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Efficient blind search: optimal power of detection under computational cost constraints. (English) Zbl 1161.62087
Summary: Some astronomy projects require a blind search through a vast number of hypotheses to detect objects of interest. The number of hypotheses to test can be in the billions. A naive blind search over every single hypothesis would be far too costly computationally. We propose a hierarchical scheme for blind search, using various “resolution” levels. At lower resolution levels, “regions” of interest in the search space are singled out with a low computational cost. These regions are refined at intermediate resolution levels and only the most promising candidates are finally tested at the original fine resolution. The optimal search strategy is found by dynamic programming. We demonstrate the procedure for pulsar search from satellite gamma-ray observations and show that the power of the naive blind search can almost be matched with the hierarchical scheme while reducing the computational burden by more than three orders of magnitude.

MSC:
62P35 Applications of statistics to physics
85A35 Statistical astronomy
90C39 Dynamic programming
90C90 Applications of mathematical programming
85A05 Galactic and stellar dynamics
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