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Found 16 papers, 12 papers with code
Explaining dark matter halo density profiles with neural networks
We use explainable neural networks to connect the evolutionary history of dark matter halos with their density profiles.
A robust estimator of mutual information for deep learning interpretability
We develop the use of mutual information (MI), a well-established metric in information theory, to interpret the inner workings of deep learning models.
Discovering the building blocks of dark matter halo density profiles with neural networks
The additional dimension in the representation contains information about the infalling material in the outer profiles of dark matter halos, thus discovering the splashback boundary of halos without prior knowledge of the halos' dynamical history.
Angular momentum evolution can be predicted from cosmological initial conditions
However, the process by which dark matter haloes acquire angular momentum is not fully understood; in particular, it is unclear whether angular momentum growth is stochastic.
Cosmology and Nongalactic Astrophysics Astrophysics of Galaxies Instrumentation and Methods for Astrophysics
An emulator for the Lyman-$α$ forest in beyond-$Λ$CDM cosmologies
Our emulator is appropriate for cosmologies in which the linear matter power spectrum is described to percent level accuracy by just an amplitude and slope across the epoch of interest, and in the regime probed by eBOSS/DESI data.
Cosmology and Nongalactic Astrophysics
Deep learning insights into cosmological structure formation
We train a three-dimensional convolutional neural network (CNN) to predict the mass of dark matter halos from the initial conditions, and quantify in full generality the amounts of information in the isotropic and anisotropic aspects of the initial density field about final halo masses.
An interpretable machine learning framework for dark matter halo formation
The addition of tidal shear information does not yield an improved halo collapse model over one based on density information alone; the difference in their predictive performance is consistent with the statistical uncertainty of the density-only based model.
Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics
Bayesian emulator optimisation for cosmology: application to the Lyman-alpha forest
Starting with a Latin hypercube sampling (other schemes with good space-filling properties can be used), we iteratively augment the training set with extra simulations at new parameter positions which balance the need to reduce interpolation error while focussing on regions of high likelihood.
Cosmology and Nongalactic Astrophysics
Unbiased Hubble constant estimation from binary neutron star mergers
Gravitational wave (GW) observations of binary neutron star (BNS) mergers can be used to measure luminosity distances and hence, when coupled with estimates for the mergers' host redshifts, infer the Hubble constant, $H_0$.
Cosmology and Nongalactic Astrophysics
Inferring properties of the local white dwarf population in astrometric and photometric surveys
With such a large data set, it is possible to infer properties of the WD population using only astrometric and photometric information.
Solar and Stellar Astrophysics
Machine learning cosmological structure formation
We train a machine learning algorithm to learn cosmological structure formation from N-body simulations.
Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics
Prospects for resolving the Hubble constant tension with standard sirens
The Hubble constant ($H_0$) estimated from the local Cepheid-supernova (SN) distance ladder is in 3-$\sigma$ tension with the value extrapolated from cosmic microwave background (CMB) data assuming the standard cosmological model.
Cosmology and Nongalactic Astrophysics
Science-Driven Optimization of the LSST Observing Strategy
The Large Synoptic Survey Telescope is designed to provide an unprecedented optical imaging dataset that will support investigations of our Solar System, Galaxy and Universe, across half the sky and over ten years of repeated observation.
Instrumentation and Methods for Astrophysics Cosmology and Nongalactic Astrophysics Earth and Planetary Astrophysics Astrophysics of Galaxies Solar and Stellar Astrophysics
Hierarchical Bayesian inference of galaxy redshift distributions from photometric surveys
We illustrate this technique on simulated galaxy survey data, and demonstrate that it delivers correct posterior distributions on the underlying type and redshift distributions, as well as on the individual types and redshifts of galaxies.
Cosmology and Nongalactic Astrophysics
Directional spin wavelets on the sphere
We construct a directional spin wavelet framework on the sphere by generalising the scalar scale-discretised wavelet transform to signals of arbitrary spin.
Information Theory Instrumentation and Methods for Astrophysics Information Theory
Genetically modified halos: towards controlled experiments in $Λ$CDM galaxy formation
We propose a method to generate `genetically-modified' (GM) initial conditions for high-resolution simulations of galaxy formation in a cosmological context.
Astrophysics of Galaxies Cosmology and Nongalactic Astrophysics
