. Here we improve coherence in a qubit using real-time Hamiltonian parameter estimation. Using a rapidly converging Bayesian approach, we precisely measure the splitting in a singlet-triplet spin qubit faster than the surrounding nuclear bath fluctuates. We continuously adjust qubit control parameters based on this information, thereby improving the inhomogenously broadened coherence time (T2*) from tens of nanoseconds to >2 μs. Because the technique demonstrated here is compatible with arbitrary qubit operations, it is a natural complement to quantum error correction and can be used to improve the performance of a wide variety of qubits in both meteorological and quantum information processing applications.

DOI
10.1038/ncomms6156

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Unwanted interaction between a quantum system and its fluctuating environment leads to decoherence and is the primary obstacle to establishing a scalable quantum information processing architecture. Strategies such as environmental and materials engineering, quantum error correction and dynamical decoupling can mitigate decoherence, but generally increase experimental complexity. Here we improve coherence in a qubit using real-time Hamiltonian parameter estimation. Using a rapidly converging Bayesian approach, we precisely measure the splitting in a singlet-triplet spin qubit faster than the surrounding nuclear bath fluctuates. We continuously adjust qubit control parameters based on this information, thereby improving the inhomogenously broadened coherence time (T2*) from tens of nanoseconds to >2 μs. Because the technique demonstrated here is compatible with arbitrary qubit operations, it is a natural complement to quantum error correction and can be used to improve the performance of a wide variety of qubits in both meteorological and quantum information processing applications.
Abstract Decoherence, resulting from unwanted interaction between a qubit and its environment, poses a serious challenge towards the development of quantum technologies. Recently, researchers have started analysing how real-time Hamiltonian learning approaches, based on estimating the qubit state faster than the environmental fluctuations, can be used to counteract decoherence. In this work, we investigate how the back-action of the quantum measurements used in the learning process can be harnessed to extend qubit coherence. We propose an adaptive protocol that, by learning the qubit environment, narrows down the distribution of possible environment states. While the outcomes of quantum measurements are random, we show that real-time adaptation of measurement settings (based on previous outcomes) allows a deterministic decrease of the width of the bath distribution, and hence an increase of the qubit coherence. We numerically simulate the performance of the protocol for the electronic spin of a nitrogen-vacancy centre in diamond subject to a dilute bath of 13C nuclear spin, finding a considerable improvement over the performance of non-adaptive strategies.
Scalable quantum information processing requires the ability to tune multiqubit interactions. This makes the precise manipulation of quantum states particularly difficult for multiqubit interactions because tunability unavoidably introduces sensitivity to fluctuations in the tuning parameters, leading to erroneous multiqubit gate operations. The performance of quantum algorithms may be severely compromised by coherent multiqubit errors. It is therefore imperative to understand how these fluctuations affect multiqubit interactions and, more importantly, to mitigate their influence. In this study, we demonstrate how to implement dynamical-decoupling techniques to suppress the two-qubit analogue of the dephasing on a superconducting quantum device featuring a compact tunable coupler, a trending technology that enables the fast manipulation of qubit-qubit interactions. The pure-dephasing time shows up to an approximate 14 times enhancement on average when using robust sequences. The results are in good agreement with the noise generated from room-temperature circuits. Our study further reveals the decohering processes associated with tunable couplers and establishes a framework to develop gates and sequences robust against two-qubit errors.
Optimal control of qubits requires the ability to adapt continuously to their ever-changing environment. We demonstrate a real-time control protocol for a two-electron singlet-triplet qubit with two fluctuating Hamiltonian parameters. Our approach leverages single-shot readout classification and dynamic waveform generation, allowing full Hamiltonian estimation to dynamically stabilize and optimize the qubit performance. Powered by a field-programmable gate array (FPGA), the quantum control electronics estimates the Overhauser field gradient between the two electrons in real time, enabling controlled Overhauser-driven spin rotations and thus bypassing the need for micromagnets or nuclear polarization protocols. It also estimates the exchange interaction between the two electrons and adjusts their detuning, resulting in extended coherence of Hadamard rotations when correcting for fluctuations of both qubit axes. Our study highlights the role of feedback in enhancing the performance and stability of quantum devices affected by quasistatic noise.
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In many realizations of electron spin qubits the dominant source of decoherence is the fluctuating nuclear spin bath of the host material. The slowness of this bath lends itself to a promising mitigation strategy where the nuclear spin bath is prepared in a narrowed state with suppressed fluctuations. Here, this approach is realized for a two-electron spin qubit in a GaAs double quantum dot and a nearly tenfold increase in the inhomogeneous dephasing time T₂* is demonstrated. Between subsequent measurements, the bath is prepared by using the qubit as a feedback loop that first measures its nuclear environment by coherent precession, and then polarizes it depending on the final state. This procedure results in a stable fixed point at a nonzero polarization gradient between the two dots, which enables fast universal qubit control.
This paper investigates the application of quantum decoherence control techniques to enhance distributed quantum computing. The core challenge in distributed quantum computing lies in mitigating the detrimental effects of quantum decoherence, which rapidly degrades the delicate quantum states of qubits, hindering computation accuracy and fidelity. This research proposes a novel approach utilizing precisely controlled interactions between qubits to suppress decoherence and establish robust entanglement, ultimately facilitating accurate and efficient distributed quantum computation. The theoretical framework outlines key control strategies and associated mathematical formulations, demonstrating the potential for significant improvements in performance. Specifically, we explore the use of tailored pulse sequences designed to minimize dephasing and minimize the impact of environmental noise. The proposed method leverages a feedback control system to dynamically adjust the control parameters based on real-time decoherence monitoring. The presented formalism includes the Bloch equations and their extensions to account for controlled interactions, providing a rigorous foundation for the theoretical analysis. We demonstrate the feasibility of achieving high-fidelity entanglement and quantum gates in a distributed system, paving the way for scalable quantum computation. Finally, we discuss the limitations and future directions of this approach, emphasizing the need for advanced noise mitigation techniques and improved qubit coherence times.