The key to take down the Monte Carlo rate is to introduce repulsiveness between the quadrature nodes. Blackjack will provide Monte Carlo methods that unlock inference for expensive models in biology by directly addressing the slow rate of convergence and the parallelization of Monte Carlo methods. Meanwhile, the use of parallel computing architectures for Monte Carlo is often limited to running independent copies of the same algorithm. Monte Carlo methods, for example, are ubiquitous in statistical inference for scientific data, but they scale poorly with the number of model evaluations. On the other hand, fitting these models to data can require millions of serial evaluations. A single evaluation of such complex models takes minutes or hours on today's hardware. Astrophysicists design complex models of the evolution of galaxies, biologists develop intricate models of cells, ecologists model the dynamics of ecosystems at a world scale. Expensive computer simulations have become routine in the experimental sciences.
