WFMOS: a tool for probing dark energy David Parkinson EDEN in Paris, December 2005.

Slides:



Advertisements
Similar presentations
1 Palermo nd May Looking ahead to MOONS William Taylor on behalf of the MOONS consortium.
Advertisements

Prospects for the Planck Satellite: limiting the Hubble Parameter by SZE/X-ray Distance Technique R. Holanda & J. A. S. Lima (IAG-USP) I Workshop “Challenges.
What Figure of Merit Should We Use to Evaluate Dark Energy Projects? Yun Wang Yun Wang STScI Dark Energy Symposium STScI Dark Energy Symposium May 6, 2008.
Optimization of large-scale surveys to probe the DE David Parkinson University of Sussex Prospects and Principles for Probing the Problematic Propulsion.
SDSS-II SN survey: Constraining Dark Energy with intermediate- redshift probes Hubert Lampeitl University Portsmouth, ICG In collaboration with: H.J. Seo,
Unveiling the formation of the Galactic disks and Andromeda halo with WFMOS Masashi Chiba (Tohoku University, Sendai)
Non-linear matter power spectrum to 1% accuracy between dynamical dark energy models Matt Francis University of Sydney Geraint Lewis (University of Sydney)
The Science of JWST Caleb Wheeler. Table of Contents First Paper Second Paper Nervous standing after I finish early and everyone is too bored to formulate.
Nikolaos Nikoloudakis Friday lunch talk 12/6/09 Supported by a Marie Curie Early Stage Training Fellowship.
Science Team Management Claire Max Sept 14, 2006 NGAO Team Meeting.
Bayesian Analysis of X-ray Luminosity Functions A. Ptak (JHU) Abstract Often only a relatively small number of sources of a given class are detected in.
July 7, 2008SLAC Annual Program ReviewPage 1 Future Dark Energy Surveys R. Wechsler Assistant Professor KIPAC.
Complementary Probes ofDark Energy Complementary Probes of Dark Energy Eric Linder Berkeley Lab.
The Structure Formation Cookbook 1. Initial Conditions: A Theory for the Origin of Density Perturbations in the Early Universe Primordial Inflation: initial.
Dark Energy J. Frieman: Overview 30 A. Kim: Supernovae 30 B. Jain: Weak Lensing 30 M. White: Baryon Acoustic Oscillations 30 P5, SLAC, Feb. 22, 2008.
Nikos Nikoloudakis and T.Shanks, R.Sharples 9 th Hellenic Astronomical Conference Athens, Greece September 20-24, 2009.
30/6/09 Unity of the Universe 1. Michael Drinkwater for the team Australia: Blake, Brough, Colless, Couch, Croom, Davis, Glazebrook, Jelliffe, Jurek,
P olarized R adiation I maging and S pectroscopy M ission Probing cosmic structures and radiation with the ultimate polarimetric spectro-imaging of the.
The Science Case for the Dark Energy Survey James Annis For the DES Collaboration.
NAOKI YASUDA, MAMORU DOI (UTOKYO), AND TOMOKI MOROKUMA (NAOJ) SN Survey with HSC.
Eric V. Linder (arXiv: v1). Contents I. Introduction II. Measuring time delay distances III. Optimizing Spectroscopic followup IV. Influence.
Cosmology & Large Scale Structure Case, Matthew Colless, GSMT SWG, 4-5 Dec 2002 11 GSMT Science - Case Studies Large Scale Structure and Cosmology Matthew.
WFMOS Feasibility Study Value-added Science Bob Nichol, ICG Portsmouth.
Robust cosmological constraints from SDSS-III/BOSS galaxy clustering Chia-Hsun Chuang (Albert) IFT- CSIC/UAM, Spain.
1 BDRv3 - November 26, Markus Kissler-Patig E-ELT Programme 1 E-ELT Science Case Markus Kissler-Patig.
Stellar Populations Science Knut Olsen. The Star Formation Histories of Disk Galaxies Context – Hierarchical structure formation does an excellent job.
Observational test of modified gravity models with future imaging surveys Kazuhiro Yamamoto (Hiroshima U.) Edinburgh Oct K.Y. , Bassett, Nichol,
BigBOSS Survey and Spectral Simulations Nick Mostek.
Clustering in the Sloan Digital Sky Survey Bob Nichol (ICG, Portsmouth) Many SDSS Colleagues.
Dark Energy & LSS SDSS & DES teams (Bob Nichol, ICG Portsmouth) Marie Curie (EC)
PAU survey collaboration: Barcelona (IFAE, ICE(IEEC/CSIC), PIC), Madrid (UAM & CIEMAT), València (IFIC & UV), Granada (IAA) PAU survey Physics of the Accelerating.
Next generation redshift surveys with the ESO-VLT
Francisco Javier Castander Serentill Institut d’Estudis Espacials de Catalunya (IEEC) Institut de Ciències de l’Espai (ICE/CSIC) Barcelona Exploiting the.
Yun Wang, 3/2011 Baryon Acoustic Oscillations and DE Figure of Merit Yun Wang Yun Wang WFIRST SDT #2, March 2011 WFIRST SDT #2, March 2011 BAO as a robust.
