CAMELS project

The Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project.

[CAMELS project @camels_project]

For details, check out the paper and the documentation https://t.co/WsK7DXo2FW

[CAMELS project @camels_project]

The newest ‘hump’ of the CAMELS project is live! We present and make publicly available 768 hydrodynamical zoomed-in simulations of massive halos varying 5 cosmological parameters and 23 astrophysical parameters within the IllustrisTNG model. Check out https://t.co/MxBiGC2fXL

[CAMELS project @camels_project]

to see how they were made, utilizing our new CARPoolGP method and by running base+surrogate simulations. All data from CAMELS-zoomGZ can be accessed via Globus or Binder at @FlatironInst. Work led by Max Lee at Columbia!

[natalidesanti @natalidesanti]

Paper day: https://t.co/yZjp1g68yL. We are measuring the impact of systematics training GNNs to perform field-level simulation-based inference with galaxy catalogs from @camels_project. We do not have and cut on scale and the models are robust. First steps before using real data!

[Ben Oppenheimer 🇺🇦 @nonstopbenopp]

Here's something exciting about what the @camels_project can do for low-redshift filament science in the near future.

[JFK Whitlam @JfkWhitlam]

@camels_project @NASAWebb @CdSportal @DanielPomarede @NASAHubble @chandraxray @VRubinObs @NASARoman @almaobs @ehtelescope @AlyssaAGoodman @theDESurvey @satellitegalaxy @LIGO @NANOGrav @iaa_coin @galaxy_map @CosmoStatLab @ACT_Pol @NOIRLabAstro @WhatDaMath @allen_ai @drbecky_ @fcain @DJSnM @david_kipping @CalgaryRASC @ESAGaia @ceers_jwst https://t.co/dEwKYdczVH

[CAMELS project @camels_project]

CAMELS is in the streets of New York City! 🗽🐫🐪🐫🐪🐫🗽

[LinkNYC @LinkNYC]

LinkNYC is out of this world!

[Francisco Villaescusa-Navarro @paco_astro]

The CAMELS project keeps growing. We have made publicly available 2,124 hydrodynamic simulations of CAMELS-ASTRID; a new suite run with the MP-Gadget code using the ASTRID subgrid physics model. All the data is accessible through globus and binder at @FlatironInst

[Jay Wadekar @JayWadekar1]

In our new PNAS paper, we use machine learning to discover novel equations for deriving masses of clusters of galaxies from observational quantities! (1/10)

https://t.co/WXARcecsX8

with @MilesCranmer @paco_astro@jcolinhill @DavidSpergel @cosmo_shirley,Leander,Nick,Daniel,Lars.

[natalidesanti @natalidesanti]

Paper day: https://t.co/4Zzdguexl5. We train GNNs to perform field-level likelihood-free inference using galaxy catalogs from @camels_project. Our models have no scale cutoff, achieved a precision of ~12% when inferring Ωm, and it is robust for 5 != subgrid models! Check it out!

[Francisco Villaescusa-Navarro @paco_astro]

Really proud of our latest paper: "Robust field-level inference with dark matter halos". We study the robustness of field-level inference to differences in N-body codes, hydrodynamics, and astrophysics using thousands of N-body and hydrodynamic simulations. We have developed a

[CAMELS project @camels_project]

Many thanks to Yueying Ni and all Astrid team for the amazing and hard work. CAMELS-Astrid contains more than 1,000 simulated Universes with different cosmologies and value of the astrophysics parameters. Check https://t.co/6m8cyT0797 for more details.

[CAMELS project @camels_project]

Feeling frustrated because CAMELS "only" contains 4,233 simulations? If so, we have good news; we have added 2,092 new simulations: 1) 1,092 state-of-the-art hydrodynamic simulations run with MP-Gadget using the Astrid subgrid model and 2) all their N-body counterparts.

[CAMELS project @camels_project]

The video shows the spatial distribution of gas density (blue) and gas temperature (red) as a function of time for three simulations run with the same initial conditions but different codes. The high-resolution video available in https://t.co/jtrOxWUpyy. Differences are striking!

[Pablo Villanueva Domingo @CosmoPabloVD]

Happy to announce a new paper with @paco_astro !

We apply deep learning methods to infer clustering and cosmological parameters on galaxy catalogues from CAMELS simulations @camels_project. (1/4)

https://t.co/Vkmdg8ljal

[The New Yorker @NewYorker]

What could information about one galaxy say about the universe in which it resided? New research may hold the answer.
https://t.co/dRPHutgCze

[Kaze Wong @physicskaze]

My visualization for @camels_project is featured in the #iamai video at @nvidia #GTC22 ! (~4 minutes in the stream)

[CAMELS project @camels_project]

Impressive!

[Alejandro Benítez-Llambay @bllalejandro]

More features for real-time rendering using #Python. Proud to show the use interactive keyframes to produce videos of simulations in just a few minutes. This feature opens up new opportunities for #science and #outreach. Thanks to @camels_project for data. https://t.co/pTNbTWTIwN

[CAMELS project @camels_project]

What is the relation between volcanos, climate, galaxies, and the cosmic microwave background? Leander Thiele tells us about it in a new CAMELS blog:
https://t.co/JfAscaiLnM. Check it out!

[CAMELS project @camels_project]

Check out our new post where Emily Moser explains how to use Sunyaev-Zeldovich observations of the circumgalactic medium to learn about galactic physics.
https://t.co/JfAscaiLnM