Reducing depth and measurement weights in Pauli-based computation
Filipa C. R. Peres, Ernesto F. Galv\~ao

TL;DR
This paper introduces new techniques to reduce measurement weights, CNOT complexity, and computational depth in Pauli-based quantum computation, improving efficiency for certain circuit classes and proposing a new universal model.
Contribution
It presents novel bounds, heuristics, and a new universal model to optimize Pauli-based quantum computation, outperforming existing methods in specific scenarios.
Findings
Heuristic algorithm reduces average measurement weight by over 30% for certain circuits.
Outperforms state-of-the-art compilers by reducing CNOT count by up to 96%.
Introduces incPBC, a universal model with low-weight incompatible Pauli measurements.
Abstract
Pauli-based computation (PBC) is a universal measurement-based quantum computation model steered by an adaptive sequence of independent and compatible Pauli measurements on separable magic-state qubits. Here, we propose several new techniques for reducing the weight of the Pauli measurements and their associated \textsc{cnot} complexity; we also demonstrate how to decrease this model's computational depth. We start by proving new upper bounds on the required weights and computational depth, obtained via a pre-compilation step. We also propose a heuristic algorithm that can contribute reductions of over 30\% to the average weight of Pauli measurements (and associated \textsc{cnot} count) when simulating and compiling Clifford-dominated random quantum circuits with up to 22 gates and over 20\% for instances with larger counts. This PBC-compilation scheme, boosted by the heuristic…
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Taxonomy
TopicsAdvanced Measurement and Metrology Techniques · Numerical methods in inverse problems · Force Microscopy Techniques and Applications
