Classical simulation of a quantum circuit with noisy magic inputs
Jiwon Heo, Sojeong Park, Changhun Oh

TL;DR
This paper investigates how noise in magic states affects the classical simulability of quantum circuits, identifying conditions under which noisy magic enables efficient classical simulation, thus impacting quantum advantage.
Contribution
It introduces a resource-centric noise model and develops an approximate classical sampling algorithm with explicit noise-dependent efficiency conditions.
Findings
Noise on magic states can make quantum circuits classically simulable
The paper provides explicit thresholds for efficient simulation under noise
Applicable to qubit Clifford and fermionic matchgate circuits
Abstract
Magic states are essential for universal quantum computation and are widely viewed as a key source of quantum advantage, yet in realistic devices they are inevitably noisy. In this work, we characterize how noise on injected magic resources changes the classical simulability of quantum circuits and when it induces a transition from classically intractable behavior to efficient classical simulation. We adopt a resource-centric noise model in which only the injected magic components are noisy, while the baseline states, operations, and measurements belong to an efficiently simulable family. Within this setting, we develop an approximate classical sampling algorithm with controlled error and prove explicit noise-dependent conditions under which the algorithm runs in polynomial time. Our framework applies to both qubit circuits with Clifford baselines and fermionic circuits with matchgate…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum many-body systems · Quantum Information and Cryptography
