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5 key quantum computing insights

The five key messages from our interview with Prof John Morton, Director of UCL's Quantum Science and Technology Institute.
5 Key Quantum Computing Insights

We’ve just seen the interview with Professor John Morton, Director of UCL’s Quantum Science and Technology Institute.

Here are five key messages we took from the video. If you think we’ve missed anything, please add your thoughts to the discussion below.

1. Nature isn’t classical

In the early 1980s, before quantum computing as a field really took off, Richard Feynman remarked:

Nature isn’t classical, dammit, and if you want to make a simulation of nature, you’d better make it quantum mechanical, and by golly it’s a wonderful problem, because it doesn’t look so easy.

Although classical computers can model chemicals and materials, models require simplification and approximation which limit the accuracy of the results you can obtain. He identified that in order to accurately model chemicals, drugs, catalysts and materials, we would need computers based on quantum mechanics.

2. Quantum computers could help in the fight against climate change

Quantum simulation is predicted to be one of the first real-world applications of quantum computers. Quantum simulation describes the process of accurately modelling quantum systems such as chemical reactions or how electrons behave in particular materials.

One potential applications of quantum simulation relates to fertiliser manufacture. Producing fertiliser contributes to around 2% of global carbon emissions but using quantum simulation it might be possible to make this process more efficient, and in doing so reduce its carbon footprint. Additionally, quantum simulation may help with improving solar panels and making better batteries. Both of which could also help in the worldwide effort to reduce energy consumption.

3. Quantum simulation could be faster and cheaper than laboratory testing

Quantum simulation’s ability to accurately model quantum systems, such as chemical reactions, has significant potential in scenarios that currently require conducting real-world tests in the laboratory.

If scientists can test all of the physical parameters of chemicals and materials using a quantum computer then the need to physically make and test them in a lab may not be necessary. Moreover, quantum simulation could rapidly speed up the processes of protoyping and testing. This would have huge impact in industries such as pharmaceuticals, when researchers are developing new drugs.

With increases in speed, there will likely be cost-savings for organisations and perhaps more exciting there might be a dramatic change in the pace of new discoveries.

4. The power of Grover’s algorithm

Grover’s algorithm is an algorithm designed for quantum computers that offers a way of finding an entry in a database in a much faster way than conventional algorithms.

Using the example John gives (which is the same one Lov Grover put forward when first proposing his algorithm), let’s think about a phonebook where all the names have been mixed up. If the phonebook has 1 million entries, a conventional computer might take n attempts (in this case 1 million) to find the correct entry. However Grover’s algorithm can find the entry in a time that scales with the square root of n, so in the 1 case of a phonebook with 1 million entries, it might take 1000 attempts.

5. The real potential of quantum computers is yet to be realised

Although we have confidence in some of the applications quantum computers will be useful for, we don’t yet know exactly what they are capable of. This is very exciting.

It is not until we put quantum computing technology in the hands of quantum developers, will we see a step-change in the kinds of applications they might be suitable for.

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Introduction to Quantum Computing

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