We propose a new method of constraining the redshifts of individual extragalactic sources based on their celestial coordinates. Techniques from integer linear programming are utilized to optimize simultaneously for the angular two-point cross- and autocorrelation functions. Our novel formalism introduced here not only transforms the otherwise hopelessly expensive, brute-force combinatorial search into a linear system with integer constraints but is also readily implementable in off-the-shelf solvers. We adopt Gurobi and use Python to dynamically build the cost function. The preliminary results on simulated data show great promise for future applications to sky surveys by complementing and enhancing photometric redshift estimators. Our approach is the first use of linear programming in astronomy.
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