Demonstrates a new computational framework for analyzing time series data with super resolution, suggesting practical applications in various fields.
Multiple-frequency periodograms—based on time-series models consisting of two or more independent sinusoids—have long been discussed. What is new here is the presentation of a practical, simple-to-use computational framework implementing this concept. Our algorithms have super resolution that evades the Rayleigh criterion, as well as provision for statistical weighting and tapering. They can be used for essentially any time series (e.g., time-tagged events or point measurements) with arbitrary sampling—even or uneven. Examples of super resolution of synthetic data, sunspot numbers, and the rich pulsations of white dwarf J0135+5722 demonstrate practical applications. Appendices derive generalized periodograms using an arbitrary number of arbitrary basis functions and define several examples of nonsinusoidal bases for these omnigrams . Application beyond the frequency domain is demonstrated with an autoregressive model exhibiting super resolution in the time domain. A GitHub repository contains omnigram code and symbolic algebra scripts for generating it.
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Scargle et al. (2026) studied this question.
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