This is the straight-through version of the Q70 eyepiece view, useful in case you didn't get the target LCD square close enough and you can't ID stars. This is a wider view in the correct orientation to make the ID easier.
This is a high rank event and the path should be fairly solid. I'm closest to the southern limit at Cabrillo College (for Astro 8A final exam duties), Kirk's deeper in, and Karl is best of all near the centerline. Liu is also on the path near the northern limit and is on OW. The altitude is 30 degrees, Az=217, and it 10 degrees ENE of Saturn, at about 9:45 o'clock as you look at Saturn. It's between two fairly bright stars in the "jar" of Aquarius.
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This is the straight-through version of the Q70 eyepiece view, useful in case you didn't get the target LCD square close enough and you can't ID stars. This is a wider view in the correct orientation to make the ID easier. |
A success for all 3 of us - although Karl's recorder failed to record - he had a backup from recording the screen with his iPhone. We just have to get the video from his iPhone.
I had my Astro 8A final exam night at this time, so I brought my gear to Cabrillo College and parked on the walkway directly below room 705. A half hour before the event, I walked down and set up. It all went smoothly and I got a recording at 8x. The bright lights of the area made the event more difficult than it could have been. 16x was too bright a sky, and I also worried there would be too few occulted points to pass the red bar test, so left it at 8x setting. It was hard to follow this faint star on the bright pixeled monitor but it looked like it was gone for about a second at about the right time.
Lat: 36 59 22.04"
long: 121 55 26.04
Elev 228 ft.
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magDrop report: percentDrop: 80.6 magDrop: 1.778 +/- 0.513 (0.95 ci)
DNR: 3.80
D time: [03:46:41.6842]
D: 0.6800 containment intervals: {+/- 0.0371} seconds
D: 0.9500 containment intervals: {+/- 0.0904} seconds
D: 0.9973 containment intervals: {+/- 0.1956} seconds
R time: [03:46:42.8544]
R: 0.6800 containment intervals: {+/- 0.0371} seconds
R: 0.9500 containment intervals: {+/- 0.0904} seconds
R: 0.9973 containment intervals: {+/- 0.1956} seconds
Duration (R - D): 1.1702 seconds
Duration: 0.6800 containment intervals: {+/- 0.0543} seconds
Duration: 0.9500 containment intervals: {+/- 0.1230} seconds
Duration: 0.9973 containment intervals: {+/- 0.2361} seconds
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Observed from home, got a short event.
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recorded the charts and commentary on settings using the camcorder as camera, as he usually does before an event. Then recorded the event but it did not record on tape. Just blue screen of death, on playback. But he used his iPhone to record the monitor and saw the ~1 sec event, so it should be recoverable.
I analyzed it 3 times.
Analysis 1: assumed incorrect 4x setting as suggested by PyOTE.
Analsysi 2: Used wider aperture, got better tracking in PyMovie, but in PyOTE still assumed 4x setting
Analysis 3: Used csv file from Analysis 2, but in PyOTE used 16x setting, and better assignment of manual time stamps as described below. This is the analysis used in the IOTA report.
My 3rd analysis assumes, correctly I confirmed, that he used 16x setting. This gives far fewer points in the occultation and reduces the significance so that while it looks to give good timings and duration expected, it's too noisy to satisfy the 5-sigma false positive test. His duration was 1.75s which is quite reasonable and consistent given the 1.1s for Kirk and I closer to the southern limit of this high rank event. If instead I assume a 4x setting, which is what PyOTE automatically assumed , then it satisfies the 5-sigma false positive. But given his lower sensitivity Watec 910hx and the fact that I used 8x for my data, he used 16x. Also PyOTE said the auto-correlation of points at 4x setting was suspicously high and suggested a longer integration time was used. My interpretation is that given the fact the video I'm actually analyzing is a hand-held video with moment to moment focus changes, the typical grouping of frame points within an integration is noisier and harder to see the grouping.
For time stamps, due to the migration of the time across the frames, I suspect that Karl's iPhone was recording at 30fps while the VTI was outputting at 29.97 fps and this caused the time stamp migration slowly. To deal with this, I will be increasing the error bars on his times from that shown by PyOTE by an additional field duration of 1/60s. Also to minimize error, I used two manual time stamp assignments inside PyOTE just a couple of seconds before and after the event, which were clear on the video (2nd field) and gave frame numbers of an additional 0.5 added on, to designate there were the 2nd field of the frame. I assume that this then gives the most accurate time stamp.
Below is the raw timings and confidence intervals from PyOTE
magDrop report: percentDrop: 64.0 magDrop: 1.109 +/- 0.293 (0.95 ci)
DNR: 1.94
D time: [03:46:41.6210]
D: 0.6800 containment intervals: {+/- 0.0995} seconds (.026s reported)
D: 0.9500 containment intervals: {+/- 0.3418} seconds (.343s reported)
D: 0.9973 containment intervals: {+/- 0.8215} seconds (.838s reported)
R time: [03:46:43.3791]
R: 0.6800 containment intervals: {+/- 0.0995} seconds
R: 0.9500 containment intervals: {+/- 0.3418} seconds
R: 0.9973 containment intervals: {+/- 0.8215} seconds
Duration (R - D): 1.7581 seconds
Duration: 0.6800 containment intervals: {+/- 0.1591} seconds
Duration: 0.9500 containment intervals: {+/- 0.4154} seconds
Duration: 0.9973 containment intervals: {+/- 0.8910} seconds
Below is the PyMovie Analysis #2 light curves
Screen capture of the 2nd run of PyMovie on Karl's iPhone video, with target star shown |
PyMovie composite light curves of 2nd Analysis. |
PyMovie target star light curve from 2nd analysis |
Reference star "Ref1" light curve in PyMovie analysis #2. |
Below is the PyOTE solution for the 2nd PyMovie analysis. The first two table entries are assuming the correct 16x setting. With fewer points, the statistical significance of the occultation is reduced, but yet still agrees nicely with the high confidence occultation data from Kirk Bender and I further south. The last two table entries are with the same Analysis #2 data, but this time falsely assuming a 4x setting as PyOTE decided best fit the data. The false positive test is passed, but that's due to the higher point total and sharper edges.
Light curve and solution. The 1.75s duration fits well with the assumed diameter and the shorter events for Kirk Bender and I farther from the centerline. |
False positive test for the 16x setting assumed. |
Assuming 4x setting, and reference star fitting. |
False positive test is passed well, but mainly because the D and R edges are sharper and the event has many more occulted points, erroneously. |
My conclusion is that the event was real at Karl's station; in fact given the data from Kirk and I, it's hardly possible that Karl did NOT get a near central occultation. The data is poor quality due to the iPhone hand-held videography and so noisy photometry, but it is real. I've added 1/60s to the duration of each of the determined D and R confidence limits to reflect the uncertainty in the offset of the time stamp moments from the VTI vs the start and end frame times of the iPhone video.
