Rahko is unlocking discovery with quantum machine learning for chemical simulation
Quantum computers will offer us far greater computational power than classical computers.
This will allow us to unlock areas of research and technology currently limited by the computational power of classical computers.
However, it has been widely believed that near-term (‘NISQ’) quantum computers will not be able to deliver useful applications due to their high error rates (‘noise’).
Quantum machine learning
At the intersection of quantum computing and machine learning, quantum machine learning (‘QML’) has been proven to be remarkably resilient to noise by Rahko and a small number of teams across the world.
Rahko’s team focuses on 2nd generation QML algorithms, ‘parametrized quantum circuits’ that can be trained like deep learning models and can be highly robust to noise on today’s quantum computers.
Using these 2nd generation QML algorithms, we are constantly pushing the boundaries of what can be achieved with current and near-term quantum computers.
Hyrax: the Quantum Discovery Framework
Our work is enabled by our proprietary Hyrax platform, which allows us to rapidly test and prototype algorithms, and efficiently access the best available quantum computers.
Using Hyrax, we work with customers on commercially valuable problems in chemical simulation that were previously impossible to solve with classical computers. Read more about Hyrax here.
The clearest immediate potential for QML is in chemical simulation. Chemical simulation allows us to model reality, taking extremely time consuming and expensive research out of the lab and onto a computer.
Chemical simulation has fuelled research in several important areas of research and technology including chemical engineering, drug discovery and material science. It allows the development of batteries, superconductors, therapeutic drugs, solar technologies and advanced materials, among others.
However, in many areas, advances in chemical simulation have stalled due to the limitations of the computational power available to us with classical computers. Modelling reality with a classical computer requires us to approximate results. Imprecise results significantly limit our modelling capabilities.
Modelling reality at the quantum level
Chemical simulation on a quantum computer will allow us to model reality at the quantum level, and will enable us to solve intractable problems with previously unattainable levels of precision.
If your team has a need for the highest levels of precision in chemical simulation, get in touch with Rahko here.