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The Detection and Properties of Planetary Systems Prof. Dr. Artie Hatzes.

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1 The Detection and Properties of Planetary Systems Prof. Dr. Artie Hatzes

2 Artie Hatzes Tel:036427-863-51 Email: → Lehre → Vorlesungen → Jena

3 The Detection and Properties of Planetary Systems: Wed. 14-16 h Hörsaal 2, Physik, Helmholz 5 Prof. Dr. Artie Hatzes The Formation and Evolution of Planetary Systems: Thurs. 14-16 h Hörsaal 2, Physik, Helmholz 5 Prof. Dr. Alexander Krivov

4 Detection and Properties of Planetary Systems 14. AprilIntroduction/The Doppler Method 21. AprilThe Doppler Method/Results from Doppler Surveys I 28. AprilResults from Doppler Surveys II 05. May Transit Search Techniques: (Ground ) 06. MayTransit Search Techniques (Space: CoRoT and Kepler) 12. MayCharacterization: Internal Structure 19. MayCharacterization: Atmospheres 26. MayExoplanets in Different Environments (Eike Guenther) 02 JuneThe Rossiter McClaughlin Effect and “Doppler Imaging” of Planets 09. JuneAstrometric Detections 16. JuneDirect Imaging 23. JuneMicrolensing 30. June Habitable Planets 07. JulyPlanets off the Main Sequence

5 Literature Planet Quest, Ken Croswell (popular) Extrasolar Planets, Stuart Clark (popular) Extasolar Planets, eds. P. Cassen. T. Guillot, A. Quirrenbach (advanced) Planetary Systems: Formation, Evolution, and Detection, F. Burke, J. Rahe, and E. Roettger (eds) (1992: Pre-51 Peg)

6 Resources: The Nebraska Astronomy Applet Project (NAAP) This is the coolest astronomical website for learning basic astronomy that you will find. In it you can find: 1. Solar System Models 2. Basic Coordinates and Seasons 3. The Rotating Sky 4. Motions of the Sun 5. Planetary Orbit Simulator 6. Lunar Phase Simulator 7. Blackbody Curves & UBV Filters 8. Hydrogen Energy Levels 9. Hertzsprung-Russel Diagram 10. Eclipsing Binary Stars 11. Atmospheric Retention 12. Extrasolar Planets 13.Variable Star Photometry

7 The Nebraska Astronomy Applet Project (NAAP) On the Exoplanet page you can find: 1. Descriptions of the Doppler effect 2. Center of mass 3. Detection And two nice simulators where you can interactively change parameters: 1.Radial Velocity simulator (can even add data with noise) 2. Transit simulator (even includes some real transiting planet data)

8 And where is Nebraska?

9 Resources: The Extrasolar Planets Encyclopaedia In 7 languages Grouped according to technique Can download data, make plots, correlation plots, etc.

10 This Week: 1.Brief Introduction to Exoplanets 2.The Doppler Method: Technique

11 Why Search for Extrasolar Planets? How do planetary systems form? Is this a common or an infrequent event? Are these qualities important for life to form? Up until now we have had only one laboratory to test planet formation theories. We need more! How unique are the properties of our own solar system? Extrasolar Planets

12 "There are innumerable worlds which differ in size. In some worlds there is no sun and moon, in others they are larger than in our world, and in others more numerous. They are destroyed by colliding with each other. There are some worlds without any living creatures, plants, or moisture." Democritus (460-370 B.C.): The Concept of Extrasolar Planets

13 Believed that the Universe was infinite and that other worlds exists. He was burned at the stake for his beliefs. Giordano Bruno (1548-1600)

14 What kinds of explanetary systems do we expect to find? The standard model of the formation of the sun is that it collapses under gravity from a proto-cloud Because of rotation it collapses into a disk. Jets and other mechanisms provide a means to remove angular momentum

15 The net result is you have a protoplanetary disk out of which planets form.

16 Solar proto-planetary disk was viscous. Any eccentric orbits would rapidly be damped out – Exoplanets should be in circular orbits – Orbital axes should be aligned and prograde Giant planets need a lot of solid core to build up sufficient mass to accrete an envelope. This core should form beyond a so-called ice line at 3-5 AU – Giant Planets should be found at distances > 3 AU Our solar system is dominated by Jupiter – Exoplanetary systems should have one Jovian planet Only Terrestrial planets are found in inner regions Expectations of Exoplanetary Systems from our Solar System

