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SUMMARY:Networks of non-equilibrium condensates for global optimisation of
  spin Hamiltonians - Kirill Kalinin
DTSTART:20190224T121500Z
DTEND:20190224T125000Z
UID:TALK120781@talks.cam.ac.uk
CONTACT:73969
DESCRIPTION:The majority of optimisation problems are computationally impr
 actical for\nconventional classical computers and known as NP-hard optimis
 ation problems.\nSuch problems deal with scheduling\, the dynamic analysis
  of neural networks and\nfinancial markets\, the prediction of new chemica
 l materials\, and machine learning.\nIncredibly\, it is possible to reform
 ulate these optimisation problems into the\nproblem of finding the ground 
 state of a particular spin Hamiltonian.\nIn my talk I will address various
  physical platforms that can simulate such spin\nHamiltonians in order to 
 solve optimisation problems orders of magnitude faster\nthan can be achiev
 ed on a classical computer. In particular\, the spin Hamiltonians\ncan be 
 simulated experimentally with polariton condensates. These are effectively
 \ncomprised of a “mix” of the states of light and matter\, and can be 
 explicitly\nmapped into problems such as the travelling salesman problem. 
 Using such\nmappings\, one can study physical systems experimentally and e
 ffectively “read\nout” the solution to an optimisation problem one wis
 hes to solve. A possible speedup opens a path to global minimisation of la
 rge-scale\, real-world problems not\naccessible by classical simulations. 
LOCATION:Winstanley Lecture Theatre\, Trinity College
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