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