A city can be studied in different ways: one person maps the streets, another tracks traffic flows, and a third maps population density. The maps don't match, but they describe the same place. A similar problem arises when biologists look at a cell through different instruments: one shows its shape, another the distribution of proteins inside. We need to understand how these data are related.

The new method UnSyncOT does exactly that. It takes two sets of measurements from different spaces (for example, a tissue image and a list of active genes) and finds how mass flows between them. Mass doesn't have to be conserved: some cells die, some are born. The method can synchronize such "maps" even without exact point-to-point correspondence.

Tests on numerical models showed that the calculations converge and work stably. Such a tool will be useful wherever data are collected in different ways, from biology to transportation.