  The bandwidth limit between cryogenic and room-temperature environments is a
critical bottleneck in superconducting noisy intermediate-scale quantum
computers. This paper presents the first trial of algorithm-aware system-level
optimization to solve this issue by targeting the quantum approximate
optimization algorithm. Our counter-based cryogenic architecture using
single-flux quantum logic shows exponential bandwidth reduction and decreases
heat inflow and peripheral power consumption of inter-temperature cables, which
contributes to the scalability of superconducting quantum computers.
