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Bob Nichol's talk on cosmological surveys at the Cape Town International Cosmology School, 2012

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  1. 1. Surveys  Bob  Nichol  
  2. 2. Comments  •  Tried  to  be  complementary  to  other  lectures   –  Please  ask  ques<ons  (some<mes  controversial  on   purpose!)  •  Only  talks  about  cosmological  surveys   –  Galaxy  evolu<on,  planetary  searches,  galaxy   archeology  are  not  covered  •  Personal  views   –  Many  surveys  will  be  missed  (sorry)   –  Op<cal  astronomy  (radio/CMB  surveys  are  poorly   represented)  
  3. 3. Advice  •  Wise  •  Old  •  ForgoKen  •  Sartre  "Youre  free,  choose,  that  is,  invent.”  •  Nichol  “I  told  you  so!  I’m  always  right”  
  4. 4. History  of  Surveys    
  5. 5. 1970s  
  6. 6. EDSGC   1980s   1,495,877  galaxies  over  1182  sq  deg  Plate  to  plate  accuracy  of  0.1  mags  only  12%  of  galaxies  could  be  stars!    
  7. 7. Redshibs   λobs Random  galaxy   z= −1 λemitted Z=0.182   cz ≈ H 0 d (locally)  
  8. 8. Era  of  Redshib  Surveys   z~0.05  1985   1989  
  9. 9. 1995  
  10. 10. Era  of  Redshib  Surveys   z~0.13   1992  
  11. 11. Fermilab   Industrial  Astronomy   (driven  by  technology)   Random  galaxy  Apache  Point   UWashington   2009  Nobel  Prize  for  CCDs  and  op<cal  fibers  
  12. 12. LSS   Observational Definition pcs   rs   -­‐  420  MSDSS   i llion  ly 1.37  b CfA2   2dfGRS   Structures  larger  than  clusters,  typically  >  10Mpc   (larger  than  a  galaxy  could  have  moved  in  a  Hubble  <me)  
  13. 13. Percival  et  al.  2010  
  14. 14. Measuring  ξ(r)  or  P(k)   Simple  es<mator:   Data   ξ(r)  =  DD(r)/RR(r)  -­‐  1   Advanced  es<mator:   ξ(r)  =  (DD-­‐RR)2/RR-­‐1   r   The  la,er  does  a  be,er   job  with  edge  effects,   which  cause  a  bias  to  the  Random   mean  density  of  points   Usually  10x  as  many   random  points  over   SAME  area  /  volume   Same  techniques  for  P(k)  -­‐  take  Fourier  transform  of  density  field  rela<ve  to  a  random   catalog  over  same  volume.  Several  techniques  for  this  -­‐  see  Tegmark  et  al.  and  Pope  et  al.   Also  “weighted”  and  mark  correla<ons    
  15. 15. Measuring  ξ(r)  II  Essential the random catalog looks like the real data!
  16. 16. Errors  on  ξ(r)    Hardest  part  of  esLmaLng  these  staLsLcs   On  small  scales,  the  errors  are  Poisson   On  large  scales,  errors  correlated  and  typically  larger  than   Poisson     •  Use  mocks  catalogs     •  PROS:  True  measure  of  cosmic  variance   •  CONS:  Hard  to  include  all  observa<onal      effects  and  model  clustering   •  Use  jack-­‐knifes  (JK)   •  PROS:  Uses  the  data  directly   •  CONS:  Noisy  and  unstable  matrices    
  17. 17. Jack-­‐knife  Errors    Real  Data   •   Split  data  into  N   equal  subregions   1   3   •   Remove  each   subregion  in  turn   and  compute  ξ(r  )   4   5   6   •   Measure  variance   between  regions  as   func<on  of  scale     N=6   2   3   N (N −1) σ = 2 N i=1 ∑ (ξi − ξ ) 2 4   5   6   Note  the  (N-­‐1)  factor  because  there  are  N-­‐1   es<mates  of  mean  
  18. 18. SDSS  &  WMAP  •  Now  the  most  successful  astronomical   facili<es  in  the  world  •  4187  papers  with  162913  cita<ons      (Jan  17th  at  4pm)  •  At  least  a  paper  a  day!      
