Subsystem CSS codes, a tighter stabilizer-to-CSS mapping, and Goursat's Lemma
November 29, 2023 Β· Declared Dead Β· π Quantum
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Michael Liaofan Liu, Nathanan Tantivasadakarn, Victor V. Albert
arXiv ID
2311.18003
Category
quant-ph: Quantum Computing
Cross-listed
cs.IT
Citations
5
Venue
Quantum
Last Checked
5 months ago
Abstract
The CSS code construction is a powerful framework used to express features of a quantum code in terms of a pair of underlying classical codes. Its subsystem extension allows for similar expressions, but the general case has not been fully explored. Extending previous work of Aly, Klappenecker, and Sarvepalli [quantph/0610153], we determine subsystem CSS code parameters, express codewords, and develop a Steane-type decoder using only data from the two underlying classical codes. Generalizing a result of Kovalev and Pryadko [Phys. Rev. A 88 012311 (2013)], we show that any subsystem stabilizer code can be "doubled" to yield a subsystem CSS code with twice the number of physical, logical, and gauge qudits and up to twice the code distance. This mapping preserves locality and is tighter than the Majorana-based mapping of Bravyi, Terhal, and Leemhuis [New J. Phys. 12 083039 (2010)]. Using Goursat's Lemma, we show that every subsystem stabilizer code can be constructed from two nested subsystem CSS codes satisfying certain constraints, and we characterize subsystem stabilizer codes based on the nested codes' properties.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Quantum Computing
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Quantum machine learning: a classical perspective
R.I.P.
π»
Ghosted
Noise-Adaptive Compiler Mappings for Noisy Intermediate-Scale Quantum Computers
R.I.P.
π»
Ghosted
ProjectQ: An Open Source Software Framework for Quantum Computing
R.I.P.
π»
Ghosted
Quantum Recommendation Systems
R.I.P.
π»
Ghosted
Traffic flow optimization using a quantum annealer
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted