Thanks to IBM Q, not that difficult!

With the recent breakthrough and innovation under way, excitement is building around Quantum computing as the possibilities of what could be achieved becomes clearer. Not least for those in attendance at the recent Quantum Computing Hackathon run by the London Quantum Computing Meetup group at ThoughtWorks offices in Central London. Individuals from a variety of backgrounds, reflecting the broad spectrum of industries that quantum will likely be applicable to, came together to learn about and experience quantum computing, many for the first time, using IBM Q Experience.

The Event

During the event, which didn’t require any prior knowledge of Quantum, teams were challenged with using IBM Q Experience to find the most stable bond energy (ground state molecular energy) for two hydrogen atoms, reproducing the results IBM’s 2017 publication in Nature (Hardware-efficient Variational Quantum Eigensolver for Small Molecules and Quantum Magnets).

Without using quantum computing, understanding the properties of quantum systems such as chemical bonds is very difficult. It’s only with this completely different kind of computing that we’re now able to do things like simulate chemical reactions accurately, the impact of which will be significant for chemists to design new molecules, reaction and chemical processes.

Fortunately, it wasn’t necessary to understand in any detail this quantum chemistry problem space, only that the approach used to calculate bond length between the two atoms combined classical computing, to optimize the search space, and quantum computing, to calculate an initial guess (known as the ansatz) and the energy of the system. The hybrid quantum-classical algorithm called the Variation Quantum Eigensolver (VQE) has been hugely important in driving significant progress with near-term quantum hardware.

What Did We Do?

To do this, participants were introduced to the Quantum Information Science Kit (QISKit), an open-source quantum computing framework for leveraging quantum and conducting research. Using the Collective Knowledge (CK) repository for QISKit (https://github.com/ctuning/ck-qiskit), we were able to jump straight into running quantum experiments with a command as simple as:

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Collective Knowledge (CK) is an open-source workflow framework to speed up collaborative and reproducible R&D with reusable, customizable and portable components. The next step was to use the CK QISKit Variational Quantum Eigensolver algorithm to run experiments either on a local quantum simulator, a remote quantum simulator or on remote hardware with the aim to minimize the time to a solution within chemical accuracy of the known value. To do this each team explored a set of different optimizers (the classical part of the VQE algorithm) and the ansatz (initial quantum states). A visualization program allowed participants to monitor the convergence process to see if their particular combination of optimizer and ansatz was a good one (both quick and accurate!).

What Did We Learn?

While Quantum can seem intimidating to get to grips with, by far the best way to learn is to give it a go, and that was certainly demonstrated at the hack. At the end of the Quantum Computing Hackathon, teams gathered to reflect on insights they had gained from their hands on experience with a quantum computer. Many had gone from having no knowledge of quantum computing to being able to run quantum experiments on a real quantum computer in just a few hours! IBM Q Experience made that possible and there is even a beginners guide to get you started!

There is still a long way to go before Quantum computers become fault tolerant, providing us the accuracy that we completely take for granted with classical computing, but none the less there is still much to be excited about.

Thank you to the London Quantum Computing Meetup group for organising and running the hack! You did a great job!

For anyone who wants to learn more, here's a few resources to explore:







