small scale structure in voids danny pan advisor: michael vogeley
TRANSCRIPT
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Small Scale Structure in VoidsSmall Scale Structure in Voids
Danny PanDanny Pan
Advisor: Michael VogeleyAdvisor: Michael Vogeley
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Motivation/GoalMotivation/Goal
LL-CDM models show small scale structure -CDM models show small scale structure in voidsin voids
Goal is to verify the small scale structure of Goal is to verify the small scale structure of voidsvoids
Possible results?Possible results?Structure exists, agree with modelsStructure exists, agree with modelsStructure does not exist, models may not tell Structure does not exist, models may not tell
the whole storythe whole story
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Millenium Run SimulationMillenium Run Simulation
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Simulated UniverseSimulated Universe
Gottlober (2003)Gottlober (2003)
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OutlineOutline
IntroductionIntroductionResearch in VoidsResearch in VoidsVoidFinder (finds voids!)VoidFinder (finds voids!)Methods of AnalysisMethods of Analysis
Void StatisticsVoid StatisticsCorrelation FunctionCorrelation FunctionShapeFinderShapeFinder
Conclusion/ResultsConclusion/ResultsFuture WorkFuture Work
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IntroductionIntroduction
The Universe contains objects, but it is The Universe contains objects, but it is mostly emptymostly empty
Modern cosmology tells us that evolution of Modern cosmology tells us that evolution of the Universe causes clumpinessthe Universe causes clumpinessDense regions stay dense and grow Dense regions stay dense and grow
asymmetricallyasymmetricallyUnderdense regions stay underdense and Underdense regions stay underdense and
grow symmetricallygrow symmetricallyResult is spherical voids with dense walls in the Result is spherical voids with dense walls in the
UniverseUniverse
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Research in VoidsResearch in Voids
Gregory and Tifft (1976) first looked at Gregory and Tifft (1976) first looked at structure in Coma Superclusterstructure in Coma SuperclusterFound regions that seemed very emptyFound regions that seemed very empty
Kirshner et al (1982) found a 1,000,000 cu Kirshner et al (1982) found a 1,000,000 cu Mpc region in Bootes that was emptyMpc region in Bootes that was empty
Interest in voids grewInterest in voids grewRojas et al. (2004) observed differences in Rojas et al. (2004) observed differences in
void and wall galaxiesvoid and wall galaxies
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VoidFinderVoidFinder
Used to determine sample of Void regions Used to determine sample of Void regions and Void galaxiesand Void galaxies
Volume limited sample from SDSSVolume limited sample from SDSS4783 square degrees of the sky4783 square degrees of the skymagnitude cut of 17.5magnitude cut of 17.5
approximately Lapproximately L** at furthest distance at furthest distance
radial cut of 100 and 300 hradial cut of 100 and 300 h-1-1 Mpc Mpc61,000 galaxies61,000 galaxies
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GalaxiesGalaxies
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3 Nearest Neighbors3 Nearest Neighbors
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Potential Void GalaxiesPotential Void Galaxies
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Walls OnlyWalls Only
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Maximal SpheresMaximal Spheres
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Void GalaxiesVoid Galaxies
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VoidFinderVoidFinder
ResultsResults527 void regions527 void regions3369 void galaxies3369 void galaxies40% of the volume are voids40% of the volume are voids
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Picture of VoidFinderPicture of VoidFinder
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Methods of AnalysisMethods of Analysis
Void StatisticsVoid StatisticsCorrelation FunctionCorrelation FunctionShapeFinderShapeFinder
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Void StatisticsVoid Statistics
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Void StatisticsVoid Statistics
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Void StatisticsVoid Statistics
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Void StatisticsVoid Statistics
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Void StatisticsVoid Statistics
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Correlation FunctionCorrelation Function
Probability of two points separated by a Probability of two points separated by a distance r is:distance r is:
P r =n 2
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Correlation FunctionCorrelation Function
Landy-Szalay (1993) equationLandy-Szalay (1993) equation
Correlation depends on data points as well as Correlation depends on data points as well as random pointsrandom points
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Correlation FunctionCorrelation Function
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ShapeFinderShapeFinder
Defined by Sahni et al. (1998) to assess Defined by Sahni et al. (1998) to assess shapes of objectsshapes of objects
Uses Minkowski Functionals to help Uses Minkowski Functionals to help determine shapesdetermine shapesVolume (V)Volume (V)Surface Area (S)Surface Area (S) Integrated Mean Curvature (C)Integrated Mean Curvature (C)Gaussian Curvature (G)Gaussian Curvature (G)
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ShapeFinderShapeFinder
Can determine 3 phase space lengthsCan determine 3 phase space lengths L1 = V/SL1 = V/S L2 = S/CL2 = S/C L3 = CL3 = C
L1=L2<L3 FilamentL1=L2<L3 Filament L1<L2=L3 PancakeL1<L2=L3 Pancake
2 ShapeFinder statistics2 ShapeFinder statistics K1 = (L2-L1)/(L2+L1)K1 = (L2-L1)/(L2+L1) K2 = (L3-L2)/(L3+L2)K2 = (L3-L2)/(L3+L2)
K1=0, K2=0 SphereK1=0, K2=0 Sphere K1=1, K2=0 PancakeK1=1, K2=0 Pancake K1=0, K2=1 FilamentK1=0, K2=1 Filament
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ShapeFinder ImagesShapeFinder Images
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ShapeFinder ResultsShapeFinder Results
TABLE OF SHAPEFINDER RESULTS ON TABLE OF SHAPEFINDER RESULTS ON LARGEST VOIDSLARGEST VOIDS
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ConclusionsConclusions
Void Statistics match other observational Void Statistics match other observational results as well as theoretical modelsresults as well as theoretical models
Radial density profiles match very well with Radial density profiles match very well with expected results, validates VoidFinderexpected results, validates VoidFinder
2 Point Correlation Function matches 2 Point Correlation Function matches various other samplesvarious other samples Implies correlation of underdense regions Implies correlation of underdense regions
mimic that of the entire samplemimic that of the entire sample
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Future WorkFuture Work
ShapeFinder needs to be expanded to ShapeFinder needs to be expanded to accommodate for multiple “objects” within accommodate for multiple “objects” within each void regioneach void region
Analysis needs to be done on the Analysis needs to be done on the Millenium Run sample or another Lambda Millenium Run sample or another Lambda CDM model to compare resultsCDM model to compare results
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AcknowledgementsAcknowledgements
Thank youThank youDr. Michael VogeleyDr. Michael VogeleyDr. Fiona HoyleDr. Fiona Hoyle
CommitteeCommitteeDr. Avijit GhoshDr. Avijit GhoshDr. Dave GoldbergDr. Dave GoldbergDr. Bhuvnesh JainDr. Bhuvnesh JainDr. Gordon RichardsDr. Gordon Richards