Seeing the Sky Visualization & Astronomers Alyssa A. Goodman Harvard Smithsonian Center for Astrophysics & Radcliffe Institute for Advanced Study @aagie WorldWide Telescope Gm1m2 F= gluemultidimensional data exploration R2 Cognition “Paper of the Future” Language* Data Pictures Communication *“Language” includes words & math Why Galileo is my Hero Explore-Explain-Explore Notes for & re-productions of Siderius Nuncius 1610 WorldWide Telescope Galileo’s New Order, A WorldWide Telescope Tour by Goodman, Wong & Udomprasert 2010 WWT Software Wong (inventor, MS Research), Fay (architect, MS Reseearch), et al., now open source, hosted by AAS, Phil Rosenfield, Director see wwtambassadors.org for more on WWT Outreach WorldWide Telescope Galileo’s New Order, A WorldWide Telescope Tour by Goodman, Wong & Udomprasert 2010 WWT Software Wong (inventor, MS Research), Fay (architect, MS Reseearch), et al., now open source, hosted by AAS, Phil Rosenfield, Director see wwtambassadors.org for more on WWT Outreach Cognition “Paper of the Future” Language* Data Pictures Communication *“Language” includes words & math enabled by d3.js (javascript) outputs d3po Cognition Communication [demo] [video] Many thanks to Alberto Pepe, Josh Peek, Chris Beaumont, Tom Robitaille, Adrian Price-Whelan, Elizabeth Newton, Michelle Borkin & Matteo Cantiello for making this posible. 1610 4 Centuries from Galileo to Galileo 1665 1895 2009 2015 WorldWide Telescope Gm1m2 F= gluemultidimensional data exploration R2 WorldWide Telescope gluemultidimensional data exploration WorldWide Telescope gluemultidimensional data exploration Data, Dimensions, Display 1D: Columns = “Spectra”, “SEDs” or “Time Series” 2D: Faces or Slices = “Images” 3D: Volumes = “3D Renderings”, “2D Movies” 4D:4D Time Series of Volumes = “3D Movies” Data, Dimensions, Display Spectral Line Observations Loss of 1 dimension Mountain Range No loss of information Data, Dimensions, Display mm peak (Enoch et al. 2006) sub-mm peak (Hatchell et al. 2005, Kirk et al. 2006) 13CO (Ridge et al. 2006) mid-IR IRAC composite from c2d data (Foster, Laakso, Ridge, et al.) Optical image (Barnard 1927) 3D Viz made with VolView AstronomicalMedicine@ NATURE Vol 457 1 January 2009 LETTERSLETTERS NATURE | Vol 457 | 1| January 2009| abab usingusing 2D maps 2D of maps column of column density. density. With this With early this 2D work early as 2D inspira- work as inspira- tion,tion, we have we developed have developed a structure-identification a structure-identification algorithm algorithm that that abstractsabstracts the hierarchical the hierarchical structure structure of a 3D (ofp– ap– 3Dv) data (p–p cube–v) data into cube into an easilyan easily visualized visualized representation representation called a ‘dendrogram’ called a ‘dendrogram’10. Although10. Although 11,12 well developedwell developed in other in data-intensive other data-intensive fields , fields it is curious11,12, it is that curious the that the applicationapplication of treeof methodologies tree methodologies so far in astrophysicsso far in astrophysics has been rare, has been rare, and almostand almost exclusively exclusively within thewithin area the of galaxy area of evolution, galaxy evolution, where where ‘merger trees’ are being used with increasing frequency13. ‘merger trees’ are being used with increasing frequency13. (dec.) (dec.) Figure 3 and its legend explain the construction of dendrograms v vz z y y (dec.) (dec.) Figure 3 and its legend explain the construction of dendrograms v vz z y y schematically. The dendrogram quantifies how and where local max- x (RA) x (RA) ima ofschematically. emission merge The with dendrogram each other, quantifies and its implementation how and where is local max- x (RA) x (RA) explainedima inof Supplementary emission merge Methods. with each Critically, other, the and dendrogram its implementation is is Click to rotate determinedexplained almost in Supplementary entirely by the data Methods. itself, and Critically, it has negligible the dendrogram is Click to rotate sensitivitydetermined to algorithm almost parameters. entirely To by make the data graphical itself, presentation and it has negligible c 8 Self-gravitating Self-gravitating All structure leaves structures possiblesensitivity on paper to and algorithm 2D screens, parameters. we ‘flatten’ Tothe makedendrograms graphical of 3D presentation c 8 Self-gravitating Self-gravitating All structure data (see Fig. 3 and its legend), by sorting their ‘branches’ to not 6 leaves structures possible on paper and 2D screens, we ‘flatten’ the dendrograms of 3D cross, which eliminates dimensional information on the x axis while (K) 6 data (see Fig. 3 and its legend), by sorting their ‘branches’ to not mb 4 preserving all information about connectivity and hierarchy. T cross, which eliminates dimensional information on the x axis while (K) Numbered ‘billiard ball’ labels in the figures let the reader match mb 42 preserving all information about connectivity and hierarchy. T features between a 2D map (Fig. 1), an interactive 3D map (Fig. 2a online)Numbered and a sorted ‘billiard dendrogram ball’ labels (Fig. 2c). in the figures let the reader match 20 features between a 2D map (Fig. 1), an interactive 3D map (Fig. 2a d CLUMPFIND segmentation A dendrogram of a spectral-line data cube allows for the estimation 8 online) and a sorted dendrogram (Fig. 2c). 