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Extrasolar planet detection: a view from the trenches Alex Wolszcza n (Penn State) 01/23/06 Collaborators: A. Niedzielski (TCfA) M. Konacki

Extrasolar planet detection: a view from the trenches

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Extrasolar planet detection: a view from the trenches. Alex Wolszczan (Penn State) 01/23/06 Collaborators: A. Niedzielski (TCfA) M. Konacki (Caltech). Ways to find them…. Methods that actually work …. Radial velocity. Pulse timing. Microlensing. Transit photometry. Some examples…. - PowerPoint PPT Presentation

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Page 1: Extrasolar planet detection: a view from the trenches

Extrasolar planet detection: a view from the

trenches

Extrasolar planet detection: a view from the

trenches

Alex Wolszczan (Penn State)

01/23/06

Collaborators:A. Niedzielski (TCfA)M. Konacki (Caltech)

Page 2: Extrasolar planet detection: a view from the trenches

Ways to find them…Ways to find them…

Page 3: Extrasolar planet detection: a view from the trenches

Methods that actually work …Methods that actually work …

Pulse timing

Microlensing Transit photometry

Radial velocity

Page 4: Extrasolar planet detection: a view from the trenches

Some examples…Some examples…

Neptune-mass planet

A “super-comet” around PSR B1257+12?

The transit classic: HD209458

QuickTime™ and aYUV420 codec decompressor

are needed to see this picture.

QuickTime™ and aYUV420 codec decompressor

are needed to see this picture.

Microlensing planet

Page 5: Extrasolar planet detection: a view from the trenches

Orbits from Vr measurementsOrbits from Vr measurements

• Observations are given in the form of a time series, Vr(i), at epochs t(i), i = 1,…,n

• A transition from t(i) to (i) is accomplished in two steps:

E − esinE =2π

P(t −T)

tanθ

2

⎝ ⎜

⎠ ⎟=

1+ e

1− e

⎝ ⎜

⎠ ⎟

1/ 2

tanE

2

⎝ ⎜

⎠ ⎟

Vr =K cos(θ +ω) + ecosω( )

Equation foreccentric anomaly, E

K =2πa1 sini

P 1− e2

• From the fit (least squares, etc.), one determines parameters K, e, , T, P

Page 6: Extrasolar planet detection: a view from the trenches

…and from pulsar timing…and from pulsar timing In phase-connected timing, one models pulse

phase in terms of spin frequency and its derivatives and tries to keep pulse count starting at t0

A predicted time-of-arrival (TOA) of a pulse at the Solar System barycenter depends on a number of factors:

In phase-connected timing, one models pulse phase in terms of spin frequency and its derivatives and tries to keep pulse count starting at t0

A predicted time-of-arrival (TOA) of a pulse at the Solar System barycenter depends on a number of factors:

φ=φ+ν(t − t0) +1

2ν•

(t − t0)2 + ...

t = τ −D / f 2 + ΔRsun− ΔEsun

+ ΔSsun+ ΔR + ...

ΔR =a1 sini

csinω(cosθ − e) +

a1 sin i

c(1− e2)

1

2 cosω sinθ

Page 7: Extrasolar planet detection: a view from the trenches

Determining binary orbits…

Determining binary orbits…

Collect data: measure Vr’s, TOA’s, P’s

Estimate orbital period, Pb (see below)

Use Vr’s to estimate a1sini, e, T0, Pb, (use P’s to obtain an “incoherent orbital solution”)

Use TOA’s to derive a “phase-connected” orbital solution

Collect data: measure Vr’s, TOA’s, P’s

Estimate orbital period, Pb (see below)

Use Vr’s to estimate a1sini, e, T0, Pb, (use P’s to obtain an “incoherent orbital solution”)

Use TOA’s to derive a “phase-connected” orbital solution

Page 8: Extrasolar planet detection: a view from the trenches

Figuring out the orbital period…

Figuring out the orbital period…

Go Lomb-Scargle! If in doubt, try this procedure (borrowed from Joe Taylor):

Get the best and most complete time series of your observable (the hardest part)

