Green quantum computing

Quantum Computing has the potential to be revolutionary in many computation-heavy area’s: ranging from drug discovery to financial applications. The reason? Higher accuracy and faster computation times. However, one question is often neglected: at which cost? We’ve seen that supercomputers and data centres can consume an enormous amount of energy [1,2]. Will quantum computers be the next energy-thirsty technology, or are they instead the gateway to a green computing era?

Quantum computing uses the most intriguing properties of quantum physics: entanglement, superposition, and interference. Quantum computers use these phenomena to do calculations in a completely different way than normal computers do. The result is an enormous speedup of the calculations, the ability to achieve higher accuracy levels, and solve problems that are intractable for the classical computer.

These quantum phenomena take place at a very small scale: the scale of an electron. As such, one computer calculation would barely cost any energy. However, to observe these potent quantum phenomena, the system must be completely isolated. Temperatures must be cooled to near absolute zero (-273 degrees Celsius). This comes with a large energy bill.

The energy consumption of a quantum computer scales fundamentally different from a classical computer. Classically, there is a linear scaling with problem size and complexity. For quantum computers, this may be very different. Insight into this new energy consumption of a quantum computer is essential for a green future of quantum computing.

The Scaling of the Energy Consumption

Currently, the power consumption of a quantum computer is about 15-25kW, due to the cryogenic refrigerator [3, 4, 5]. This is comparable to the energy consumption of about 25 households. Note that this power is not only consumed when a calculation is performed but is continuously consumed by the quantum computer. This leads to a large energy bill.

There is hope for the future. When a classical computer becomes twice as large, it requires twice as much energy. In the near future, a quantum computer, by contrast, may barely increase its energy consumption when scaling up. This is because the cooling volume barely increases, and heat created by extra electronics is also not expected to be significant. The largest quantum computer today is 127 qubits and scaling to 1.000 or even 10.000 qubit is possible with similar energy consumption.

In the far future, we envision quantum computers with millions of qubits, situated in large data centres. It would be naive to assume that this does not add any energy costs. Recent research shows that the energy costs will scale with the number of qubits and operations at a point in the future. This is mostly due to increased cooling costs.

There is another very important factor that positions quantum computers as potential candidates for green computing. The idea is as follows: if you must run a supercomputer for a month to solve a specific problem and a quantum computer can do it within minutes – this drastically reduces the energy cost. An example of how energy costs would scale differently for Monte Carlo simulations is shown in figure 1.

Figure 1: The Energy Consumption of a Quantum Computer scales very differently than that of classical computers. When high accuracy or complexity is required, the quantum computer may become the more “sustainable” candidate.

Recent research shows a difference in energy consumption between quantum computers and classical computers of a factor of 10.000 (!) [4]. A clear quantum energy advantage, but for a toy problem, favouring the quantum computer. The question remains whether this is applicable to more generic problems.

Recently, an energy estimate for a more generic problem was made, namely breaking the RSA encryption [6]. RSA is a very common encryption method for secure data transmission. The quantum computer is expected to have an energy consumption of 1000 times as little as a classical computer. It must be noted that this energy estimate was based on futuristic full-stack quantum computers, and still require major advances in quantum hardware.

Interestingly, this estimation also showed the timeframe where a quantum computer might be slower but requires less energy [6]. This gives a great perspective for the future. Before implementing quantum computers due to their speedup, can we implement them for green computing?

Green Computing for Financial Institutions

At Capgemini, the Olive project researched the opportunity of using quantum computers for green computing in the financial industry. This is specifically applied to using quantum computers for pricing derivatives, based on a new algorithm that allows one to do this on a quantum computer [7,8]. (See more here)

Green Computing is becoming increasingly important for financial institutions. Mischa Vos, Quantum Lead at Rabobank (one of the largest banks in The Netherlands), emphasises its importance for Rabobank:

“At Rabobank, sustainability is an integral part of our corporate mission: “Growing a better world together. The focus is now on green coding and sustainable data centres. On top of that, Rabobank is investing in green computing technologies. Quantum Computers would be an interesting new candidate.”

Financial institutions use an enormous amount of computational power to ensure security, price financial products and perform risk management. Based on the insight about the “quantum energy advantage”, quantum computing can reduce the carbon impact of these computations. Would this be interesting for Rabobank?

