title: Maximum-Entropy Inference with a Programmable Annealer.
abstract: Optimisation problems typically involve finding the ground state (i.e. the minimum energy configuration) of a cost function with respect to many variables. If the variables are corrupted by noise then this maximises the likelihood that the solution is correct. The maximum entropy solution on the other hand takes the form of a Boltzmann distribution over the ground and excited states of the cost function to correct for noise. Here we use a programmable annealer for the information decoding problem which we simulate as a random Ising model in a field. We show experimentally that finite temperature maximum entropy decoding can give slightly better bit-error-rates than the maximum likelihood approach, confirming that useful information can be extracted from the excited states of the annealer. Furthermore we introduce a bit-by-bit analytical method which is agnostic to the specific application and use it to show that the annealer samples from a highly Boltzmann-like distribution. Machines of this kind are therefore candidates for use in a variety of machine learning applications which exploit maximum entropy inference, including language processing and image recognition.
authors.affiliation: London Centre For Nanotechnology 19 Gordon St, London, WC1H 0AH, UK.
authors.forename: Nicholas
authors.initials: N
authors.lastname: Chancellor
authors.affiliation: Department of Electronic and Electrical Engineering, UCL, Torrington Place, London, WC1E 7JE, UK.
authors.forename: Szilard
authors.initials: S
authors.lastname: Szoke
authors.affiliation: University of Southern California Department of Electrical Engineering 825 Bloom, Walk Los Angeles CA, 90089, USA.|University of Southern California Center for Quantum Information Science Technology 825 Bloom Walk, Los Angeles CA, 90089, USA.
authors.forename: Walter
authors.initials: W
authors.lastname: Vinci
authors.affiliation: Department of Physics, ETH Zürich, Zürich, CH-8093, Switzerland.|Department of Physics, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, CH-1015, Switzerland.|Synchrotron and Nanotechnology Department, Paul Scherrer Institute, Villigen, CH-5232, Switzerland.
authors.forename: Gabriel
authors.initials: G
authors.lastname: Aeppli
authors.affiliation: London Centre For Nanotechnology 19 Gordon St, London, WC1H 0AH, UK.|Department of Electronic and Electrical Engineering, UCL, Torrington Place, London, WC1E 7JE, UK.
authors.forename: Paul A
authors.initials: PA
authors.lastname: Warburton
mesh_terms: D019277:Entropy; D008962:Models, Theoretical