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Reposted by Shashank Dholakia

Sabina Sagynbayeva @sabinastro.bsky.social · 5d

Okay people, welcome my new paper into the world!!! With Isabel Colman and @farrwill.bsky.social

arxiv.org/abs/2510.02255

Rotation Periods for Stars in Open Cluster NGC 6819 From Kepler IRIS Light Curves

We present an updated catalog of stellar rotation periods for the 2.5 Gyr open cluster NGC 6819 using the Kepler IRIS light curves from superstamp data. Our analysis uses Gaussian Process modeling to ...

arxiv.org

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Shashank Dholakia @astroshashank.bsky.social · 2d

Yeah, it was labor intensive for sure. 15 mins for each video plus >100gb, but I'm a grad student so I've got time 😆

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Shashank Dholakia @astroshashank.bsky.social · 2d

It's all hand-tracked! I aligned the long axis of the camera in the direction of the drift and would recenter it every few seconds.

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Shashank Dholakia @astroshashank.bsky.social · 2d

And as a bonus, here's a false-color composite of the same. Blue is mapped to all of visible, green is infrared beyond 850nm, and red is the methane band at 889nm.

🔭 #astrophotography #saturn

An azure planet on a stark black background with neon orange-pink rings seen nearly edge-on.

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Shashank Dholakia @astroshashank.bsky.social · 2d

Been imaging Saturn while its rings are nearly edge-on and tried some infrared filters. At this 889nm methane band, Saturn strongly absorbs light, whereas its rings scatter equally across wavelengths.

Also a good visual demo of how astronomers measure exoplanet atmospheres!

🔭🧪 #astrophotography

Three images of Saturn from top to bottom: First, a standard RGB color image showing the rings nearly edge-on at about a 30 degree angle. Middle, a black and white image similar to above, but a little sharper taken with a filter that allows only wavelengths longer than 850nm. Lastly, at bottom, the rings seen as starkly white and the planet dark. This is a very narrow wavelength range of about 20nm centered on 889nm where methane absorbs light, making Saturn itself appear dark and the rings bright.

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Reposted by Shashank Dholakia

Kevin J. CREATURE @kevinjkircher.com · 4d

Sometimes I think about how from 1935-1975ish, Bell Labs produced an insane amount of revolutionary science and technology, including 11 Nobel Prizes, the transistor, UNIX, C, the laser, the solar cell, information theory, etc. The secret? Provide scientists with ample, steady, no-strings funding.

sites.stat.columbia.edu

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Reposted by Shashank Dholakia

Kevin J. CREATURE @kevinjkircher.com · 4d

Research also shows that spreading smaller amounts of funding out over more researchers generally delivers better scientific outcomes per dollar spent than focusing bigger grants on fewer researchers.

journals.plos.org/plosone/arti...

Big Science vs. Little Science: How Scientific Impact Scales with Funding

Agencies that fund scientific research must choose: is it more effective to give large grants to a few elite researchers, or small grants to many researchers? Large grants would be more effective only...

journals.plos.org

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Reposted by Shashank Dholakia

Mychal Threets @mychal3ts.bsky.social · 7d

There have been two hosts in the history of Reading Rainbow. The Legend of Literacy, LeVar Burton! And... me, Mychal Threets, a librarian 🥹🤯

I am a reader, a librarian because LeVar Burton and Reading Rainbow made us believe and see we belong in books, we belong everywhere ✨

youtu.be/e7es7qdWVnU

Smiling Mychal with hands raised wears an outer space shirt in a library. It is a still from an episode of Reading Rainbow.

LeVar Burton smiles with hands behind his head as he lies down on a colorful pile of books. ENEMY PIE book rests on his chest.

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Reposted by Shashank Dholakia

Abode Press @abodepress.bsky.social · 7d

Happy Pub Day to Earth and Earth-like Planets by Devaki D. Devi 🥳

Earth and Earth-like Planets is officially out for publication! 🧡 All pre-orders will be shipped as soon as possible.📦 If you haven't ordered your copy yet, you can purchase one here: www.abodepress.com/product-page...

