Estimating the Coherence of Noise in Quantum Control of a Solid-State Qubit

Feng, Guoliang; Wallman, Joel J.; Buonacorsi, Brandon; Park, Daniel K.; Xin, Tao; Lu, Dawei; Baugh, Jonathan; Laflamme, Raymond

doi:10.1103/physrevlett.117.260501

Cited by 54 publications

(58 citation statements)

References 48 publications

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“…Similarly, the decoherence level is defined as r decoh /r. Equation (66) strengthens the insight behind the notion of coherence level introduced (under different appellations) in [15,40]. In those previous works, the RHS of eq.…”

Section: The Coherence Levelsupporting

confidence: 78%

A polar decomposition for quantum channels (with applications to bounding error propagation in quantum circuits)

Carignan-Dugas

Alexander

Emerson

2019

Quantum

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1 They attribute all the error dynamics on the qubit; the intuitive geometric picture offered by parameterization of processes acting on the Bloch sphere allows showing the saturation of the bound for unital channels. The bound in the non-unital case included a dimensional factor which prevented its saturation.2 Given realistic errors, which are properly defined in section 5.1, and are more formally referred to as "equable". The equability assumption corresponds to ruling out two types of errors. 1) Extreme dephasing effects between a small set of states and the rest of the systems. 2) Extreme Hamiltonian alterations.

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Section: The Coherence Levelsupporting

confidence: 78%

A polar decomposition for quantum channels (with applications to bounding error propagation in quantum circuits)

Carignan-Dugas

Alexander

Emerson

2019

Quantum

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“…This method provides a way to visualize how an error channel is modified by QEC. In real quantum information processing systems, errors arise from both incoherent and coherent processes [27,28]. However, we focus on purely incoherent and coherent errors to emphasize their respective distinctive features.…”

Section: Introductionmentioning

confidence: 99%

Errors and pseudothresholds for incoherent and coherent noise

et al. 2016

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We compare the effect of single qubit incoherent and coherent errors on the logical error rate of the Steane [[7,1,3]] quantum error correction code by performing an exact full-density-matrix simulation of an error correction step. We find that the effective 1-qubit process matrix at the logical level reveals the key differences between the error models and provides insight into why the Pauli twirling approximation is a good approximation for incoherent errors and a poor approximation for coherent ones. Approximate channels composed of Clifford operations and Pauli measurement operators that are pessimistic at the physical level result in pessimistic error rates at the logical level. In addition, we observe that the pseudo-threshold can differ by a factor of five depending on whether the error is calculated using the fidelity or the distance.

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“…Measuring the incoherent error rate of a quantum channel has significant implications in the development of quantum devices. The incoherent error can be quantified using purity benchmarking [36,37]. Purity benchmarking can be combined with the standard randomized benchmarking protocol to distinguish coherent and incoherent error, which is an important step to understand different types of noise affecting quantum control.…”

Section: Purity Benchmarking For Quantum Controlmentioning

confidence: 99%

Parallel quantum trajectories via forking for sampling without redundancy

et al. 2019

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The computational cost of preparing a quantum state can be substantial depending on the structure of data to be encoded. Many quantum algorithms require repeated sampling to find the answer, mandating reconstruction of the same input state for every execution of an algorithm. Thus, the advantage of quantum computation can diminish due to redundant state initialization. We present a framework based on quantum forking that bypasses this fundamental issue and expedites a family of tasks that require sampling from independent quantum processes. Quantum forking propagates an input state to multiple quantum trajectories in superposition, and a weighted power sum of individual results from each trajectories is obtained in one measurement via quantum interference. The significance of our work is demonstrated via applications to implementing non-unitary quantum channels, studying entanglement and benchmarking quantum control. A proof-of-principle experiment is implemented on the IBM and Rigetti quantum cloud platforms.

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Estimating the Coherence of Noise in Quantum Control of a Solid-State Qubit

Cited by 54 publications

References 48 publications

A polar decomposition for quantum channels (with applications to bounding error propagation in quantum circuits)

A polar decomposition for quantum channels (with applications to bounding error propagation in quantum circuits)

Errors and pseudothresholds for incoherent and coherent noise

Parallel quantum trajectories via forking for sampling without redundancy

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