Jack Raymond

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Properties of computing Boolean circuits composed of noisy logical gates are studied using the statistical physics methodology. A formula-growth model that gives rise to random Boolean functions is mapped onto a spin system, which facilitates the study of their typical behavior in the presence of noise. Bounds on their performance, derived in the(More)
Sampling from a Boltzmann distribution is NP-hard and so requires heuristic approaches. Quantum annealing is one promising candidate. The failure of annealing dynamics to equilibrate on practical time scales is a well understood limitation, but does not always prevent a heuristically useful distribution from being generated. In this paper, we evaluate(More)
Computing circuits composed of noisy logical gates and their ability to represent arbitrary boolean functions with a given level of error are investigated within a statistical mechanics setting. Existing bounds on their performance are straightforwardly retrieved, generalized, and identified as the corresponding typical-case phase transitions. Results on(More)
We study a one-dimensional lattice flocking model incorporating all three of the flocking criteria proposed by Reynolds [Computer Graphics 21, 4 (1987)]: alignment, centering, and separation. The model generalizes that introduced by O. J. O'Loan and M. R. Evans [J. Phys. A. 32, L99 (1999)]. We motivate the dynamical rules by microscopic sampling(More)