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Astronomy Visualization The State of the Art 207 th American Astronomical Society Meeting Washington, DC January 11, 2006 STScI Public Lecture Series February 7, 2006

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Page 1: Astronomy Visualization The State of the Art - …hubblesite.org/about_us/public_talks/presentations/summers_2006_02...Astronomy Visualization The State of the Art ... Druyan and SkyWorks

Astronomy VisualizationThe State of the Art

207th American Astronomical Society MeetingWashington, DCJanuary 11, 2006

STScI Public Lecture SeriesFebruary 7, 2006

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Astro-Viz Special Session

• Frank Summers, John Stoke• Bryan Preston, Lucy Albert, Faith Abney

• Call for Viz – 46 submissions• Jury Duty• DVD – 40 visualizations, 2 hours• Session – 9 visualizations

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Scientific Visualization in the Age of Buzz Lightyear,

Yoda, and Gandalf

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Hollywood vs Academia• Simulation• Illustrate point• Complex physics• Simple geometry• Simple lighting• Simple camera• No compositing• Exact / approximate• Intellectual• Left brain• Accuracy

• Animation• Tell story• Simple physics• Complex geometry• Complex lighting• Complex camera• Heavy compositing• Whatever looks good• Emotional• Right brain• Aesthetics

Fantasy Verité

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Inspiration

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Illustration

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Intuition

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Intuition

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Flying Through Valles Marineris

Dana BerrySkyworks Digital Animation

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“Valles Marineris”

Animation Case StudyAnimation by Dana Berry and Kees Veenenbos

Executive Producers Paul Gasek, Ann Druyan and Steve Burns

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The Cosmic Background

• Production began in 1978 through 1979 at a cost of $8.7 Million by KCET Los Angeles.

• 13 Episodes first broadcast in 1980.• Audience eventually reached well over half a

billion viewers in 60 countries. • The series won both Emmy and Peabody Awards.• The spinoff book from the series spent 70 weeks

in the New York Times best seller list, including 15 weeks as the number 1 best seller.

• Proved that art and science can peacefully coexist.

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The Cosmic Background• Several iterations exist.

– Tenth Anniversary edition, with an epilogue added in which Sagan updates the science of each show.

– 20th Anniversary edition was released with some updated imagery.

– The Arts and Entertainment Channel scheduled to broadcast 20th anniversary edition on the evening of September 11, 2001. Consequently the show was shelved and never aired.

– The Discovery Channel arranged with rights owner Ann Druyan and SkyWorks Digital to recut each show and swap out nearly all of the graphics.

– Series aired on the Discovery Science Channel in fall of 2005 and will be repeated in 2006. The fall broadcast increased the size of the Science Channel’s audience 6-fold. No plans for DVD distribution.

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The Task:

• PBS non-commercial format 58 minutes to be edited for commercial 44 minute format: 14 minutes to be trimmed from each show.

• Prune scientifically outdated portions of the show. • Swap original graphics and animation with newer,

more scientifically correct visualizations.• Produce 164 new animations 5 months within small,

finite budget.• Minimize impact on other concurrent in-house

productions.

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Valles MarinerisGraphics Update Case Study

• 3 kinds of science visualization:– Data visualization, simulation: reveals information

hidden within a data set.– Pedagogical animation: teaches us something.– Experiential animation. Emphasizes emotion,

drama and art. Cosmos animation is experiential.

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Valles MarinerisGraphics Update Case Study

• Make decision to replace existing studio model footage.• Plan production strategy and choose production tools.

– Storyboards– Source images– Division of labor

• Build accurate 3D model of Valles Marineris Topography.• Add correct color for ground, lighting and atmospherics. • Choreograph Camera Move.• Develop Render Strategy.

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Valles MarinerisGraphics Update Case Study

Original fly-through was generated from a studio model. (Don Davis, Adlolf Schaller, Rick Sternbach, John Allison, Justin Segal) In its day this was state-of-the-art special effects.

