optimization of multi-object spectroscopy in astronomy
TRANSCRIPT
Optimisation of Multi-Object Spectroscopy
in AstronomyBrent Miszalski
SALT Research [email protected]
Sunday 18 March 12
• Galaxy redshift surveys
• Multi-object spectroscopy (MOS)
• MOS field configuration by simulated annealing
• MOS at the Southern African Large Telescope (SALT)
Overview
Miszalski et al. 2006, MNRAS, 371,1537Sunday 18 March 12
NGC 1376Sunday 18 March 12
M 101Sunday 18 March 12
Hubble Ultra Deep FieldSunday 18 March 12
• 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=H0 d
Hubble’s law
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Galaxies cluster together
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Comoving distance
Density parameters
matter
dark energy
curvature
DC - distance between two galaxies
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Millenium Simulation (Springel et al. 2005)Sunday 18 March 12
• 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...
We need more redshifts
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Multi-Object Spectroscopy
• Developed in late 80s/early 90s
• Highly successful but very complex (more focus on getting instrument working, rather than optimising it)
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2dF: Two-degree Field facility4-m Anglo-Australian
Telescope
Lewis et al. (2002)Sunday 18 March 12
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wavelength
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wavelength
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2dFGRS (Colless et al. 2001)
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N(z)~250,000!
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WigglezDrinkwater et al. 2010
wigglez.swin.edu.au
Sunday 18 March 12
WigglezDrinkwater et al. 2010
Blake et al. 2010
wigglez.swin.edu.au
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WigglezDrinkwater et al. 2010
Blake et al. 2010
wigglez.swin.edu.au
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• 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
• Prefer straighter fibres
A challenging optimisation problem
[quicker config times]
[no structure imprint]
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Fibre and target reach
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Fibre and target reach
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• 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
Simulated Annealing
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Travelling Salesman ProblemNumerical Recipes (Ch. 10)
(b) large river penalty (c) negative river penalty!
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• 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
Annealing schedule
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Four randomisation cases
before
after
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Metropolis algorithm
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Metropolis algorithm
Boltzmann distribution instatistical mechanics
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Objective functionclose pairs
targetpriority
straightenfibres maximise
me!
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Objective function
Temperature
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A sample run
Temperature
E
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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 eachSunday 18 March 12
Total target yield
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Total target yield
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Target priorities
highestlowestSunday 18 March 12
Target priorities
highestlowestSunday 18 March 12
Target priorities
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Target priorities
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Target priorities
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Uniformity
Oxford
SA
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OLD(Oxford)
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NEW(Annealing)
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Fibre straightness
γ=0.0 γ=0.125 γ=2.0
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Fibre straightness
γ=0.0 γ=0.125 γ=2.0
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• 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!
Algorithm summary
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• 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
SALT
photo: Lisa CrauseSunday 18 March 12
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• 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
MOS masks
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MOS @ SALTLaser mask cutter
Slit mask cutter software GUI
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~1/
2 de
gree
IMACS on Magellan 6.5-m telescope
Chile
courtesyDavid
Gilbank
Sunday 18 March 12
~1/
2 de
gree
IMACS on Magellan 6.5-m telescope
Chile
courtesyDavid
Gilbank
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slits
courtesyDavid
Gilbank
Sunday 18 March 12
courtesyDavid
Gilbank
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• 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
AIMS project
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• 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?
MOS mask design issues
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• 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!
MOS mask design issues
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• 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.
Applications
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Omega Centauri (ESO)
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Über cluster (D. Gilbank)z~0.7
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