  19. 19. Current  and  near-­‐term  surveys  
  20. 20.                        The  DETF  figure-­‐of-­‐merit  is  the   reciprocal  of  the  area  of  the      error  ellipse  enclosing  the  95%   confidence  limit  in  the  w0–wa  plane.      Stage  II  –  today  (ish)  Stage  III  –  factor  of  3  Stage  IV  –  factor  of  10  
  21. 21. Dark  Energy  is  bad  for  Astronomy   (ArXiv:0704.2291)1.  Cultural differences: HEPs are fundamentalists (“specialists”) and astronomers are generalists. Respect each others cultures2. Don’t over optimize your surveys - plan for the unexpected3. Don’t over prioritize DE surveys to the expense of others4. Be inclusive and publish your data5. Nurture young talent and give recognition where due The  SDSS  is  the  last  of  its  kind!  
  22. 22. Don’t over-optimize•  Dark energy is now systematics limited - young scientists should do PhD’s in dust and biasing. •  DETF proposed diversity in experiments•  All the new surveys are building this in, e.g., DES will get less SNe but (hopefully) understand them better•  These will greatly benefit astrophysics and I would argue would not be done without the driving force of DE (unfocused science is also a risk and can be expensive)•  DE experiments will deliver more numbers and area. Excellent for cosmic variance, environment studies and high-dimensional parameter searches. •  Larger field of views are driven by technology, so we would do large area surveys anyway.
  23. 23. BOSS  in  a  nutshell  8,000 deg2 footprint in Spring (Eisenstein  et  al.  2011)  3,000 deg2 footprint in Fall•  Upgraded spectrographs (with better throughput) •  1000x 2-arcsec fibers in cartridges •  Increase wavelength range to 3600-10,000A (R=1500-2600)•  Finished ~3,000 deg2 southern imaging in Fall 2008. •  Released as part of DR8, published in ApJS (2011).•  Currently doing only spectroscopy •  1.5 million galaxies, i<19.9, z<0.8, over 10,000 deg2 •  150,000 QSOs, g<22, 2.3<z<3, over 8,000 deg2
  24. 24. Data  so  far   et  al.  2011,  Ho  et  al.  2012,  Seo  et  al.  2012   Ross   Current  status   Done  by  2014  
  25. 25. LSS  at  high  z  (Slozar  et  al.  2011)  
  26. 26. BOSS  •  BOSS  is  designed  as  a  “stage  III”  project  to  constrain  DE  using   the  baryon  acous<c  oscilla<on  (BAO)  method   –  Galaxies  z~0.1-­‐0.7   1%  dA,  2%  H(z),  z~0.35  &  0.6   –  QSOs  (LyAF)  z~2-­‐3   1.5%  dA,H  at  z~2.5  
  27. 27. AS3:  e-­‐BOSS   •  gri selection conducted on a single plate based on DR8 photometry (targeting the CFHT-LS W3 field) •  78% redshift success efficiency - ~68% in 0.6<z<1 DES  overlap   BOSS e-BOSS MaNGA  Start    2014?   J.P. Kneib 28  
  28. 28. The Dark Energy Survey Blanco  4-­‐meter  at  CTIO  •  Survey project using 4 complementary techniques: I. Cluster Counts II. Weak Lensing III. Large-scale Structure IV. Supernovae• Two multiband surveys: 5000 deg2 grizY to 24th mag 30 deg2 repeat (SNe)• Build new 3 deg2 FOV camera and Data management system Survey 2012-2017 (525 nights) Facility instrument for Blanco29  
  29. 29. DECam     C4  in  its  cell   (UCL)   New  flat-­‐field     Screen  (CTIO)   Completed   Imager  (FNAL)  
  30. 30. DES Science Summary Forecast  Constraints  on  DE   Equa<on  of  State  Four Probes of Dark Energy•  Galaxy Clusters DES   •  ~100,000 clusters to z>1 •  Synergy with SPT, VHS •  Sensitive to growth of structure and geometry•  Weak Lensing •  Shape measurements of 300 million galaxies •  Sensitive to growth of structure and geometry•  Large-scale Structure •  300 million galaxies to z = 1 and beyond Planck  prior  assumed   •  Sensitive to geometry•  Supernovae •  30 sq deg time-domain survey •  ~4000 well-sampled SNe Ia to z ~1 Factor  3-­‐5  improvement  over     •  Sensitive to geometry Stage  II  DETF  Figure  of  Merit  31  
  31. 31. DES Science Summary II Planck  prior  assumed  32  
  32. 32. Which  Survey  or  Probe?  
