Approximate Bayesian computation in large-scale structure: constraining the galaxy–halo connection

The Small and Large Magellanic Clouds (SMC, LMC) are of considerable interest from a kinematical viewpoint. The tidal interation of the Clouds with each other and with the Galaxy appears to have been quite significant in recent times (Murai & Fujimoto 1980). The SMC in particular appears to have been considerably disrupted by a recent close passage to the LMC (Mathewson & Ford 1984, Mathewson 1984, Mathewson et al. 1986). For the LMC Freeman et al. (1983) found that the young and old populations have significantly different rotation solutions.Planetary Nebulae (PN) form a population with age intermediate between the HI and young clusters and the old Population II clusters. A large number of PN are known in the MCs. Sanduleak et al. (1978) compiled a list of 102 in the LMC and 28 in the SMC. Since then other authors have increased the total number known to approximately 140 in the LMC and 50 in the SMC.

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Distribution of CO in the Southern Milky Way and large-scale structure in the Galaxy

Symposium - International Astronomical Union ◽

10.1017/s0074180900242435 ◽

1985 ◽

Vol 106 ◽

pp. 203-204

Author(s):

W.H. Mccutcheon ◽

B. J. Robinson ◽

R. N. Manchester ◽

J. B. Whiteoak

Keyword(s):

Large Scale ◽

Milky Way ◽

Galactic Plane ◽

Large Scale Structure ◽

Sampling Interval ◽

Scale Structure ◽

Plane Region ◽

The Galaxy ◽

Csiro Division

The southern galactic-plane region, in the ranges 294° ≤ 1 ≤ 358°, −0°.075 ≤ b ≤ 0°.075, has been surveyed in the J = 1–0 line of 12CO with a sampling interval of 3′ arc. Observations were made with the 4-metre telescope at the CSIRO Division of Radiophysics in 1980 and 1981. Details of equipment and observing procedure are given in Robinson et al. (1982, 1983); see also McCutcheon et al. (1983).

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The Local Large-Scale Structure from HIPASS

Symposium - International Astronomical Union ◽

10.1017/s0074180900196639 ◽

2005 ◽

Vol 216 ◽

pp. 196-202

Author(s):

Martin Zwaan ◽

Martin Meyer ◽

Rachel Webster ◽

Lister Staveley-Smith

Keyword(s):

Large Scale ◽

Large Scale Structure ◽

Scale Structure ◽

Sky Survey ◽

The Galaxy ◽

Point Correlation ◽

Point Correlation Function ◽

Fisher Relation ◽

Galaxy Population ◽

Mass Functions

The HI Parkes All Sky Survey (HIPASS) offers a unique perspective on the galaxy population in the local universe. A catalogue of 4315 HI-selected galaxies has been extracted from the southern region of the survey (δ < +2°). This catalogue gives a clear view of the local large-scale structure and is used to study the two-point correlation function, the Tully-Fisher relation, and galaxy luminosity and mass functions. Some initial results are discussed here.

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The Large-Scale Radio Continuum Structure of Spiral Galaxies

Symposium - International Astronomical Union ◽

10.1017/s0074180900143645 ◽

1978 ◽

Vol 77 ◽

pp. 33-48 ◽

Cited By ~ 1

Author(s):

P.C. van der Kruit

Keyword(s):

Large Scale ◽

Spiral Galaxies ◽

Large Scale Structure ◽

Scale Structure ◽

Optical Image ◽

Radio Continuum ◽

Continuum Emission ◽

The Galaxy ◽

Continuum Structure ◽

Disk Component

This review concerns the large-scale structure of radio continuum emission in spiral galaxies (“the smooth background”), by which we mean the distribution of radio surface brightness at scales larger than, say, 1 kpc. Accordingly the nuclear emission and structure due to spiral arms and HII regions will not be a major topic of discussion here. Already the first mappings of the galactic background suggested that there is indeed a distribution of radio continuum emission extending throughout the Galaxy. This conclusion has been reinforced by the earliest observations of M31 by showing that the general emission from this object extended over at least the whole optical image. More recently, van der Kruit (1973a, b, c) separated the radio emission from a sample of spiral galaxies observed at 1415 MHz with the Westerbork Synthesis Radio Telescope (WSRT) into a nuclear, spiral arm and “base disk” component, showing that the latter component usually contains most of the flux density. This latter component is largely non-thermal and extends over the whole optical image (see also van der Kruit and Allen, 1976). Clearly it is astrophysically interesting to discuss the large-scale structure of the radio continuum emission.

