Quantum computing promises exponential speedup for specific computational tasks, potentially delivering significant energy savings compared to classical systems. However, current quantum hardware relies on energy-intensive cryogenic systems and classical control electronics, resulting in high overhead energy consumption. This chapter presents a comprehensive evaluation of quantum computing’s environmental impact and sustainability prospects. It contrasts the energy footprints of classical and quantum platforms, explores theoretical efficiency limits, and compiles real-world power consumption data. Strategies for minimizing energy usage—particularly quantum circuit optimization—are analyzed alongside hardware-level innovations such as cryogenic control and system-level design. The discussion also addresses benchmarking standards, lifecycle considerations, and future paradigms including analog and photonic quantum computing. While current quantum systems are energy-inefficient prototypes, advances in scale, integration, and application targeting may enable a “green quantum advantage” where quantum platforms outperform classical systems in both speed and energy use.

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Energy Efficiency for Quantum Computers: Minimizing the Environmental Footprint

  • J. Nirmaladevi

摘要

Quantum computing promises exponential speedup for specific computational tasks, potentially delivering significant energy savings compared to classical systems. However, current quantum hardware relies on energy-intensive cryogenic systems and classical control electronics, resulting in high overhead energy consumption. This chapter presents a comprehensive evaluation of quantum computing’s environmental impact and sustainability prospects. It contrasts the energy footprints of classical and quantum platforms, explores theoretical efficiency limits, and compiles real-world power consumption data. Strategies for minimizing energy usage—particularly quantum circuit optimization—are analyzed alongside hardware-level innovations such as cryogenic control and system-level design. The discussion also addresses benchmarking standards, lifecycle considerations, and future paradigms including analog and photonic quantum computing. While current quantum systems are energy-inefficient prototypes, advances in scale, integration, and application targeting may enable a “green quantum advantage” where quantum platforms outperform classical systems in both speed and energy use.