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Atomic and Laser Physics
Credit: Jack Hobhouse

Dr Elliot Bentine

Royal Academy of Engineering Enterprise Fellowship

Research theme

  • Instrumentation
  • Quantum optics & ultra-cold matter

Sub department

  • Atomic and Laser Physics

Research groups

  • Ultracold quantum matter
elliot.bentine@physics.ox.ac.uk
Telephone: 01865 (2)72203
Clarendon Laboratory
  • About
  • Publications

Observation of the Berezinskii-Kosterlitz-Thouless transition in a two-dimensional Bose gas via matter-wave interferometry

Physical Review Letters American Physical Society 128:25 (2022) 250402

Authors:

S Sunami, Vp Singh, D Garrick, A Beregi, Aj Barker, K Luksch, E Bentine, L Mathey, Cj Foot

Abstract:

We probe local phase fluctuations of trapped two-dimensional (2D) Bose gases using matter-wave interferometry. This enables us to measure the phase correlation function, which changes from an algebraic to an exponential decay when the system crosses the Berezinskii-Kosterlitz-Thouless (BKT) transition. We determine the temperature dependence of the BKT exponent 畏 and find the critical value 畏c = 0.17(3) for our trapped system. Furthermore, we measure the local vortex density as a function of the local phase-space density, which shows a scale-invariant behaviour across the transition. Our experimental investigation is supported by Monte Carlo simulations and provides a comprehensive understanding of the BKT transition in a trapped system.

Coherent splitting of two-dimensional Bose gases in magnetic potentials

New Journal of Physics IOP Publishing 22:10 (2020) 103040

Authors:

Aj Barker, S Sunami, D Garrick, A Beregi, K Luksch, E Bentine, Cj Foot

Abstract:

Investigating out-of-equilibrium dynamics with two-dimensional (2D) systems is of widespread theoretical interest, as these systems are strongly influenced by fluctuations and there exists a superfluid phase transition at a finite temperature. In this work, we realise matter-wave interference for degenerate Bose gases, including the first demonstration of coherent splitting of 2D Bose gases using magnetic trapping potentials. We improve the fringe contrast by imaging only a thin slice of the expanded atom clouds, which will be necessary for subsequent studies on the relaxation of the gas following a quantum quench.

Realising a species-selective double well with multiple-radiofrequency-dressed potentials

Journal of Physics B: Atomic, Molecular and Optical Physics IOP Publishing 53:15 (2020) 155001

Authors:

Aj Barker, S Sunami, D Garrick, A Beregi, K Luksch, E Bentine, Cj Foot

Abstract:

Techniques to manipulate the individual constituents of an ultracold mixture are key to investigating impurity physics. In this work, we confine a mixture of hyperfine ground states of 87Rb atoms in a double-well potential. The potential is produced by dressing the atoms with multiple radiofrequencies. The amplitude and phase of each frequency component of the dressing field are controlled to independently manipulate each species. Furthermore, we verify that our mixture of hyperfine states is collisionally stable, with no observable inelastic loss.

AEDGE: Atomic Experiment for Dark Matter and Gravity Exploration in Space

EPJ QUANTUM TECHNOLOGY Springer Science and Business Media LLC 7:1 (2020) ARTN 6

Authors:

Yousef Abou El-Neaj, Cristiano Alpigiani, Sana Amairi-Pyka, Henrique Araujo, Antun Balaz, Angelo Bassi, Lars Bathe-Peters, Baptiste Battelier, Aleksandar Belic, Elliot Bentine, Jose Bernabeu, Andrea Bertoldi, Robert Bingham, Diego Blas, Vasiliki Bolpasi, Kai Bongs, Sougato Bose, Philippe Bouyer, Themis Bowcock, William Bowden, Oliver Buchmueller, Clare Burrage, Xavier Calmet, Benjamin Canuel, Laurentiu-Ioan Caramete, Andrew Carroll, Giancarlo Cella, Vassilis Charmandaris, Swapan Chattopadhyay, Xuzong Chen, Maria Luisa Chiofalo, Jonathon Coleman, Joseph Cotter, Yanou Cui, Andrei Derevianko, Albert De Roeck, Goran S Djordjevic, Peter Dornan, Michael Doser, Ioannis Drougkakis, Jacob Dunningham, Ioana Dutan, Sajan Easo, Gedminas Elertas, John Ellis, Mai El Sawy, Farida Fassi, Daniel Felea, Chen-Hao Feng, Robert Flack

Abstract:

漏 2020, The Author(s). We propose in this White Paper a concept for a space experiment using cold atoms to search for ultra-light dark matter, and to detect gravitational waves in the frequency range between the most sensitive ranges of LISA and the terrestrial LIGO/Virgo/KAGRA/INDIGO experiments. This interdisciplinary experiment, called Atomic Experiment for Dark Matter and Gravity Exploration (AEDGE), will also complement other planned searches for dark matter, and exploit synergies with other gravitational wave detectors. We give examples of the extended range of sensitivity to ultra-light dark matter offered by AEDGE, and how its gravitational-wave measurements could explore the assembly of super-massive black holes, first-order phase transitions in the early universe and cosmic strings. AEDGE will be based upon technologies now being developed for terrestrial experiments using cold atoms, and will benefit from the space experience obtained with, e.g., LISA and cold atom experiments in microgravity. KCL-PH-TH/2019-65, CERN-TH-2019-126.

Applying machine learning optimization methods to the production of a quantum gas

Machine Learning: Science and Technology IOP Publishing 1:1 (2020) 015007

Authors:

Adam J Barker, Harry Style, Kathrin Luksch, Shinichi Sunami, David Garrick, Felix Hill, Christopher J Foot, Elliot Bentine

Abstract:

We apply three machine learning strategies to optimize the atomic cooling processes utilized in the production of a Bose鈥揈instein condensate (BEC). For the first time, we optimize both laser cooling and evaporative cooling mechanisms simultaneously. We present the results of an evolutionary optimization method (differential evolution), a method based on non-parametric inference (Gaussian process regression) and a gradient-based function approximator (artificial neural network). Online optimization is performed using no prior knowledge of the apparatus, and the learner succeeds in creating a BEC from completely randomized initial parameters. Optimizing these cooling processes results in a factor of four increase in BEC atom number compared to our manually-optimized parameters. This automated approach can maintain close-to-optimal performance in long-term operation. Furthermore, we show that machine learning techniques can be used to identify the main sources of instability within the apparatus.

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