Accelerated Time-of-Flight Mass Spectrometry

We study a simple modification to the conventional time-of-flight mass spectrometry (TOFMS) where a variable and (pseudo)-random pulsing rate is used, which allows for traces from different pulses to overlap. This modification requires little alteration to the currently employed hardware. However, it requires a reconstruction method to recover the spectrum from highly aliased traces. We propose and demonstrate an efficient algorithm that can process massive TOFMS data using computational resources that can be considered modest by today's standards. This approach can be used to improve duty cycle, speed, and mass resolving power of TOFMS at the same time. We demonstrate the efficacy of our method by running an experiment using a conventional TOFMS instrument and simulating the output of the modified scheme using these observations. Our result shows that the new scheme can result in a ten fold speed up of the instrument. We expect this to extend the applicability of TOFMS to new domains. Moreover, we detailed how our work represents an example in the statistically sparse signal acquisition paradigm. In this regime, a (possibly dense) signal x can be observed only through noisy sparse measurements where all but a small, random, unknown fraction of the entries are set to zero in each observation. We argue that improving the acquisition efficiency through random linear measurements in this regime has many possible applications and represents a host of both practical and theoretical challenges.