17 So how do we define an extrasolar Planet? We can simply use mass: Star: Has sufficient mass to fuse hydrogen to helium. M > 80 M Jupiter Brown Dwarf: Insufficient mass to ignite hydrogen, but can undergo a period of Deuterium burning. 13 M Jupiter < M < 80 M Jupiter Planet: Formation mechanism unknown, but insufficient mass to ignite hydrogen or deuterium. M < 13 M Jupiter

18 1.Objects with true masses below the limiting mass for thermonuclear fusion of deuterium (currently calculated to be 13 Jupiter masses for objects of solar metallicity) that orbit stars or stellar remnants are "planets" (no matter how they formed). The minimum mass/size required for an extrasolar object to be considered a planet should be the same as that used in our Solar System. 2.Substellar objects with true masses above the limiting mass for thermonuclear fusion of deuterium are "brown dwarfs", no matter how they formed nor where they are located. 3.Free-floating objects in young star clusters with masses below the limiting mass for thermonuclear fusion of deuterium are not "planets", but are "sub-brown dwarfs" (or whatever name is most appropriate). IAU Working Definition of Exoplanet In other words „A non-fusor in orbit around a fusor“

19 How to search for Exoplanets 1. Radial Velocity 2. Astrometry 3. Transits 4. Microlensing 5. Imaging 6. Timing Variations

20 radialvelocitydemo.htm 8 Radial velocity measurements using the Doppler Wobble

21 Requirements: Accuracy of better than 10 m/s Stability for at least 10 Years Jupiter: 12 m/s, 11 years Saturn: 3 m/s, 30 years Radial Velocity measurements

22 Center of mass   = 8 mas at  Cen  1 mas at 10 pcs Current limits:  mas (ground) 0.1 mas (HST) Since  ~ 1/D can only look at nearby stars Astrometric Measurements of Spatial Wobble m M a D  =

23 Jupiter only 1 milliarc-seconds for a Star at 10 parsecs

24 Microlensing

25 times fainter planet 4 Arcseconds Separation = width of your hair at arms length Direct Imaging: This is hard!

26 For large orbital radii it is easier

27 Transit Searches: Techniques

28 Timing Variations If you have a stable clock on the star (e.g. pulsations, pulsar) as the star moves around the barycenter the time of „maximum“ as observed from the earth will vary due to the light travel time from the changing distance to the earth The Pulsar Planets were discovered in this way

29 The Discovery Space

30 Radial Velocity Detection of Planets: I. Techniques 1. Keplerian Orbits 2. Spectrographs/Doppler shifts 3. Precise Radial Velocity measurements

31 apap asas V P 2 = 4242 (a s + a p ) 3 G(m s + m p ) msms mpmp Newton‘s form of Kepler‘s Law

32 P 2 = 4242 (a s + a p ) 3 G(m s + m p ) Approximations: a p » a s m s » m p P2 ≈P2 ≈ 4242 ap3ap3 Gm s

33 Circular orbits: V = 2as2as P Conservation of momentum: m s × a s = m p × a p a s = m p a p msms Solve Kepler‘s law for a p : a p = P 2 Gm s 4242 () 1/3 … and insert in expression for a s and then V for circular orbits

34 V = 22 P(4  2 ) 1/3 m p P 2/3 G 1/3 m s 1/3 V = 0.0075 P 1/3 m s 2/3 mpmp = 28.4 P 1/3 m s 2/3 mpmp m p in Jupiter masses m s in solar masses P in years V in m/s 28.4 P 1/3 m s 2/3 m p sin i V obs =

35 PlanetMass (M J )V(m s –1 ) Mercury1.74 × 10 –4 0.008 Venus2.56 × 10 –3 0.086 Earth3.15 × 10 –3 0.089 Mars3.38 × 10 –4 0.008 Jupiter1.012.4 Saturn0.2992.75 Uranus0.0460.297 Neptune0.0540.281 Pluto1.74 × 10 –4 3×10 –5 Radial Velocity Amplitude of Planets in the Solar System

