The mathematical area of topology is all about figuring out what truly defines a shape. Famously, topologists consider a coffee cup to be the same as a doughnut because one can be turned into the other without cutting or gluing — what defines and relates these two shapes for a topologist is that they have a single hole.

As you might imagine, if you have ever tried to drink coffee out of a doughnut, topology has traditionally been part of pure mathematics. Topological data analysis (TDA), however, opens up a world of applications by applying ideas from topology to vast data sets, helping us to understand their "shape" and draw out important features.

In this episode of Maths on the Move we talk to algebraic topologist Michael Hill about some of the fascinating uses of topological data analysis — from understanding breast cancer to making sure that voting is fair.

We talked to Michael after he gave a brilliant Rothschild lecture at the Isaac Newton Institute for Mathematical Sciences (INI) in Cambridge. He was at the INI to attend the research programme Equivariant homotopy theory in context.

To find out more about the topics mentioned in this podcast see:

• Maths in a minute: Topology — a quick introduction to topology.
• Understanding life with topology — a quick introduction to TDA and some of its uses.
• Euromaths: Heather Harrington — An episode of our Maths on the move podcast giving and introduction to topological data analysis.
• Watch Mike Hill's Rothschild lecture at the INI.
• Topology based data analysis identifies a subgroup of breast cancers with a unique mutational profile and excellent survival - The paper by Nicolau, Levine and Carlesson, mentioned by Michael in the podcast, which uses TDA to identify a novel type of breast cancer.
• The Data and Democracy Lab — mentioned by Mike in the podcast.

Also, here is an image illustrating the intuition behind topological data analysis. As discs drawn around a bunch of points arranged in a circle increase in radius, they eventually overlap to form a ring, and later overlap to form a single blob.

This podcast forms part of our collaboration with the Isaac Newton Institute for Mathematical Sciences (INI) – you can find all the content from the collaboration here.

The INI is an international research centre and our neighbour here on the University of Cambridge's maths campus. It attracts leading mathematical scientists from all over the world, and is open to all. Visit www.newton.ac.uk to find out more.

Welcome to the new season of the Maths on the Move podcast!

We start the season with theoretical physicist David Tong of the University of Cambridge looking at an important milestone in the history of physics: the 100th birthday of quantum mechanics which we celebrate this year. David tells us why a new theory was needed, which of the many strange aspects of quantum mechanics is, in his opinion, the most significant, and that Erwin Schrödinger had a tendency to be grumpy.

David also tells us how quantum mechanics links to quantum field theory, the language in which all of modern physics is formulated, and reveals some mysterious connections between very different areas of physics — such as the theory of black holes and fluid mechanics. Join us in a wavy dance from the very small to the very large!

For some background and further reading and viewing see:

• David Tong's series of text books
• A ridiculously short introduction to some very basic quantum mechanics
• A brief history of quantum field theory
• Heisenberg's uncertainty principle
• Maths in a Minute: Black holes
• What is general relativity? Plus asks David Tong
• Sean Carroll's Mindscape podcast featuring David Tong

We may not notice it, but mathematics impacts our lives on a daily basis. Mathematical models inform policy decisions around the economy and public health. They are used to understand climate change and how to respond to it. They are vital in the design of public buildings and spaces. They are even used to try and prevent crime.

It seems reasonable, then, that the mathematical models should reflect people's interaction with each other and their environment, and that they should take account of people's perspectives and priorities. In this episode of Maths on the Move we talk to Liz Fearon, an epidemiologist at University College London, about a pioneering new project which aims to involve people in the production of mathematical models from the start, treating them as valued and equal members of the research team. Liz tells out about the motivation behind the project, how it works, and what she hopes to achieve.

To find out more about topics mentioned in this podcast see:

• Co-production of mathematical models — the article accompanying this podcast

• The website of the COMMET project

• Disease modelling for beginners — our introduction to some basic concepts in infectious disease modelling

• The inequalities of COVID-19 — our article exploring the role of the pandemic in amplifying social inequalities

• Tracing mpox — our article about modelling the spread of mpox.

This podcast is part of our collaboration with JUNIPER, the Joint UNIversity Pandemic and Epidemic Response modelling consortium. JUNIPER comprises academics from the universities of Cambridge, Warwick, Bristol, Exeter, Oxford, Manchester, and Lancaster, who are using a range of mathematical and statistical techniques to address pressing questions about the control of COVID-19. You can see more content produced with JUNIPER here.