A SAT Scalpel for Lattice Surgery: Representation and Synthesis of Subroutines for Surface-Code Fault-Tolerant Quantum Computing

Quantum error correction is necessary for largescale quantum computing. A promising quantum error correcting code is the surface code. For this code, fault-tolerant quantum computing (FTQC) can be performed via lattice surgery, i.e., splitting and merging patches of code. Given the frequent use of c...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:2024 ACM/IEEE 51st Annual International Symposium on Computer Architecture (ISCA) s. 325 - 339
Hlavní autori: Tan, Daniel Bochen, Niu, Murphy Yuezhen, Gidney, Craig
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 29.06.2024
Predmet:
Algorithms
compilation
Fault tolerance
Fault tolerant systems
fault-tolerant
lattice surgery
Merging
quantum
Quantum computing
surface code
Surgery
synthesis
Synthesizers
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:Quantum error correction is necessary for largescale quantum computing. A promising quantum error correcting code is the surface code. For this code, fault-tolerant quantum computing (FTQC) can be performed via lattice surgery, i.e., splitting and merging patches of code. Given the frequent use of certain lattice-surgery subroutines (LaS), it becomes crucial to optimize their design in order to minimize the overall spacetime volume of FTQC. In this study, we define the variables to represent LaS and the constraints on these variables. Leveraging this formulation, we develop a synthesizer for LaS, LaSsynth, that encodes a LaS construction problem into a SAT instance, subsequently querying SAT solvers for a solution. Starting from a baseline design, we can gradually invoke the solver with shrinking spacetime volume to derive more compact designs. Due to our foundational formulation and the use of SAT solvers, LaSsynth can exhaustively explore the design space, yielding optimal designs in volume. For example, it achieves 8% and 18% volume reduction respectively over two states-of-the-art human designs for the 15-to-1 T-factory, a bottleneck in FTQC.
DOI:10.1109/ISCA59077.2024.00032