PRX Quantum· 2026Q1
Optimal Quantum Purity Amplification: A Top-Down Approach to Error Suppression via Symmetry and Reversibility
- 29citations
- Q1SCImago
- 2026year
Short summary
A new optimal quantum purity amplification (QPA) protocol reduces sample complexity exponentially for general quantum systems under strong depolarization, resolving a 20-year-old problem.
AI-generated from the title and abstract; the full text is not read.
Key points
- Introduced the optimal quantum purity amplification (QPA) protocol for general quantum systems and global noise.
- Achieves an exponential reduction in sample complexity under strong depolarization compared to prior methods.
- Provides an efficient implementation via generalized quantum phase estimation.
- Introduced SWAPNET, a sparse and shallow circuit for QPA in near-term experiments.
- Protocol validated through simulations and experiments on superconducting quantum processors.
AI-generated from the title and abstract; the full text is not read.
Abstract
Quantum purity amplification (QPA) provides a novel approach to counteracting the pervasive noise that degrades quantum states. We present the optimal QPA protocol for general quantum systems and global noise, resolving a two-decade open problem. Under strong depolarization, our protocol achieves an exponential reduction in sample complexity over the best-known methods. We provide an efficient implementation of the protocol based on generalized quantum phase estimation. Additionally, we introduce SWAPNET, a sparse and shallow circuit that enables QPA for near-term experiments. Simulations in both digital and analog quantum settings, along with experiments on superconducting quantum processors, confirm the protocol's robustness and practical utility. Our findings suggest that QPA could improve the performance of quantum information processing tasks, particularly in the context of Noisy Intermediate-Scale Quantum (NISQ) devices, where reducing the effect of noise with limited resources is critical.
The authors' abstract, as published at the source. PRX Quantum, 2026 · DOI ↗
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Field: Artificial Intelligence
Artificial IntelligenceComputer Science