47 citations · 112 across the 20 of their papers we have counts for
10 papers · 1 filter
Evidence for renormalized instantons in real-time simulations of vacuum decay
Emilie Hertig, Alexander C. Jenkins, Hiranya V. Peiris +2
While vacuum decay is traditionally described by Euclidean instanton methods, lattice simulations enable real-time modeling of dynamical observables relevant to cosmology and upcom…
pop-cosmos: Disentangling galaxy properties from observables using data-driven approaches
Benedict Van den Bussche, Sinan Deger, Hiranya V. Peiris +6
The physical processes that shape a galaxy's spectrum are strongly degenerate in observations, obscuring which processes act independently. Leveraging the pop-cosmos generative gal…
pop-cosmos: Galaxy size evolution across structural and star-formation classifications in COSMOS-Web
Madalina N. Tudorache, Hiranya V. Peiris, Stephen Thorp +7
Galaxy sizes are correlated with stellar mass and redshift, as characterised by size scaling relations. The inferred forms of these scaling relations are sensitive to how galaxies…
Thermostats, Not Engines: A New Picture of Halo Gas Regulation
Hiranya V. Peiris, Andrew Pontzen, Madalina N. Tudorache +5
We propose that black hole feedback regulates gas in massive halos by establishing an entropy ceiling; the resulting buoyant gas migrates to the virial radius with no additional en…
StAD: Stein Amortized Divergence for Fast Likelihoods with Diffusion and Flow
Gurjeet Jagwani, Stephen Thorp, Sinan Deger +1
Diffusion and flow-based models are ubiquitously used for generative modelling and density estimation. They admit a deterministic probability flow ordinary differential equation (P…
The limits of feedback from active galactic nuclei
Andrew Pontzen, Hiranya V. Peiris, Joop Schaye +1
We use FLAMINGO to investigate why feedback from active galactic nuclei (AGN) significantly depletes gas in galaxy groups but is ineffective in clusters. We delineate three radial…
Large language models are not the problem
Hiranya V. Peiris
If a Large Language Model (LLM) can replicate your scientific contribution, the problem is not the LLM. What does it say about our field that so much of the anxiety about AI comes…
pop-cosmos: Forward modeling KiDS-1000 redshift distributions using realistic galaxy populations
Boris Leistedt, Hiranya V. Peiris, Anik Halder +13
The accuracy of the cosmological constraints from Stage~IV galaxy surveys will be limited by how well the galaxy redshift distributions can be inferred. We have addressed this chal…
pop-cosmos: Redshifts and physical properties of KiDS-1000 galaxies
Anik Halder, Hiranya V. Peiris, Stephen Thorp +8
Principled Bayesian inference of galaxy properties has not previously been performed for wide-area weak lensing surveys with millions of sources. We address this gap by applying th…
Opportunities in AI/ML for the Rubin LSST Dark Energy Science Collaboration
LSST Dark Energy Science Collaboration, Eric Aubourg, Camille Avestruz +63
The Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) will produce unprecedented volumes of heterogeneous astronomical data (images, catalogs, and alerts) that cha…