36 Radial Velocity Amplitude of Planets at Different a



39 eccentricity Elliptical Orbits = OF1/a O

40  : angle between Vernal equinox and angle of ascending node direction (orientation of orbit in sky) i: orbital inclination (unknown and cannot be determined P: period of orbit  : orientation of periastron e: eccentricity M or T: Epoch K: velocity amplitude Important for radial velocities Not important for radial velocities

41 Radial velocity shape as a function of eccentricity:

42 Radial velocity shape as a function of , e = 0.7 :

43 Eccentric orbit can sometimes escape detection: With poor sampling this star would be considered constant

44 Eccentricities of bodies in the Solar System

45 Important for orbital solutions: The Mass Function f(m) = (m p sin i) 3 (m p + m s ) 2 = P 2G2G K 3 (1–e 2 ) 3/2 P = period K = Amplitude m p = mass of planet (companion) m s = mass of star e = eccentricity

46 Observer Because you measure the radial component of the velocity you cannot be sure you are detecting a low mass object viewed almost in the orbital plane, or a high mass object viewed perpendicular to the orbital plane We only measure M Planet x sin i i

47 The orbital inclination We only measure m sin i, a lower limit to the mass. What is the average inclination? i The probability that a given axial orientation is proportional to the fraction of a celestrial sphere the axis can point to while maintaining the same inclination P(i) di = 2  sin i di

48 The orbital inclination P(i) di = 2  sin i di Mean inclination: =  ∫ P(i) sin i di 0  ∫ P(i) di 0 =  /4 = 0.79 Mean inclination is 52 degrees and you measure 80% of the true mass

49 The orbital inclination P(i) di = 2  sin i di But for the mass function sin 3 i is what is important : =  ∫ P(i) sin 3 i di 0  ∫ P(i) di 0 =  ∫ sin 4 i di  0 = 3  /16 = 0.59

50 The orbital inclination P(i) di = 2  sin i di Probability i <  : P(i<  ) =  ∫ P(i) di 0  ∫ 0 2 (1 – cos  ) =  < 10 deg : P= 0.03 (sin i = 0.17)

51 Measurement of Doppler Shifts In the non-relativistic case: – 0 0 = vv c We measure  v by measuring 

52 The Radial Velocity Measurement Error with Time How did we accomplish this?

53 The Answer: 1. Electronic Detectors (CCDs) 2. Large wavelength Coverage Spectrographs 3. Simultanous Wavelength Calibration (minimize instrumental effects)

54 Instrumentation for Doppler Measurements High Resolution Spectrographs with Large Wavelength Coverage

55 collimator Echelle Spectrographs slit camera detector corrector From telescope Cross disperser


57 5000 A 4000 A n = –1 5000 A 4000 A n = –2 4000 A 5000 A n = 2 4000 A 5000 A n = 1 Most of light is in n=0

58 yy ∞ 2 y m-2 m-1 m m+2 m+3   Free Spectral Range  m Grating cross-dispersed echelle spectrographs

59 On a detector we only measure x- and y- positions, there is no information about wavelength. For this we need a calibration source y x

60 CCD detectors only give you x- and y- position. A doppler shift of spectral lines will appear as  x  x →  →  v How large is  x ?

61 Spectral Resolution d 1 2 Consider two monochromatic beams They will just be resolved when they have a wavelength separation of d Resolving power: d = full width of half maximum of calibration lamp emission lines R = d ← 2 detector pixels

62 R = 50.000 →  = 0.11 Angstroms → 0.055 Angstroms / pixel (2 pixel sampling) @ 5500 Ang. 1 pixel typically 15  m 1 pixel = 0.055 Ang → 0.055 x (310 8 m/s)/5500 Ang → = 3000 m/s per pixel = v  c  v = 10 m/s = 1/300 pixel = 0.05  m = 5 x 10 –6 cm  v = 1 m/s = 1/1000 pixel → 5 x 10 –7 cm

63 RAng/pixelVelocity per pixel (m/s)  pixel Shift in mm 500 0000.0053000.060.001 200 0000.1257500.0274×10 –4 100 0000.02515000.01332×10 –4 50 0000.05030000.006710 –4 25 0000.1060000.0335×10 –5 10 0000.25150000.001332×10 –5 5 0000.5300006.6×10 –4 10 –5 1 0002.51500001.3×10 –4 2×10 –6 So, one should use high resolution spectrographs….up to a point For  v = 20 m/s How does the RV precision depend on the properties of your spectrograph?

