Predicting the Number, Spatial Distribution, and Merging History of Dark Matter Halos

Monaco, Pierluigi; Theuns, Tom; Taffoni, Giuliano; Governato, Fabio; Quinn, Thomas; Stadel, Joachim

doi:10.1086/324182

Cited by 78 publications

(88 citation statements)

References 40 publications

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“…A similar problem is faced by the so-called semi analytical models (Monaco et al 2002;Somerville et al 2008). However parameter searches for SAM are computationally cheaper and can be performed using different statistical approaches such as emulation (Bower et al 2010), Monte Carlo Markov Chain (MCMC) (Benson 2014) or Particle Swarm Optimization (Ruiz et al 2015).…”

Section: Appendix A: Quantitative Parameter Search For Sf and Smbhs Pmentioning

confidence: 94%

The Romulus cosmological simulations: a physical approach to the formation, dynamics and accretion models of SMBHs

Tremmel

Karcher

Governato

et al. 2017

Monthly Notices of the Royal Astronomical Society

284

316

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We present a novel implementation of supermassive black hole (SMBH) formation, dynamics, and accretion in the massively parallel tree+SPH code, ChaNGa. This approach improves the modeling of SMBHs in fully cosmological simulations, allowing for a more detailed analysis of SMBH-galaxy co-evolution throughout cosmic time. Our scheme includes novel, physically motivated models for SMBH formation, dynamics and sinking timescales within galaxies, and SMBH accretion of rotationally supported gas. The sub-grid parameters that regulate star formation (SF) and feedback from SMBHs and SNe are optimized against a comprehensive set of z = 0 galaxy scaling relations using a novel, multi-dimensional parameter search. We have incorporated our new SMBH implementation and parameter optimization into a new set of high resolution, large-scale cosmological simulations called Romulus. We present initial results from our flagship simulation, Romulus25, showing that our SMBH model results in SF efficiency, SMBH masses, and global SF and SMBH accretion histories at high redshift that are consistent with observations. We discuss the importance of SMBH physics in shaping the evolution of massive galaxies and show how SMBH feedback is much more effective at regulating star formation compared to SNe feedback in this regime. Further, we show how each aspect of our SMBH model impacts this evolution compared to more common approaches. Finally, we present a science application of this scheme studying the properties and time evolution of an example dual AGN system, highlighting how our approach allows simulations to better study galaxy interactions and SMBH mergers in the context of galaxy-BH co-evolution.

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Section: Appendix A: Quantitative Parameter Search For Sf and Smbhs Pmentioning

confidence: 94%

The Romulus cosmological simulations: a physical approach to the formation, dynamics and accretion models of SMBHs

Tremmel

Karcher

Governato

et al. 2017

Monthly Notices of the Royal Astronomical Society

284

316

View full text Add to dashboard Cite

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“…We also note that our halo finder is similar in spirit to the PTHalos algorithm introduced by Scoccimarro & Sheth (2002) to generate mock galaxy surveys at low redshifts and to the PINOCCHIO algorithm of Monaco et al (2002bMonaco et al ( , 2002a. There are two key differences.…”

