Screen Saver & Graphics Display - SETI@Home
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[edit] General
Original Story by Ron Hipschman; mutated by Paul D. Buck … so any mistakes are mine, and mine alone … don't blame Ron!
The SETI@Home Science Application is a complicated piece of scientific analytical software. It performs a large set of mathematical operations on the data that you are downloading from the Berkeley SETI program. It also displays the processes as they are being performed by your computer. What you see on the screen gives you only a glimpse of what is happening inside your computer. The SETI@Home Screensaver display is broken into four main sections:
- Data Analysis
- Data Info
- Participant Info
- Frequency-Time-Power graph
The screen is divided into two main sections with the top half of the screen containing three of the data areas and the bottom half containing the remaining section.
- Data Analysis is in the top left corner
- Data Info & User Info are in the top top right corner (stacked, with Data info on the top)
- Frequency-Time-Power Graph - Bottom half of the screen
The two text panes in the upper right corner have a fixed presentation at all times, until the Work Unit being processed changes.
On the other hand, the Data Analysis pane and the Frequency-Time-Power graph are continually updated with information as the Work Unit is processed.
The graphics and screen savers can be controlled and modified by preferences settings that are contained on the SETI@Home Preferences Page. The documentation and the effects of the setting changes is covered within the documentation for that page in the SETI@Home Web Site Owners Manual.
[edit] Data Analysis
This is one of the two places where all the action takes place. The two text panes remain fixed while the data is processed, this section is dynamically updated as your computer works. This section of the screen contains a wealth of information about what your computer is doing at any given moment during the analysis of your work-unit. Keeping a watchful eye on this pane will help you understand what SETI@Home is doing with all the data.
[edit] What is the Screensaver doing NOW?
The top line tells you what the program is currently doing. It can say any of several things. We'll list them below and explain what each means.
[edit] Scanning Result Header File
- When the SETI@Home science application starts running (or when you launch it manually) the screen saver must somehow recollect where it was when it last left off doing its calculations. To find this information it reads a file that we've stored on your hard disk. The screen saver then resumes its work exactly where it left off with all the data on the screen intact.
[edit] Doing Baseline Smoothing
- When you receive a new work-unit from the Data Server at Berkeley, there are signals of all kinds mixed in. We are only interested in looking at the narrow bandwidth signals. These narrowband signals are what we believe an alien civilization would use to communicate. On the other hand, broadband signals are most likely due to natural astronomical processes. To reject broadband noise, the screen saver does a sort of "average" through the data that eliminates this broadband noise and brings all the other narrow bandwidth signals down (or up) to a common "baseline" level. Also, over the 107 seconds the signal sometimes gets slowly louder and/or softer. Baseline smoothing brings it all to the same level. This is the first thing that is done to the data after you've received your work-unit and it's usually only done once. Certain clients (like the Mac client) do not keep the smoothed data in RAM and must re-compute this whenever the screen saver is started. A progress bar appears to the right lets you know how far your computer has gotten through this process.
[edit] Computing Fast Fourier Transform
- This is where all the work gets done. The data supplied to you from the telescope is a signal that varies with time - like a line on an oscilloscope that wiggles up and down in response to your voice through an attached microphone. In this case, time runs along the horizontal x-axis and signal strength (air pressure) along the vertical y-axis. The raw radio telescope signal is not very useful to us. What we would like to see is if there are any constant (and loud) "tones" within the signal. We would rather be looking at a graph with frequency running along the horizontal x-axis, and power along the vertical y-axis. Any spike in this graph would be a loud signal at a single frequency.
- To turn a set of time-based data into a set of frequency-based data, we apply a relatively complex mathematical operation called a "fast fourier transform" or FFT. For more information on the FFT, please consult a book on digital signal processing.
- The result of this processing is the graph produced in the lower frame of the screen saver. You may notice a few interesting things about the FFT. At the beginning of a work-unit, we do 15 different FFT's, each looking at the data with varying accuracy. We start looking for details as small as .07 Hz wide. There are tradeoffs when you are doing this kind of analysis. If you want to be very accurate in frequency, you have to observe the data for a longer time. You will notice that at the 0.075 Hz frequency resolution, we must look at chunks of data 13.42 seconds in length. To completely analyze our 107 second sample, we need to do 8 of these FFT's. When we reduce the frequency resolution to 0.14 Hz we only have to look at a 6.7 second sample of data. We now have less frequency resolution, but we have more time resolution. We have to look at twice the number of these (16 of them) to cover our 107 seconds of data! We look at 15 different frequency resolutions (0.075, 0.15, 0.3, 0.6, 1.2, 2.5, 5, 10, 20, 40, 75, 150, 300, 600, and 1200 Hz) in our analysis. With each halving of the frequency resolution we must do twice the number of FFT's to cover our 107 seconds of data. The amount of number crunching is dizzying!
