Advancing Galaxy Formation Modeling Andrew Benson California Institute of Technology.

Slides:



Advertisements
Similar presentations
Late gas accretion onto primordial mini-halos a model for pre-reionization dwarfs and extragalactic compact High-Velocity Clouds Massimo Ricotti (U of.
Advertisements

Semi-analytic Models based on Millennium II Haloes 1.
Section 6.2. Record data by magnetizing the binary code on the surface of a disk. Data area is reusable Allows for both sequential and direct access file.
18 July Monte Carlo Markov Chain Parameter Estimation in Semi-Analytic Models Bruno Henriques Peter Thomas Sussex Survey Science Centre.
On the nature of AGN in hierarchical galaxy formation models Nikos Fanidakis and C.M. Baugh, R.G. Bower, S. Cole, C. Done, C. S. Frenk Leicester, March.
TUPEC057 Advances With Merlin – A Beam Tracking Code J. Molson, R.J. Barlow, H.L. Owen, A. Toader MERLIN is a.
Galaxy Formation, Theory and Modelling Shaun Cole (ICC, Durham) 25 th October 2007 ICC Photo: Malcolm Crowthers Collaborators: Geraint Harker John Helly.
Scientific Programming MAIN INPUTINITCOMPUTEOUTPUT SOLVER DERIV FUNC2 TABUL FUNC1 STATIC BLASLAPACKMEMLIB.
Modeling the Physics of Galaxy Formation Andrew Benson California Institute of Technology.
Constraining Astronomical Populations with Truncated Data Sets Brandon C. Kelly (CfA, Hubble Fellow, 6/11/2015Brandon C. Kelly,
ARCS Data Analysis Software An overview of the ARCS software management plan Michael Aivazis California Institute of Technology ARCS Baseline Review March.
Module on Computational Astrophysics Professor Jim Stone Department of Astrophysical Sciences and PACM.
In The Beginning  N-body simulations (~100s particles) – to study Cluster formation  Cold collapse produces too steep a density profile (Peebles 1970)
Dark Matter and Galaxy Formation Section 4: Semi-Analytic Models of Galaxy Formation Joel R. Primack 2009, eprint arXiv: Presented by: Michael.
Software Group © 2006 IBM Corporation Compiler Technology Task, thread and processor — OpenMP 3.0 and beyond Guansong Zhang, IBM Toronto Lab.
A Multiphase, Sticky Particle, Star Formation Recipe for Cosmology
A Multiphase, Sticky Particle, Star Formation Recipe for Cosmology Craig Booth Tom Theuns & Takashi Okamoto.
A Unified, Merger-Driven Model of the Origin of Starbursts, Quasars, the Cosmic X-Ray Background, Supermassive Black Holes, and Galaxy Spheroids Hopkins,
Numerical Modeling of Hierarchical Galaxy Formation Cole, S. et al. 2000, MNRAS 319, Adam Trotter December 4, 2007 Astronomy 704, UNC-Chapel Hill,
APNe Conference, Seattle, July 2003 Clumpy Flows in Protoplanetary and Planetary Nebulae Alexei Poludnenko, Adam Frank University of Rochester, Laboratory.
Shutting Down AGN Nick Cowan University of Washington October 20, 2006 Nick Cowan University of Washington October 20, 2006.
Chapter 8 Physical Database Design. McGraw-Hill/Irwin © 2004 The McGraw-Hill Companies, Inc. All rights reserved. Outline Overview of Physical Database.
Estimate* the Total Mechanical Feedback Energy in Massive Clusters Bill Mathews & Fulai Guo University of California, Santa Cruz *~ ±15-20% version 2.
Advanced Methods for Studying Astronomical Populations: Inferring Distributions and Evolution of Derived (not Measured!) Quantities Brandon C. Kelly (CfA,
Cosmological formation of elliptical galaxies * Thorsten Naab & Jeremiah P. Ostriker (Munich, Princeton) T.Naab (USM), P. Johannson (USM), J.P. Ostriker.
© Janice Regan, CMPT 128, Jan CMPT 128 Introduction to Computing Science for Engineering Students Creating a program.
WorkPlace Pro Utilities.
Module 1: Introduction to C# Module 2: Variables and Data Types
(MNRAS 327, 610, 2001 & 347, 1234, 2004) David Churches, Mike Edmunds, Alistair Nelson - Physics & Astronomy, Cardiff University - Physics & Astronomy,
I N T R O D U C T I O N The mechanism of galaxy formation involves the cooling and condensation of baryons inside the gravitational potential well provided.
