Quantum computing promises to redefine the boundaries of computation and has also been touted as a potential game-changer in energy savings. The technology’s potential to enable new material discovery, improve EV batteries and solar cells, optimize logistic routes, all while consuming much less energy than traditional power-hungry supercomputers, paint a promising picture. However, as with any emerging technology, there are skeptics who question these claims.

Critics argue that the overall infrastructure required to support quantum computing, including the need for traditional computers to move control signals and data into and out of a quantum computer, and the energy-consuming cooling requirements, may negate the energy savings as the quantum computers become larger and more powerful. While these concerns are valid, it’s important to consider the broader context and the potential of quantum computing.

Firstly, it’s important to acknowledge that quantum computers will indeed solve certain problems much more efficiently than classical computers. Problems in cryptography, optimization, and material science can potentially be solved exponentially faster on a quantum computer. This means that a task that might take a classical computer several years to complete could potentially be done by a quantum computer in a matter of hours. This level of efficiency could lead to significant energy savings in the long run.

Secondly, it’s worth noting that the development of quantum computing is still in its early stages. Much like the early days of classical computing, where the focus was on making the technology work before making it efficient, quantum computing is currently in the “make it work” phase. As the technology matures, it’s likely that more energy-efficient quantum computing infrastructures will be developed.

Organizations like the Quantum Energy Initiative (QEI) are already working towards this goal. Co-founded by Olivier Ezratty, Rob Whitney, Alexia Auffèves, and Janine Splettstoesser, the QEI aims to bridge the gap between the quantum technology and energy sectors. By fostering collaboration and knowledge exchange, the QEI is working to raise awareness and address the challenges associated with their energy consumption.

Innovations in quantum technology are also paving the way for more energy-efficient quantum computing. For instance, QuEra’s neutral atom quantum computers do not require cryogenic cooling, which is one of the most energy-consuming aspects of traditional quantum computing infrastructure. Occupying a small footprint, and operating at room temperature, the power requirements of QuEra’s Aquila computer are less than 10kW, and even looking a couple of product generations out, it would still be a tiny fraction of the megawatts consumed by supercomputers.

The energy efficiency of quantum computers has significantly influenced the interest of High-Performance Computing (HPC) centers. While the ability of quantum computers to solve intractable problems remains a key area of interest, it’s no longer the sole criterion. HPC centers are now showing keen interest in quantum computing even if these systems solve the same problems as supercomputers, but at a fraction of the energy cost. This shift in interest underscores the recognition of quantum computing’s potential to deliver similar computational results as traditional supercomputers, but with significantly improved energy efficiency.

The concern regarding data loading in quantum computing is a valid one, given the unique operational principles of these advanced systems. Unlike classical computers, which can readily load and store vast amounts of data, quantum computers currently face limitations in this area. However, it’s important to note that extensive research is underway to address this issue. Scientists and engineers are exploring various methods to enhance data loading in quantum computers, with promising techniques such as quantum RAM (qRAM) under development.

Another solution can be the use of hybrid quantum-classical systems. Another approach is the use of data reduction techniques like Principal Component Analysis (PCA). PCA can be used to select the most relevant data for input into a quantum computer. By reducing the dimensionality of the data and retaining only the most significant variables, PCA can help to mitigate the data loading problem, making the process more manageable and efficient for quantum systems.

However, it’s important to temper optimism with realism. While there is significant potential for energy savings with quantum computing, the technology is still in its infancy, and there are many challenges to overcome. The jury is still out on whether the energy savings promised by quantum computing will outweigh the energy consumed by its supporting infrastructure.

While the energy savings with quantum computing may currently seem more like fiction than fact, there is hope. With ongoing research and development, collaboration between different sectors, and innovations in quantum technology, it’s likely that quantum computing could become a significant contributor to energy savings in the future.

[1] Excerpt from paper’s abstract: “..Quantum computation is known to offer advantages over classical computation in terms of various computational resources; however, its advantage in energy consumption has been challenging to analyze due to the lack of a theoretical foundation to relate the physical notion of energy and the computer-scientific notion of complexity for quantum computation with finite computational resources. To bridge this gap, we introduce a general framework for studying energy consumption of quantum and classical computation based on a computational model with a black-box oracle, as conventionally used for studying query complexity in computational complexity theory..”