Camera begins at high altitude and descends into the valley.

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Valles MarinerisGraphics Update Case Study

• New Animation was totally data driven MOLA data projected into a deformation plane.

• Camera move roughly follows original studio model shot.

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Valles MarinerisGraphics Update Case Study

Tools Used:Terragen V1 – Generate framesAfter FX – Compositing, noise reduction, motion blur and

color correction

Resources Used: Mars Global Surveyor MOLA data set for topographyRendering Hardware: one 3.6mhz Sony and four 3.2mhz

Hewlitt Packards (Average render time 46 minutes per frame, 3,000 frames. (cpus spent 1 month rendering this shot in hi-def).

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Valles MarinerisGraphics Update Case Study

• The Deformation Map, (right) where the deeper the hole, the darker the gray tone. Image on the left shows the deformation map projected and shaded.

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Valles MarinerisGraphics Update Case Study

• Camera Path roughly the same as original, except the camera spins around to look back as we rise above the canyon.

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Valles MarinerisGraphics Update Case Study

General look of the sequence has more earthlike feel. The canyon feels broader, wider than in the original version.

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Valles MarinerisGraphics Update Case Study

• The MOLA data was not high enough resolution to sustain illusion as camera approached the ground.

• Soft fractal noise added to MOLA data to help sustain illusion.• Final render showed jitter problems caused by the fractal noise.• Solution to jitter was painful: cut fractal noise down to .001% of

its original value, scale up original render by 200% and scale it back down and add motion blur in After Effects.

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Cosmos, 25th Anniversary

“Evolution is a fact, not a theory.”-Carl Sagan

Show 2, One Voice in the Cosmic Fugue

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Strange New Worlds

Robert HurtSpitzer Science Center

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The Art of Science• Artist’s Concepts Are Powerful

Communications Tool– A picture can help explain complex result at a glance

– A movie can tell more in short clip

– Aesthetic appeal can stimulate interest to read more

• Developing the Concept– Identify key science themes of result

– Artist, PA rep, & PI discuss visualization

• Converge on single image to tell story

• Develop “bullet list” of science results for image

• Ongoing artist/scientist interaction can speed convergence on final product

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Case Study:Transiting Planets

• The Data:– Graph of light curve

from two stars showing dip when planet passes behind star

• The Story:– First light ever directly

detected from extrasolar “hot Jupiter” worlds

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Case Study:Transiting Planets

• Goal for the animation:– Visually explain the significance of the data graphs

• Science Bullet Points:– Planet is close to star, Jupiter-sized but very different from Jupiter– Visible light: only reflected light from sun– Infrared light: planet is self-luminous– Improved viewing contrast in the infrared– Geometry of the transiting system: we see planet pass behind star– Dip in light curve implies we see light from planet (blended with

light from the star)

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Case Study:Transiting Planets

• First Sequence:– “Dramatic” shot showing system.– Start in familiar visible light, then transition to infrared view– Show best-guess infrared “color”– Planetary atmosphere derived from atmospheric simulation of “hot Jupiters”

• Second Sequence:– Maintain infrared view through movie– Start with familiar overhead view with orbit for reference– Pivot down to our line-of-sight, drop orbit once the geometry is clear– Overlay time-synchronized graph as planet passes behind star

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Galactic Center Fly-in

Andrew HansonIndiana University, Bloomington

Priscilla FrischUniversity of Chicago

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2006 AAS Washington DC

Galactic Center Fly-In

Astronomy: Navigating to Compact Radio Source Sgr A* at Center of Milky Way Galaxy

Computer Science: Correctly Visualizing Galactic Scenery across Huge Scales

Andrew Hanson (Indiana University)Priscilla Frisch (University of Chicago)

AAS, Washington DC, January 2006

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2006 AAS Washington DC

Galactic Center Data Cover an Immense Spatial and Spectral Range

•Task: Zoom in from 8 kpc to 3 Light Days away from the Galactic Center Black Hole.

