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How do you encode combinatorial optimization problems when they have inequality constraints on quantum computers? well, the usual approach is using slack variables. But, this approach is quite expensive and makes the search for possible solutions even harder. In this work, https://arxiv.org/abs/2211.13914, we present “unbalanced penalization” a new approach to encode the inequality constraints of combinatorial optimization problems.

Collection of software tools for the scientific community to facilitate access to and processing of TOAR data

Code related to the CHRRT (Coordinate Hit-and-Run with Rounding and Thinning) project.

Contains scripts for sampling & evaluating performance. Also contains ESS and RHAT data for the runs used in the manuscript.

Working title, please don't tell me how bad the name is, but provide a better one :)

Simulation of Shor's algorithm with the semiclassical Fourier transform using multiple GPUs and MPI