Calypso is a parameter-conditioned stochastic surrogate model for circumbinary accretion flows using PCA and multivariate Gaussian modeling, released as open-source software with a closed-form likelihood for parameter inference from time series.
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A simulation-based procedure for cluster strong lensing that remaps uniform boxes and traces rays through resolved particles, finding uncorrelated line-of-sight structure shifts images by arcseconds and changes critical areas by 16+20-14 percent at zs=4.
Resolved HI observations of six baryon-dominated dwarf galaxy candidates show four are dark-matter deficient with high baryon efficiency, two in isolated environments without tidal signs.
SHAMe-SF modeling of small-scale DESI ELG clustering delivers 6% precision on σ8 and Ωm h², matching full DR1 results with 1% volume.
Bursty stellar feedback produces systematically flatter metallicity gradients than smooth feedback in high-redshift galaxies across multiple simulation suites.
TNG50 shows galactic outflow mass loading is non-monotonic with stellar mass, rising rapidly above 10^10.5 Msun due to black hole feedback, and produces fast multi-phase outflows with emergent collimation.
KMeans clustering of star-formation histories for 6051 LAEs in IllustrisTNG100 at z=2 yields four classes, with 35% showing the typical recent-burst profile and 65% having bursts 0.3-1.3 Gyr earlier.
A large collaboration compiles and compares merger rate predictions for massive black holes across multiple galaxy formation models to forecast LISA detections and quantify uncertainties.
A conditional graph neural network serves as an accurate and fast surrogate for semi-analytic galaxy formation models, predicting key properties across cosmic time.
COLIBRE simulations find kinematic galaxy morphology peaks in rotational support at stellar masses of 1-2 x 10^10 solar masses and correlates more with internal properties like gas richness than with host halo properties.
New CAMELS simulations in larger (50 Mpc/h)^3 boxes with 35 varied parameters produce tighter neural-network constraints on model parameters than prior smaller-volume runs, with public data release.
citing papers explorer
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\texttt{calypso}: a Parameter-Conditioned Stochastic Surrogate Model for Circumbinary Accretion Time-Series
Calypso is a parameter-conditioned stochastic surrogate model for circumbinary accretion flows using PCA and multivariate Gaussian modeling, released as open-source software with a closed-form likelihood for parameter inference from time series.
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A Consistent Implementation of Cluster Strong Lensing in Cosmological Simulation Light Cones
A simulation-based procedure for cluster strong lensing that remaps uniform boxes and traces rays through resolved particles, finding uncorrelated line-of-sight structure shifts images by arcseconds and changes critical areas by 16+20-14 percent at zs=4.
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HI Observations of Baryon-Dominated Dwarf Galaxy Candidates
Resolved HI observations of six baryon-dominated dwarf galaxy candidates show four are dark-matter deficient with high baryon efficiency, two in isolated environments without tidal signs.
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Cosmological constraints from the small scale clustering of Emission Line Galaxies
SHAMe-SF modeling of small-scale DESI ELG clustering delivers 6% precision on σ8 and Ωm h², matching full DR1 results with 1% volume.
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The new era of Lyman alpha emitters (LAEs): Typical star formation histories of LAEs in the ILLUSTRIS simulation
KMeans clustering of star-formation histories for 6051 LAEs in IllustrisTNG100 at z=2 yields four classes, with 35% showing the typical recent-burst profile and 65% having bursts 0.3-1.3 Gyr earlier.
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The LISA Astrophysics MBHcatalogues Project: A comparison of predictions of simulated massive black hole binaries
A large collaboration compiles and compares merger rate predictions for massive black holes across multiple galaxy formation models to forecast LISA detections and quantify uncertainties.
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A graph-based Neural Network surrogate model for accelerating semi-analytical model of galaxy formation and evolution
A conditional graph neural network serves as an accurate and fast surrogate for semi-analytic galaxy formation models, predicting key properties across cosmic time.
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The morphologies of present-day galaxies in the COLIBRE simulations
COLIBRE simulations find kinematic galaxy morphology peaks in rotational support at stellar masses of 1-2 x 10^10 solar masses and correlates more with internal properties like gas richness than with host halo properties.
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Learning the Universe with the 2nd Generation of CAMELS: Varying 35 parameters of the IllustrisTNG model in (50Mpc/h)^3 boxes
New CAMELS simulations in larger (50 Mpc/h)^3 boxes with 35 varied parameters produce tighter neural-network constraints on model parameters than prior smaller-volume runs, with public data release.