A competitive NISQ and qubit-efficient solver for the LABS problem
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arXiv
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| Format: | Preprint |
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2025
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| _version_ | 1866910000433070080 |
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| author | Sciorilli, Marco Camilo, Giancarlo Maciel, Thiago O. Canabarro, Askery Borges, Lucas Aolita, Leandro |
| author_facet | Sciorilli, Marco Camilo, Giancarlo Maciel, Thiago O. Canabarro, Askery Borges, Lucas Aolita, Leandro |
| contents | Pauli Correlation Encoding (PCE) is as a qubit-efficient variational approach to combinatorial optimization problems. The method offers a polynomial reduction in qubit count and a super-polynomial suppression of barren plateaus. Here, we extend the PCE-based framework to solve the Low Autocorrelation Binary Sequences (LABS) problem, a notoriously hard problem often used as a benchmark for classical and quantum solvers. To illustrate this,we simulate two variants of the PCE quantum solver for LABS instances of up to $N=45$ binary variables: one with commuting and one with maximally non-commuting sets of Pauli operators. The simulations use $4$ qubits and a circuit Ansatz with a total of $30$ two-qubit gates. We benchmark our method against the state-of-the-art classical solver and other quantum schemes. We observe improved scaling in the total time to reach the exact solution, outperforming the best-performing classical heuristic while using only a fraction of the quantum resources required by other quantum approaches. In addition, we perform proof-of-principle demonstrations on IonQ's Forte quantum processor, showing that the final solution is resilient to noise. Our findings point at PCE-based solvers as a promising quantum-inspired classical heuristic for hard problems as well as a tool to reduce the resource requirements for actual quantum algorithms. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_17391 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A competitive NISQ and qubit-efficient solver for the LABS problem Sciorilli, Marco Camilo, Giancarlo Maciel, Thiago O. Canabarro, Askery Borges, Lucas Aolita, Leandro Quantum Physics Pauli Correlation Encoding (PCE) is as a qubit-efficient variational approach to combinatorial optimization problems. The method offers a polynomial reduction in qubit count and a super-polynomial suppression of barren plateaus. Here, we extend the PCE-based framework to solve the Low Autocorrelation Binary Sequences (LABS) problem, a notoriously hard problem often used as a benchmark for classical and quantum solvers. To illustrate this,we simulate two variants of the PCE quantum solver for LABS instances of up to $N=45$ binary variables: one with commuting and one with maximally non-commuting sets of Pauli operators. The simulations use $4$ qubits and a circuit Ansatz with a total of $30$ two-qubit gates. We benchmark our method against the state-of-the-art classical solver and other quantum schemes. We observe improved scaling in the total time to reach the exact solution, outperforming the best-performing classical heuristic while using only a fraction of the quantum resources required by other quantum approaches. In addition, we perform proof-of-principle demonstrations on IonQ's Forte quantum processor, showing that the final solution is resilient to noise. Our findings point at PCE-based solvers as a promising quantum-inspired classical heuristic for hard problems as well as a tool to reduce the resource requirements for actual quantum algorithms. |
| title | A competitive NISQ and qubit-efficient solver for the LABS problem |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2506.17391 |