Archive for March 29, 2019

A Change of Units

Posted in The Universe and Stuff with tags , , , , on March 29, 2019 by telescoper

To round off a very strange week I’ve just been to an interesting talk by Dr Bajram Zeqiri of the National Physical Laboratory in Teddington (UK) about imminent changes to the International System of Units (usually known as SI units). In a nutshell, what is to happen is that the current seven base units are to be redefined in terms of fundamental constants. In effect this means that the these constants will fix the standard units rather than the other way round. For more details, see here. The change is due to come into effect on 20th May 2019.

Our speaker Dr Zeqiri is nearing the end of a short tour of Ireland speaking about these changes. Before giving the third talk on this subject talk today, 29th March 2019, thought to be the date on which the United Kingdom would leave the European Union, he wondered whether he might be able to claim political asylum in Ireland. Fortunately, today is not Brexit Day and following today’s events in Westminster it is by no means certain when that might be or indeed whether Brexit will even happen at all…

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Machine Learning in the Physical Sciences

Posted in The Universe and Stuff with tags , , , , , on March 29, 2019 by telescoper

If, like me, you feel a bit left behind by goings-on in the field of Machine Learning and how it impacts on physics then there’s now a very comprehensive review by Carleo et al on the arXiv.

Here is a picture from the paper, which I have included so that this post has a picture in it:

The abstract reads:

Machine learning encompasses a broad range of algorithms and modeling tools used for a vast array of data processing tasks, which has entered most scientific disciplines in recent years. We review in a selective way the recent research on the interface between machine learning and physical sciences.This includes conceptual developments in machine learning (ML) motivated by physical insights, applications of machine learning techniques to several domains in physics, and cross-fertilization between the two fields. After giving basic notion of machine learning methods and principles, we describe examples of how statistical physics is used to understand methods in ML. We then move to describe applications of ML methods in particle physics and cosmology, quantum many body physics, quantum computing, and chemical and material physics. We also highlight research and development into novel computing architectures aimed at accelerating ML. In each of the sections we describe recent successes as well as domain-specific methodology and challenges.

The next step after Machine Learning will of course be Machine Teaching…