  33. 33. Which  Survey  or  Probe?   Stocks  Government    Bonds  
  34. 34. Future  Surveys  
  35. 35. BigBOSS  •  5000-­‐fiber  instrument  on  4m  telescope  •  Stage  IV  BAO  on  the  “cheap”  
  36. 36. The  Euclid  machine     Space-based Vis and NIR observations of galaxies VIS  Imaging   NIR  Spectroscopy  NIR  Photometry   NIR  Imaging  Tomographic  shear   Redshib  machine   machine   Dark  MaRer  and  Galaxy     PowerSpectra-­‐meters   Astronomical  data  base  for     Explorer  of  gravity  and  expansion   Legacy  science  
  37. 37. Area  requirements  •  FoM  increases  with  increasing  area/volume  and  galaxy  number  density.    •  This  ignores  that  any  survey  is  limited  by  cost:  <me  is  finite  •  weak-­‐lensing,  intrinsic  alignments  become  increasingly  important  for  shallower  surveys  •  This  changes  the  trade-­‐off  between  area  and  depth  •  6-­‐year  dura<on,  WL+GC  gives  op<mal  survey  area  of  15,000  deg2  
  38. 38. Euclid  clustering  measurements  20%  of  the  Euclid  data,  assuming  the  slitless  baseline  at  z~1   Distance-­‐redshib   rela<on  moves  P(k)  
  39. 39. Science  summary  
  40. 40. Measuring  Modified  Gravity  •  The  growth  factor  [or  its  deriva<ve,  the  growth  rate  f(z)]  quan<fies   the  efficiency  with  which  cosmological  structure  is  built.  •  The  growth  rate  well  described  by  f(z)=Ωm(z)γ.    •  A  detec<on  of  γ≠0.55  would  indicate  a   devia<on  from  General  Rela<vity,  and  thus  a   completely  different  origin  of  cosmic   accelera<on,  rather  than  dark  energy.  •  Euclid  can  constrain  this  parameter  to  0.01   (where  ΛCDM  corresponds  to  γ=0.55).    •  the  γ-­‐parameterisa<on  is  merely  an  example.   In  general,  Euclid  will  provide  <ght  constraints   on  the  cosmological  growth  rate.  
  41. 41. Outreach  and  data  issues  
  42. 42. Explosion  BANG!  
  43. 43. Most  people  look  at  about  20  galaxies.  All  galaxies  looked  at  by  at  least  20  people  (median  38).  
  44. 44. Karen  Masters:  The  Enigma  of  Red  Spirals.  Wednesday  9th  December  2009   49  
  45. 45. Summary  •  Era  of  surveys  is  here   –  More  to  come  (DR9,  DES,  Euclid).     –  By  end  of  decade,  billions  of  galaxies  in  public  domain   –  Only  held  back  by  your  imagina<on!   –  Wonderful  technologies  to  share  and  collaborate  with   such  data  •  Era  of  maximal  ignorance   –  We  know  “nothing”,  but  not  what  caused  it  or  what  it   could  be   –  Progress  will  only  be  made  through  observa<on!   –  Don’t  let  anyone  tell  you  it’s  a  “crazy  idea”  
  46. 46. Advice  Session  at  4pm  
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