1. Optimisation of
Multi-Object Spectroscopy
in Astronomy
Brent Miszalski
SALT Research Fellow
brent@saao.ac.za
Sunday 18 March 12

2. Overview
• Galaxy redshift surveys
• Multi-object spectroscopy (MOS)
• MOS field configuration by
simulated annealing
• MOS at the Southern African Large
Telescope (SALT)
Miszalski et al. 2006, MNRAS, 371,1537
Sunday 18 March 12

3. NGC 1376
Sunday 18 March 12

4. M 101
Sunday 18 March 12

5. Hubble Ultra Deep Field
Sunday 18 March 12

6. Hubble’s law
• Expansion of the
universe produces a
Doppler-shift in light
of galaxies towards
red end of spectrum
• The ‘redshift’ z=(λ-
λ0)/λ0 is related to
recessional velocity
of each galaxy V~cz
• V=H 0d
Sunday 18 March 12

7. Galaxies cluster together
Sunday 18 March 12

8. Comoving distance
DC - distance between two galaxies
Density parameters
matter
dark energy
curvature
Sunday 18 March 12

9. Millenium Simulation (Springel et al. 2005)
Sunday 18 March 12

10. We need more redshifts
• Measuring fundamental cosmological
parameters depends on statistical analysis
of large scale structure
• A few thousand galaxies is not enough
• Need hundreds of thousands or millions
• Cannot do this one object at a time...
Sunday 18 March 12

11. Multi-Object Spectroscopy
• Developed in late 80s/early 90s
• Highly successful but very complex (more focus on
getting instrument working, rather than optimising it)
Sunday 18 March 12

12. 2dF: Two-degree Field facility
4-m Anglo-Australian
Telescope
Lewis et al. (2002)
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16. wavelength
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17. wavelength
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18. 2dFGRS (Colless et al. 2001)
Sunday 18 March 12

19. N(z)~250,000!
Sunday 18 March 12

20. wigglez.swin.edu.au
Wigglez
Drinkwater et al. 2010
Sunday 18 March 12

21. wigglez.swin.edu.au
Wigglez
Drinkwater et al. 2010
Blake et al. 2010
Sunday 18 March 12

22. wigglez.swin.edu.au
Wigglez
Drinkwater et al. 2010
Blake et al. 2010
Sunday 18 March 12

23. A challenging optimisation problem
• 400 fibres to match up to N
targets (up to ~1000)
• Targets have priorities 1(lowest)
to 9(highest)
• Limited fibre reach
• Fibres and buttons cannot
collide, but fibre crossover ok
• Uniformly sample targets [no structure imprint]
• Prefer straighter fibres [quicker config times]
Sunday 18 March 12

24. Fibre and target reach
Sunday 18 March 12

25. Fibre and target reach
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26. Sunday 18 March 12

27. Simulated Annealing
• Donnelly et al. (1992) first proposed and
implemented SA for field configuration, but not
fast enough back then
• SA simulates slow cooling of physical systems
(e.g. glass), making small random changes at each
temperature level
• Metropolis (1953) algorithm determines whether
a change is accepted
• Fewer and fewer “bad” changes are accepted at
lower temperatures
Sunday 18 March 12

28. Travelling Salesman Problem
Numerical Recipes (Ch. 10)
(b) large river penalty (c) negative river penalty!
Sunday 18 March 12

29. Annealing schedule
• Start with unallocated fibres, a few hundred targets
and an initial temperature Ti
• Slowly cool Ti by multiplication with (1-ΔT)
• Randomly choose new targets for each fibre,
multiple times (up to 105 swaps per ΔT)
• The randomisation of each fibre occurs in four ways
• Metropolis (1953) algorithm accepts or denies each
change, depending on global ‘quality’ of field
• Reach quasi-static equilibrium at each temperature
Sunday 18 March 12

30. Four randomisation cases
before
after
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31. Metropolis algorithm
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32. Metropolis algorithm
Boltzmann distribution in
statistical mechanics
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33. Objective function
target close straighten
priority pairs fibres maximise
me!
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34. Objective function
Temperature
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35. A sample run
E
Temperature
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36. Simulations
• Both uniform and clustered fields
• Also use actual cosmological
simulations (mock catalogues)
• Different priority distributions
• Fields with close pairs
• LOTS of trial and error in
selecting best algorithm
parameters
• Usually configure 1000 fields each
Sunday 18 March 12