–Spatial scale: Over 6 orders of magnitude–Spectral scale: Radio to IR to X-Ray

1010 A (90 cm) 105 A (20 μm) 1 A (10 keV)

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2006 AAS Washington DC

Zoom from 8 kpc Solar Distance to 3 Light Daysaway from the Black Hole at the Galaxy Center

Axel Mellinger Milky WayGalaxy Montage (many kpc)

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2006 AAS Washington DC

Align Infrared, X-ray, Radio Images with uncertain common point sources and very different scales

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2006 AAS Washington DC

Rosetta Stone Images needed for Alignment when Point Sources Lacking

•Hard to match diffuse object locations•Exact pointing hard to get for large FOV images•IPAC gallery has Combined 2MASS-MSX image

R=MSX 6-11 μm, G=2MASS Ks, B=2MASS J.• MSX Image: R=21 μm, G=13 μm, Β=8 μm•Chandra gallery image has RGB radio, infrared, X-ray image: 21 μm -> 90 cm -> 10 keV

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2006 AAS Washington DC

2MASS-MSX(IPAC gallery)

MSX(IPAC gallery)

X-ray,Radio, MSX(Chandra gallery)

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2006 AAS Washington DC

Task: Cross Register Diverse Data Sources

•Match both diffuse and pointlike objects•Align small subimages deep inside enclosing images•Match coordinate system and epoch•Adapt computer graphics methods to 6+ order-of-magnitude• Flyin: final pixel is 1/millionth of the starting pixel

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2006 AAS Washington DC

Cross-RegistrationSolution Example

DustyBowshock (Keck)

Ionized GasMinispiral (VLA) Galactic Center

(Paranal)

Dusty Bowshock(Keck)

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2006 AAS Washington DC

VISUALIZATION AS A TOOL TO UNCOVER THE SCIENTIFIC CONTEXT OF THE

GALACTIC CENTER

SYNOPSIS: This is a pedagogically stimulating exercise because data are embedded in their full multispectral and multiscale context, creating a rich landscape marked by galactic landmarks derived from all colors of the spectrum.

Acknowledgments: NASA grants NAG5-8163, NAG5-11999, NAG5-13558. Many individuals helped with the galactic center science, including Tom Geballe, Mark Morris, Mark Reid, and Andrea Ghez.

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Hubble: Galaxies Across Space and Time

Frank SummersSpace Telescope Science Institute

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GOODS CDFS

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GOODS CDFS

32,195 pixels

19,464 pixels

627 M pixels

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ResolutionsTV / VGA 640 x 480 300 kXGA 1024 x 768 800 kHDTV 1920 x 1080 2.1 MWFPC2 1600 x 1600 2.6 MDome < 3800 x 3800 < 14.4 MACS WFC 4096 x 4096 16.7 MViz Wall 5120 x 4096 21 MIMAX 5616 x 4096 23 MSombrero 11,472 x 6429 74 MGOODS 32,195 x 19,464 627 M

Dimensions Total Pixels

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Image Cleaning

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Image Cleaning

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Image Cleaning

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Galaxy Cut-outs

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Galaxy Cut-outs• 11,392 galaxies

with image & redshift

• 3D Model– texture mapped

planes, sized for distance

– always face camera

– transparency proportional to brightness

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Data Pipeline

Culling, crossmatch (perl)

Crop, clean, alpha(perl, IRAF, C)

Galaxy Images

RedshiftSourceData

ImageSourceData

SourceSegmentation

Map

GOODS Images

GalaxyData

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Data to Visualization

• Test in Maya• Save as ASCII• Edit• Shortcuts

• Galaxy script• Command script• Camera script• About a million lines

of MEL

GalaxyData

3D modelling(perl) MEL Scripts

Galaxy Images

Maya

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Camera tracks in x, y and z Dots are keyframe positions

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Visualization Wall

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Hubble: Galaxies Across Space and Time

Best Short Film 2004Large Format

Cinema Association

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Klemperer’s Dream

John DubinskiUniversity of Toronto

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Gravitas ProjectScience and Art Collaboration

John Dubinski - astronomy/simulationsJohn Kameel Farah - composer/pianist

Goal: Express the beauty of the dynamic universe usinganimations from supercomputer simulations accompanied by original music. The idea is to inspire people on many levels including the scientific, educational, artistic, musical and spiritual.

