Realizing string-net condensation: Fibonacci anyon braiding for universal gates and sampling chromatic polynomials
arXiv:2406.12820 · doi:10.1038/s41467-025-61493-8
Abstract
The remarkable complexity of the vacuum state of a topologically-ordered many-body quantum system encodes the character and intricate braiding interactions of its emergent particles, the anyons.} Quintessential predictions exploiting this complexity use the Fibonacci string-net condensate (Fib-SNC) and its Fibonacci anyons to go beyond classical computing. Sampling the Fib-SNC wavefunction is expected to yield estimates of the chromatic polynomial of graph objects, a classical task that is provably hard. At the same time, exchanging anyons of Fib-SNC is expected to allow fault-tolerant universal quantum computation. Nevertheless, the physical realization of Fib-SNC and its anyons remains elusive. Here, we introduce a scalable dynamical string-net preparation (DSNP) approach, suitable even for near-term quantum processors, which dynamically prepares Fib-SNC and its anyons through reconfigurable graphs. Using a superconducting quantum processor, we couple the DSNP approach with composite error-mitigation on deep circuits to successfully create, measure, and braid anyons of Fib-SNC in a scalable manner. We certify the creation of anyons by measuring their `anyon charge', finding an average experimental accuracy of . Furthermore, we validate that exchanging these anyons yields the { expected} golden ratio~ with~ average accuracy and~ measurement uncertainty. Finally, we sample the Fib-SNC to estimate the chromatic polynomial at~ for {several} graphs. Our results establish the proof of principle for using Fib-SNC and its anyons for fault-tolerant universal quantum computation and {for aiming at} a classically-hard problem.
4 pages and 4 figures with Supplemental Materials (49 pages, 20 Figures)
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- Universal Gates from Braiding and Fusing Anyons on Quantum Hardware
- Universal fault tolerant quantum computation in 2D without getting tied in knots
- Utility-Scale Quantum State Preparation: Classical Training using Pauli Path Simulation