- Again, the progress bar that appears to the right lets you know how far your computer has gotten through each set of FFT's. You can also watch the FFT's accumulate in the graph in the bottom section.
[edit] Chirping Data
- It's quite unlikely that an alien planet will be at rest with respect to our Earth. You may remember that humankind is whizzing along on a rotating planet which is revolving around the Sun, which itself is orbiting the center of our Milky Way galaxy. We can assume that our extra-terrestrial friends are likewise situated.
- There is an interesting effect that all this motion will have on a signal emitted from a moving source and/or received on a moving planet. This is the doppler effect. You are undoubtedly familiar with this if you've heard a car honking its horn as it passes you. The frequency, or pitch, of the sound changes as the car passes. You can go out and try this yourself. Stand at the side of the road and listen as a friend drives by with the horn blasting. You could also drive by a stationary car honking its horn and you will also hear the pitch change. It's the relative velocity that's important.
- Although our remote friends aren't honking their horns at us, they are sending waves (electromagnetic waves) at us. Their signal will be distorted by the mutual motions of our two systems in much the same way that the car horns are distorted. To disentangle this the SETI@Home screen saver analyzes the data many times over trying a great variety of possible doppler accelerations. Actually, the screen saver first takes the raw data and mathematically "undoes" a specific doppler acceleration or "chirp". It then feeds the resulting "de-accelerated" data to the FFT (Fast Fourier Transform) routines. This is called "De-chirping" the data. SETI@Home tries to do this at many points between -50 Hz/sec to +50 Hz/sec. At the finest frequency resolution of 0.075 Hz we check for 5409 different chirp rates between -10 Hz/sec and +10 Hz/sec!
[edit] Searching For Gaussians
- As explained briefly in the FFT section, when the frequency resolution is coarser, the time resolution is finer. When the time resolution is high enough, we can look at the data to see if signals get stronger and weaker in the 12 seconds it takes them to pass through the telescope's field of view. This is an excellent test to tell if the signal is "out there" rather than a simple source of interference somewhere here on the earth. An earthbound signal would not get louder and then softer over the 12 second period we are interested in. This curve fitting checks to see if the signal gets louder and softer over this 12 second period. The test is only applied for frequency resolutions greater than or equal to 0.59 Hz.
- Since we are looking for these 12 second "gaussians", your 107 seconds of data overlaps the previous and next blocks of data by 15 seconds. In this way we make sure that we don't miss an important signal by splitting it in the middle.
[edit] Searching For Pulses / Triplets
- A new feature in the SETI@Home science application looks for repeated pulses in the radio signals. Our alien neighbors may not be sending out a nice even tone for us to detect. They may be sending a series is closely or widely spaced set of pulses. This is much more economical "power-wise" at their transmitter if they are doing it intentionally (and who knows what they are sending if it's unintentional!) For all frequency resolutions greater than or equal to .59 Hz, the screen saver will do a search for repeating Pulses and Triplets of pulses.
- That finishes the first line of the Data Analysis panel. Phew!
[edit] Doppler Drift Rate
The second line of the Data Analysis panel contains the current "Doppler drift rate". The first tests that are made on the data assumes a drift rate of 0 Hz/sec. These un-accelerated signals are more likely to be sources of Radio Frequency Interference (RFI) from earth based terrestrial transmitters. Between the drift rates of -10 Hz/sec and +10 Hz/sec we try all 15 frequency resolutions and increment the doppler drift rate by 0.002 Hz/sec between FFT's. Between +-10 and +-50 we increment by 0.296 Hz/sec.
[edit] Frequency Resolution
The second line also tells us the current frequency resolution (bandwidth) we are using in our calculations. You will notice that most of the time we will be calculating FFT's with a frequency resolution of 0.075 Hz. Every 4 FFT's we'll do one with a frequency resolution of 0.14 Hz. Every 16 FFT's we'll do one with a frequency resolution of 0.29 Hz. Every 64 FFT's... well, you get the idea. Remember that there are 15 different frequency resolutions (0.075, 0.15, 0.3, 0.6, 1.2, 2.5, 5, 10, 20, 40, 75, 150, 300, 600, and 1200 Hz). We drop the two finest frequency resolutions (0.075 Hz and 0.15 Hz) when the doppler drift rate is greater than 10 Hz/sec or less than -10 Hz/sec.
