Understanding how materials behave is one of the most promising applications of quantum computers, from pioneering new battery cathodes to creating next-generation solar cells. However, in the near-term, quantum computers are unable to carry out complex simulations because they’re limited by the number of operations they can reliably perform and have a limited number of qubits.
Phasecraft’s proprietary brings together classical methods of mapping materials, with novel quantum techniques for simulating their behaviour. The first stage performs calculations and optimisations on classical computers to produce an effective representation of the material, while the second produces extremely efficient quantum circuits to simulate that material’s behaviour. The whole framework is encapsulated in an integrated software pipeline that goes from the description of a material all the way through to a quantum circuit to simulate that material.
This approach, described in the paper published in Nature Communications, Towards near-term quantum simulation of materials, is said to drastically cut the number of quantum gates needed to run the simulations, by a factor of more than a million in some cases.
To put this into perspective, Phasecraft’s approach was able to show that lithium copper oxide (Li2CuO2 – a material used in advanced lithium-ion battery technology) – could be simulated with 410,000 quantum gates. The previous baseline technique used 1.5 trillion. What’s more, Phasecraft’s approach doesn’t just show how the simulation process can be simplified, but it can identify which materials are best suited for quantum simulation in the first place.
According to Phasecraft this advancement, which was part funded through Innovate UK and National Quantum Computing Centre (NQCC) grants and carried out in collaboration with the Scientific Computing Department at the Science and Technology Facilities Council (STFC), is a substantial step towards being able to run complex materials simulations on near-term quantum computers, enabling simulations that were previously out of reach.
It’s also further progress in Phasecraft’s mission to close the gap between quantum’s promise and the real-world applications of the technology.
This breakthrough could also help to accelerate advancements in the development of more efficient batteries, photovoltaics, supercapacitors, and fuel cells, which are crucial for the advancement of renewable energy technologies. In addition, more accurate simulations using quantum computers could lead to a better understanding of how drugs interact at the molecular level, speeding up the development of new medications and reducing the cost and time to market.
To coincide with the publication of its latest paper, Phasecraft has launched its Materials Modelling Quantum Complexity Database which reveals the quantum circuit complexity for more than 40 materials identified as having potential for practical applications.
Each material lists the current circuit depth and number of qubits needed, along with the main structural properties of the material. Researchers can filter the materials database by their application, from batteries to construction, nuclear energy, electronics and more.
Commenting Toby Cubitt, co-founder and CTO/Chief Science Officer at Phasecraft, said, “The improvements we've made in circuit depths with our latest algorithms fundamentally shift the landscape and timeline of materials simulation on quantum computers. What was once deemed beyond reach of near-term quantum computers now looks to be within striking distance. We’ve taken an important step towards the promise of modelling and designing novel materials using quantum computing.”
According to Ashley Montanaro, co-founder and CEO at Phasecraft, "By publishing our materials database, we aim to bridge the gap between quantum computing theory and practical application. With each material's circuit depth and qubit requirements at their fingertips, scientists and engineers now have a new tool to assess where the greatest benefits of quantum computation are in the pursuit of accurate materials modelling."
