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Research PaperResearchia:202607.02072

Optimizing Symmetry Informed Probabilistic Error Cancellation

Tom O'Leary

Abstract

We show that combining quantum error detection (QED) with probabilistic error cancellation (PEC) gives more accurate and lower-variance estimates than PEC alone, provided that the symmetry measurements required for QED are carefully chosen. Because noisy symmetry measurements can negate the benefits of the PEC+QED approach, we cast the selection of measurement configurations as a classical optimization problem that systematically suppresses the impact of noise. Applying optimized PEC+QED to GHZ-...

Submitted: July 2, 2026Subjects: Quantum Physics; Quantum Computing

Description / Details

We show that combining quantum error detection (QED) with probabilistic error cancellation (PEC) gives more accurate and lower-variance estimates than PEC alone, provided that the symmetry measurements required for QED are carefully chosen. Because noisy symmetry measurements can negate the benefits of the PEC+QED approach, we cast the selection of measurement configurations as a classical optimization problem that systematically suppresses the impact of noise. Applying optimized PEC+QED to GHZ-state output distributions and to simulating the time-dynamics of a generalized superfast encoded Fermi-Hubbard model, we find consistent improvements over PEC. For GHZ states, the optimization over symmetry measurement configurations is essential for achieving an advantage. For the Fermi-Hubbard model, PEC+QED improves observable estimation on a 2×22 \times 2 lattice and for larger systems the mitigation overheads can be reduced by measuring only subsets of stabilizers. Our results demonstrate the importance of circuit-specific tailoring of QEM techniques and that fault-tolerant design principles may already provide value for near-term devices.


Source: arXiv:2607.01072v1 - http://arxiv.org/abs/2607.01072v1 PDF: https://arxiv.org/pdf/2607.01072v1 Original Link: http://arxiv.org/abs/2607.01072v1

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Date:
Jul 2, 2026
Topic:
Quantum Computing
Area:
Quantum Physics
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