Cosmological Particle Physics Tamara Davis University of Queensland With Signe Riemer-Sørensen, David Parkinson, Chris Blake, and the WiggleZ team.
WFMOS KAOS concept identified via the Gemini Aspen Process and completed a Feasibility Study (Barden et al.) Proposed MOS on Subaru via an international.
David Weinberg, Ohio State University Dept. of Astronomy and CCAPP The Cosmological Content of Galaxy Redshift Surveys or Why are FoMs all over the map?
G. Miknaitis SC2006, Tampa, FL Observational Cosmology at Fermilab: Sloan Digital Sky Survey Dark Energy Survey SNAP Gajus Miknaitis EAG, Fermilab.
Wiggles and Bangs SDSS, DES, WFMOS teams. Understanding Dark Energy No compelling theory, must be observational driven We can make progress on questions:
Advanced Stellar Populations Advanced Stellar Populations Raul Jimenez
DMD Spectroscopy Yun Wang Yun Wang (with DMD slides from Massimo Robberto) WFIRST SDT #2, March, 2011.
Expected progress and break-throughs in ground-based extragalactic astronomy Ralf Bender ESO Council FORS Deep Field.
FastSound A BAO Survey in NIR using Subaru/FMOS 戸谷 友則 TOTANI, Tomonori (Kyoto University, Dept. Astronomy) Spectroscopy in Cosmology and Galaxy Evolution.
Dark Energy and Cosmic Sound Daniel Eisenstein Steward Observatory Eisenstein 2003 (astro-ph/ ) Seo & Eisenstein, ApJ, 598, 720 (2003) Blake & Glazebrook.
BAOs SDSS, DES, WFMOS teams (Bob Nichol, ICG Portsmouth)
Data Reduction with NIRI Knut Olsen and Andrew Stephens Gemini Data Workshop Tucson, AZ July 21, 2010 Knut Olsen and Andrew Stephens Gemini Data Workshop.
23 Sep The Feasibility of Constraining Dark Energy Using LAMOST Redshift Survey L.Sun Peking Univ./ CPPM.
ALMA Science Examples Min S. Yun (UMass/ANASAC). ALMA Science Requirements  High Fidelity Imaging  Precise Imaging at 0.1” Resolution  Routine Sub-mJy.
The Feasibility of Constraining Dark Energy Using LAMOST Redshift Survey L.Sun.
3rd International Workshop on Dark Matter, Dark Energy and Matter-Antimatter Asymmetry NTHU & NTU, Dec 27—31, 2012 Likelihood of the Matter Power Spectrum.
Emission Line Galaxy Targeting for BigBOSS Nick Mostek Lawrence Berkeley National Lab BigBOSS Science Meeting Novemenber 19, 2009.
The Gaia-ESO Survey Sofia Randich INAF-Arcetri Survey Co-PIs: Gerry Gilmore & Sofia Randich 350+ Co-Is (mostly from Europe, but not only) 90++ institutes.
1 Baryon Acoustic Oscillations Prospects of Measuring Dark Energy Equation of State with LAMOST Xuelei Chen ( 陳學雷 ) National Astronomical Observatory of.
Goals for HETDEX Determine equation of state of Universe and evolutionary history for dark energy from 0
1 1 Dark Energy with SNAP and other Next Generation Probes Eric Linder Berkeley Lab.
Future observational prospects for dark energy Roberto Trotta Oxford Astrophysics & Royal Astronomical Society.
FIRST LIGHT A selection of future facilities relevant to the formation and evolution of galaxies Wavelength Sensitivity Spatial resolution.
SOFIA and the ISM of Galaxies Xander Tielens & Jessie Dotson Presented by Eric Becklin.
Brenna Flaugher for the DES Collaboration; DPF Meeting August 27, 2004 Riverside,CA Fermilab, U Illinois, U Chicago, LBNL, CTIO/NOAO 1 Dark Energy and.
Probing Dark Energy with Cosmological Observations Fan, Zuhui ( 范祖辉 ) Dept. of Astronomy Peking University.
Carlos Hernández-Monteagudo CE F CA 1 CENTRO DE ESTUDIOS DE FÍSICA DEL COSMOS DE ARAGÓN (CE F CA) J-PAS 10th Collaboration Meeting March 11th 2015 Cosmology.
Competitive Science with the WHT for Nearby Unresolved Galaxies Reynier Peletier Kapteyn Astronomical Institute Groningen.
Sample expanded template for one theme: Physics of Galaxy Evolution Mark Dickinson.
NIRSS: the Near-Infrared Sky Surveyor WFIRST Meeting 2011 February 3 Daniel Stern (JPL/Caltech)
Jochen Weller Decrypting the Universe Edinburgh, October, 2007 未来 の 暗 黒 エネルギー 実 験 の 相補性.
Stellar Populations Science Knut Olsen. The Star Formation Histories of Disk Galaxies Context – Hierarchical structure formation does an excellent job.
Reducing Photometric Redshift Uncertainties Through Galaxy Clustering
The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey : cosmological analysis of the DR12 galaxy sample arXiv:
Complementarity of Dark Energy Probes
6-band Survey: ugrizy 320–1050 nm
Presentation transcript:

