Logical Noise Bias in Magic State Injection
Fault-tolerant architectures aim to reduce the noise of a quantum computation. Despite such architectures being well studied a detailed understanding of how noise is transformed in a fault-tolerant primitive such as magic state injection is currently lacking. We use numerical simulations of logical process tomography on a fault-tolerant gadget that implements a logical <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>T</mml:mi><mml:mo>=</mml:mo><mml:mi>Z</mml:mi><mml:mo stretchy="false">(</mml:mo><mml:mi>&#x03C0;</mml:mi><mml:mrow class="MJX-TeXAtom-ORD"><mml:mo>/</mml:mo></mml:mrow><mml:mn>4</mml:mn><mml:mo stretchy="false">)</mml:mo></mml:math> gate using magic state injection, to understand how noise characteristics at the physical level are transformed into noise characteristics at the logical level. We show how, in this gadget, a significant phase (<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>Z</mml:mi></mml:math>) bias can arise in the logical noise, even with unbiased noise at the physical level. While the magic state injection gadget intrinsically induces biased noise, with extant phase bias being further amplified at the logical level, we identify noisy error correction circuits as a key limiting factor in the circuits studied on the magnitude of this logical noise bias. Our approach provides a framework for assessing the detailed noise characteristics, as well as the overall performance, of fault-tolerant logical primitives.
Authors
- Stephen D. Bartlett (ORCID: https://orcid.org/0000-0003-4387-670X)
- Robin Harper (ORCID: https://orcid.org/0000-0003-4949-8754)
- Nicholas Fazio (ORCID: https://orcid.org/0000-0002-8325-6778)
Institutions
- The University of Sydney (AU)
- ARC Centre of Excellence for Engineered Quantum Systems (AU)
Publication Details
- Journal
- Quantum
- Published
- 2025-06-24
- DOI
- https://doi.org/10.22331/q-2025-06-24-1779
- Citations
- 1
- Primary Topic
- Quantum Computing Algorithms and Architecture
- Type
- article
- Field-Weighted Citation Impact
- 2.48
Funders
- National Computational Infrastructure
- Australian Government
- University of Sydney
- National Cancer Institute
- Army Research Office