43 research outputs found
The Nature of Emission-Line Galaxies in Hierarchical Cosmologies
We use a galaxy formation model to study the nature and evolution of emission line
galaxies. In particular, we focus on the properties of Ly-alpha and H-alpha emitters,
due to their many cosmological applications being considered for current and future
observational studies.
By combining a semianalytical model with a large N-body simulation we predict the
clustering of Ly-alpha emitters. With increasing redshift, Ly-alpha emitters are found to trace
progressively rarer, higher density regions of the Universe. We measure the clustering of Ly-alpha emitters by constructing mock catalogues
of surveys finding a good agreement between the model and the observational measurements. Furthermore, we use
the mock catalogues to study the sample variance of current and
forthcoming Ly-alpha surveys. Current surveys should be extended significantly in
solid angle to allow a robust measurement of the clustering of Ly-alpha emitters, particularly
at z>8.
On the other hand, future space-based galaxy surveys will map the galaxy distribution using H-alpha emitters or H-band selected galaxies
at 0.5<z<2 to constrain the nature of the dark energy by measuring the large-scale structure of the
Universe.
Therefore, we investigate the abundance and clustering of galaxies found using these two selections. H-alpha emitters
are found to avoid massive dark matter haloes, whereas
H-band selected galaxies are found in the highest mass haloes. By using mock catalogues, we predict the
effectiveness of measuring the large scale structure of the Universe for a range of survey configurations using
both galaxy selections.
Finally, we study the escape of Ly-alpha photons from galaxies using a Monte Carlo
radiative transfer code. We simulate galactic outflows in a
semianalytical model to study the physical properties of Ly-alpha emitters in a cosmological context.
We find that the escape fraction of Ly-alpha emitters can vary greatly depending on the properties of the galaxies, although
our results depend on the outflow model used. Our results suggest the need to consider additional physical effects to
understand the observed properties of Ly-alpha emitters
An AI-enabled Agent-Based Model and Its Application in Measles Outbreak Simulation for New Zealand
Agent Based Models (ABMs) have emerged as a powerful tool for investigating
complex social interactions, particularly in the context of public health and
infectious disease investigation. In an effort to enhance the conventional ABM,
enabling automated model calibration and reducing the computational resources
needed for scaling up the model, we have developed a tensorized and
differentiable agent-based model by coupling Graph Neural Network (GNN) and
Long Short-Term Memory (LSTM) network. The model was employed to investigate
the 2019 measles outbreak occurred in New Zealand, demonstrating a promising
ability to accurately simulate the outbreak dynamics, particularly during the
peak period of repeated cases. This paper shows that by leveraging the latest
Artificial Intelligence (AI) technology and the capabilities of traditional
ABMs, we gain deeper insights into the dynamics of infectious disease
outbreaks. This, in turn, helps us make more informed decision when developing
effective strategies that strike a balance between managing outbreaks and
minimizing disruptions to everyday life.Comment: 11 pages, 9 figure
The nebular emission of star-forming galaxies in a hierarchical universe
Galaxy surveys targeting emission lines are characterizing the evolution of star-forming galaxies, but there is still little theoretical progress in modelling their physical properties. We predict nebular emission from star-forming galaxies within a cosmological galaxy formation model. Emission lines are computed by combining the semi-analytical model SAG with the photoionization code MAPPINGS-III. We characterize the interstellar medium of galaxies by relating the ionization parameter of gas in galaxies to their cold gas metallicity, obtaining a reasonable agreement with the observed Hα, [O II] λ 3727, [O III] λ 5007 luminosity functions, and the BPT diagram for local star-forming galaxies. The average ionization parameter is found to increase towards low star formation rates and high redshifts, consistent with recent observational results. The predicted link between different emission lines and their associated star formation rates is studied by presenting scaling relations to relate them. Our model predicts that emission-line galaxies have modest clustering bias, and thus reside in dark matter haloes of masses below Mhalo ≲ 1012 [h−1 M⊙]. Finally, we exploit our modelling technique to predict galaxy number counts up to z ∼ 10 by targeting far-infrared emission lines detectable with submillimetre facilities.Fil: Orsi, Alvaro. Pontificia Universidad Católica de Chile; ChileFil: Padilla, Nelson David. Pontificia Universidad Católica de Chile; ChileFil: Groves, Brent. Max Planck Institute For Astronomy;Fil: Cora, Sofia Alejandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica la Plata; ArgentinaFil: Tecce, Tomas Enrique. Pontificia Universidad Católica de Chile; ChileFil: Gargiulo, Ignacio Daniel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Astrofísica La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Astronómicas y Geofísicas. Instituto de Astrofísica la Plata; ArgentinaFil: Ruiz, Andrés Nicolás. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Astronomia Teórica y Experimental. Universidad Nacional de Córdoba. Observatorio Astronómico de Córdoba. Instituto de Astronomia Teórica y Experimental; Argentin