Galactic Metamorphoses: Role of Structure Christopher J. Conselice.
THE ROLE OF BLACK HOLES IN GALAXY EVOLUTION Tiziana Di Matteo Carnegie Mellon University Volker Springel, Lars Hernquist, Phil Hopkins, Brant Robertson,
Equal- and unequal-mass mergers of disk and elliptical galaxies with black holes Peter Johansson University Observatory Munich 8 th Sino-German workshop.
Updating JUPITER framework using XML interface Kobe University Susumu Kishimoto.
Maxime KUBRYK, IAP, Ph.D student advisors: Nikos PRANTZOS, IAP Lia ATHANASSOULA, OAMP LIA-ORIGINS, May 2012.
Evolving Virtual Creatures & Evolving 3D Morphology and Behavior by Competition Papers by Karl Sims Presented by Sarah Waziruddin.
Introduction Advantages/ disadvantages Code examples Speed Summary Running on the AOD Analysis Platforms 1/11/2007 Andrew Mehta.
Scaling relations of spheroids over cosmic time: Tommaso Treu (UCSB)
The coordinated growth of stars, haloes and large-scale structure since z=1 Michael Balogh Department of Physics and Astronomy University of Waterloo.
Jacqueline Keane NASA Astrobiology Pavel Senin University of Hawaii at
Modelling the Stellar Populations of The Milky Way and Andromeda Collaborators: Theory:Observations: Kathryn Johnston (Columbia) Annette Ferguson (Edinburgh)
Warm Absorbers: Are They Disk Outflows? Daniel Proga UNLV.
The dynamics of the gas regulator model and the implied cosmic sSFR-history Yingjie Peng Cambridge Roberto Maiolino, Simon J. Lilly, Alvio Renzini.
XP New Perspectives on XML, 2 nd Edition Tutorial 7 1 TUTORIAL 7 CREATING A COMPUTATIONAL STYLESHEET.
Chapter 8 Physical Database Design. Outline Overview of Physical Database Design Inputs of Physical Database Design File Structures Query Optimization.
March 27, 2008 Milan Raicevic ICC, Durham University Studying the role of inhomogeneous reionization in galaxy formation with GALFORM and SimpleX Collaborators:
Semi-analytical model of galaxy formation Xi Kang Purple Mountain Observatory, CAS.
Lec 5 part2 Disk Storage, Basic File Structures, and Hashing.
SPH Simulations of the Galaxy Evolution NAKASATO, Naohito University of Tokyo.
© 2010 Pearson Education, Inc. Galaxies. © 2010 Pearson Education, Inc. Hubble Deep Field Our deepest images of the universe show a great variety of galaxies,
The non-causal origin of black hole–galaxy scaling relations (and its consequences) Knud Jahnke Andrea Macciò Max-Planck-Institut für Astronomie, Heidelberg.
Improved Chemical Evolution Model for the Early Galaxy Evolution 中里直人 東大天文.
Random Logic l Forum.NET l State Machine Mechanism Forum.NET 1 st Meeting ● December 27, 2005.
Anders Nielsen Technical University of Denmark, DTU-Aqua Mark Maunder Inter-American Tropical Tuna Commission An Introduction.
LISA double BHs Dynamics in gaseous nuclear disk.
“Black hole spin and radioloudness in a ΛCDM universe” Claudia Lagos (PUC, Chile) Nelson Padilla (PUC, Chile) Sofía Cora (UNLP, Argentina) SOCHIAS 2008.
On the initial conditions and evolution of isolated galaxy models 2012 Workshop on Computational Sciences and Research Hub Induck Hall at Pusan Nat'l University.
Arman Khalatyan AIP 2006 GROUP meeting at AIP. Outline What is AGN? –Scales The model –Multiphase ISM in SPH SFR –BH model Self regulated accretion ?!
An Introduction to AD Model Builder PFRP
Robust Predictions for High-z Galaxies: What will we learn with JWST? Andrew Benson California Institute of Technology.
Models of Black Holes and Black Box Models
On the Origin of Galaxy Morphology in a Hierarchical Universe
Metrics of Software Quality
Speaker: Bingxiao Xu Peking University
Grid and Scientific applications
Galaxy populations within clusters in the 2PIGG catalogue
J-Zephyr Sebastian D. Eastham
Implementation of a Functional Programming Language
Max-Planck-Institut für Astronomie, Heidelberg
Scientific Workflows Lecture 15
Presentation transcript:

