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This kind of observation is a big deal for solar physics.

It's been believed for decades that these small-scale (~100km and below) turbulent features are critical to understanding how energy dissipates in the Sun. And thus, how sunspots and flares form.

The subject has been very qualitative but is yielding on both observational and simulation fronts. I worked adjacent to this area from the 1990s-2010s, and it had been true that MHD numerical simulations of significant volumes of the Sun (but at a scale fine enough to resolve these features) were not possible. That has obviously changed!

Additionally, it had been that the best solar observatories could not quite resolve these features. In the late 1990s some of the best images came from a couple of observatories in the Canary Islands (e.g., the 1-meter Swedish telescope -- https://svs.gsfc.nasa.gov/4715/). The spatial resolution was perhaps in the ~100km range.

Of course, these are absolutely mind-boggling images. You're looking at a slice of the solar photosphere that has a temperature such that it activates a spectral line around 400nm. By isolating that wavelength, we can see what's happening at that temperature, and thus, sample a slice of the photosphere.

So, that had been the state of affairs. Now DKIST (4m aperture), with the particular instrument highlighted in OP, appears to be at a spatial resolution ~5x finer than the above imagery -- see Fig. 1c in the Nature paper (https://www.nature.com/articles/s41586-026-10871-3). It appears also (https://dkist.virtualsolar.org/vanNoortfastcam/) to be observing at 740Hz (!) for speckle reconstructions at ~1Hz.

At this scale, vortices of the flow are well-resolved -- where before you just resolved the convective cells but not the turbulent features around them. It's these turbulent features that are transporting energy.

To contextualize with respect to a HN perennial topic: DKIST (commissioned 2021) is funded by NSF, from the same pile of money that once funded Arecibo (up to 2020).



Thanks a lot for sharing your experience with us.

I worked adjacent to this area from the 1990s-2010s when the topic is solar physics is definitely why this forum is one of the last "places" of the internet.


Sure thing.

Remote sensing of the Sun is different from anything else, because you have so many photons. The idea of binning it down so fine (20x20km, 740Hz, a single nm of spectrum around a band center) is unheard of for any other target.


It was a great comment, HN still offers nuggets now and then


Silly question but how does a 4m aperture focused onto a smaller area not concentrate the heat and melt the instruments?


It's highly filtered, you are only getting a small slice of all of the wavelengths. Only a tiny fraction of all that energy hits the photo collector. I believe the collector is also actively cooled, but I might be wrong there.


Yes, just 0.5nm of spectrum in the instrument used (https://dkist.virtualsolar.org/vanNoortfastcam/, see under “DataSetDescriptions.pdf”).

If the pixels really are 20x20km, located at 1AU, I get 500k photons (within that bandpass) per pixel per frame at 740 Hz, not counting optical losses.

Space solar instruments like HMI on SDO (https://science.nasa.gov/mission/sdo/) have one or more pre-filters in front of the instrument to block some light far from the passband and keep heating under control. I’m not sure if DKIST has such filters.


740hz is the frame rate you’re capturing at?


Not “me,” but yes, that’s the rate quoted in the document I linked about the instrument that captured the images in OP.


This is not just about the Sun. As we progress towards developing nuclear fusion reactors, a better understanding of the underlying physics may have practical implications for reactor design and could even reveal factors currently being overlooked. At the very least, it will improve modelling. Better models could help fusion reactors retain heat for longer and increase fusion gain (Q), while reducing uncertainty, improving plasma-edge control, and predicting divertor heat loads more accurately.


> The subject has been very qualitative

What does this mean?


People were identifying gross features (like the convection cells in the first website I linked), and giving those features names. Like “sunspots”, “faculae”, “pores”, “granulation”, “bright points”, etc. That’s on the observational side.

I’m less informed about simulations in this era - perhaps some simplified MHD simulations had been more quantitative in linking equations of state to the emergence of these features - but I believe they were not realistic enough to provide definite constraints on the scale of the structures.

It was clear that these features had to do with energy transport and some of the mechanisms were hypothesized. But the spatial scale of the gross energy transfer in these convective cells was not known, either through simulations or observation.


"Qualitative" means that the field had good conceptual theories, but didn't have sufficient observational and computational resolution to determine the detailed numerical values


Well put. And to round out the nomenclature for those that are curious, the corollary here is that it can now become much more quantitative.


quality vs quantity

seeing something new vs observing same stuff many many times to do statistics


Interesting that you use the phrase "quality vs quantity". Normally, I think of precision being on the side of "quality". As in, you carefully make a thing to meet a certain standard instead of making a lot of them.

In the case of "qualitative vs quantitative", despite having the same roots, I think of precision being on the side of the quantitative --with qualitative work answering yes/no questions and quantitative yielding precise measurements.


Yes, the latter is what is implied. "Quality" has more than one meaning, and "observed characteristic" is what is meant, not "goodness".




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