---
tags: Hamiltonian-level, Theory
sort-date: 2026-05-27
description: We present a resource analysis for generating high-fidelity logical magic states on silicon spin-qubit platforms.
---
Songqinghao Yang,
[[/index|Christopher K. Long]],
Rubén M. Otxoa,
Prakash Murali,
Crispin H. W. Barnes, and
David R. M. Arvidsson-Shukur
Preprint published: 27 May 2026
DOI: [10.48550/arXiv.2605.28936](https://doi.org/10.48550/arXiv.2605.28936)
[[PDFs/2605.28936v1.pdf|PDF Download]], [[TeX_Source/2605.28936v1.tar.gz|TeX Source Download]]
# Abstract
> We present a resource analysis for generating high-fidelity logical magic states on silicon spin-qubit platforms. We consider a range of architectures, including a shuttling-based SpinBus design, a dense nearest-neighbor layout, and a hybrid scheme with shuttling-connected patches. We compare surface, color, and biased error-correcting codes, and analyze the $5\to 1$ and $15\to 1$ magic-state distillation protocols. Our approach combines bottom-up and top-down methodologies. We construct a hardware-level noise model based on a silicon-processor Hamiltonian with realistic parameters and $1/f$ non-Markovian noise, enabling estimation of physical resources required to reach target logical error rates. These results are propagated to system-level overheads for applications including spin dynamics, integer factorization, and quantum chemistry. Conversely, we fix target logical fidelities and derive corresponding constraints on hardware performance. Our framework enables systematic evaluation of resource-reduction strategies. We find that optimized control pulses reduce magic-state distillation overhead by $42\%$ compared to standard gate implementations. In addition, silicon-tailored biased error-correcting codes achieve an approximately threefold reduction in physical footprint relative to the surface code, even without physical-bias-preserving operations.
# Citation
Songqinghao Yang, Christopher K. Long, Rubén M. Otxoa, Prakash Murali, Crispin H. W. Barnes, and David R. M. Arvidsson-Shukur. Hardware-tailored resource estimation for magic-state distillation on silicon spin qubits, 2026, arXiv:2605.28936 [quant-ph].
## BibTeX
```bibtex
@misc{yang2026hardwaretailoredresourceestimationmagicstate,
title={Hardware-Tailored Resource Estimation for Magic-State Distillation on Silicon Spin Qubits},
author={Songqinghao Yang and Christopher K. Long and Rubén M. Otxoa and Prakash Murali and Crispin H. W. Barnes and David R. M. Arvidsson-Shukur},
year={2026},
eprint={2605.28936},
archivePrefix={arXiv},
primaryClass={quant-ph},
url={https://arxiv.org/abs/2605.28936},
}
```
# Software
- [[/Software/QuGradLab/index|QuGradLab]] [@QuGradLab]
- [[/Software/QuGrad/index|QuGrad]] [@QuGrad]
- [[/Software/PySTE/index|PySTE]] [@PySTE]
- [[/Software/Suzuki-Trotter-Evolver/index|Suzuki-Trotter-Evolver]] [@SuzukiTrotterEvolver]
# Analytics
- [Google Scholar](https://scholar.google.com/citations?view_op=view_citation&citation_for_view=GRSIcsEAAAAJ:Se3iqnhoufwC)
- [SciRate](https://scirate.com/arxiv/2605.28936)
- [INSPIRE-HEP](https://inspirehep.net/literature/3162528)
- [Semantic Scholar](https://www.semanticscholar.org/paper/Hardware-Tailored-Resource-Estimation-for-on-Spin-Yang-Long/3227b4cef90ded84f71678dd7178c75ff0bb02e1)
# Social media posts
## Bluesky
> [!Thread]
> In our recent arXiv (arxiv.org/abs/2605.28936) we benchmarked QEC and magic state factories for spin qubits. By computing magic state production overheads as a function of initialization, gate, measurement, and decoherence times we estimated the runtimes for typical algorithms—see Fig.
[image or embed]
— Christopher K. Long (@christopher-k-long.bsky.social) 11 June 2026 at 13:46
> My favourite result was showing pulse optimization can cut magic state production overheads by 42%.
— Christopher K. Long (@christopher-k-long.bsky.social) 11 June 2026 at 13:46
## LinkedIn
In our recent arXiv (https://lnkd.in/e3erv9AE) Peter Yang, I, Rubén Miguel Otxoa de Zuazola, Prakash Murali, Prof. Crispin H. W. Barnes, and David Arvidsson-Shukur benchmarked QEC and magic state factories for spin qubits. By computing magic state production overheads as a function of initialization, gate, measurement, and decoherence times we estimated the runtimes for typical algorithms. My favourite result was showing pulse optimization can cut magic state production overheads by 42%.
— Christopher K. Long (LinkedIn) 12 June 2026
## X
> [!Thread]
>
>