Reporting New Discoveries

Occasionally you will make a discovery. After recording your data, if you think that you have made a discovery it is important that you report your suspicions accurately and quickly. It is also important not to waste other people's time with false claims.

First, if after rigorous examination you are convinced that you have made a discovery, it is important to determine its position as accurately as possible. You may need assistance doing this. Reporting a suspected discovery by saying that it's a little to the left, and down, from the big bright star, won't work. You'll need to determine its right ascension and declination to a fairly good accuracy; within a couple of arcsec, at least!

Second, you must ensure that you have a bona fide discovery! Take extraordinary care when doing so. You must get a second opinion! Call a friend, or use the Internet to request assistance. Your discovery will remain secure if it is in fact a real discovery but getting other astronomers to help determine it's existence is important. Calmly request help. You'll find many observers willing to help you.

It may take a day or more for your discovery to be recognized so be patient. Many discoveries turn out to be something that is known but not well observed, so be prepared for this too. In time, undoubtedly you'll end up observing something that you can call a discovery so hang in there.

Chapter 13

Variable Star Data Management, Reduction and Analysis

There are three kinds of lies: lies, damned lies, and statistics.

Benjamin Disraeli

"What kind of story is my observations telling me?"

Without a doubt, your observations of variable stars will provide some insight into the specific characteristics of each. Of course, the quality of your observations will determine the depth of the insight. In any case, before long, you will find yourself the custodian of a large amount of information that may have scientific value. It will certainly be valuable to you. Your ability to properly analyze the growing mound of information and to tease from within the hidden secrets will increase its value. With an understanding of basic data analysis, interpreting the secrets hidden within your own observations can be rewarding and is an important part of variable-star observing. Basic analysis of your data will elevate you above simple bean counting.

As a result of your VSO activities, presumably you will soon begin to suffer from information overload. Consider observing only 20 or 30 stars, once a week, over the course of a year. This modest schedule will result in over 1500 observations. Observe a greater number of stars or observe more frequently and this number will increase dramatically. Unquestionably, some observers never return to their past observations once they are collected and reported. Some observers are interested only in observing and reporting. The story contained within their observations remains unread except by others.

However, many variable-star observers enjoy conducting long baseline time analysis of their program stars and then comparing their observations from past seasons in an effort to confirm a predicted characteristic or detect anomalous behavior. Basic analysis of your data can be fascinating when examining the mass transfer between entangled eclipsing binary stars, RV Tauri stars exhibiting the interesting RVb phenomenon, RR Lyrae stars demonstrating the Blazhko effect, long-period Mira variables displaying fluctuating periods and amplitudes in response to internal stellar dynamics or when following superhump evolution within SU UMa stars. These are a few of the interesting phenomena that you can study and there are many more interesting characteristics of variable stars that basic analysis will expose.

Many visual observers dedicate two or three hours, a couple of nights a week, to observing, particularly during the winter months when darkness comes early, the air is crystal clear, and the stars intensely sharp. During exceptional evenings, you'll be able to make a visual estimate every minute or two (taking into account bathroom breaks, cups of hot cocoa, talking with colleagues, recording your estimates, roaming the star fields, etc.). A great evening of observing can easily produce over a hundred visual estimates. Using a CCD and the automatic capabilities of many telescopes available today, in a short 8-hour night it's relatively easy to collect 500 digital images or more. Either way, after a handful of nights of observing you won't have enough daytime hours to properly analyze your data. You'll begin to wish for a cloudy night or two just so you can catch up. In extreme cases, you'll just have to quit your job!

At this modest pace, in a few years, you may find yourself struggling to find a handful of observations that you made a season or two ago among the many thousands that you've made and recorded over time. As a visual observer, you may possess books of data and if you're using a CCD, thousands of images will eventually fill your hard drive. With a stellar photometer, since you will need to make sky measurements for your comparison star and check star, as well as your variable star, your resulting records will grow at an even faster pace. How are you going to manage what will eventually become a huge amount of information in such a way that you will be able to retrieve individual observations when needed?

At this point, you're wondering, "Why do I need old observations anyway?"

Well, old observations will be needed to compare with newer ones when searching for suspected period changes and amplitude changes. Or when verifying comparison and check stars from a season or two ago. Checking previous integration time, camera temperature and which filters were used can be important for CCD and PEP observers. Perhaps, a request to share your data with another observer will arrive. Or even checking a star field in an older CCD image because a recent image shows a "new" star. Past observational data is valuable. By virtue of some weird universal law, your observations are most valuable when you can't find them. Suffice it to say, finding data from past observing seasons can be frustrating without a formal storage and retrieval method.

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