Advancing Galaxy Formation Modeling Andrew Benson California Institute of Technology

17 December 2010Advancing Galaxy Formation Modeling2 Advancing Galaxy Formation Codes Why a new code?  Adding in new features (e.g. self-consistent reionization, noninstantaneous recycling, new star formation rules) to existing models can be challenging How?  Create a code which is modular by design, isolating assumptions so that they don't have consequences throughout the code. Introduction | Models | Design | Modularity | Components | Evolution | Pros/Cons | Physics | Summary G ALACTICUS sites.google.com/site/galacticusmodel

17 December 2010Advancing Galaxy Formation Modeling3 Design Features Open source (compiles with GNU compilers) Modular design  Each function can have multiple implementations, selected by input parameter.  “Node” can have arbitrary number of components (e.g. DM halo, disk, spheroid), all with multiple implementations Combination of smooth (ODE) evolution and instantaneous events (e.g. mergers) Introduction | Models | Design | Modularity | Components | Evolution | Pros/Cons | Physics | Summary

17 December 2010Advancing Galaxy Formation Modeling4 Design Features Well documented Promotes a standard format for merger tree data  Parallelized  OpenMP  MPI (soon...)  Currently simple, but allows for expansion Introduction | Models | Design | Modularity | Components | Evolution | Pros/Cons | Physics | Summary Source code Binaries Cloud (Amazon EC2)

17 December 2010Advancing Galaxy Formation Modeling5 External Tools GNU Scientific Library/ FGSL  ODE solver; integration; other numerics FoX library  Read/write XML files FSPS  Population synthesis Cloudy  Cooling times Introduction | Models | Design | Modularity | Components | Evolution | Pros/Cons | Physics | Summary

17 December 2010Advancing Galaxy Formation Modeling6 Modularity New implementation of function easily added:  Write a module containing the function  Add directives indicating that this function is for, e.g., disk star formation timescale calculations  Recompile – build system automatically finds this new module and works out how to compile it into the code Modules are self-contained and independent Self-initializing and recursive Introduction | Models | Design | Modularity | Components | Evolution | Pros/Cons | Physics | Summary

17 December 2010Advancing Galaxy Formation Modeling7 Node Components Component could be, e.g. disk (exponential) Stores various types of data:  Properties – evolved within ODE system  Data – internal data, not evolved  Histories – records of past/future history (e.g. star formation history) Allows for multiple components of each type Introduction | Models | Design | Modularity | Components | Evolution | Pros/Cons | Physics | Summary

17 December 2010Advancing Galaxy Formation Modeling8 Node Components Defining a component:  Set of ODEs giving rates of change of properties (can access properties of other components/nodes as needed)  Responses to events (merging, becoming satellite etc.)  Specify properties to be output Introduction | Models | Design | Modularity | Components | Evolution | Pros/Cons | Physics | Summary

