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This sequence from the all-sky camera is a blog post in and of itself:

It’s been a cloudy couple of nights at Las Campanas.

We’ve watched cloud banks as we walk to the telescope:

Clouds stream overhead as we open the the dome:

Clouds fill the all-sky cam once our targets are up:

monitored the clouds from space:

saw clouds over the Magellan telescopes from the “Hotel”:and noted clouds as we walk to breakfast in the minutes before dawn:

 

Nevertheless, we’ve gotten on sky and collected data. Past bloggers have likened the MagAO team to a F1 pit crew. The racing doesn’t happen  in our little mountain runabouts:

or on the mountain roads:

But at the Clio controls, where Katie reminded me it takes an aggressive-just-get out-there-and-start-saving-frames attitude, while you check the exposure times and nodding angles, to come out of a blustery and far-from-photometric Las Campanas night with some data. To strain the auto racing analogy, perhaps this also reflects the an improvisational MagAO “straight out of scratch” street racing attitude. With that we’ll leave you with a song:

After two summers of working with Kate, she let me (an undergrad who has never been observing before) come with her to LCO. In short, this might be the most beautiful place I’ve ever been, viscachas are my new favorite animal, and I’m realizing more and more how little I know. (According to Kate, knowing what you don’t know is one of the steps on the path from novice to expert, so I’m making progress.)

I’ve spent the past two summers reducing MagAO data, and have been getting by with nothing more than a basic knowledge of the data reduction pipeline and enough background to briefly explain to someone sitting next to me on an airplane what I’m doing with my life. Since getting here, I’ve realized that all of the instrumentation is slightly more complicated than the 10 second explanation’s I’ve memorized over the past year, but everyone here has been so patient with me and has explained everything so well. I’ve learned much more than I could’ve hoped to.

Kate has even let me drive visao and, while it took some getting used to, I’ve gotten pretty good at pressing “Enter” (grad schools please accept me). It’s been pretty cool fully realizing that astronomical data doesn’t come straight from a hard drive, and that the little blobs of light in all the images actually are stars. Everything has become so much more real.

As far as tonight goes, things have been quite cloudy so we had to stop taking data pretty early, but before then I did get to see the very large telescope spin very quickly to follow a star with a very sharp transit.

The only thing that could add more pressure to writing this blog post is having to pick a song to go with it. Also, the wifi is down on the mountain which isn’t much help.

It is way past my bedtime.

 

 

Do you want high winds, clouds, or bad seeing? If you wait long enough you can have all 3 at once.

Btw, you can tell Katie was driving because she just popped the clutch and peeled out (no 10 modi loop). See this post to understand.

Quote of the day: “The AO might be making it worse.” — Laird Close

Tonight was the first science night of 2017B for the Giant Accreting Protoplanet Survey (GAPlanetS). Unfortunately, the timing of the run is such that all of our best targets are reaching their highest point in the sky as the sun sets. This is important because stars rotate the most rapidly with respect to our instrument right around when they reach their highest point, and maximizing rotation is key to our data reduction technique. For that reason, we usually try to center our observations around this “transit” point in order to maximize rotation.

So we started the night by trying really hard to lock on a nearly 12th magnitude star in early twilight. Hernan heroically acquired the star all of about 5min after sunset, but the AO system just couldn’t handle the twilight, so we moved on to a backup target. Unfortunately, seeing was also not as good as we’ve come to expect here at Magellan – hovering near an arcsecond for most of the night. We got a couple of nice long datasets in variable conditions, with occasional setbacks due to the adaptive optics loop breaking because of rapid changes in seeing and high winds.

In better news, my student Clare got her first taste of instrument operation and did a great job running VisAO for most of the night. Here’s a picture of her doing her thing.

Fingers crossed for better weather tomorrow, but the forecast is a bit dire and I used up all of my good weather karma on my eclipse trip to Idaho last week, so I’m not super optimistic. In honor of that amazing event, the song of the day…