Imperial College London


Faculty of Natural SciencesDepartment of Mathematics

Borland Fellow in Mathematics



t.elliott20 Website




Blackett LaboratorySouth Kensington Campus





Simulating quantum dynamics on a classical computer bears a resource cost that grows exponentially with the size of the system; studying systems of more than a few particles quickly becomes intractable. Yet, underpinning this is a fascinating duality - the very properties of quantum systems that make them appear complex to classical systems can be exploited to efficiently study complex classical systems with quantum devices. My research approaches this duality from both sides.

Under the broad umbrella of ‘quantum simulation’, I investigate how quantum technologies can be used to emulate and study the behaviour of complex systems, and conversely, seek to understand which structures of quantum dynamics makes them appear complex to classical hardware. I am interested in the foundational aspects of this, such as the insight this provides into the intrinsic computation of dynamical systems, as well as the practical applications for stochastic modelling and machine learning - particularly in terms of adaptive systems (or ‘agents’).

I was awarded my DPhil in Atomic and Laser Physics from the University of Oxford in 2016. I worked in the Frontiers of Quantum Physics group under the supervision of Vlatko Vedral. My thesis, "Topics in Quantum Measurement of Many-Body Systems", investigated a range of questions centred around the theme of measurement of many-body quantum systems, including techniques for probing atomic systems non-destructively, and using the quantum Zeno effect to engineer states and dynamics of atoms in optical lattices. Following this, I held the Lee Kuan Yew Research Fellowship at Nanyang Technological University, where I was a member of the Quantum and Complexity Science Initiative. During this time, I became interested in the role quantum technologies can play in studies of complex systems. In particular, I developed an extensive toolbox for achieving extreme compression advantages when simulating stochastic systems on a quantum processor.

All my publications may be found on the arXiv.

Selected Publications

Journal Articles

Elliott TJ, Yang C, Binder FC, et al., 2020, Extreme dimensionality reduction with quantum modeling, Physical Review Letters, Vol:125, ISSN:0031-9007, Pages:260501 – 1-260501 – 6

Liu Q, Elliott TJ, Binder FC, et al., 2019, Optimal stochastic modeling with unitary quantum dynamics, Physical Review A, Vol:99, ISSN:2469-9926

Elliott TJ, Gu M, 2018, Superior memory efficiency of quantum devices for the simulation of continuous-time stochastic processes, Npj Quantum Information, Vol:4, ISSN:2056-6387

Elliott TJ, Johnson TH, 2016, Nondestructive probing of means, variances, and correlations of ultracold-atomic-system densities via qubit impurities, Physical Review A, Vol:93, ISSN:2469-9926

Elliott TJ, Kozlowski W, Caballero-Benitez SF, et al., 2015, Multipartite Entangled Spatial Modes of Ultracold Atoms Generated and Controlled by Quantum Measurement, Physical Review Letters, Vol:114, ISSN:0031-9007

More Publications