Optimal algorithms for materializing stabilizer states and Clifford gates from compact descriptions

TL;DR

This paper presents optimal algorithms for efficiently materializing stabilizer states and Clifford gates from compact descriptions, achieving the theoretical $O(2^n)$ time complexity.

Contribution

The authors develop the first algorithms that materialize stabilizer states and Clifford gates in optimal $O(2^n)$ time from their compact descriptions.

Findings

Algorithms run in $O(2^n)$ time and space.

Efficiently materialize stabilizer states from check-matrix descriptions.

Expand Clifford tableau into full dense matrix optimally.

Abstract

Stabilizer states admit compact classical descriptions, but many downstream tasks still require their full amplitude vectors. Since the output itself has size $2^n$, the main algorithmic question is whether one can materialize an $n$-qubit stabilizer state vector in optimal $O(2^n)$ time, rather than paying an additional polynomial overhead. We answer this question in the affirmative. Starting from the standard quadratic-form representation of stabilizer states, we give an algorithm that runs in $O(2^n)$ time and $O(2^n)$ space. The idea is to maintain a cached parity word that records all future off-diagonal quadratic phase increments simultaneously. As consequences, we obtain an optimal procedure for materializing a stabilizer state vector from a standard check-matrix description, and an optimal algorithm for expanding a Clifford tableau into its full dense matrix. These results close the asymptotic gap for dense stabilizer and Clifford materialization.