Conner Dailey Physics graduate student, hobby photographer

Search for transient ultralight dark matter signatures with networks of precision measurement devices using a Bayesian statistics method

Benjamin M. Roberts, Geoffrey Blewitt, Conner Dailey, & Andrei Derevianko

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We analyze the prospects of employing a distributed global network of precision measurement devices as a dark matter and exotic physics observatory. In particular, we consider the atomic clocks of the global positioning system (GPS), consisting of a constellation of 32 medium-Earth orbit satellites equipped with either Cs or Rb microwave clocks and a number of Earth-based receiver stations, some of which employ highly-stable H-maser atomic clocks. High-accuracy timing data is available for almost two decades. By analyzing the satellite and terrestrial atomic clock data, it is possible to search for transient signatures of exotic physics, such as “clumpy” dark matter and dark energy, effectively transforming the GPS constellation into a 50 000 km aperture sensor array. Here we characterize the noise of the GPS satellite atomic clocks, describe the search method based on Bayesian statistics, and test the method using simulated clock data. We present the projected discovery reach using our method, and demonstrate that it can surpass the existing constrains by several order of magnitude for certain models. Our method is not limited in scope to GPS or atomic clock networks, and can also be applied to other networks of precision measurement devices.


The global scale of the GPS network offers a unique opportunity to search for spatially-extended DM objects (or “clumps”), such as topological defects (TDs), which are otherwise not detectable by most ongoing and planned DM searches. The large number of clocks and the very large aperture of the network increase both the chance of an interaction and the sensitivity of the search, since we seek the correlated propagation of new physics signals throughout the entire network. The large network diameter also increases the overall interaction time. Therefore, by analyzing the GPS timing data, one can perform a sensitive search for transient signals of exotic physics, and if no sought signals are found, stringent limits on the relevant interaction strengths can be placed.

Recently, our GPS.DM collaboration carried out an initial analysis of the archival GPS data, looking for signatures of a particular type of TDs (domain walls, quasi-2D cosmic structures). While no such signatures were found, we placed limits on certain DM couplings to atoms that are many orders of magnitude more stringent than the previous constraints. Here, we present a search method based on Bayesian statistics. We demonstrate that compared to our initial search, the Bayesian approach greatly increases the search sensitivity. This approach also broadens the discovery reach to more general DM models and to lower DM field masses.