Daisuke Kawata is Professor of Astronomy at UCL’s Department of Space & Climate Physics, based at the Mullard Space Science Laboratory.
He was among the recipients of the inaugural UCL-University of Toronto seed funding in 2017, to encourage collaboration between academics at the two institutions. A year on from the initial funding, we caught up with him to hear more about how the collaboration is progressing.
How did you first become interested in astronomy?
My undergraduate degree was actually in Engineering, but when computer simulations started getting bigger and bigger, I became interested in using computers to understand physics and how the universe is made up. I then became fascinated with the evolution of the Milky Way. So I moved from undergraduate Engineering to a master’s course in Astronomy, and I did a PhD in Astronomy in Japan.
Where has your research taken you?
After my post doc in Japan, I worked in Australia for about four years, and I then went to California in the USA. I worked there for three and a half years or so. Now, at UCL, I feel lucky to be part of this research-intensive institution. The research level in the UK is very high and lots of people gather in London: it’s an international environment. At the moment I’m working with colleagues in the Computer Science department, so the opportunities to work with people elsewhere in the UCL family is exciting.
You were one of the recipients of the UCL-University of Toronto seed funding for collaboration with academics at Toronto in 2017. What are you working on together?
Our research aims to understand the structure of the Milky Way, as well as how it formed and evolved. It’s quite an exciting moment for us because the European Space Agency launched a space craft called Gaia in December 2013, which is observing the motion of over a billion stars in the Milky Way, and they release intermittent data to the community so that we can use the satellite data for our research.
As you can imagine, if you’re in the forest looking out at the trees, it’s very difficult to understand how big the forest is and how the trees are distributed – and the same applies for our galaxy. You need a physical, computer model to understand the Gaia Data. So that’s what our collaboration has set up. It’s a computer simulated Milky Way model, and our hope is that this computer model will be used to picture the whole structure of the galaxy.
How did the connection with Toronto first come about?
We met Jo Bovy, my counterpart in Toronto, at a conference about the Milky Way about eight years or so ago, when he was still a PhD student. I knew him because he was making quite advanced statistical models to understand the Milky Way. I knew he was a rising star in our field, but it was two years ago when I was at one of the institutes in New York and he was doing a sabbatical there that we were able to spend a week in the same location and really discuss this modelling technique, ‘Made-to-measure.’
We talked about advancing this computer simulation model, which my PhD student Jason hunt and I had already made a prototype of. We had an intense discussion with Jo on how we could improve it and made a big road map for how we could do so. So that was the starting point, almost two years ago.
What was the outcome of your recent visit to Toronto?
We visited at the beginning of October, and had a series of meetings almost every day, which meant lots of discussion time. We came up with ideas for improving the Made-to-measure technique and other ideas about using Gaia Data to understand the structure of the galaxy. We also started working on some papers together.
Do you have advice for anyone who hasn’t collaborated on such a global scale before? How do you make an international partnership work?
Conferences are always a good starting point – with a couple of hundred people there, there are plenty of people to talk to. And tea time is a good time to start! The next step is, if you’ve met a scientist you want to work with, try and spend an extended period of time at the same location to talk about a specific topic.
What are next steps for the project with Toronto?
We’re going to try and apply this Made-to-measure model to the Gaia Data. Before this application we will try to understand it in a more local neighbourhood: we still don’t know much dark matter is around us, and using this technique we hope we can get more accurate measurements of the dark matter density in the solar neighbourhood.