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Project Components• Website - www.galaxydynamics.org

– Downloadable animations with detailed descriptions• Gravitas DVD - 9 animations - 45:00 runtime

– Structure formation, galaxy interactions, galaxy clusters, star clusters, some 3D animation, scientific and artistic narration (optional), educational booklet

• Live solo performance by John Farah with visualsby JD - 3 shows so far in Toronto with more planned

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Plans for 2006• Many new animations planned with improved

numerical resolution plus new material• HD format resolution• HD-DVD/Blu-ray version• Digital Dome/IMAX format animations…• More live performances

Please check out: www.galaxydynamics.org

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Mapping the Universe with the Sloan Digital Sky Survey

Mark SubbaRaoAdler Planetarium and Astronomy

Museum and University of Chicago

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Who are we?Who are we?

What are we trying to visualize?What are we trying to visualize?

Visualization:Dinoj Surendran Mark SubbaRaoDaniela Rosner

Advisors:Randy LandsbergJoshua Frieman

Music:Dan MohrTaylor AuneColin BischoffJay CrosbyJoaquin Viera

How is it used?How is it used?

Sloan Digital Sky Survey• Large Scale Structure• Survey Process

• Interactive stereoscopic presentations• Stereoscopic movie in Adler’s 3D theater• Full-dome Planetarium shows

Jose Francisco Salgado

Dan Dry

COSMUS: KICP (U. of Chicago) + Adler Planetarium

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Year 1

Year 5Year 4

Year 3

Year 2

SDSS

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Immersion vs. Context(Immersion vs. Context(LODLOD))

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Tools:Tools:Partiview - Stuart Levy

for the visualizationFinal Cut Pro

for video editing

Story:Story:

flythrough -> control room

telescope->flythrough-> control room

VizViz Details:Details:• > 500,000 objects• Comoving distance• 104 galaxy images matched to spectral type• Size scaled up ~ factor of 50• Orientations are random

Jurek Krzesinski

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Flight Through the Millenium Simulation

Simon WhiteMax Planck Institute for Astrophysics

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Flight through the Millennium Simulation

Volker Springel & Simon D.M. WhiteMax-Planck-Institut für Astrophysik

Washington D.C., January 2006

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Millennium Run Statistics

Particle number: N = 21603 = 10,077,696,000 ≈ 1010

Box size: L = 500 Mpc/h, Softening: ε = 5 kpc/h L/ε = 105

Initial redshift: zinit = 127

Cosmology: Ωtot=1, Ωm=0.25, Ωb=0.045, h =0.73, n=1, σ8=0.9

343,000 processor-hours on 512 nodes of an IBM Regatta (28 machine days @ 0.2 Tflops using 1 Tbyte RAM)

Full raw and reduced data stored at 64 redshifts

27 Tbytes of stored data A testbed for studying galaxy formation models

Springel et al 2005: The Virgo Consortium

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Visualizing the Millennium

Need to be faithful to the available linear dynamic range (~106) Zoom by a factor of ~1000

Need to (adaptively) filter out discreteness noise Define a local (SPH) smoothing kernel in 3-DUse to assign densities to image pixels

Encode scientific information using both colour and intensity e.g. intensity for mass/luminosity density

colour for velocity dispersion/B – V colour

Use motion to convey 3-D structure

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z = 0 Dark Matter

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z = 0 Galaxy Light

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