New algorithm puts time-scrambled data into chronological order

An international team of scientists has developed an algorithm that can put data with large time uncertainty into chronological order. After applying statistical techniques to data obtained with a 300 fs (300 × 10–15 s) timing uncertainty, the team was able to describe the laser-driven explosion of a nitrogen molecule with 1 fs resolution – an improvement in time resolution of two orders of magnitude. Because the algorithm is based on statistics, it could potentially be applied to other disciplines with timing uncertainty, such as climate science and astronomy.

Abbas Ourmazd of the University of Wisconsin-Milwaukee and colleagues used data from an imaging experiment at the Linac Coherent Light Source (LCLS) at the SLAC National Accelerator Laboratory in the US. The experiment involved firing two consecutive pulses at nitrogen molecules – with each molecule consisting of two nitrogen atoms that share three of their outermost electrons in a triple chemical bond. The first pulse (called the trigger) comprises infrared light. It rips away the inner unshared electrons from each atom in the molecule, leaving the chemical bond intact but the two atoms positively charged. The two positively charged atoms then repel each other, with a force that explodes the molecule apart. Within picoseconds of the first pulse, a second pulse (called the flash) comprising X-rays is fired at the nitrogen, which allows the team to measure the momentum of the molecule as it explodes.