vega visual environment for gravitational waves data analysis d. buskulic / lapp annecy root 2000...
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VEGA
Visual Environmentfor Gravitational waves data
Analysis
D. Buskulic / LAPP AnnecyROOT 2000 Workshop
Outlook
What is a Gravitational Wave ?How to detect it ? Example : VIRGOData Handling : Similarities/Differences
with HEPVEGA : an environment based on ROOTStrengthsWeaknesses and problemsConclusion
What is a Gravitational Wave ?
Very small deformations of space time Amplitude h = L/L < 10
-21 (1 = flat
space)Travelling (waves) at the speed of light Generated by cosmic events :
Supernovae, Coalescing binary neutron stars, Formation of black holes...
Gives new insights in fundamental Physics and Astrophysics
How to detect it ?
One way : Resonant bars
Another way : Measure time of flight of a light
beam : Michelson Interferometer
How to detect it ? (II)
Principle:
Detect the difference in light travel time between the two arms (interferometry)
GW travelling along z axischanges distance in x and y : change in x is opposite to change in y and oscillating
Located in Cascina, near Pisa, ItalyArms length : 3 kmSensitivity zone : 10 Hz-1 kHzSensitivity max :Begins running in 2002
Example : VIRGO
Hz1/233.10
Example : VIRGO (II)
Data Handling : Similarities/Differences with
HEPData flux : 7.6 MB/s -> 150 - 200 TB/year
(few channels, continuous recording)Online selection -> 3 TB of selected dataMain difference with HEP : no events, but
data have a temporal linkDefinition of a specific data format : the
Frame1 Frame = data chunk of 1 sec of
interferometer running
VEGA : an environment based on ROOT
Evaluated by the VIRGO experiment
User interaction : use ROOT facilities
Data access : the metadatabaseSignal processing/analysisGraphics
VEGA : the metadatabase
Data stored in Frame format Time is the main access parameter
Need to access simply any vector/frame
Build a database containing metadata (data about data)
Indexes a set of Frame files
VEGA : the metadatabase (II)
VEGA : the metadatabase (III)
Performances : Tested with 10
5 files, 1 frame each
If 100 frames/file, simulates 107 frames in
terms of memory and speed (3 months of VIRGO data)
Memory : ~ 500 MB to index ~ 1 TB of data Speed : Metadatabase overhead in access
time = 2% of frame access time on average
VEGA : Signal processing/analysis
Plan to use VIRGO data analysis library Basic signal analysis
FFT, Convolution, Filters
Standard VIRGO analysis tools for GW signals
Need 100s of GFlops of computing power, use of PROOF ?
VEGA : Graphics
Time is everywhere in GPS format : Today 14:00:00 is GPS 633618013 !
Need a reference timeAdded time on the axis into ROOT
Not perfect but worksUse of plots with large number of
points (>105)
Weaknesses/Problems
(T) = Technical problem
(T) Time on the axis still has problems, related to the way axis are drawn
(T) Numbers (time) on the axis grow rapidly May want to display 1 sec of data
going from 1000000 to 1000001problems in graphics in that case
What people dislike
Interactivity Finding the right object is not natural
(though logical)For one histogram -> five objects in a padEnhance popups with info on neighboring
objects ?
(T) Histogram is hard to pick with mouse when large number of points
TPaveStats::SetStat(111) : Meaning of 111 in dialog… ? See point about doc and help
What people dislike (II)
The Interpreter Sometimes dereferencing 0 gives a segfault If segfault, no core, no info where it
happened (macro line) But less complaints about the interpreter
Graphics Axis on the right are not intuitive to draw
-> Doc in TGaxis, people search in TAxis
What people dislike (III)
The class doc contains almost everything but…
Finding a piece of info is not trivial No reference where to search Examples
Greek letters-> TPostscript or TLatex or TText ?Axis -> TGaxis or TAxis ?
You have to know the name of the class, not trivial for beginners
Sometimes three classes to find one info
What people like
Tab completionInteractivity (zoom, changing
properties of objects…)The Interpreter… and many more !
Strengths of ROOT for us
We hope connection with batch is simplified thanks to the interpreter
Frame access is fast through the metadatabase
Keep the Frame formatConsistency across the whole data
analysis
All in All...
VEGA is based on ROOT, and happy like this !
Also based on the Framelib managing Frame files
Consistency through the analysis For the language For the input/output
http://wwwlapp.in2p3.fr/virgo/vega
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