Quantifying the Dual-isotope Advantage for Ytterbium-array Surface Codes using Realistic Noise Models

Quantum Physics arXiv:2608.27568 (quant-ph) [Submitted on 27 Aug 2026] Title:Quantifying the Dual-isotope Advantage for Ytterbium-array Surface Codes using Realistic Noise Models Authors:Fumiyoshi Kobayashi, Toshi Kusano, Nicholas Fazio, Yuma Nakamura View a PDF of the paper titled Quantifying the Dual-isotope Advantage for Ytterbium-array Surface Codes using Realistic Noise Models, by Fumiyoshi Kobayashi and 3 other authors View PDF HTML (experimental) Abstract:Neutral-atom quantum computers are a promising platform for fault-tolerant quantum computation, but logical performance depends on systemic realistic noise factors during syndrome extraction. In dual-isotope Yb arrays, the roles of data and ancilla qubits are separated spectrally, allowing ancilla qubits to be measured in place without additional transport or shelving operations. Here we quantify the advantage of a dual-isotope Yb architecture for surface code memories. We develop an experimentally motivated Clifford-compatible noise model for dual-isotope 171Yb-174Yb systems using generalised Pauli twirling and implement it as a wrapper for Stim called DualYbSim, which has been packaged as an open source Python library. Simulations of rotated and XZZX surface codes show that a dual-isotope architecture with in-place measurement achieves the lowest logical error rates among the architectures considered, outperforming single-isotope schemes based on shelving or zoned measurement. Our error-budget analysis also identifies Rydberg-state decay as the dominant limitation, contributing to 74-80% of the logical error rate scaling, highlighting concrete experimental targets for improving FTQC performance. Comments: Subjects: Quantum Physics (quant-ph); Atomic Physics (physics.atom-ph) Cite as: arXiv:2608.27568 [quant-ph] (or arXiv:2608.27568v1 [quant-ph] for this version) https://doi.org/10.48550/arXiv.2608.27568 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Submission history From: Nicholas Fazio [view email] [v1] Thu, 27 Aug 2026 18:00:13 UTC (905 KB) Full-text links: Access Paper: View a PDF of the paper titled Quantifying the Dual-isotope Advantage for Ytterbium-array Surface Codes using Realistic Noise Models, by Fumiyoshi Kobayashi and 3 other authorsView PDFHTML (experimental)TeX Source view license Current browse context: quant-ph new | recent | 2026-08 Change to browse by: physics physics.atom-ph References & Citations INSPIRE HEP NASA ADSGoogle Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)