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A galaxy halo model of large-scale structure

Monthly Notices of the Royal Astronomical Society ◽

10.1111/j.1365-2966.2005.09309.x ◽

2005 ◽

Vol 362 (1) ◽

pp. 337-348 ◽

Cited By ~ 9

Author(s):

Mark C. Neyrinck ◽

Andrew J. S. Hamilton ◽

Nickolay Y. Gnedin

Keyword(s):

Large Scale ◽

Large Scale Structure ◽

Scale Structure ◽

Galaxy Halo

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Model Based Inference of Large Scale Brain Networks with Approximate Bayesian Computation

10.1101/785568 ◽

2019 ◽

Cited By ~ 1

Author(s):

Timothy O. West ◽

Luc Berthouze ◽

Simon F. Farmer ◽

Hayriye Cagnan ◽

Vladimir Litvak

Keyword(s):

Large Scale ◽

Approximate Bayesian Computation ◽

Model Comparison ◽

Brain Networks ◽

Face Validity ◽

Inverse Modelling ◽

Neural Dynamics ◽

Bayesian Computation ◽

Bayesian Model Comparison ◽

Approximate Bayesian

AbstractBrain networks and the neural dynamics that unfold upon them are of great interest across the many scales of systems neuroscience. The tools of inverse modelling provide a way of both constraining and selecting models of large scale brain networks from empirical data. Such models have the potential to yield broad theoretical insights in the understanding of the physiological processes behind the integration and segregation of activity in the brain. In order to make inverse modelling computationally tractable, simplifying model assumptions have often been adopted that appeal to steady-state approximations to neural dynamics and thus prevent the investigation of stochastic or intermittent dynamics such as gamma or beta burst activity. In this work we describe a framework that uses the Approximate Bayesian Computation (ABC) algorithm for the inversion of neural models that can flexibly represent any statistical feature of empirically recorded data and eschew the need to assume a locally linearized system. Further, we demonstrate how Bayesian model comparison can be applied to fitted models to enable the selection of competing hypotheses regarding the causes of neural data. This work establishes a validation of the procedures by testing for both the face validity (i.e. the ability to identify the original model that has generated the observed data) and predictive validity (i.e. the consistency of the parameter estimation across multiple realizations of the same data). From the validation and example applications presented here we conclude that the proposed framework provides a novel opportunity to researchers aiming to explain how complex brain dynamics emerge from neural circuits.

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The PAU survey: measurement of narrow-band galaxy properties with approximate bayesian computation

Journal of Cosmology and Astroparticle Physics ◽

10.1088/1475-7516/2021/12/013 ◽

2021 ◽

Vol 2021 (12) ◽

pp. 013

Author(s):

Luca Tortorelli ◽

Malgorzata Siudek ◽

Beatrice Moser ◽

Tomasz Kacprzak ◽

Pascale Berner ◽

...

Keyword(s):

Population Model ◽

Approximate Bayesian Computation ◽

Narrow Band ◽

Forward Model ◽

Accelerating Universe ◽

Bayesian Computation ◽

The Galaxy ◽

Spectral Coefficients ◽

Approximate Bayesian ◽

Galaxy Population

Abstract Narrow-band imaging surveys allow the study of the spectral characteristics of galaxies without the need of performing their spectroscopic follow-up. In this work, we forward-model the Physics of the Accelerating Universe Survey (PAUS) narrow-band data. The aim is to improve the constraints on the spectral coefficients used to create the galaxy spectral energy distributions (SED) of the galaxy population model in Tortorelli et al. 2020. In that work, the model parameters were inferred from the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) data using Approximate Bayesian Computation (ABC). This led to stringent constraints on the B-band galaxy luminosity function parameters, but left the spectral coefficients only broadly constrained. To address that, we perform an ABC inference using CFHTLS and PAUS data. This is the first time our approach combining forward-modelling and ABC is applied simultaneously to multiple datasets. We test the results of the ABC inference by comparing the narrow-band magnitudes of the observed and simulated galaxies using Principal Component Analysis, finding a very good agreement. Furthermore, we prove the scientific potential of the constrained galaxy population model to provide realistic stellar population properties by measuring them with the SED fitting code CIGALE. We use CFHTLS broad-band and PAUS narrow-band photometry for a flux-limited (i < 22.5) sample of galaxies up to redshift z ∼ 0.8. We find that properties like stellar masses, star-formation rates, mass-weighted stellar ages and metallicities are in agreement within errors between observations and simulations. Overall, this work shows the ability of our galaxy population model to correctly forward-model a complex dataset such as PAUS and the ability to reproduce the diversity of galaxy properties at the redshift range spanned by CFHTLS and PAUS.

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