Concentration Bounds for Quantum States and Limitations on the QAOA from Polynomial Approximations
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| Title: | Concentration Bounds for Quantum States and Limitations on the QAOA from Polynomial Approximations |
|---|---|
| Authors: | Anshu, Anurag, Metger, Tony |
| Contributors: | Anurag Anshu and Tony Metger |
| Publisher Information: | Schloss Dagstuhl – Leibniz-Zentrum für Informatik |
| Publication Year: | 2023 |
| Collection: | DROPS - Dagstuhl Research Online Publication Server (Schloss Dagstuhl - Leibniz Center for Informatics ) |
| Subject Terms: | quantum computing, polynomial approximation, quantum optimization algorithm, QAOA, overlap gap property |
| Description: | We prove concentration bounds for the following classes of quantum states: (i) output states of shallow quantum circuits, answering an open question from [De Palma et al., 2022]; (ii) injective matrix product states; (iii) output states of dense Hamiltonian evolution, i.e. states of the form e^{ιH^{(p)}} ⋯ e^{ιH^{(1)}} |ψ₀⟩ for any n-qubit product state |ψ₀⟩, where each H^{(i)} can be any local commuting Hamiltonian satisfying a norm constraint, including dense Hamiltonians with interactions between any qubits. Our proofs use polynomial approximations to show that these states are close to local operators. This implies that the distribution of the Hamming weight of a computational basis measurement (and of other related observables) concentrates. An example of (iii) are the states produced by the quantum approximate optimisation algorithm (QAOA). Using our concentration results for these states, we show that for a random spin model, the QAOA can only succeed with negligible probability even at super-constant level p = o(log log n), assuming a strengthened version of the so-called overlap gap property. This gives the first limitations on the QAOA on dense instances at super-constant level, improving upon the recent result [Basso et al., 2022]. |
| Document Type: | article in journal/newspaper conference object |
| File Description: | application/pdf |
| Language: | English |
| Relation: | Is Part Of LIPIcs, Volume 251, 14th Innovations in Theoretical Computer Science Conference (ITCS 2023); https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2023.5 |
| DOI: | 10.4230/LIPIcs.ITCS.2023.5 |
| Availability: | https://doi.org/10.4230/LIPIcs.ITCS.2023.5 https://nbn-resolving.org/urn:nbn:de:0030-drops-175085 https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2023.5 |
| Rights: | https://creativecommons.org/licenses/by/4.0/legalcode |
| Accession Number: | edsbas.CBC5BECC |
| Database: | BASE |
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