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Evidence for the utility of quantum computing before fault tolerance

Youngseok Kim, Andrew Eddins, Sajant Anand

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Ken Xuan Wei, Ewout van den Berg, Sami Rosenblatt, Hasan Nayfeh, Yantao Wu, Michael Zaletel, Kristan Temme, Abhinav Kandala

2023 · Nature

PhysicsDistributed systemsComputer systems
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From the abstract

Abstract Quantum computing promises to offer substantial speed-ups over its classical counterpart for certain problems. However, the greatest impediment to realizing its full potential is noise that is inherent to these systems. The widely accepted solution to this challenge is the implementation of fault-tolerant quantum circuits, which is out of reach for current processors. Here we report experiments on a noisy 127-qubit processor and demonstrate the measurement of accurate expectation values for circuit volumes at a scale beyond brute-force classical computation. We argue that this represents evidence for the utility of quantum computing in a pre-fault-tolerant era. These experimental results are enabled by advances in the coherence and calibration of a superconducting processor at this scale and the ability to characterize 1 and controllably manipulate noise across such a large device. We establish the accuracy of the measured expectation values by comparing them with the output of exactly verifiable circuits. In the regime of strong entanglement, the quantum computer provides correct results for which leading classical approximations such as pure-state-based 1D (matrix product states, MPS) and 2D (isometric tensor network states, isoTNS) tensor network methods 2,3 break down. These experiments demonstrate a foundational tool for the realization of near-term quantum applications 4,5 .

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Original HN comments, with labels from simple text rules. A label describes the whole comment and may miss context or irony. Read the discussion to make up your own mind. About the labels

4 selected excerpts · 4 total mentions

westurner
Neutral mention · rule
"Confinement in the Transverse Field Ising model on the Heavy Hex lattice" (2024) https://journals.aps.org/prl/abstract/10.1103/PhysRevLett.13... : > Abstract: Inspired by a recent quantum computing experiment [Y. Kim et al., Nature (London), 618, 500–5 (2023)], we study the emergence of confinement in the transverse field Ising model on a decorated hexagonal lattice. Using an infinite tensor network state optimized with belief propagation we show how a quench from a broken symmetry state leads to striking nonthermal behavior underpinned by persistent oscillations and saturation of the entanglement entropy. We explain this phenomenon by constructing a minimal model based…
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on the confinement of elementary excitations. Our model is in excellent agreement with our numerical results. For quenches to larger values of the transverse field and/or from nonsymmetry broken states, our numerical results display the expected signatures of thermalization: a linear growth of entanglement entropy in time, propagation of correlations, and the saturation of observables to their thermal averages. These results provide a physical explanation for the unexpected classical simulability of the quantum dynamics. "Evidence for the utility of quantum computing before fault tolerance" (2023) https://www.nature.com/articles/s41586-023-06096-3 : > Abstract: [...] In the regime of strong entanglement, the quantum computer provides correct results for which leading classical approximations such as pure-state-based 1D (matrix product states, MPS) and 2D (isometric tensor network states, isoTNS) tensor network methods [2,3] break down. These experiments demonstrate a foundational tool for the realization of near-term quantum applications [4,5]
Original comment Confinement in the Transverse Field Ising Model on the Heavy Hex Lattice
yorwba
Neutral mention · rule
Chasing through a bunch of links, their claim to "usefulness" seems to be based on this paper https://www.nature.com/articles/s41586-023-06096-3 where "Our benchmark circuit is the Trotterized time evolution of a 2D transverse-field Ising model, sharing the topology of the qubit processor" which sounds like a task picked to be easy for this particular quantum processor to solve, and maybe of interest to some physicists working with Ising models, but not really "useful" in the general sense.
Original comment IBM demonstrates useful Quantum computing within 133-qubit Heron
deepburner
Neutral mention · rule
Quantum Computing/Information researcher here. This article is largely garbage, the original (~2 month old) paper is surprisingly readable [0] and I suggest you to check it out. Here's my $0.02: The efforts of the Google team is commendable in that they're trying to squeeze as much out of their noisy systems as possible until error correction is here (they need to, to justify their existence after all) and they are aware of the shortcomings of the paradigm. But personally I don't see anything useful coming out until error correction and number of qubits are improved many orders of magnitude to have fault tolerant QC. The jury is still out on their utility once realized;…
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Shor's algorithm is an obvious one followed by quantum simulation algorithms that might benefit chemistry and fundamental physics, but it's not as big of a silver bullet as we thought before for simulation. Maybe someone can tell me what fast prime factorization is good for besides breaking encryption. Also IBM released a paper[1] recently making similar claims ("quantum advantage without complete error correction") which got obliterated by 2 back to back papers [2,3] that did what they did for much cheaper on a classical computer. [0]: https://arxiv.org/pdf/2304.11119.pdf [1]: https://www.nature.com/articles/s41586-023-06096-3 [2]: https://arxiv.org/pdf/2306.14887.pdf [3]: https://arxiv.org/pdf/2306.16372.pdf
Original comment Google’s quantum computer instantly makes calculations that take rivals 47 years
westurner
Neutral mention · rule
Quantum annealing > D-Wave implementations : https://en.wikipedia.org/wiki/Quantum_annealing#D-Wave_imple... : > In December 2015, Google announced that the D-Wave 2X outperforms both simulated annealing and Quantum Monte Carlo by up to a factor of 100,000,000 on a set of hard optimization problems.[35] Timeline of quantum computing and communication > 2023: https://en.wikipedia.org/wiki/Timeline_of_quantum_computing_... : > 14 June [2023] – IBM computer scientists report that a quantum computer produced better results for a physics problem than a conventional supercomputer.[365][366] : "Evidence for the utility of quantum computing before fault tolerance" (2023) :…
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https://www.nature.com/articles/s41586-023-06096-3 : > Quantum advantage can be approached in two steps: first, by demonstrating the ability of existing devices to perform accurate computations at a scale that lies beyond brute-force classical simulation, and second by finding problems with associated quantum circuits that derive an advantage from these devices. Here we focus on taking the first step and do not aim to implement quantum circuits for problems with proven speed-ups. Quantum Algorithm Zoo lists speedups by algorithm; https://quantumalgorithmzoo.org/ https://westurner.github.io/hnlog/#q-tequila ctrl-f "tequila" : From "Computational Chemistry Using PyTorch" https://news.ycombinator.com/item?id=36825353 : > Tequila wraps Psi4, Madness, and/or PySCF for Quantum Chemistry with Expectation Values: https://github.com/tequilahub/tequila#quantumchemistry And from https://github.com/tequilahub/tequila#quantum-backends : > Quantum Backends currently supported by tequilahub/tequila: Qulacs, Qibo, Qiskit, Cirq (SymPy), PyQuil, QLM / myQLM tequilahub/tequila-tutorials: https://github.com/tequilahub/tequila-tutorials - tequila-tutorials/BasicUsage.ipynb: https://github.com/tequilahub/tequila-tutorials/blob/main/Ba... - tequila-tutorials/Quantum_Calculator.ipynb : https://github.com/tequilahub/tequila-tutorials/blob/main/Qu... Practical Q12 QIS STEM learning exercise ideas: https://news.ycombinator.com/item?id=38687045#38801630
Original comment Ask HN: What has quantum computing achieved so far?

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