WFMOS: a tool for probing dark energy David Parkinson EDEN in Paris, December 2005

BAO as a standard ruler Acoustic Oscillations are imprinted into the matter power spectra. Fundamental wavelength fixed at recombination Can be used as a ‘standard ruler’ to probe geometry and dark energy

–Dark matter distributions via kinematics of LG galaxies –The structure of the LMC disk –Milky Way halo survey at MS –Population III and the dSph’s –Milky Way interstellar medium –Studies of high-velocity clouds –Kuiper Belt objects WFMOS is also a very broadly capable facility instrument: –Studies of large-scale structure –Formation and evolution of galaxies at high redshift –The growth of structure –AGN physics at high redshift –The relation between galaxies and the IGM at high redshift –Stellar pops in LG galaxies WFMOS Science WFMOS has two flagship science programs: –Acoustic oscillations  What is the dark energy? –Galactic archeology  How do galaxies form? (See KAOS Purple Book -

‘Archival’ Science Additional science from survey data… –Constrain dark energy from cluster counts and Alcock-Paczsynki test –Spectroscopically identify thousands of SNe Ia –Test reciprocity relation d A /d L = (1+z) 2 to constrain GR and photon conservation (axion-photon interactions) –Accurately measure luminosity functions & star- formation rate densities with redshift & environment –Constrain shape of primordial power spectrum to 2% and thus mass of the neutrino to 0.1eV (2  )

‘Community’ Science Science from other WFMOS observations… –Detailed studies of local low-luminosity galaxies, down to Mr~-11 (r~24) in the Coma Cluster –High redshift (z>4) studies of galaxies and QSOs selected from multi-color photometry –Observations of M31 and M33 to provide kinematical and abundance information in the bulges and disks –Simultaneously observing QSOs and galaxies (in the same fields) to quantify the relation between the IGM and the large-scale structures as traced by galaxies.

WFMOS History WFMOS is a proposed second-generation Gemini instrument that emerged from the ‘Aspen’ process. Before that, it was the KAOS conceptual instrument (see Originally intended for Gemini, the potential technical, financial, observational and strategic advantages of building WFMOS for Subaru, sharing Gemini & Subaru resources, has since been recognized. The WFMOS feasibility study has lead to a RfP for two competing concept studies, for review Oct/Nov 2006.

