Exploring photometric redshifts as an optimization problem: an ensemble MCMC and simulated annealing-driven template-fitting approach
Abstract
Using a 4D grid of ∼2 million model parameters (Δz = 0.005) adapted from Cosmological Origins Survey photometric redshift (photo-z) searches, we investigate the general properties of template-based photo-z likelihood surfaces. We find these surfaces are filled with numerous local minima and large degeneracies that generally confound simplistic gradient-descent optimization schemes. We combine ensemble Markov Chain Monte Carlo sampling with simulated annealing to robustly and efficiently explore these surfaces in approximately constant time. Using a mock catalogue of 384 662 objects, we show our approach samples ∼40 times more efficiently compared to a `brute-force' counterpart while maintaining similar levels of accuracy. Our results represent first steps towards designing template-fitting photo-z approaches limited mainly by memory constraints rather than computation time.
- Publication:
-
Monthly Notices of the Royal Astronomical Society
- Pub Date:
- October 2016
- DOI:
- 10.1093/mnras/stw1503
- arXiv:
- arXiv:1508.02484
- Bibcode:
- 2016MNRAS.461.3432S
- Keywords:
-
- methods: statistical;
- techniques: photometric;
- galaxies: distances and redshifts;
- Astrophysics - Astrophysics of Galaxies;
- Astrophysics - Instrumentation and Methods for Astrophysics
- E-Print:
- 14 pages, 8 figures