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arXiv:0704.0771 · Physical Review A

Suppression of 1/fα noise in one-qubit systems

Pekko Kuopanportti, Mikko Möttönen, Ville Bergholm, O.-P. Saira, Jun Zhang, K. Birgitta Whaley

Published Mar 20, 2008• 41 citations
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Abstract

We investigate the generation of quantum operations for one-qubit systems under classical Markovian noise with a $1/{f}^{\ensuremath{\alpha}}$ power spectrum, where $2>\ensuremath{\alpha}>0$. We present an efficient way to approximate the noise with a discrete multistate Markovian fluctuator. With this method, the average temporal evolution of the qubit state operator under $1/{f}^{\ensuremath{\alpha}}$ noise can be feasibly determined from recently derived deterministic master equations. We obtain qubit operations such as quantum memory and the NOT gate to high fidelity by a gradient-based optimization algorithm. For the NOT gate, the computed fidelities are qualitatively similar to those obtained earlier for random telegraph noise. In the case of quantum memory, however, we observe a nonmonotonic dependency of the fidelity on the operation time, yielding a natural access rate of the memory.

DOI
10.1103/physreva.77.032334

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We address the problem of implementing high-fidelity one-qubit operations subject to time-dependent noise in the qubit energy splitting. We show with explicit numerical results that high-fidelity bit flip operations may be generated by imposing bounded control fields. For noise correlation times shorter than the time for a $\ensuremath{\pi}$ pulse, the time-optimal $\ensuremath{\pi}$ pulse itself yields the highest fidelity. For very long correlation times, fidelity loss is approximately due to systematic error, which is efficiently tackled by compensation for off resonance with a pulse sequence (CORPSE). For intermediate ranges of the noise correlation time, we find that short CORPSE, which is less accurate than CORPSE in correcting systematic errors, yields higher fidelities. Numerical optimization of the pulse sequences using gradient ascent pulse engineering results in noticeable improvement of the fidelity for a bit flip operation on the computational basis states and a small but still positive fidelity enhancement for the NOT gate.
Abstract A crucial task to obtain optimal and reliable quantum devices is to quantify their overall performance. The average fidelity of quantum gates is a particular figure of merit that can be estimated efficiently by randomized benchmarking (RB). However, the concept of gate-fidelity itself relies on the crucial assumption that noise behaves in a predictable, time-local, or so-called Markovian manner, whose breakdown can naturally become the leading source of errors as quantum devices scale in size and depth. We analytically show that error suppression techniques such as dynamical decoupling (DD) and Pauli-twirling can operationally Markovianize RB: (i) fast DD reduces non-Markovian RB to an exponential decay plus longer-time corrections, while on the other hand, (ii) Pauli-twirling generally does not affect the average, but (iii) it always suppresses the variance of such RB outputs. We demonstrate these effects numerically with a qubit noise model. Our results show that simple and efficient error suppression methods can simultaneously tame non-Markovian noise and allow for standard and reliable gate quality estimation, a fundamentally important task in the path toward fully functional quantum devices.
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We apply a graybox machine-learning framework to model and control a qubit undergoing Markovian and non-Markovian dynamics from environmental noise. The approach combines physics-informed equations with a lightweight transformer neural network based on the self-attention mechanism. The model is trained on simulated data and learns an effective operator that predicts observables accurately, even in the presence of memory effects. We benchmark both non-Gaussian random-telegraph noise and Gaussian Ornstein-Uhlenbeck noise and achieve low prediction errors even in challenging noise coupling regimes. Using the model as a dynamics emulator, we perform gradient-based optimal control to identify pulse sequences implementing a universal set of single-qubit gates, achieving fidelities above 99% for the lowest considered value of the coupling and remaining above 90% for the highest.
The ubiquitous effects of the environment on quantum-mechanical systems generally cause temporally correlated fluctuations. This particularly holds for systems of interest for quantum computation where such effects lead to correlated errors. The Markovian approximation neglects these correlations and thus fails to accurately describe open-system dynamics where these correlations become relevant. In driven open systems, yet another approximation is persistently used, often unknowingly, in which one describes the decay effects independently from the time-dependent controlling fields acting on the system, thereby ignoring further temporally correlated effects. To overcome these shortcomings, we develop a quantum master equation for driven systems weakly coupled to quantum environments that avoids the aforementioned field-independent approximation, as well as the Markovian approximation. Our method makes it possible to track all occurring decay channels and their time-dependent generalized rates which we illustrate in the example of a generally driven two-level system. We also demonstrate that correlated and field-dependent dissipative effects can lead to an increase in the performance of single-qubit gate operations.