Target Specifications for WFMOS Top-level design performance guidelines for WFMOS… –Wavelength range: 0.39–1.0 µm –Field of view: ~1.5 deg diameter –Spatial sampling: ~1 arcsec fiber entrance –Spectral resolution: 1000–40,000 –One-shot coverage:~0.4 µm (at low resolution) –Simultaneous targets: 4000–5000

Advantages of WFMOS What differentiates WFMOS from other instruments? –Large field area: the FoV of WFMOS is 10x larger than that of any other 8m multi-object spectrograph. –Multiplex: multiplex gain of WFMOS is 5x that of any other 8m MOS (though fiber density is relatively low compared to multi-slit instruments). –Limiting magnitude: with nod & shuffle designed-in, WFMOS is not limited by sky-subtraction systematics when compared to multi-slit instruments. –WFMOS can deliver of order 20,000 spectra per night!

Instrument Comparison WFMOS

WFMOS FoV - Moon and Andromeda

DEIMOS VIRMOS FMOS GMOS Comparison of MOS fields of view FLAMES 15 deg ~ 300 Mpc/h at z  1 WFMOS Surveys of Large Scale Structure

WFMOS Efficiency Advantages Multiplex-limited case (density targets > density of fibers) FoV-limited case (density targets < density of fibers) WFMOS

WFMOS major science programs

Measuring the acoustic oscillations

Dark Energy Constraints

Optimisation The Unique Selling Point of BAO is that they act as standard rulers and can probe the dark energy. Our goal is to get the best possible constraints on the dark energy. How do we optimize the survey to do this? Constraining equation of state, w, and its evolution in time is seen as the primary goal.

IPSO Even selecting some parameterization of w (e.g. w(a)=w 0 +w a z/(1+z)) the errors on w of our survey still depends on the fiducial cosmology. Integrated Parameter Survey Optimization (Bassett 2004; Bassett, Parkinson and Nichol 2005) The Figure of Merit is the integral of the performance (I) over the cosmological parameters. D-optimality: performance (I) is measured as the determinant of the Fisher matrix of the dark energy parameters (w 0, w a ) [using Linder expansion w(a)=w 0 +(1-a)w a ].

Procedure

Optimization Procedure 1.Select survey configuration (area coverage, redshift bins, exposure time etc.) 2.Estimate number density of galaxies using LFs. 3.Estimate error on D A (z) and H(z) using scaling relations. 4.Calculate Fisher matrix of parameters, using distance data plus other info (Planck+SDSS). 5.Use Fisher matrix to calculate FoM. 6.Monte-carlo markov chain search over survey configuration parameter space, attempting to minimize determinant.

Survey Parameters Time: split between the high and low redshift regions. Total time = 1500 hours (expected observing time over three years). Area: different areas assigned to high and low redshift regions. Exposure time and number of pointings: generated from area and time. Redshift binning: Redshift regions broken down into a number of bins.

Scaling Relations It is computationally intensive to find full error covariances for power spectrum (requires FFTs). Computed errors on x and x’ for a grid of survey parameters and derived fitting formula. For photo-z surveys, assumed Gaussian photometric error  r. See paper by Blake, DP, Bassett, Glazebrook, Kunz And Nichol

Fitting Formulae

Monte-carlo Markov Chain We conduct an MCMC search through the parameter space, accepting or rejecting surveys depending on the figure of merit. To find the optimum survey, have to search over large parameter space (>10 different parameters). Lots of degenerate minima! We “heat” and “cool” the chains, attempting to guarantee we reach the global minima.

Design Objectives Using these techniques we can optimize: –The observational area in the low and high redshift regimes –The number of redshift bins in each regime –The redshifts of the bins –The number of spectroscopic fibres –The gain in information from pushing into the redshift desert.

Line Emission

Continuum

Error ellipse

Summary WFMOS is a next generation Multi-Object Spectrograph currently in the design phase. It will be developed as part of a Subaru-Gemini partnership. It will dominate seeing-limited survey spectroscopy. It will enable flagship high-impact science programs, such as the dark energy. Using IPSO the survey will be optimised to extract information about the dark energy