Energy use in quantum data centers: Scaling the impact of computer architecture, qubit performance, size, and thermal parameters

TL;DR

This paper models the energy consumption of quantum data centers, highlighting the dominant cooling energy, and explores how architecture and thermal parameters influence overall energy efficiency.

Contribution

It introduces a first-principles energy model for quantum data centers, analyzing the impact of system and thermal parameters on energy use and proposing strategies for energy minimization.

Findings

Cooling energy dominates total energy consumption

Power use correlates with quantum volume

Design strategies can reduce cooling requirements

Abstract

As quantum computers increase in size, the total energy used by a quantum data center, including the cooling, will become a greater concern. The cooling requirements of quantum computers, which must operate at temperatures near absolute zero, are determined by computing system parameters, including the number and type of physical qubits, the operating temperature, the packaging efficiency of the system, and the split between circuits operating at cryogenic temperatures and those operating at room temperature. When combined with thermal system parameters such as cooling efficiency and cryostat heat transfer, the total energy use can be determined. Using a first-principles energy model, this paper reports the impact of computer architecture and thermal parameters on the overall energy requirements. The results also show that power use and quantum volume can be analytically correlated. Approaches are identified for minimizing energy use in integrated quantum systems relative to computational power. The results show that the energy required for cooling is significantly larger than that required for computation, a reversal from energy usage patterns seen in conventional computing. Designing a sustainable quantum computer will require both efficient cooling and system design that minimizes cooling requirements.