Section: Halo Filteringmentioning

confidence: 99%

Efficient Simulations of Early Structure Formation and Reionization

Mesinger

Furlanetto

2007

ApJ

462

643

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Detailed theoretical studies of the high-redshift universe, and especially reionization, are generally forced to rely on time-consuming N-body codes and/or radiative transfer algorithms. We present a method to construct seminumerical ''simulations,'' which can efficiently generate realizations of halo distributions and ionization maps at high redshifts. Our procedure combines an excursion-set approach with first-order Lagrangian perturbation theory and operates directly on the linear density and velocity fields. As such, the achievable dynamic range with our algorithm surpasses the current practical limit of N-body codes by orders of magnitude. This is particularly significant in studies of reionization, where the dynamic range is the principal limiting factor, because ionized regions reach scales of tens of comoving Mpc. We test our halo-finding and ionization-mapping algorithms separately against N-body simulations with radiative transfer and obtain excellent agreement. We compute the size distributions of ionized and neutral regions in our maps. We find even larger ionized bubbles than do purely analytic models at the same volume-weighted mean hydrogen neutral fraction,x H i , especially early in reionization. We also generate maps and power spectra of 21 cm brightness temperature fluctuations, which for the first time include corrections due to gas bulk velocities. We find that velocities widen the tails of the temperature distributions and increase small-scale power, although these effects quickly diminish as reionization progresses. We also include some preliminary results from a simulation run with the largest dynamic range to date: a 250 Mpc box that resolves halos with masses M ! 2:2 ; 10 8 M . We show that accurately modeling the late stages of reionization,x H i P 0:5, requires such large scales. The speed and dynamic range provided by our seminumerical approach will be extremely useful in the modeling of early structure formation and reionization.

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“…This is the publicly-available PINOCCHIO code developed by P. Monaco and collaborators [14,15,16] , [85]. (A similar tool that can be used to generate mock catalogs of halos rapidly is PTHalos developed by Scoccimarro and Sheth [83,84]) The great value of the PINOCCHIO code is that it is considerably less computationally expensive than a cosmological N-body simulation but predicts halo properties and formation histories that are in better agreement with N-body results relative to the simple excursion set approach (for a recent example see Ref.…”

Section: E the Pinocchio Algorithmmentioning

confidence: 99%

The Excursion Set Theory of Halo Mass Functions, Halo Clustering, and Halo Growth

Zentner

2007

Int. J. Mod. Phys. D

239

261

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I review the excursion set theory with particular attention toward applications to cold dark matter halo formation and growth, halo abundance, and halo clustering.After a brief introduction to notation and conventions, I begin by recounting the heuristic argument leading to the mass function of bound objects given by Press & Schechter. I then review the more formal derivation of the Press-Schechter halo mass function that makes use of excursion sets of the density field. The excursion set formalism is powerful and can be applied to numerous other problems. I review the excursion set formalism for describing both halo clustering and bias and the properties of void regions. As one of the most enduring legacies of the excursion set approach and one of its most common applications, I spend considerable time reviewing the excursion set theory of halo growth. This section of the review culminates with the description of two Monte Carlo methods for generating ensembles of halo mass accretion histories. In the last section, I emphasize that the standard excursion set approach is the result of several simplifying assumptions. Dropping these assumptions can lead to more faithful predictions and open excursion set theory to new applications. One such assumption is that the height of the barriers that define collapsed objects is a constant function of scale. I illustrate the implementation of the excursion set approach for barriers of arbitrary shape. One such application is the now well-known improvement of the excursion set mass function derived from * National Science Foundation Fellow 2 the "moving" barrier for ellipsoidal collapse. I also emphasize that the statement that halo accretion histories are independent of halo environment in the excursion set approach is not a general prediction of the theory. It is a simplifying assumption.I review the method for constructing correlated random walks of the density field in the more general case. I construct a simple toy model to illustrate that excursion set theory (with a constant barrier height) makes a simple and general prediction for the relation between halo accretion histories and the large-scale environments of halos:regions of high density preferentially contain late-forming halos and conversely for regions of low density. I conclude with a brief discussion of the importance of this prediction relative to recent numerical studies of the environmental dependence of halo properties.

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Predicting the Number, Spatial Distribution, and Merging History of Dark Matter Halos

Cited by 78 publications

References 40 publications

The Romulus cosmological simulations: a physical approach to the formation, dynamics and accretion models of SMBHs

The Romulus cosmological simulations: a physical approach to the formation, dynamics and accretion models of SMBHs

Efficient Simulations of Early Structure Formation and Reionization

The Excursion Set Theory of Halo Mass Functions, Halo Clustering, and Halo Growth

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