AutoBraid: A Framework for Enabling Efficient Surface Code Communication in Quantum Computing

Quantum computers can solve problems that are intractable using the most powerful classical computer. However, qubits are fickle and error prone. It is necessary to actively correct errors in the execution of a quantum circuit. Quantum error correction (QEC) codes are developed to enable fault-tolerant quantum computing. With QEC, one logical circuit is converted into an encoded circuit. Most studies on quantum circuit compilation focus on NISQ devices which have 10-100 qubits and are not fault-tolerant. In this paper, we focus on the compilation for fault-tolerant quantum hardware. In particular, we focus on optimizing communication parallelism for the surface code based QEC. The execution of surface code circuits involves non-trivial geometric manipulation of a large lattice of entangled physical qubits. A two-qubit gate in surface code is implemented as a virtual “pipe” in space-time called a braiding path. The braiding paths should be carefully routed to avoid congestion. Communication between qubits is considered the major bottleneck as it involves scheduling and searching for simultaneous paths between qubits. We provide a framework for efficiently scheduling braiding paths. We discover that for quantum programs with a local parallelism pattern, our framework guarantees an optimal solution, while the previous greedy-heuristic-based solution cannot. Moreover, we propose an extension to the local parallelism analysis framework to address the communication bottleneck. Our framework achieves orders of magnitude improvement after addressing the communication bottleneck.

[1]  D. Gottesman An Introduction to Quantum Error Correction and Fault-Tolerant Quantum Computation , 2009, 0904.2557.

[2]  D. Maslov,et al.  Linear depth stabilizer and quantum Fourier transformation circuits with no auxiliary qubits in finite-neighbor quantum architectures , 2007 .

[3]  Fernando Magno Quintão Pereira,et al.  Qubit allocation , 2018, CGO.

[4]  Frederic T. Chong,et al.  Quantum rotations: a case study in static and dynamic machine-code generation for quantum computers , 2013, ISCA.

[5]  Gushu Li,et al.  Tackling the Qubit Mapping Problem for NISQ-Era Quantum Devices , 2018, ASPLOS.

[6]  Robert Wille,et al.  RevLib: An Online Resource for Reversible Functions and Reversible Circuits , 2008, 38th International Symposium on Multiple Valued Logic (ismvl 2008).

[7]  Li Yang,et al.  A quantum algorithm for approximating the influences of Boolean functions and its applications , 2014, Quantum Information Processing.

[8]  Andrew W. Cross,et al.  The IBM Q experience and QISKit open-source quantum computing software , 2018 .

[9]  Moinuddin K. Qureshi,et al.  Taming the Instruction Bandwidth of Quantum Computers via Hardware-Managed Error Correction , 2017, 2017 50th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).

[10]  Moinuddin K. Qureshi,et al.  Ensemble of Diverse Mappings: Improving Reliability of Quantum Computers by Orchestrating Dissimilar Mistakes , 2019, MICRO.

[11]  Kae Nemoto,et al.  Requirements for fault-tolerant factoring on an atom-optics quantum computer , 2012, Nature Communications.

[12]  Moinuddin K. Qureshi,et al.  Not All Qubits Are Created Equal: A Case for Variability-Aware Policies for NISQ-Era Quantum Computers , 2018, ASPLOS.

[13]  Robert Wille,et al.  Efficient mapping of quantum circuits to the IBM QX architectures , 2017, 2018 Design, Automation & Test in Europe Conference & Exhibition (DATE).

[14]  Niraj K. Jha,et al.  Automated Quantum Circuit Synthesis and Cost Estimation for the Binary Welded Tree Oracle , 2017, ACM J. Emerg. Technol. Comput. Syst..

[15]  Alexandru Paler,et al.  SurfBraid: A concept tool for preparing and resource estimating quantum circuits protected by the surface code , 2019, ArXiv.

[16]  Margaret Martonosi,et al.  Optimized Surface Code Communication in Superconducting Quantum Computers , 2017, 2017 50th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).

[17]  Robert Raussendorf,et al.  Topological fault-tolerance in cluster state quantum computation , 2007 .

[18]  W. Munro,et al.  Quantum error correction for beginners , 2009, Reports on progress in physics. Physical Society.

[19]  Margaret Martonosi,et al.  Magic-State Functional Units: Mapping and Scheduling Multi-Level Distillation Circuits for Fault-Tolerant Quantum Architectures , 2018, 2018 51st Annual IEEE/ACM International Symposium on Microarchitecture (MICRO).

[20]  R. Barends,et al.  Qubit metrology of ultralow phase noise using randomized benchmarking , 2014, 1411.2613.

[21]  Chi Zhang,et al.  Time-optimal Qubit mapping , 2021, ASPLOS.

[22]  Margaret Martonosi,et al.  Noise-Adaptive Compiler Mappings for Noisy Intermediate-Scale Quantum Computers , 2019, ASPLOS.

[23]  Margaret Martonosi,et al.  ScaffCC: a framework for compilation and analysis of quantum computing programs , 2014, Conf. Computing Frontiers.

[24]  Robert Wille,et al.  Mapping Quantum Circuits to IBM QX Architectures Using the Minimal Number of SWAP and H Operations , 2019, 2019 56th ACM/IEEE Design Automation Conference (DAC).

[25]  Karem A. Sakallah,et al.  Transistor placement for noncomplementary digital VLSI cell synthesis , 2003, TODE.

[26]  A. Fowler,et al.  A bridge to lower overhead quantum computation , 2012, 1209.0510.

[27]  M. Mariantoni,et al.  Surface codes: Towards practical large-scale quantum computation , 2012, 1208.0928.