We were inspired by recent developments in quantum optimisation algorithms, specifically VQE and so decided to try and make our own version of this, given that there have been many developments in the uses of quantum computing in stock calculations and predictions, we thought that it would be an interesting area to work in to try and make our own version of this, inspired by current developments in the field.

How we made it

To make the program, we would need to both work on the quantum code, so that the program can actually work and function, and also to create a guided user interface to enable the user to actually be able to use our program.

To do this, Agnij, who has the most experience of quantum computing in the group, did some web scraping using Qandl to find how stock markets had been performing over the last four years and then used a VQE style algorithm to find the probabilities that the markets would continue to be successful in the next few years.

In terms of creating a user interface, Harpreet used PyQt5 and pyqt-tools to allow the user to...


We encountered several challenges during the weekend including time zone differences, a lack of software and varying levels of experience and knowledge in different areas of code. In order to account for these, we:

  • Set tasks for different team members to be able to do independently whilst other team members were asleep. This helped us to get the problem statement done early on so we could spend most of the second day coding.
  • Gave different people different roles based on what they had access to. If a team member could not access PyQt5, we would not make them make the UI as they would be unable to.
  • Assigned roles based on different levels of experience. Isabella was able to put the video together because of their previous experience and Agnij, Pranav and Harpreet could do the quantum coding because of their knowledge in the area, for example.

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