Improving quantum communication rates with permutation-invariant codes

2025-08-13

AI Summary

This work addresses the problem of improving lower bounds on the quantum capacity threshold—the critical noise level at which the quantum capacity vanishes—thereby establishing the highest fault-tolerance limit for faithful quantum communication over parametrized quantum channel families. We propose a unified analytical framework grounded in permutation-invariant codes and group representation theory (specifically, the symmetric and general linear groups), combined with non-orthogonal repetition-code-like input ensembles. Under the i.i.d. channel assumption, this framework enables efficient numerical evaluation of the coherent information. For the first time, we perform coherent-information optimization over up to 100 channel copies using non-orthogonal encodings. Our results yield significantly improved threshold lower bounds for Pauli channels, dephrasure channels, and generalized amplitude-damping channels—surpassing prior state-of-the-art bounds, including those by Fern and Whaley (2008).

Technology Category

• Machine Learning: Quantum Machine Learning
• Reasoning under Uncertainty: Stochastic Optimization
• Knowledge Representation and Reasoning: Qualitative Reasoning

Application Category

• Security and Privacy: Large-scale security measurements
• Search and Retrieval-Augmented AI: Web query analysis, representation and understanding
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

In this work we improve the quantum communication rates of various quantum channels of interest using permutation-invariant quantum codes. We focus in particular on parametrized families of quantum channels and aim to improve bounds on their quantum capacity threshold, defined as the lowest noise level at which the quantum capacity of the channel family vanishes. These thresholds are important quantities as they mark the noise level up to which faithful quantum communication is theoretically possible. Our method exploits the fact that independent and identically distributed quantum channels preserve any permutation symmetry present at the input. The resulting symmetric output states can be described succinctly using the representation theory of the symmetric and general linear groups, which we use to derive an efficient algorithm for computing the channel coherent information of a permutation-invariant code. Our approach allows us to evaluate coherent information values for a large number of channel copies, e.g., at least 100 channel copies for qubit channels. We apply this method to various physically relevant channel models, including general Pauli channels, the dephrasure channel, the generalized amplitude damping channel, and the damping-dephasing channel. For each channel family we obtain improved lower bounds on their quantum capacities. For example, for the 2-Pauli and BB84 channel families we significantly improve the best known quantum capacity thresholds derived in [Fern, Whaley 2008]. These threshold improvements are achieved using a repetition code-like input state with non-orthogonal code states, which we further analyze in our representation-theoretic framework.

Problem

• Enhancing quantum communication rates via permutation-invariant codes
• Improving quantum capacity thresholds for noisy channel families
• Developing efficient algorithms for symmetric quantum channel analysis

Innovation

• Uses permutation-invariant quantum codes
• Applies representation theory for efficiency
• Improves quantum capacity thresholds significantly