Improved Error Thresholds for Measurement-Free Error Correction

Crow, Daniel; Joynt, Robert; Saffman, M.

doi:10.1103/physrevlett.117.130503

Cited by 47 publications

(52 citation statements)

References 38 publications

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“…As a consequence, the results shown in this paper are applicable to the optimisation of other QEC codes and the compensation of systematic errors appearing in other physical platforms for quantum-information processing such as, e.g. trapped ions [20][21][22][23][24][25][26][27][28], Rydberg atoms [29][30][31] in optical lattices [32][33][34] or tweezer arrays [35,36] or other AMO or solid-state architectures [37][38][39][40][41][42].…”

Section: Introductionmentioning

confidence: 84%

Adaptive Bayesian phase estimation for quantum error correcting codes

2019

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Realisation of experiments even on small and medium-scale quantum computers requires an optimisation of several parameters to achieve high-fidelity operations. As the size of the quantum register increases, the characterisation of quantum states becomes more difficult since the number of parameters to be measured grows as well and finding efficient observables in order to estimate the parameters of the model becomes a crucial task. Here we propose a method relying on application of Bayesian inference that can be used to determine systematic, unknown phase shifts of multi-qubit states. This method offers important advantages as compared to Ramsey-type protocols. First, application of Bayesian inference allows the selection of an adaptive basis for the measurements which yields the optimal amount of information about the phase shifts of the state. Secondly, this method can process the outcomes of different observables at the same time. This leads to a substantial decrease in the resources needed for the estimation of phases, speeding up the state characterisation and optimisation in experimental implementations. The proposed Bayesian inference method can be applied in various physical platforms that are currently used as quantum processors.

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Section: Introductionmentioning

confidence: 84%

Adaptive Bayesian phase estimation for quantum error correcting codes

2019

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“…In fact the slow down from classical processing for syndrome extraction and correction could be removed entirely using a measurement free protocol, see e.g. [PSBT10] which in a recent analysis show error thresholds [CJS16] only about 5 times worse than the measurement heavy surface code. This could potentially dramatically improve overall speed of error correction.…”

Section: Future Enhancements Of Quantum Attacksmentioning

confidence: 99%

Quantum Attacks on Bitcoin, and How to Protect Against Them

Aggarwal¹,

Brennen²,

Lee³

et al. 2018

ledger

107

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The key cryptographic protocols used to secure the internet and financial transactions of today are all susceptible to attack by the development of a sufficiently large quantum computer. One particular area at risk are cryptocurrencies, a market currently worth over 150 billion USD. We investigate the risk of Bitcoin, and other cryptocurrencies, to attacks by quantum computers. We find that the proof-of-work used by Bitcoin is relatively resistant to substantial speedup by quantum computers in the next 10 years, mainly because specialized ASIC miners are extremely fast compared to the estimated clock speed of near-term quantum computers. On the other hand, the elliptic curve signature scheme used by Bitcoin is much more at risk, and could be completely broken by a quantum computer as early as 2027, by the most optimistic estimates.We analyze an alternative proof-of-work called Momentum, based on finding collisions in a hash function, that is even more resistant to speedup by a quantum computer. We also review the available post-quantum signature schemes to see which one would best meet the security and efficiency requirements of blockchain applications.

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“…However, Paz-Silva et al demonstrated that measurementfree error correction for the Bacon-Shor code could have thresholds only about an order of magnitude worse than conventional schemes [17]. More recently, Crow et al improved these results by using redundant syndrome extractions and reported thresholds for three qubit bitflip (BF), Bacon-Shor, and Steane codes that are comparable to measurement-based values [18]. However, measurement-free surface code implementations have not yet been thoroughly investigated.…”

Section: Introductionmentioning

confidence: 99%

Measurement-free implementations of small-scale surface codes for quantum-dot qubits

et al. 2018

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The performance of quantum error correction schemes depends sensitively on the physical realizations of the qubits and the implementations of various operations. For example, in quantum dot spin qubits, readout is typically much slower than gate operations, and conventional surface code implementations that rely heavily on syndrome measurements could therefore be challenging. However, fast and accurate reset of quantum dot qubits-without readout-can be achieved via tunneling to a reservoir. Here, we propose small-scale surface code implementations for which syndrome measurements are replaced by a combination of Toffoli gates and qubit reset. For quantum dot qubits, this enables much faster error correction than measurement-based schemes, but requires additional ancilla qubits and non-nearest-neighbor interactions. We have performed numerical simulations of two different coding schemes, obtaining error thresholds on the orders of 10 −2 for a 1D architecture that only corrects bit-flip errors, and 10 −4 for a 2D architecture that corrects bit-and phase-flip errors.

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Improved Error Thresholds for Measurement-Free Error Correction

Cited by 47 publications

References 38 publications

Adaptive Bayesian phase estimation for quantum error correcting codes

Adaptive Bayesian phase estimation for quantum error correcting codes

Quantum Attacks on Bitcoin, and How to Protect Against Them

Measurement-free implementations of small-scale surface codes for quantum-dot qubits

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