Science and Progress: Short Period Planets in Q1
Chris Lintott (Zookeeper Chris) and I wanted to give an update on what the team is working on and some of the changes made to the PH site to help us answer the question we are tackling right now. We used very simple cuts and visual inspection to come up with a preliminary list of planet candidates that John has discussed in an earlier post. We’ve been brainstorming on how to combine the results from all the multiple user classifications (about 10 users looking at each lightcurve) to tease out every transit in the database of over 2.0 million classifications. We are working hard on more sophisticated algorithms and techniques to take all your Q1 classifications and transit boxes and extract transits and planet candidates.
After starting to look at your classifications and results from the simulated transits, Chris and I think an interesting question to look at is what are the abundances of planets on short period orbits (less than 15 days ) in the Q1 data. The Kepler team is doing something similar and it will be very interesting to compare the two results. As an initial step we are only looking at planets bigger than 2 Earth radii so only gas and ice giants because the transits are more pronounced than the smaller rocky planets. Less than 2 Earth radii will be much harder to detect, so we first we want to develop the analysis tools and then we’ll come back to the less than 2 Earth radii planets later.
With just the transit discoveries alone we can’t answer this question. This is because we don’t know how complete the sample is. If we found 120 Neptune-sized planets for example, we can’t say anything about their abundance compared to Jupiter-sized planets, since we don’t know how many we might have missed in the data set. This is where the synthetic transits we insert into the interface play an important role. If users flag 100% of the Jupiter-sized simulations with orbital periods shorter than 15 days, but only 50% of the Neptune-sized synthetic transits, then we know that the number of transiting Neptunes in the real light curves is a factor of two larger than what we found. With this completeness estimate we can debias our sample and begin to understand the spectrum of solar systems providing crucial context for own solar system.
We find that we need higher numbers and finer resolution in period and radii for the synthetic lightcurves to do this analysis. Starting today, mixed in with the Q2 data, we will be showing newly generated synthetic Q1 lightcurves specifically made for this task. As always with the simulated transits ,we will identify the simulated transit points in red after you’ve classified the star and will mark the lightcurve as simulated data in Talk . With the results from these synthetics we can better tweak our analysis tools for extracting transits from your classifications as well as get sufficient numbers to calculate the short period planet detection efficiency for Planet Hunters. The new synthetics won’t be the only non-Q2 lightcurves you see. We also have about 5800 additional lightcurves from Q1 that were released by the Kepler team on Feb 1st,. Now that the Q2 data upload is complete, these have now been introduced into the database and we’ll be showing these mixed in the classify interface as well as a small subset of the Q1 data previously looked at to examine how classifications have changed over time since December.
Chris and I have are aiming to have the bulk of the analysis complete before October, so we can present the results at the joint meeting of the European Planetary Science Congress (EPSC) and the American Astronomical Society Division for Planetary Sciences (DPS) meeting being held in Nantes, France, in October. We will keep you posted on our progress and results as time goes on. Abstracts are due in May, and so we need to start work now to be able to have results for the Nantes meeting. With your help, we think this will lead to a very interesting paper.
Cheers,
Q2 Data now fully online!
Hi all –
The Q2 data (chopped up into Q2.1, Q2.2 and Q2.3) are now fully online. Since these data cover a much longer time frame than just the Q1 data, we can now start looking for planets with longer periods. If you spot a single transit in a light curve that you think looks good, why not check all the other data (bot Q1 and Q2) for similar transits; it may be a long period planet.
Why is this so interesting? A planet around a star like our sun that is far enough away not to be fried by the star takes about one year to go around the star once. So you’d see one transit every year. Like our own earth. Around a dimmer star than our sun, the habitable zone is closer in, but still long. So happy hunting, especially for long period transits!
Gaps in the Data
I wanted to give a brief update on the gap question and talk a little more about what causes those gaps in the data.
You might have noticed that the gap question is no more. All of the lightcurve sections from Quarter 2 have breaks of varying sizes in them which was not the case for the Q1 data, so we removed the gap question from the interface yesterday. The gaps are caused by a few different things: Kepler went into safe mode and wasn’t taking data, the spacecraft was rotating towards the Earth, the spacecraft has executing a roll (or quarterly roll as its called) to reorient its solar panels, or the data is bad either due to a cosmic ray hit or something else.
The spacecraft rolls and safe mode tend to make of the majority of the data breaks. Kepler must rotate towards Earth to send its science data on timescales of approximately 30 days. During those monthly data downlinks Kepler must point away from the field and point its antenna towards the Earth to send the 150,000 lightcurves of data collected to the science operations center via NASA’s Deep Space Network. Every few months, the spacecraft must also reposition its solar panels toward the Sun and point Kepler’s radiator into deep space with a quarter turn, which causes an additional gap of about 1 day in the lightcurves. The reason we don’t see any gaps in the Q1 data (about 35 days) is because it encompasses one downlink of data, but since Q2 is 90 days there is both the quarterly and month rolls.
I’m off to Kitt Peak for an observing run to observe a transit in our own solar system. Dwarf planet Huamea’s moon (Nemaka) is passing in front of Haumea Friday night and I’ll be attempting to observe the drop in light caused by Nemaka on the WIYN telescope (3.5 m) while my collaborators will be observing the event from the Hale Telescope (200 inch) at Palomar Observatory.
Happy Hunting,
PS. I also wanted to say thank you for everyone’s patience and understanding while we’ve sorted out the Q2 data upload and the Talk links.They should hopefully be done late tonight early tomorrow
