Theoretical Physics - From Outer Space to Plasma

Latest Episodes:

Classical and Quantum Black Holes Jan 16, 2021

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Prof March-Russell explains our latest understanding of black holes, some of the most mysterious objects in the Universe.

Why is Quantum Gravity so hard? Jan 16, 2021

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A pressing question in our quest to understand the Universe is how to unify quantum mechanics and gravity, the very small and the very large.

Machine learning techniques in modern quantum-mechanics experiments Mar 22, 2020

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In this talk, Dr Elliott Bentine shall discuss how recent experiments have exploited machine-learning techniques, both to optimize the operation of these devices and to interperet the data they produce. Modern table-top experiments can engineer physical systems that are deeply into the quantum mechanical regime. These cutting-edge instruments provide new insights into fundamental physics, and a pathway to future devices that will harness the power of quantum mechanics. They typically require complex operations to prepare and control the quantum state, involving time-dependent sequences of magnetic, electric and laser fields. This presents experimental physicists with an overwhelming number of tunable parameters, which may be subject to uncertainty or fluctuations.

Machine Learning and String Theory Mar 22, 2020

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Professor Andre Lukas will discuss how string theorists have started to use methods from data science - particularly machine learning - to analyse the vast landscape of string data.

An Introduction to deep learning Mar 22, 2020

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Professor Ard Louis gives a basic introduction to deep learning for physicists and addresses a few questions such as: Is the hype around deep learning justified, or are we about to hit some fundamental limitations? In less than ten years, machine learning techniques based on deep neural networks have moved from relative obscurity to central stage in the AI industry. Large firms such as Google and Facebook are pouring billions into research and development of these new technologies. The use of deep learning in physics is also growing exponentially. Can physics help us understand why deep learning works so well? And conversely: How can deep learning provide new insight into the world around us?

Welcome by Ian Shipsey Head of the Department of Physics Mar 22, 2020

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Ian Shipsey give an update on the department and introduces the next three talk on 'AI in Physics'.

Cosmic acceleration revealed by Type la supernovae? Nov 01, 2019

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In this talk Subir Sarkar will explain how deflagration supernovae have been used to infer that the Hubble expansion rate is accelerating, and critically assess whether the acceleration is real and due to `dark energy’.

Supernova Explosions and their Role in the Universe Nov 01, 2019

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In this talk, Philipp Podsiadlowski will explain how this energy (sometimes) creates a visible fireball, before going on to explain the role of supernovae in the production of the heaviest elements in the periodic table.

What makes stars go bang? Nov 01, 2019

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In this talk, James Binney will outline the physics that leads to prodigeous release of energy in core-collapse and deflagration supernovae.

... from collisions to the Higgs boson May 16, 2019

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To study the Higgs boson at the LHC we also need to understand how highly energetic quarks and gluons interact, among themselves and with the Higgs. These interactions are described by quantum field theory, a beautiful mathematical framework that combines quantum mechanics with Einstein’s theory of special relativity. In recent years, our understanding of quantum field theory has progressed significantly, allowing us to develop a new generation of accurate theoretical predictions for key LHC reactions. In this talk, I will highlight some of the ideas behind this progress, and illustrate how they are being applied to investigate the Higgs sector at the LHC.