Define the shortest reasonable Pb for your data set Compute orbital phases, I = mod(ti/Pb,1.0) Sort (Pi, ti, I) in order of increasing Compute s2 = ∑(Pj-Pj-1)2 ignoring terms for which j-

j-1> 0.1 Increment Pb = [1/Pb-0.1/(tmax-tmin)]-1

Repeat these steps until an “acceptable” Pb has been reached

Choose Pb for the smallest value of s2

Go Lomb-Scargle! If in doubt, try this procedure (borrowed from Joe Taylor):

Get the best and most complete time series of your observable (the hardest part)

Define the shortest reasonable Pb for your data set Compute orbital phases, I = mod(ti/Pb,1.0) Sort (Pi, ti, I) in order of increasing Compute s2 = ∑(Pj-Pj-1)2 ignoring terms for which j-

j-1> 0.1 Increment Pb = [1/Pb-0.1/(tmax-tmin)]-1

Repeat these steps until an “acceptable” Pb has been reached

Choose Pb for the smallest value of s2

Page 9: Extrasolar planet detection: a view from the trenches

The pulsar planet story…The pulsar planet story…

Page 10: Extrasolar planet detection: a view from the trenches

… and the latest puzzle to play with

… and the latest puzzle to play with

a Timing (TOA) residuals at 430 MHz show a 3.7-yr periodicity with a ~10 µs amplitude

b At 1400 MHz, this periodicity has become evident in late 2003, with a ~2 µs amplitude

c Two-frequency timing can be used to calculate line-of-sight electron column density (DM) variations, using the cold plasma dispersion law. The data show a typical long-term, interstellar trend in DM, with the superimposed low-amplitude variations

d By definition, these variations perfectly correlate with the timing residual variations in (a)

Because a dispersive delay scales as 2, the observed periodic TOA variations are most likely a superposition of a variable propagation delay and the effect of a Keplerian motion of a very low-mass body

a Timing (TOA) residuals at 430 MHz show a 3.7-yr periodicity with a ~10 µs amplitude

b At 1400 MHz, this periodicity has become evident in late 2003, with a ~2 µs amplitude

c Two-frequency timing can be used to calculate line-of-sight electron column density (DM) variations, using the cold plasma dispersion law. The data show a typical long-term, interstellar trend in DM, with the superimposed low-amplitude variations

d By definition, these variations perfectly correlate with the timing residual variations in (a)

Because a dispersive delay scales as 2, the observed periodic TOA variations are most likely a superposition of a variable propagation delay and the effect of a Keplerian motion of a very low-mass body

Page 11: Extrasolar planet detection: a view from the trenches

Examples of Vr time series “under construction”

Examples of Vr time series “under construction”

Page 12: Extrasolar planet detection: a view from the trenches

One of the promising candidates…

One of the promising candidates…

Periods from time domain search: 118, 355 days

Periods from periodogram: 120, 400 days

Periods from simplex search: 118, 340, also 450 days

Periods from time domain search: 118, 355 days

Periods from periodogram: 120, 400 days

Periods from simplex search: 118, 340, also 450 days

Page 13: Extrasolar planet detection: a view from the trenches

…and the best orbital solutions

…and the best orbital solutions

P~340 (e~0.35) appears to be best (lowest rms residual, 2 ~ 1)

This case will probably be resolved in the next 2 months, after >2 years of observations

P~340 (e~0.35) appears to be best (lowest rms residual, 2 ~ 1)

This case will probably be resolved in the next 2 months, after >2 years of observations

Page 14: Extrasolar planet detection: a view from the trenches

Summary…Summary…

Given: a time series of your observable Sought: a stable orbital solution to get orbital parameters and planet characteristics

Question: astrophysical viability of the model (e.g. stellar activity, neutron star seismology, fake transit events by background stars)

Future: new challenges with the advent of high-precision astrometry from ground and space and planet imaging in more distant future

Given: a time series of your observable Sought: a stable orbital solution to get orbital parameters and planet characteristics

Question: astrophysical viability of the model (e.g. stellar activity, neutron star seismology, fake transit events by background stars)

Future: new challenges with the advent of high-precision astrometry from ground and space and planet imaging in more distant future