[edit] Analysis Results
The next part of the data analysis panel displays intermediate results about the best Gaussian, Pulse and Triplet found so far. This part of the panel alternates between all three, but only when a significant result is available. For instance, if there are no significant Triplets, you will not see Triplets displayed.
[edit] Best Gaussian
If a signal is above the average noise and also gets stronger and then weaker in a "Gaussian" fashion as the object passes through the telescope beam, we're interested!
The number labeled "power" tells us how strong the signal is relative to the baseline power calculated above. The number labeled "fit" is a measure of how well the rising and falling signal fits an ideal gaussian (bell curve) profile. A lower "fit" number means a better fit. (It's actually a chi-square fit, i.e.. how far the data departs from an ideal gaussian.) Even if you see a strong peak and a low fit number, do not call the press or announce to the world that you have discovered the aliens. Any strong signal must be verified (several ways) to rule out sources of Radio Frequency Interference (RFI) before it becomes "official". Since noise can sometimes randomly simulate a gaussian, we've set a threshold to avoid being overwhelmed with trivial results. If the signals are stronger than 3.2 times the average noise level that have a fit better (less than) 10, they are returned by the screen saver client to our server in Berkeley.
The graph below the power and fit numbers displays the curve fitting analysis as it is happening and also displays the best gaussian so far for this Work Unit.
- Note:
- If the telescope is slewing across the sky too slowly or too quickly during the observation, no graph is drawn.
The red line shows the actual data - power at a given frequency, as seen over time. This view is a back to front slice of the big chart at the bottom of your screen saver display. This aspect of the graph changes each time the gaussian fitting moves to a new frequency. The white line shows best fit gaussian for that data, i.e. what your client is actually calculating!
At each data point we try a new fit. You see this as the white line changing very quickly. If the analysis were not happening so quickly you would see the gaussian (the bump in the white line) move from left to right across the graph as we try to best fit your data.
[edit] Best Pulse
In order to look for a series of weak repeated pulses, the SETI@Home screen saver applies a special test called a "fast folding algorithm." If the routine finds a set of repeating pulses, it will display them with statistics describing what it found.
The number labeled "power" tells us how strong the pulses are relative to the baseline power calculated above. The number labeled "period" is a measure of how far apart the pulses are in seconds. Because both RFI and random noise can simulate a pulsed signal, we've set a threshold here, too. This threshold is calculated dynamically and depends upon the period and the number of times the data has been folded. (For you math nerds, it involves inverting a function known as the "incomplete gamma function".) The score value for a pulse is the ratio of the pulse amplitude to this threshold value. A pulse with a score of greater than 1 will be reported when your screen saver client returns a result to Berkeley.
The graph below the power, period and score numbers displays the pulse analysis as it is happening and also displays the best pulse so far for this Work Unit.
- Note:
- If there are no significant pulses found, no graph is drawn.
Like the gaussian above, red line shows the actual data - power at a given frequency, as seen over time. Unlike the gaussian, this graph probably won't cover the entire 107 seconds of data, but rather will cover two periods of the pulse (twice the "period in the line above the graph...). You should see two spikes sticking up out of the noise. The right-hand and left-hand sides of the graph are the same. Showing two periods makes it easier for you to see the pulses.
For a more technical description of the SETI@Home data analysis see the The SETI@Home Sky Survey paper.
[edit] Best Triplet
The SETI@Home science application does one more test for pulses. This one looks for three equally spaced pulses. To do this, the screen saver looks at every pair of pulses that are above a certain threshold power. The client then looks for a pulse precisely between the two pulses. If one is found, it is logged and sent back to Berkeley.
If a triplet is found a line is displayed showing the power of the pulses (relative to the noise baseline) and the time between pulses (the period) in seconds.
The graph below the power and period can display the best triplet found so far for this Work Unit. The three pulses will be marked with short yellow tick marks.
- Note:
- If there are no significant pulses found, no graph is drawn.
[edit] User Info
This section gives information about the Participant running the current block of data. Here is displayed the name of the participant who is getting credit for this work. In Classic SETI@Home, it shows the total number of "work-units" this participant has completed, and the total computer time that the Participant's computer has spent analyzing data. Note that this is only time spent actually running SETI@Home, not the total time the computer has been powered on. In SETI/BOINC, it shows the number of "credits" the participant has earned.