64 Wavelength coverage: Each spectral line gives a measurement of the Doppler shift The more lines, the more accurate the measurement:  Nlines =  1line /√N lines → Need broad wavelength coverage Wavelength coverage is inversely proportional to R:  detector Low resolution High resolution 

65 Noise:  Signal to noise ratio S/N = I/  I For photon statistics:  = √I → S/N = √I I = detected photons

66  (S/N) –1 Price: S/N  t 2 exposure 14 Exposure factor 1636 144400

67 How does the radial velocity precision depend on all parameters?  (m/s) = Constant × (S/N) –1 R –3/2 (  ) –1/2  : error R: spectral resolving power S/N: signal to noise ratio  : wavelength coverage of spectrograph in Angstroms For R=110.000, S/N=150,  =2000 Å,  = 2 m/s C ≈ 2.4 × 10 11

68 The Radial Velocity precision depends not only on the properties of the spectrograph but also on the properties of the star. Good RV precision → cool stars of spectral type later than F6 Poor RV precision → cool stars of spectral type earlier than F6 Why?

69 A7 star K0 star Early-type stars have few spectral lines (high effective temperatures) and high rotation rates.

70 Including dependence on stellar parameters v sin i : projected rotational velocity of star in km/s f(T eff ) = factor taking into account line density f(T eff ) ≈ 1 for solar type star f(T eff ) ≈ 3 for A-type star f(T eff ) ≈ 0.5 for M-type star  (m/s) ≈ Constant ×(S/N) –1 R –3/2 v sin i ( 2 ) f(T eff ) (  ) –1/2

71 Eliminate Instrumental Shifts Recall that on a spectrograph we only measure a Doppler shift in  x (pixels). This has to be converted into a wavelength to get the radial velocity shift. Instrumental shifts (shifts of the detector and/or optics) can introduce „Doppler shifts“ larger than the ones due to the stellar motion z.B. for TLS spectrograph with R=67.000 our best RV precision is 1.8 m/s → 1.2 x 10 –6 cm

72 Traditional method: Observe your star→ Then your calibration source→

73 Problem: these are not taken at the same time…... Short term shifts of the spectrograph can limit precision to several hunrdreds of m/s


75 Solution 1: Observe your calibration source (Th-Ar) simultaneously to your data: Spectrographs: CORALIE, ELODIE, HARPS Stellar spectrum Thorium-Argon calibration

76 Advantages of simultaneous Th-Ar calibration: Large wavelength coverage (2000 – 3000 Å) Computationally simple: cross correlation Disadvantages of simultaneous Th-Ar calibration: Th-Ar are active devices (need to apply a voltage) Lamps change with time Th-Ar calibration not on the same region of the detector as the stellar spectrum Some contamination that is difficult to model Cannot model the instrumental profile, therefore you have to stablize the spectrograph

77 RVs calculated with the Cross Correlation Function 1. Take your spectrum, f( ) : 2. Take a digital mask of line locations, g( ) :

78 RVs calculated with the Cross Correlation Function 3. Compute Cross Correlation Function (related to the convolution) 4. Location of Peak in CCF is the radial velocity:

79 One Problem: Th-Ar lamps change with time!


81 Solution 2: Absorption cell a) Griffin and Griffin: Use the Earth‘s atmosphere:

82 O2O2 6300 Angstroms

83 Filled circles are data taken at McDonald Observatory using the telluric lines at 6300 Ang. Example: The companion to HD 114762 using the telluric method. Best precision is 15–30 m/s

84 Limitations of the telluric technique: Limited wavelength range (≈ 10s Angstroms) Pressure, temperature variations in the Earth‘s atmosphere Winds Line depths of telluric lines vary with air mass Cannot observe a star without telluric lines which is needed in the reduction process.