2009 0 of key physical properties associated with volumes bounded by iso- d 86 CLUMPFIND segmentation surfaces,A such dendrogram as radius (ofR), a velocityspectral-line dispersion data cube (sv) and allows luminosity for the estimation (L). Theof keyvolumes physical can have properties any shape, associated and in other with work volumes14 we focus bounded on by iso- (K) mb 64 the significancesurfaces, such of the as especially radius (R elongated), velocity features dispersion seen (s inv) L1448 and luminosity T (Fig.( 2a).L). The The volumes luminosity can is have an approximate any shape, and proxy in otherfor mass, work such14 we focus on (K) 20 2 21 21 2 that Mlum 5 X13COL13CO, where X13CO 5 8.0 3 10 cm K km s mb 4 the significance of the especially elongated features seen in L1448 T (ref. 15;(Fig. see 2a). Supplementary The luminosity Methods is an and approximate Supplementary proxy Fig. for 2). mass, such 0 The derived values for size, mass and velocity dispersion can20 then2 be 21 21 2 that Mlum 5 X13COL13CO, where X13CO 5 8.0 3 10 cm K km s 3D PDF Figure 2 | Comparison of the ‘dendrogram’ and ‘CLUMPFIND’ feature- used to estimate the role of self-gravity at each point in the hierarchy, (ref. 15; see Supplementary Methods and Supplementary Fig. 2). 13 via calculation of an ‘observed’ virial parameter, a 5 5s 2R/GM . identification0 algorithms as applied to CO emission from the L1448 obs v lum region of Perseus. a, 3D visualization of the surfaces indicated by colours in In principle,The derived extended values portions for size, of the mass tree (Fig. and 2,velocity yellow highlighting)dispersion can then be used to estimate the role of self-gravity at each point in the hierarchy, Figurethe dendrogram 2 | Comparison shown ofin c the. Purple ‘dendrogram’ illustrates theand smallest ‘CLUMPFIND’ scale self- feature- where aobs , 2 (where gravitational energy is comparable to or larger 13 2 High-Dimensional identificationgravitating structures algorithms in the as region applied corresponding to CO emission to the leaves from of the the L1448 than kineticvia calculation energy) correspond of an ‘observed’ to regions virial of parameter,p–p–v spacea whereobs 5 self-5sv R/GMlum. dendrogram; pink shows the smallest surfaces that contain distinct self- region of Perseus. a, 3D visualization of the surfaces indicated by colours ingravityIn is principle, significant. extended As aobs only portions represents of the the tree ratio (Fig. of kinetic 2, yellow energy highlighting) thegravitating dendrogram leaves shown within inthem;c. Purple and green illustrates corresponds the smallest to the surface scale self-in the to gravitationalwhere a energy, 2 (where at one gravitational point in time, energy and does is comparable not explicitly to or larger data cube containing all the significant emission. Dendrogram branches obs gravitating structures in the region corresponding to the leaves of the 16 corresponding to self-gravitating objects have been highlighted in yellow capturethan external kinetic over-pressure energy) correspond and/or magnetic to regions fields of ,p its–p measured–v space where self- dendrogram; pink shows the smallest surfaces that contain distinct self- over the range of T (main-beam temperature) test-level values for which valuegravity should only is significant. be used as aAs guidea toonly therepresents longevity (boundedness) the ratio of kinetic of energy data in a gravitating leaves withinmb them; and green corresponds to the surface in the obs the virial parameter is less than 2. The x–y locations of the four ‘self- any particularto gravitational feature. energy at one point in time, and does not explicitly data cube containing all the significant emission. Dendrogram branches gravitating’ leaves labelled with billiard balls are the same as those shown in capture external over-pressure and/or magnetic fields16, its measured correspondingFig. 1. The 3D visualizations to self-gravitating show position–position–velocity objects have been highlighted (p–p–v) in space. yellow value should only be used as a guide to the longevity (boundedness) of overRA, theright range ascension; of Tmb dec.,(main-beam declination. temperature) For comparison test-level with the values ability for of which Local max any particular feature. “Paper” thedendrograms virial parameter (c) to track is less hierarchical than 2. The structure,x–y locationsd shows of a pseudo- the four ‘self- Test level gravitating’dendrogram leaves of the labelled CLUMPFIND with billiard segmentation balls are (b), the with same the assame those four shown in labels used in Fig. 1 and in a. As ‘clumps’ are not allowed to belong to larger Local max Fig. 1. The 3D visualizations show position–position–velocity (p–p–v) space. Leaf RA,structures, right ascension; each pseudo-branch dec., declination.