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arXiv:2209.01648

Conjecture C Still Stands

Gil Kalai

Published Sep 4, 2022• 0 citations
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Abstract

More than ten years ago the author described a parameter $K(ρ)$ for the complexity of $n$-qubit quantum state $ρ$ and raised the conjecture (referred to as "Conjecture C") that when this parameter is superpolynomial in $n$, the state $ρ$ is not experimentally feasible (and will not be experimentally achieved without quantum fault-tolerance). Shortly afterward [6] (arXiv:1204.3404), Steve Flammia and Aram Harrow claimed that the simple easy-to-construct $W$ states are counterexamples to "Conjecture C." We point out that Flammia and Harrow's argument regarding $W$-states is incomplete. Moreover, the emergent picture from experimental progress of the past decade on noisy intermediate scale quantum (NISQ) computers suggests that $W$-states, as simple as they appear, cannot be achieved experimentally by NISQ computers, and can not be constructed without quantum fault-tolerance.

DOI
10.48550/arxiv.2209.01648

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More than ten years ago the author described a parameter K(ρ)K(ρ)K(ρ) for the complexity of nnn-qubit quantum state ρρρ and raised the conjecture (referred to as "Conjecture C") that when this parameter is superpolynomial in nnn, the state ρρρ is not experimentally feasible (and will not be experimentally achieved without quantum fault-tolerance). Shortly afterward [6] (arXiv:1204.3404), Steve Flammia and Aram Harrow claimed that the simple easy-to-construct WWW states are counterexamples to "Conjecture C." We point out that Flammia and Harrow's argument regarding WWW-states is incomplete. Moreover, the emergent picture from experimental progress of the past decade on noisy intermediate scale quantum (NISQ) computers suggests that WWW-states, as simple as they appear, cannot be achieved experimentally by NISQ computers, and can not be constructed without quantum fault-tolerance.
In this paper I revisit my 2006 conjecture on correlated errors in entangled physical qubits, originally proposed as a potential obstruction to quantum fault tolerance. The conjecture asserts that, in any physical implementation of a quantum computer, the effective noise channel acting on entangled physical qubits contains a joint fully depolarizing component, with a rate comparable to that of two-qubit gate errors. This hypothesized structural constraint goes beyond standard noise models and, if valid, would pose a significant challenge to scalable quantum fault tolerance. The conjecture remains open, but recent advances in experimental quantum computing bring it within reach of empirical testing on current devices. I also discuss two related directions in my critical study of quantum computation: the role of noise sensitivity and computational complexity in noisy intermediate-scale quantum systems, and the statistical analysis of experimental claims of quantum advantage. Finally, since this paper is written for a volume honoring Yuri Gurevich, I include some reflections on the ways in which my scientific and personal trajectory became intertwined with Yuri's.
Between NISQ (noisy intermediate scale quantum) approaches without any proof of robust quantum advantage and fully fault-tolerant quantum computation, we propose a scheme to achieve a provable superpolynomial quantum advantage (under some widely accepted complexity conjectures) that is robust to noise with minimal error correction requirements. We choose a class of sampling problems with commuting gates known as sparse IQP (Instantaneous Quantum Polynomial-time) circuits and we ensure its fault-tolerant implementation by introducing the tetrahelix code. This new code is obtained by merging several tetrahedral codes (3D color codes) and has the following properties: each sparse IQP gate admits a transversal implementation, and the depth of the logical circuit can be traded for its width. Combining those, we obtain a depth-1 implementation of any sparse IQP circuit up to the preparation of encoded states. This comes at the cost of a space overhead which is only polylogarithmic in the width of the original circuit. We furthermore show that the state preparation can also be performed in constant depth with a single step of feed-forward from classical computation. Our construction thus exhibits a robust superpolynomial quantum advantage for a sampling problem implemented on a constant depth circuit with a single round of measurement and feed-forward.
Quantum computing has made significant advancements in the last years in both hardware and software. Unfortunately, the currently available Noisy Intermediate-Scale Quantum (NISQ) hardware is still heavily affected by noise. Many optimization techniques have been developed to reduce the negative effects thereof, which, however, only works up to a certain point. Therefore, scaling quantum applications from currently considered small research examples to industrial applications requires error-correction techniques to execute quantum circuits in a fault-tolerant fashion and enter the Fault-Tolerant Quantum Computing (FTQC) era. These error-correction techniques introduce dramatic qubit overheads, leading to the requirement of tens of thousands of qubits already for toy-sized examples. Hence, quantum circuit optimization that reduces qubit overheads when shifting from the NISQ to the FTQC era is essential. This raises the question, whether we need to start from scratch, or whether current state-of-the-art optimization techniques can be used as a basis for this. To approach this question, this work investigates the effects of different optimization passes on a representative selection of quantum circuits. Since hardly any tools to automatically design and evaluate FTQC quantum circuits exist yet, we utilize resource estimation to compare the (potential) benefits gained by applying NISQ quantum circuit optimization to estimated FTQC resource requirements. The Results indicate that, indeed, the estimated resource requirements for FTQC can be improved by applying NISQ quantum circuit optimization techniques. At the same time, more detailed investigations show what techniques lead to more benefits for FTQC compared to others, providing guidelines for the transfer of NISQ optimization techniques to the FTQC era.