CNBP researchers Dr Daniel Drumm (lead author pictured) and Prof Andrew Greentree, both at RMIT University, have analysed microscopy in the contexts of Rényi-Ulam games and half-lies, developing a new family of heuristics. Their research is reported in the journal ‘Scientific Reports.’
Journal: Scientific Reports.
Authors: Daniel W. Drumm & Andrew D. Greentree.
Abstract: Finding a fluorescent target in a biological environment is a common and pressing microscopy problem. This task is formally analogous to the canonical search problem. In ideal (noise-free, truthful) search problems, the well-known binary search is optimal. The case of half-lies, where one of two responses to a search query may be deceptive, introduces a richer, Rényi-Ulam problem and is particularly relevant to practical microscopy. We analyse microscopy in the contexts of Rényi-Ulam games and half-lies, developing a new family of heuristics. We show the cost of insisting on verification by positive result in search algorithms; for the zero-half-lie case bisectioning with verification incurs a 50% penalty in the average number of queries required. The optimal partitioning of search spaces directly following verification in the presence of random half-lies is determined. Trisectioning with verification is shown to be the most efficient heuristic of the family in a majority of cases.