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Paper 1

Defect-Adaptive Lattice Surgery on Irregular Boundary Surface-Code Patches

GunSik Min, Yujin Kang, Jun Heo

Year

2026

Journal

arXiv preprint

DOI

arXiv:2604.25524

arXiv

2604.25524

Defect-adaptive surface-code methods have substantially advanced the construction of valid logical patches on imperfect hardware, but fault-tolerant computation also requires executable logical oper ations on the resulting irregular geometries. We formulate the seam-boundary defect problem: how to perform a lattice-surgery merge when the intended seam intersects deformed boundaries, disabled checks, and gauge-inferred super-stabilizers. We introduce a defect-adaptive lattice-surgery method that reconstructs the target joint logical parity from the seam-related measurements available on the irregular merged patch, together with constraints inherited from the separated pre-merge code space. The reconstruction is expressed as a compact GF(2) binary-support synthesis problem. If the requested parity is realizable, the solution gives an executable parity-extraction rule over raw, schedule-tagged gauge outcomes; otherwise, it certifies a parity-synthesis failure rather than conflat ing it with patch invalidity. The framework accommodates boundary data-qubit defects, seam-check ancilla defects, and gauge-inferred seam super-checks within a single synthesis layer. Circuit-level samples of the synthesized merge operation show improved compile yield, preserved effective dis tance, and only modest success-conditioned logical-error overhead relative to the defect-free merge reference; an explicit ZZ-merge sampling check confirms the expected transposed-geometry behav ior under the same success-conditioned observable construction. More broadly, the results identify certified parity synthesis as a compilation layer between defect-adaptive patch construction and executable fault-tolerant logical operations on imperfect surface-code hardware.

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Paper 2

Quantum Computing Approach for Energy Optimization in a Prosumer Community

Carlo Mastroianni, Luigi Scarcello, Jacopo Settino

Year

2022

Journal

arXiv preprint

DOI

arXiv:2209.04411

arXiv

2209.04411

This paper presents a quantum approach for the formulation and solution of the prosumer problem, i.e., the problem of minimizing the energy cost incurred by a number of users in an energy community, while addressing the constraints given by the balance of energy and the user requirements. As the problem is NP-complete, a hybrid quantum/classical algorithm could help to acquire a significant speedup, which is particularly useful when the problem size is large. This work describes the steps through which the problem can be transformed, reformulated and given as an input to Quantum Approximate Optimization Algorithm (QAOA), and reports some experimental results, in terms of the quality of the solution and time to achieve it, obtained with a quantum simulator, when varying the number of constraints and, correspondingly, the number of qubits.

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