85 Absorption lines of the star Absorption lines of cellAbsorption lines of star + cell b) Use a „controlled“ absorption cell

86 Campbell & Walker: Hydrogen Fluoride cell: Demonstrated radial velocity precision of 13 m s –1 in 1980!

87 Drawbacks: Limited wavelength range (≈ 100 Ang.) Temperature stablized at 100 C Long path length (1m) Has to be refilled after every observing run Dangerous

88 A better idea: Iodine cell (first proposed by Beckers in 1979 for solar studies) Advantages over HF: 1000 Angstroms of coverage Stablized at 50–75 C Short path length (≈ 10 cm) Can model instrumental profile Cell is always sealed and used for >10 years If cell breaks you will not die! Spectrum of iodine

89 Spectrum of star through Iodine cell:

90 The iodine cell used at the CES spectrograph at La Silla

91 Modelling the Instrumental Profile: The Advantage of Iodine What is an instrumental profile (IP): Consider a monochromatic beam of light (delta function) Perfect spectrograph

92 Modelling the Instrumental Profile (IP) We do not live in a perfect world: A real spectrograph IP is usually a Gaussian that has a width of 2 detector pixels The IP is a „smoothing“ or „blurring“ function caused by your instrument

93 Convolution  f(u)  (x–u)du = f *  f(x):  (x):

94 Convolution  (x-u) a1a1 a2a2 g(x) a3a3 a2a2 a3a3 a1a1 Convolution is a smoothing function. In our case f(x) is the stellar spectrum and  (x) is our instrumental profile.

95 The IP is not so much the problem as changes in the IP No problem with this IP Or this IP Unless it turns into this Shift of centroid will appear as a velocity shift

96 Use a high resolution spectrum of iodine to model IP Iodine observed with RV instrument Iodine Observed with a Fourier Transform Spectrometer

97 FTS spectrum rebinned to sampling of RV instrument FTS spectrum convolved with calculated IP Observed I 2

98 Model IP Gaussians contributing to IP IP =  g i Sampling in Data space Sampling in IP space = 5×Data space sampling

99 Instrumental Profile Changes in ESO‘s CES spectrograph 2 March 1994 14 Jan 1995

100 Instrumental Profile Changes in ESO‘s CES spectrograph over 5 years:

101 Mathematically you solve this equation: I obs ( ) = k[T I2 ( )I s ( +  )]*PSF Where: I obs ( ) : observed spectrum T I2 : iodine transmission function k: normalizing factor I s ( ): Deconvolved stellar spectrum without iodine and with PSF removed PSF: Instrumental Point Spread Function Problem: PSF varies across the detector. Solve this equation iteratively

102 Modeling the Instrumental Profile In each chunk: Remove continuum slope in data : 2 parameters Calculate dispersion (Å/pixel): 3 parameters (2 order polynomial: a0, a1, a2) Calculate IP with 5 Gaussians: 9 parameters: 5 widths, 4 amplitudes (position and widths of satellite Gaussians fixed) Calculate Radial Velocity: 1 parameters Combine with high resolution iodine spectrum and stellar spectrum without iodine Iterate until model spectrum fits the observed spectrum

103 Sample fit to an observed chunk of data

104 Sample IP from one order of a spectrum taken at TLS


106 Valenti, Butler, and Marcy, 1995, PASP, 107, 966, „Determining Spectrometer Instrumental Profiles Using FTS Reference Spectra“ Butler, R. P.; Marcy, G. W.; Williams, E.; McCarthy, C.; Dosanjh, P.; Vogt, S. S., 1996, PASP, 108, 500, „Attaining Doppler Precision of 3 m/s“ Endl, Kürster, Els, 2000, Astronomy and Astrophysics, “The planet search program at the ESO Coudé Echelle spectrometer. I. Data modeling technique and radial velocity precision tests“ Additional information on RV modeling:

107 Barycentric Correction Earth’s orbital motion can contribute ± 30 km/s (maximum) Earth’s rotation can contribute ± 460 m/s (maximum)

108 Needed for Correct Barycentric Corrections: Accurate coordinates of observatory Distance of observatory to Earth‘s center (altitude) Accurate position of stars, including proper motion:   ′  ′ Worst case Scenario: Barnard‘s star Most programs use the JPL Ephemeris which provides barycentric corrections to a few cm/s

109 For highest precision an exposure meter is required time Photons from star Mid-point of exposure No clouds time Photons from star Centroid of intensity w/clouds Clouds

110 Differential Earth Velocity: Causes „smearing“ of spectral lines Keep exposure times < 20-30 min

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