[edit] Data Info
This section contains information about the work-unit currently being processed. It's very important for us to know exact details about this data so we can keep track of it in our database. If a signal is found this information will allow us to go back to that place in the sky and re-examine the correct part of the radio spectrum to check our results.
[edit] First line: Where am I looking?
The first line in this section of the display specifies the location in the sky the data was collected from. This is where the telescope was pointed, or more accurately, the piece of the sky that was over the telescope at the time. On the earth, you need two coordinates, latitude and longitude, to locate a place on the globe. Likewise, in the sky you also need two coordinates to find an object on the "celestial sphere". In the sky these coordinates are called "right ascension" and "declination". Latitude and declination are measured in exactly the same way, starting at 0 degrees at the equator (the celestial equator in the case of declination) and moving north 90 degrees to the north pole and -90 degrees to the south pole. Right ascension is a little different from longitude. Longitude is measured east and west from the Greenwich meridian that runs through Greenwich, England. Since it is measured east and west, you can go 180 degrees either way until you reach the international date line on the opposite side of the globe. Right ascension is measured in one direction only, towards the east, and is measured in hours, minutes, and seconds rather than in degrees. There are 24 hours all the way around, each hour being broken into 60 minutes, and each minute being broken into 60 seconds. This links the rotation of the sky to the rotation of the earth very nicely. You can find out where in the sky your data was recorded by looking at the RA and Declination on the first line and finding those coordinates on a star chart.
Note that the Arecibo telescope can only see about 1/3 of the sky. The telescope is fixed in position and can only be pointed through a limited range by moving its receiving antennas. The SETI@Home search is limited to declination 0 degrees to 35 degrees north.
The telescope beam is about 1/10 of a degree wide and in the 107 seconds of data collection represented by your slice of data, the telescope beam slews across about 0.6 degrees of the sky. Your data therefore occupies a rectangular area in the sky 1/10 degree high by 6/10 degree wide.
[edit] Second line: When did I look?
The second line of the Data Info section tells you when the data was recorded. Note that the time given is GMT (Greenwich Mean Time). This is the time on the clock at the Royal Greenwich Observatory in England at a longitude of 0 degrees. All astronomers use this standard to avoid confusion with all the time zones in the world. You are sent 107 seconds of data that was recorded centered at the time on line two.
[edit] Third Line: What telescope was I using?
The next line tells you the source of the data, namely the Arecibo Radio Observatory. Ruling out some natural disaster destroying the telescope, this is not likely to change.
[edit] Fourth Line: What frequency am I analyzing?
The last line tells you the base frequency of the data you are analyzing. SETI@Home looks at a band of the radio spectrum 2.5 MHz wide. The SETI@Home project breaks this wide band up into more manageable chunks of about 10 kHz each (actually 9765 Hz). This means that every 107 seconds of data recorded for SETI@Home actually produces 256 blocks of data! The base frequency number tells you where within the wide 2.5 MHz band your 10 kHz band is located.
Combine all the lines and you know where in the sky, when, the frequency listened to and the source of the data. Everything you need to know to uniquely identify the block of data.
[edit] Frequency-Time-Power Graph
Here is where you can observe the graphical representation of the fast fourier transforms as they are calculated. Frequency runs along the horizontal x-axis, power along the vertical y-axis and time along the in/out z-axis. Here you may note the difference between the different frequency resolution FFT's. For a resolution of 0.075 Hz you will notice that we only do 8 FFT's to cover our 107 seconds of data. This will look different than the 0.14 Hz resolution where we do 16 FFT's. Every time we reduce the frequency resolution by 1/2 (doubling the bandwidth) we get twice the time resolution (we do twice the number of FFT's). At the final resolution of 1200 Hz, we get a time resolution of 0.008192 seconds which also means that we do a total of 131,072 FFT's just for this one graph! This allows detection of fairly short pulses, but the frequency measurement cannot be as precise, and the sensitivity to find continuous signals is reduced.
The colors you see in the graph signify absolutely nothing. They were used only for aesthetic purposes. We hope you enjoy them as much as we do.
A significant extraterrestrial signal may not be visible in this graph as it may be masked by all the natural noise around it. So, if you see something, don't get overly excited, it's probably just a strong source somewhere local, or a satellite passing overhead. On the average we look at the same part of the sky every 3 to 6 months, so it will get re-checked at that time for the same strong signal.
See the section on Radio Frequency Interference (RFI) for more details.




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