Alejandro Benítez-Llambay

Nice to see our research featured by @NASA and @NASAHubble

py-sphviewer 2.0 is now live on GitHub. Rebuilt with a novel super fast algorithm. Native C++ multithreading. Native rotations and panning. Deferred Rendering, and more. Is it worth a try? Ask Grok 😉 Source, Intallation & Tutorials here: github.com/alejandrobll/p…

Astronomers confirm a major prediction of the big bang creation model where dark energy is the universe's dominant component & cold dark matter is the 2nd most abundant component. They found a starless massive gas cloud in M94's halo. The hydrogen gas in this cloud has a mass equal to a million Suns, has a 9,000 light-year diameter, & contains no luminous stars, implying that it is relic gas cloud left over from the cosmic creation event. You can read about the discovery here: iopscience.iop.org/article/10.384…

If you've ever wondered what Hubble and Webb were observing at any time? 👀 Space Telescope Live can show you what the telescopes are looking at now and what the next planned observation will be, all in one space (pun intended 😁): spacetelescopelive.org

I had a wonderful interview for Our Narratives, a platform dedicated to sharing original stories, artwork, and research. It was a pleasure to be part of this experience. You can read the interview here: ournarratives.net/cloud-9-the-fa…

Gracias a Alejandro Horvat y a @LANACION por esta nota científica sobre nuestro trabajo!

Another excellent write-up of our results via @SkyandTelescope. Arielle Frommer did a fantastic job summarizing the physics at play and properly contextualizing the alternative interpretations we explored.

@StartsWithABang has done his homework! The best coverages of our research I’ve read so far. To add to the story: our VLA observations following the FAST detection were crucial. They allowed us to truly pinpoint Cloud-9’s exact location to point Hubble right at it.

Scientists trained Hubble’s sharp vision on a starless, gas-rich, dark-matter cloud and identified a new type of astronomical object—a failed galaxy that never produced stars. Nicknamed Cloud-9, it is considered a fossil from the early universe: news.stsci.edu/4bdj2Ov #AAS247

NEW from #AAS247: NSF NRAO Radio Telescopes Help Reveal Cloud-9, a Starless Dark-Matter “Failed Galaxy” Near M94 public.nrao.edu/news/starless-… 📸 Credit: NASA, ESA, NSF VLA, Gagandeep Anand (STScI), Alejandro Benitez-Llambay (University of Milano-Bicocca), Joseph DePasquale (STScI)

Our new paper with @ximexram on a comoving framework for planet migration is on arXiv! Simulating planets moving through their disk is computationally expensive. Our new method solves this by keeping the planet fixed, making simulations over >10x faster!

From preprint to final publication! The journey for this review on planet-disk interaction is complete. The officially published version is now available online. I hope it serves as a useful resource for the community! Published version: doi.org/10.1016/B978-0…

Our new @NASAHubble observations of Cloud-9, an HI cloud near M94, find no galaxy with mass > 3,000 solar masses, making it the strongest candidate yet for a starless dark matter halo, long predicted, but never observed! Exciting! arxiv.org/abs/2508.20157

Gracias por divulgar ciencia y en particular nuestra investigación @doctorfision

@elonmusk Impressive. What are the faded gray models with very low cost per task and high score?

Grok 5 will be out before the end of this year and it will be crushingly good

Interested in helping find new Milky Way satellite galaxies? Join "DELVE Dwarf Galaxy Quest: Milky Way Neighbors" on Zooniverse to classify potential candidates! zooniverse.org/projects/ywyh/…

Aston Martin testing in Monza today. Will they deliver the top speed Alonso needs? #Formula1 #monza

University of Chicago: Possible Sign of Life in Deep Space Faces New Doubts news.uchicago.edu/story/possible…

This month’s Nature Astronomy cover features our recent paper led by Davide Tornotti, in which we image a filament connecting 2 QSOs. The cover was created in seconds using our new py-sphviewer 2.0 code, which renders N-body simulations with unprecedented spatial dynamic range.