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Quantum computing, a groundbreaking technology that harnesses the principles of quantum mechanics, could revolutionize the energy sector by optimizing power systems, reducing emissions, and enhancing renewable energy sources. Unlike classical computers processing binary data, quantum computers utilize quantum bits (qubits) to store information in a fundamentally quantum manner, exploiting quantum properties like superposition, interference, and entanglement.
This emerging field holds immense potential for tackling complex energy challenges, from forecasting solar and wind resources to managing power demand, facility allocation, and ensuring grid reliability. Exploring quantum architectures and their applications in combinatorial optimization, convex optimization, and machine learning could pave the way for a sustainable, energy-efficient future driven by quantum artificial intelligence and quantum technology.
Quantum Computing and Energy Efficiency
Current Challenges in Classical Computing
Since the last century, high-performance classical computers have been growing, offering more precise and faster calculations, but they accommodate thousands of processor cores requiring entire buildings with costly cooling systems. Data centers’ consumption accounted for around 1.7% of the global electricity demand during 2022, with some supercomputers consuming as much energy as a town. For instance, the Frontier supercomputer uses 504 MWh on average daily, equivalent to the energy consumed by around 17,000 average U.S. homes.
The Potential of Quantum Algorithms
Quantum computing is rapidly emerging as a next-generation high-performance computing technology to address complex problems inaccessible to classical devices. Many scientific and industrial computations scale exponentially in time on classical machines, leading to “intractable” problems whose calculation time increases unreasonably with their size. Common examples include optimization problems, like finding the best way to deploy a communications network for good coverage and low cost, and chemistry simulations crucial for drug design and toxicity prediction. The promise of quantum technologies to tackle such intractable problems in a “human scale” amount of time is called quantum advantage.
Energy Consumption Advantages of Quantum Computers
Today, quantum computers’ electricity usage is orders of magnitude lower than supercomputers across different architectures. For example, superconducting qubit-based quantum computers consume about 25 kW (600 kWh daily), a thousand times less than Frontier, while neutral atoms quantum devices like PASQAL’s consume only 7 kW. Although current noisy quantum computers cannot yet solve industry-relevant problems, architectures like PASQAL’s neutral atoms devices hold potential for tackling many use cases before fault-tolerant quantum computers arrive, foreshadowing an energy quantum advantage in the shorter term. Even long-term, with error corrections requiring large qubit counts, quantum computers are estimated to maintain an energy advantage over classical intractable problems.
Exploring Quantum Architectures for Energy Efficiency
Comparison of Different Quantum Architectures
Different quantum architectures are competing in the market as there is no established quantum technology standard yet. The table below compares the energy usage of various popular types of quantum computers, including superconducting qubits, neutral atoms (like PASQAL’s), and others. PASQAL’s neutral (or cold) atoms machine emerges as one of the most energy-efficient options for total and per-qubit consumption.
Neutral Atoms: A Promising Approach
The current PASQAL quantum processor, capable of handling hundreds of qubits, exhibits a total power consumption of around 2.6 kW, with lasers accounting for half and the remaining divided between electronics and environment control. An independent assessment by researchers from Centrale-Supelec University shows that PASQAL’s neutral atoms machine has power consumption independent of the qubit count, unlike superconducting or silicon architectures.
Energy Consumption Projections and Scalability
While adding a 4 Kelvin cryogenic system will increase electricity usage for next-generation machines, estimates suggest a total consumption of 9.7 kW for 1000 qubits and 9.8 kW for 10,000 qubits with PASQAL’s architecture—still significantly less than superconductors. Long-term quantum technology energy usage is uncertain, but models considering scalability and error correction techniques requiring large qubit counts indicate an energy advantage for quantum computers over classical intractable problems, even with error corrections.
The Future of Quantum Computing and Sustainability
Long-term Energy Usage Estimates
There is still uncertainty around the long-term quantum technologies energy usage, but some estimations have been modeled considering scalability and error correction techniques requiring large qubit counts to perform calculations with low error rates. As shown in a figure by Alexia Auffèves and Olivier Ezratty (2022), even with error corrections, quantum computers are projected to maintain an energy advantage over classical intractable problems.
Potential Applications and Industry Collaborations
Researchers have identified potential high-impact applications of quantum computing in areas like climate change research, renewable energy development, and optimizing energy generation and storage solutions. Collaborations between the quantum computing community and climate/Earth science researchers with relevant domain expertise are crucial to ensure algorithm development aligns with real-world needs. Initiatives like the IEEE Quantum Week workshop and Q4Climate workshop represent early efforts to bridge these communities. Governments, industries, and other sectors must cooperate to harness the quantum revolution for tackling critical energy and climate challenges.
Societal and Economic Considerations
While quantum computing holds promise for sustainability, questions remain about its potential widespread adoption and limiting factors. The greenhouse gas footprint from fabricating quantum and classical computers should also be considered. Moreover, enterprises offering computing services must continue researching ways to lower their energy footprint as humanity strives towards global sustainable development goals.
Conclusion
The immense potential of quantum computing for optimizing energy systems, reducing emissions, and enhancing renewable energy sources offers an exciting path towards a sustainable future. With orders of magnitude lower electricity consumption than classical supercomputers, emerging quantum architectures like neutral atoms hold the promise of delivering energy quantum advantage in the shorter term. As collaborations between the quantum computing community and energy researchers intensify, we can expect groundbreaking applications that revolutionize power generation, storage, and distribution.
While challenges remain in terms of scalability, error correction, and widespread adoption, the ongoing research and development in quantum technologies instill hope for a future where energy-efficient quantum computers contribute significantly to tackling critical climate and energy challenges. As we strive towards global sustainable development goals, harnessing the quantum revolution will be a pivotal step in optimizing our energy systems and paving the way for a cleaner, more efficient, and sustainable world.
