The 247th meeting of the American Astronomical Society #AAS247 is underway, coming with 8 press conferences - https://aas.org/meetings/aas247/press-kit#briefings - streaming on https://www.youtube.com/@AASPressOffice. There were already two yesterday:
https://www.youtube.com/watch?v=2gAjRP1xLtQ about Galaxies Big and Small, covering e.g. https://public.nrao.edu/news/hidden-giants-of-the-early-universe/ / https://news.ucmerced.edu/news/2026/astronomers-reveal-hidden-activity-early-universe’s-most-massive-galaxies / https://keckobservatory.org/aas247-magaz3ne/ and https://iopscience.iop.org/article/10.3847/2041-8213/ae1584 (The First RELHIC? Cloud-9 is a Starless Gas Cloud) -> https://science.nasa.gov/missions/hubble/nasas-hubble-examines-cloud-9-first-of-new-type-of-object/ / https://www.esa.int/Science_Exploration/Space_Science/Cloud-9_a_new_celestial_object_found_by_Hubble / https://public.nrao.edu/news/starless-dark-matter-failed-galaxy-near-m94/.
And https://www.youtube.com/watch?v=xvpDVq-7h6E about Stars and Their Behavior, covering e.g. https://arxiv.org/abs/2601.00470 (Betelgeuse: Detection of the Expanding Wake of the Companion Star) -> https://www.cfa.harvard.edu/news/cfa-scientists-detect-wake-betelgeuses-elusive-companion-star / https://science.nasa.gov/missions/hubble/nasa-hubble-helps-detect-wake-of-betelgeuses-elusive-companion-star/ and https://aas.org/sites/default/files/2026-01/Steven and Tyler AAS Press Release.pdf and https://public.nrao.edu/news/alma-devours-cosmic-hamburger-reveals-potential-for-giant-planet-formation/
Alexander Venner,
currently studying at the Max Planck Institute for Astronomy,
picked his way by hand through the data collected by a now-retired NASA space-based telescope called Kepler,
which was used to examine the sky for exoplanets during a survey of 500,000 stars that ended 8 years ago.
Datasets like these are huge, and often combed through with search algorithms,
but the PhD student managed what others did not by rolling up his sleeves, so to speak.
Ich würde es mir anschauen, das Rhinozeros im Raum von Itamar Gov in #Magdeburg
Ist leider nur ein bisschen weit weg.
https://www.itamargov.com/projects/the-rhi
I explained something for a friend in a simple way, and I think it's worth paraphrasing again here.
You cannot create a system that constrains itself. Any constraint on a system must be external to the system, or that constraint can be ignored or removed. That's just how systems work. Every constitution for every country claims to do this impossible thing, a thing proven is impossible almost 100 years ago now. Gödel's loophole has been known to exist since 1947.
Every constitution in the world, every "separation of powers" and set of "checks and balances," attempts to do something which is categorically impossible. Every government is always, at best, a few steps away from authoritarianism. From this, we would then expect that governments trand towards authoritarianism. Which, of course, is what we see historically.
Constraints on power are a formality, because no real controls can possibly exist. So then democratic processes become sort of collective classifiers that try to select only people who won't plunge the country into a dictatorship. Again, because this claim of restrictions on powers is a lie (willful or ignorant, a lie reguardless) that classifier has to be correct 100% of the time (even assuming a best case scenario). That's statistically unlikely.
So as long as you have a system of concentrated power, you will have the worst people attracted to it, and you will inevitably have that power fall into the hands of one of the worst possible person.
Fortunately, there is an alternative. The alternative is to not centralize power. In the security world we try to design systems that assume compromise and minimize impact, rather than just assuming that we will be right 100% of the time. If you build systems that maximially distribute power, then you minimize the impact of one horrible person.
Now, I didn't mention this because we're both already under enough stress, but...
Almost 90% of the nuclear weapons deployed around the world are in the hands of ghoulish dictators. Only two of the countries with nuclear weapons not straight up authoritarian, but they're not far off. We're one crashout away from steralizing the surface of the Earth with nuclear hellfire. Maybe countries shouldn't exist, and *definitely* multiple thousands of nuclear weapons shouldn't exist and shouldn't all be wired together to launch as soon as one of these assholes goes a bit too far sideways.
Past and Sapiens 🉐
过去和智人 🉐
📷 Nikon F4E
🎞️ ERA 100, expired 1993
#filmphotography #Photography #blackandwhite
From an unusual Air Force One tour with Donald Trump
to an explanation of how that photo with his now ex-wife Kimberly Guilfoyle came to be,
here is a collection of the standout moments in “Young Man in a Hurry,” which will come out later this month:
https:…
Genus-0 Surface Parameterization using Spherical Beltrami Differentials
Zhehao Xu, Lok Ming Lui
https://arxiv.org/abs/2602.01589 https://arxiv.org/pdf/2602.01589 https://arxiv.org/html/2602.01589
arXiv:2602.01589v1 Announce Type: new
Abstract: Spherical surface parameterization is a fundamental tool in geometry processing and imaging science. For a genus-0 closed surface, many efficient algorithms can map the surface to the sphere; consequently, a broad class of task-driven genus-0 mapping problems can be reduced to constructing a high-quality spherical self-map. However, existing approaches often face a trade-off between satisfying task objectives (e.g., landmark or feature alignment), maintaining bijectivity, and controlling geometric distortion. We introduce the Spherical Beltrami Differential (SBD), a two-chart representation of quasiconformal self-maps of the sphere, and establish its correspondence with spherical homeomorphisms up to conformal automorphisms. Building on the Spectral Beltrami Network (SBN), we propose a neural optimization framework BOOST that optimizes two Beltrami fields on hemispherical stereographic charts and enforces global consistency through explicit seam-aware constraints. Experiments on large-deformation landmark matching and intensity-based spherical registration demonstrate the effectiveness of our proposed framework. We further apply the method to brain cortical surface registration, aligning sulcal landmarks and jointly matching cortical sulci depth maps, showing improved task fidelity with controlled distortion and robust bijective behavior.
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