17 December 2010Advancing Galaxy Formation Modeling9 Introduction | Models | Design | Modularity | Components | Evolution | Pros/Cons | Physics | Summary Node Evolution Repeatedly walk tree – find nodes that to evolve:  Cannot evolve if have children  Can't evolve beyond their satellites  Limit on timestep  Arbitrary other factors can be included Evolve nodes forward Stops when no more nodes to evolve

17 December 2010Advancing Galaxy Formation Modeling10 Node Evolution All component properties fed into ODE solver Evaluate derivatives – evolve forward in time No need for fixed timesteps or analytic solutions  Makes implementing, for example, Kennicutt- Schmidt law trivial (just add new star formation timescale function) Evolution can be interrupted as needed (e.g. when galaxy merges) Introduction | Models | Design | Modularity | Components | Evolution | Pros/Cons | Physics | Summary

17 December 2010Advancing Galaxy Formation Modeling11 Node Evolution Component creation:  Nodes begin with only basic component (mass, time)  If accretion from IGM occurs, stop and create a hot halo component  If cooling occurs, stop and create a disk component  Components can be destroyed as needed also Introduction | Models | Design | Modularity | Components | Evolution | Pros/Cons | Physics | Summary

17 December 2010Advancing Galaxy Formation Modeling12 Advantages Modularity makes it highly flexible:  Add new star formation rule in 5 minutes  Change in cooling model confined to few modules which compute cooling time and rate Unified ODE solver makes new features simple:  Timestepping handled automatically  No need for analytic solutions  Implemented noninstantaneous recycling in one afternoon rather than two months! Introduction | Models | Design | Modularity | Components | Evolution | Pros/Cons | Physics | Summary

17 December 2010Advancing Galaxy Formation Modeling13 Disadvantages Slower  Wasn't designed for speed, but for simplicity Missing features (planned for addition):  Ram pressure/tidal stripping  Self-consistent reionization  Satellite orbits/disk heating  etc. Introduction | Models | Design | Modularity | Components | Evolution | Pros/Cons | Physics | Summary ICM heating/X-ray emission Multi-level hierarchy Black hole merging timescales/kicks H 2 -based star formation Resolved disks Compton/H 2 cooling Deterministic spins/concentrations ICM heating/X-ray emission Multi-level hierarchy Black hole merging timescales/kicks H 2 -based star formation Resolved disks Compton/H 2 cooling Deterministic spins/concentrations

17 December 2010Advancing Galaxy Formation Modeling14 Current Feature List Components  DM profile [isothermal/ NFW]  Hot halo  Disk [exponential]  Spheroid [Hernquist]  Black holes Tracks mass and spin. Spin from mergers and accretion. Accretion spin-up using Benson & Babul formula Jet power from Benson & Babul also. Tracks mass and spin. Spin from mergers and accretion. Accretion spin-up using Benson & Babul formula Jet power from Benson & Babul also. Introduction | Models | Design | Modularity | Components | Evolution | Pros/Cons | Physics | Summary

17 December 2010Advancing Galaxy Formation Modeling15 Introduction | Models | Design | Modularity | Components | Evolution | Pros/Cons | Physics | Summary Physics  Monte-Carlo (PCH method) /N-body merger trees  CIE atomic cooling  Dynamical friction  Star formation/feedback  Galaxy merging  Adiabatic contraction/sizes  Chemical enrichment (instant or non-instant) Current Feature List

17 December 2010Advancing Galaxy Formation Modeling16 Current Feature List Physics (cont.):  Disk instabilities  Black hole merging  AGN feedback  Stellar population synthesis (with arbitrary IMF) Introduction | Models | Design | Modularity | Components | Evolution | Pros/Cons | Physics | Summary

17 December 2010Advancing Galaxy Formation Modeling17 Summary G ALACTICUS sites.google.com/site/galacticusmodel Introduction | Models | Design | Modularity | Components | Evolution | Pros/Cons | Physics | Summary