“This has great potential for Rabobank. Running these calculations, especially when Artificial Intelligence is involved, has a negative impact on the carbon footprint of Rabobank. Rabobank is dedicated to reducing this. At the same time, as a financial institution, we still need to perform accurate risk analysis and provide security. If quantum computing would allow us to combine the two, this would be very interesting.”  

There may be a timeframe when the quantum computer is slower, but more energy efficient than classical computers. Would Rabobank already be interested in quantum computers at this stage?

“There are certain batch-oriented calculations that Rabobank performs, and these would be ideal for this. For example, evaluating the risk portfolio of investments at a large scale, or certain fraud detection methods. There will definitely be opportunities where Rabobank can already use the slower, but more efficient quantum computers during this time frame.”

A future scenario

The current hardware limitations are the main bottleneck for practical quantum computing. However, it is important for financial institutions to be ready for implementing quantum computers when the time is right, especially when this can be important from a sustainability perspective.

Phase 1. Research & Development

The current hardware limitations are the main bottleneck. As such, firstly, the hardware challenges need to be overcome before it becomes feasible to run relevant calculations on quantum computers. The Quantum Energy Initiative points out it is important to already make conscious design choices during this phase to ensure an energy-efficient quantum computer [9,10]. This should not slow down technological progress but instead, prepare for long-term energy advances.

Phase 2. Green Energy Advantage

Due to slow quantum clock speeds, and intensive quantum error correction codes, the quantum computational advantage can take longer than the quantum energy advantage. As such, the first applications of quantum computers may be due to their energy efficiency. This will be dependent on the specific advances in quantum hardware.

Phase 3. Overall Quantum Advantage

Finally, both the quantum computational advantage and quantum energy advantage are achieved. Here, it is important to make conscious choices in the usage of quantum computers and avoid the Jevon paradox. See for example this blog on quantum for sustainability. On the other hand, this is also the phase where quantum computers can really make a difference in sustainability – making better simulations leading to better material design all the way to general climate crisis mitigation plans [11]. 

Technology leaves an indelible mark on the environment. Capgemini is determined to play a leadership role in ensuring technology creates a sustainable future. Capgemini can help with implementing sustainable IT as the backbone of a company for a greener future.  It is important to consider the environmental footprint of emerging technologies. Capgemini’s Quantum Lab can help clients understand the future possibilities of quantum technologies and build their organization and strategy that will make the potential become a reality. With this project, more insight into the real environmental cost of quantum computers is acquired, as well as the opportunities that Quantum Computers can give for green computing.

For more information on the results of Milou’s research, watch the webinar here

References:

[1] IEA, Data centres and data transmission networks, 2022. [Online]. Available: https://www .iea .org/reports/data-centres-and-data-transmission-networks .

[2] A. S. Andrae and T. Edler, “On global electricity usage of communication technology: Trends to 2030,” Challenges, vol. 6, no. 1, pp. 117–157, 2015. .

[3] F. Arute, K. Arya, R. Babbush, et al., “Quantum supremacy using a programmable superconducting processor,” Nature, vol. 574, no. 7779, pp. 505–510, 2019.

[4] B. Villalonga, D. Lyakh, S. Boixo, et al., “Establishing the quantum supremacy frontier with a 281 pflop/s simulation,” Quantum Science and Technology, vol. 5, no. 3, p. 034 003, 2020.

[5] Personal communication with Olaf Benningshof, Cryoengineer of QuTech, 2023.

[6] M. Fellous-Asiani, J. H. Chai, Y. Thonnart, H. K. Ng, R. S. Whitney, and A. Auffèves, “Optimizing resource efficiencies for scalable full-stack quantum computers,” arXiv preprint arXiv:2209.05469, 2022.

[7] P. Rebentrost, B. Gupt, and T. R. Bromley, “Quantum computational finance: Monte carlo pricing of financial derivatives,” Physical Review A, vol. 98, no. 2, p. 022 321, 2018.

[8] N. Stamatopoulos, D. J. Egger, Y. Sun, et al., “Option pricing using quantum computers,” Quantum, vol. 4, p. 291, 2020.

[9] A. Auffeves, “Quantum technologies need a quantum energy initiative,” PRX Quantum, 3(2), 020101., ISO 690, 2022.

[10] quantum-energy-initiative.org [11] Berger, Casey, et al., “Quantum technologies for climate change: Preliminary assessment,” arXiv preprint arXiv:2107.05362, 2021.