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Researchers at IBM, the international technology giant with headquarters in Armonk, New York, have recently made a breakthrough in quantum computing that will soon have an impact on many of the technologies defined as “clean technology”, or cleantech.
Quantum Versus Classical Computers
The IBM team used the IBM Q, a 7-qubit quantum computer, to simulate a small, three-atom molecule’s electronic structure – a breakthrough that can lead to more quantum computing-based molecular modeling that is impossible with classical electronic computing.
Chemists have previously been able to use classical computers to simulate only very small molecules. As the size of the molecule increases, exponentially more reactions of each atom’s new electrons with the other nuclei must be simulated; this quickly becomes an impossibly-sized processing task even for the largest of classical computers. When researching new chemical compounds – for instance for better battery materials for more energy storage, or better photovoltaic materials for solar energy harnessing – chemists find that even supercomputers in labs are overwhelmed by the increased complexity of the molecule’s electronic structures.
New Quantum Algorithm
The IBM team developed a new quantum algorithm to enable quantum computers like the IBM Q to simulate a molecule’s electronic structure, creating a computer model of the molecule which chemists and materials scientists would be able to utilize in further research or the creation of new chemical compounds.
The researchers tested their algorithm on small-sized molecules that had previously never been simulated in quantum computers, including lithium hydride (LiH) and beryllium hydride (BeH2). BeH2 was the largest molecule ever simulated by a quantum computer. While it and others tested have all been simulated by classical electronic supercomputers before, the new method developed by the IBM team created a precise model. This quantum modeling method can be scaled up to larger molecules and compounds when the quantum volume (the number of qubits in a quantum computer) can be increased.
They achieved this with a fresh approach that did not simply engineer a classical computing method onto the IBM Q but instead created an original quantum algorithm designed to use the computer’s limited qubits with maximum efficiency. This was achieved by the following steps:
- An efficient mapping which converted the molecule’s fermionic Hamiltonian into a qubit Hamiltonian with minimal use of the computer’s qubits
- Using the quantum gate operations in the processor to prepare trial ground states of the Hamiltonian in a quantum circuit that also minimized demand on the IBM Q hardware
- Driving the quantum processor to the trial ground state and measuring its energy
- Generating a second quantum circuit to drive the quantum processor to, by optimizing these measured energy values
- Then reiterating this process until the lowest energy – a Hamiltonian – is obtained
Benefits and Applications of Quantum Computers in Clean Technology
Quantum computers are rapidly gaining quantum volume – the number of qubits that can be arrayed and managed within them, their processing power – and the efficient algorithm developed by the IBM team can be utilized by these larger quantum computers with numerous benefits for clean technology.
For example, a great deal of research is being focussed on energy storage (batteries) which has not dramatically improved since the invention of the battery. If chemical compounds can be found which can store more energy for their density, for longer and with less energy lost in storage and transfer, then it can be transported from areas with large amounts of available renewable energy such as hydroelectric power plants, offshore wind turbines, and solar farms in deserts and even satellites.
Another clean technology application of IBM’s breakthrough research is in photovoltaics. Photovoltaic cells transfer light energy into electricity and are key components of many solar panels. New chemical compounds are constantly being researched to find a more efficient means of capturing the sun’s light for electricity generation, and the new algorithm will enable numerous new compounds to be designed, simulated and rapidly tested for their photovoltaic potential.
Conclusion
Finally, fertilizer research can benefit from the new algorithm once large-volume quantum computing becomes available. Agricultural scientists are currently looking for new fertilizer materials which will enable greater crop yields from the planet’s limited land and energy resources. This would, in turn, reduce agricultural land use, making food production more effective for a growing global population.
Source
- Kandala, A., Mezzacapo, A., Temme, K., Takita, M., Brink, M., Chow, J.M. and Gambetta, J.M. (2017). Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets. Nature, 549(7671), pp.242–246.
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