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Shashank Dholakia @astroshashank.bsky.social · 7d

FFTs are pretty hard to beat in speed but restricting to the surface of a sphere and the analytic solution certainly helps! The goal is to do HMC on the surface map coefficients

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Shashank Dholakia @astroshashank.bsky.social · 7d

I believe @astromonnier.bsky.social has work on interferometrically detecting hot Jupiters from closure phases, maybe he'd have more to add about this

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Shashank Dholakia @astroshashank.bsky.social · 7d

🫩

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Shashank Dholakia @astroshashank.bsky.social · 7d

Need to take into account a few things like rotational and tidal deformation and stellar companions to do this well, but it's absolutely in the works!

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Reposted by Shashank Dholakia

Benjamin Pope @benjaminpope.bsky.social · 7d

This work owes a lot to ideas of and conversations with Rodrigo Luger, Keaton Burns, Geoff Vasil, and Ben Roberts, and it's been a really fun project with Shashank!

... and Shashank is on the postdoc market now, so if you're working on stars and planets, Jax, imaging science and applied maths...

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Shashank Dholakia @astroshashank.bsky.social · 7d

Thanks so much Will!!

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Shashank Dholakia @astroshashank.bsky.social · 7d

Thanks so much Brett!

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Shashank Dholakia @astroshashank.bsky.social · 7d

When you say you're going to work with spherical harmonics they make you sign an agreement to only use the plasma colormap

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Shashank Dholakia @astroshashank.bsky.social · 8d

Reposting for the #astro feed! 🔭

Shashank Dholakia @astroshashank.bsky.social · 8d

New paper by me and @benjaminpope.bsky.social! How well can we map a star using optical interferometry?

This is just a submitted preprint at the moment--comments and questions welcome! (1/N)

arxiv.org/abs/2509.25433

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Shashank Dholakia @astroshashank.bsky.social · 8d

However, we find that future, more densely spaced air Cherenkov arrays such as CTA might well be able to map stellar surfaces, especially for hot, blue chemically peculiar stars!

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Shashank Dholakia @astroshashank.bsky.social · 8d

Even with simultaneous photometry and regularizing assumptions, we can't map stars with current intensity interferometers. But bc intensity interferometers operate like radio interferometers and don't involve physically combining the light, it's possible to build them more densely (14/N)

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Shashank Dholakia @astroshashank.bsky.social · 8d

Lastly, we repeated this experiment for a technique called intensity interferometry, which has recently seen a revival from air Cherenkov telescopes, which during moonlit nights can be repurposed as interferometers. Pictured here is the VERITAS Array (13/N)

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Shashank Dholakia @astroshashank.bsky.social · 8d

Interferometry does pretty well at resolving small-scale details for nearby stars. But we found that it actually lacks a lot of information about broad-scale features (low degree modes). It turns out if we get simultaneous photometry as a star rotates, it resolves these really well! (12/N)

4 different 2d graphs where brighter colors represent higher Fisher information. At top left are the broader-scale details (low spherical harmonic degrees) and towards the bottom right are finer details (high spherical harmonic degrees). Top left image is for just visibility amplitudes from interferometry, top right is for just closure phases, bottom left is with a rotational light curve, and bottom left is combining all these observations together. Each of the observations adds a complementary set of information

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Shashank Dholakia @astroshashank.bsky.social · 8d

As we increase the angular diameter of our hypothetical SPOT star, we can see the small-scale details (higher-degree spherical harmonics on its surface, in yellow) come into view. But is this information complete? (11/N)

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Shashank Dholakia @astroshashank.bsky.social · 8d

But we can go further: we really want to know how much it's possible to know about a star from interferometry and how much information is lost. To quantify information, we use something called Fisher information, which loosely tells us how many bits of information we get on the star's map (10/N)

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Shashank Dholakia @astroshashank.bsky.social · 8d

How well can we map its surface without making any assumptions (often called regularization in the field of image reconstruction)? We inject different levels of noise into our simulated data and optimize to find the best-fitting map. At high signal-to-noise we basically recover a perfect map! (9/N)

7 different star maps, at top the "true" map showing the word SPOT written in caps on the northern hemisphere. Each subsequent map is recovered from noisy data, starting with the first, where the word is nearly illegible, to the last, where it's perfectly clear.

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