Affiliation:
1. Quantum Laboratory, DAMO Academy, USA
2. Quantum Laboratory, DAMO Academy, P.R. China
3. Alibaba Cloud Intelligence, Alibaba Group, USA
4. Alibaba Cloud Intelligence, Alibaba Group, P.R. China
Abstract
Scaling bottlenecks the making of digital quantum computers, posing challenges from both the quantum and the classical components. We present a classical architecture to cope with a comprehensive list of the latter challenges
all at once
, and implement it fully in an end-to-end system by integrating a multi-core RISC-V CPU with our in-house control electronics.
Our architecture enables scalable, high-precision control of large quantum processors and accommodates evolving requirements of quantum hardware. A central feature is a microarchitecture executing quantum operations in parallel on arbitrary predefined qubit groups. Another key feature is a reconfigurable quantum instruction set that supports easy qubit re-grouping and instructions extensions.
As a demonstration, we implement the widely-studied surface code quantum computing workflow, which is instructive for being demanding on both the controllers and the integrated classical computation. Our design, for the first time, reduces instruction issuing and transmission costs to constants, which do not scale with the number of qubits, without adding any overheads in decoding or dispatching.
Our system uses a dedicated general-purpose CPU for both qubit control and classical computation, including syndrome decoding. Implementing recent theoretical proposals as decoding firmware that parallelizes general inner decoders, we can achieve unprecedented decoding capabilities of up to distances 47 and 67 with the currently available systems-on-chips for physical error rate
p
= 0.001 and
p
= 0.0001, respectively, all in just 1 μs.
Funder
Alibaba Research Intern Program
Publisher
Association for Computing Machinery (ACM)