37. Total target yield
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38. Total target yield
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39. Target priorities
lowest highest
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40. Target priorities
lowest highest
Sunday 18 March 12

41. Target priorities
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42. Target priorities
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43. Target priorities
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44. Uniformity
Oxford
SA
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45. OLD
(Oxford)
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46. NEW
(Annealing)
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47. Fibre straightness
γ=0.0 γ=0.125 γ=2.0
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48. Fibre straightness
γ=0.0 γ=0.125 γ=2.0
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49. Algorithm summary
• Power is in contained in the objective function
• Performance far exceeds previous algorithms
• Both in raw target yield and flexibility
• Routinely used by astronomers at AAT since 2006
• Routinely used by several large galaxy redshift surveys
• Generic algorithm suitable to many other MOS
instruments
• Opportune time to apply it to MOS masks at SALT!
Sunday 18 March 12

50. SALT
• Biggest single telescope in Southern Hemisphere!
• 11.1m x 9.8m optical mirror
• Refurbished instrumentation: April 2011
• Second science semester starts in May 2012
• Multi-object capability: instead of fibres, use slit-masks
• MOS is currently being tested/commissioned
• Perfect time to explore optimisation of mask design
photo: Lisa Crause
Sunday 18 March 12

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53. MOS masks
• Cheaper than developing a robot + fibre system
• Use laser to cut slits in carbon fibre mask
• Mask is placed in focal plane of telescope
• Each slit produces a spectrum
• Challenge is to ‘pack in’ the best arrangement of
slits in one mask
• A unique set of constraints c.f. fibre optimisation
Sunday 18 March 12

54. Laser mask cutter MOS @ SALT
Slit mask cutter software GUI
Sunday 18 March 12

55. courtesy
David
Gilbank
~1/2 degree
IMACS on Magellan
6.5-m telescope
Chile
Sunday 18 March 12

56. courtesy
David
Gilbank
~1/2 degree
IMACS on Magellan
6.5-m telescope
Chile
Sunday 18 March 12

57. courtesy
David
Gilbank
slits
Sunday 18 March 12

58. courtesy
David
Gilbank
Sunday 18 March 12

59. AIMS project
• An exploratory study for a new mask design algorithm
• Dr Brent Miszalski (SAAO/SALT)
• Dr David Gilbank (SAAO)
• Prof Bruce Bassett (AIMS/SAAO/UCT)
• Design clear guidelines necessary for algorithm
development to start
• Identify most efficient and clever ways to conduct basic
operations needed in a mask algorithm
Sunday 18 March 12

60. MOS mask design issues
• What data structures to use in algorithm?
• Hashes, vectors, lists, etc. Best choices == faster
• How to tilt slits to capture > 1 target in field?
• What randomisation steps to choose?
• Shifting slit centres, extending slit size??
• Shuffling groups of slits? Adding new slits?
• How do we best define a “good” mask design?
• Quantify completeness? Ensemble designs?
Sunday 18 March 12

61. MOS mask design issues
• What is the best way to explore the parameter
space of the problem?
• Monte carlo simulations, statistics on real input data
• Review previous MOS algorithms (especially mask
design algorithms)
• Most algorithms in the literature could be
considerably improved
• Your work could be used routinely at SALT!
Sunday 18 March 12

62. Applications
• An improved MOS algorithm has multiple
applications
• Not just cosmological surveys (most of which are
done on smaller telescopes with larger fields)
• Globular clusters - spectroscopy of individual stars
• Galaxy clusters - studying cluster properties as a
function of redshift to bring new insights into galaxy
formation and evolution, cosmology.
Sunday 18 March 12

63. Omega Centauri (ESO)
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64. Über cluster (D. Gilbank)
z~0.7
Sunday 18 March 12

65. Thank you!
brent@saao.ac.za
Sunday 18 March 12

66. Sunday 18 March 12