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Winton Programme for the Physics of Sustainability

Department of Physics
 

Prof Michael Köhl (Atomic, Mesoscopic and Optical Physics)

Koehl_fig

Recently, we have for the first time observed the pseudogap phase in a two-dimensional Fermi gas, in which a superconducting pairing gap opens up without the appearance of a symmetry-broken phase [M. Feld et al., Nature 480, 75 (2011)]. This work paves the way for emulating and understanding high-temperature superconductors. However, our research has also demonstrated that usual cooling methods have reached their limits in efficiently and economically achieving ultralow temperatures, and that radically new concepts are required. This project aims at demonstrating a novel cooling technique, which does not rely on thermodynamic engines but on a dynamical division of the systems into sub systems of high and low entropy. It is a fundamentally new approach to cooling and, if successful, would immediately transform the field of quantum materials because new states of matter will come within reach and open questions, for example regarding the origin of high-temperature superconductivity, will be answered.

Project Completed end of July 2012

The funding has enabled equipment to be purchased with which initial trials have been performed.  The results are encouraging that the proposed scheme is viable and work is continuing on applying this technique to ultracold cloud of neutral atoms.

Follow on funds have been acquired to support this work:

  • “Dynamics of phase transitions to gapped and ungapped quantum states“ Engineering and Physical Sciences Research Council (EPSRC), 36 months, £776k (together with Z. Hadzibabic)
  • “Quantum dynamics of low-dimensional atomic Fermi gases” Engineering and Physical Sciences Research Council (EPSRC), 36 months, £471k

Latest news

Manipulation of Quantum Entangled Triplet Pairs

7 January 2021

Researchers have uncovered a new technique to create and manipulate pairs of particle-like excitations in organic semiconductors that carry non-classical spin information across space, much like the entangled photon pairs in the famous Einstein-Podolsky-Roden “paradox”.

Machine learning algorithm helps in the search for new drugs

20 March 2019

Researchers have designed a machine learning algorithm for drug discovery which has been shown to be twice as efficient as the industry standard.