The issue here is one of data compression. On-line clock sync algorithms (like NTP) typically use a very simple piecewise linear mapping function, but update it very frequently, up to once per second. Phase is continuous, and steps in rate are small enough not to be a problem.
This is great if you only need to translate current (or very recent) timestamps, and don't care about the mapping function more than a minute ago. On the other hand, the most off-line clock sync algorithms, like those relating to UT2, use dozens of non-linear terms to enable a fit that lasts for years or decades. This makes the translation of any one timestamp much more difficult, but makes storing the mapping function much more difficult. It's a classic space/time tradeoff, like the difference between a formula and precomputed tables. The question to be decided here is, what sort of mapping function do you want? One possibility, and you must decide if this is acceptable, is to use a simple piecewise linear function in the short term, but then compress that with a higher-order fit for storage. This has the downside that the compression is lossy; the compressed mapping function will compute a different answer than the original piecewise linear one. But you can choose your compression implementation to bound that error. _______________________________________________ time-nuts mailing list -- [email protected] To unsubscribe, go to https://www.febo.com/cgi-bin/mailman/listinfo/time-nuts and follow the instructions there.
