Atlantis: Visualization Tool in Particle Physics

Transcription

1 Atlantis: Visualization Tool in Particle Physics F.J.G.H. Crijns 2, H. Drevermann 1, J.G. Drohan 3, E. Jansen 2, P.F. Klok 2, N. Konstantinidis 3, Z. Maxa 3, D. Petrusca 1, G. Taylor 4, C. Timmermans 2 1) CERN Laboratory, Geneva, Switzerland 2) Radboud University Nijmegen and NIKHEF, Nijmegen, The Netherlands 3) University College London, London, Great Britain 4) University of California, Santa Cruz (CA), USA Atlantis.Support@cern.ch Abstract Modern collision experiments in particle physics produce huge amounts of particles during a collision, which makes the analysis of such events extremely complex. A good visualization tool can be used to help the interpretation of events. Besides, the human perception of displayed data must also be considered. By using projections and transformations that are adapted to the specific properties of detector and particles and by using special techniques during display, it is sometimes surprisingly easy to view specific details and do a much better analysis. This article describes special features of a visualization tool, the event display Atlantis, which has been under development for about twenty years. Currently the program is used for the analysis of simulated data in the ATLAS detector and of experimental data from a test set-up, the Combined Test Beam of the ATLAS experiment at the CERN Laboratory. 1. Introduction 1.1. Particle Physics In short, particle physics explores what matter is made of and what forces hold it together. The necessary tools for this exploration are accelerators, which accelerate particles to almost the speed of light, and detectors to measure what happens when the particles interact. Currently a new accellerator, the Large Hadron Collider (LHC), which will be the world s most powerful accellerator, is under construction at the CERN Laboratory in Geneva, Switzerland. It will be placed underground in a ringshaped tunnel with a length of 27 km. LHC has two particle beams that will collide at specific interaction points. Detectors will be placed around those points to take the data of collisions, one of those detectors is the ATLAS detector. The ATLAS collaboration, consisting of over 100 laboratories and over 1000 physicists, develops hardware and software for the experiment. Figure 1: The events to be produced by LHC will have thousands of trajectories, all originating from nearly the same point. Which hit belongs to which trajectory? Which hit is noise and doesn t belong to a trajectory? Which trajectories are fake, which trajectories are not found by the reconstruction programs? Simulation of collisions by Monte Carlo techniques is used to develop and optimize new experiments. Hardware and software for accellerator and detectors are developed according to the results. Finally, data are taken and analysed. These steps together may take up to 20 years! And for all those steps the visualization of detector and data is crucial. The data that become available via the detector are

2 indirectly measured points on particle trajectories. They are called hits and consist of points or lines in 3D space, depending on the type of subdetector used. From those data the original trajectories are reconstructed. Reconstruction is a tough job, considering the tens of thousands of hits from a typical interaction. Human perception plays an important role in the visualization of the data. To be able to distinguish between small objects, only a very limited set of colours can be used. Also the selection of the background is very important when displaying a multitude of graphics elements. E.g., thin white and yellow lines on a dark blue background can hardly be distinguished. See reference [5]. 2. Atlantis The development of a specific visualization tool for the ALEPH experiment at CERN started about fifteen years ago by Hans Drevermann. He developed a Fortran version, DALI, that has been used intensively for ALEPH event data. For the new ATLAS experiment, DALI, with the experience of many years of use, has been adapted and converted by Gary Taylor to Atlantis, written in JAVA. Figure 2: The ATLAS detector. The various detector components can be seen in this cut away view of the detector. Only a few green chambers of the Muon System are shown on the greyish support structure. (picture by CERN/ATLAS) Parts of the detector are placed within strong magnetic fields, which cause the trajectories of electrically charged particles to be curved. This curvature helps in the computation of the energy and mass of the particle and the reconstruction of the total event. The different subdetector systems of the ATLAS detector, starting from the collision point, are the Inner Tracker, the Calorimeter System and the Muon System. The different systems detect different types of particles. The order in which the systems are placed is guided by the penetration capability of the particles: lesser penetrating particles are detected in the Inner Tracker, fully penetrating particles are detected during traversal of the Muon System. See references [2], [3] and [4] Human perception Atlantis is used to display both experiment data, i.e. the hits that are detected by the detector subsystems, and reconstructed data, i.e. the trajectories of the particles that have been computed from the hits. Since the LHC accellerator and the ATLAS detector are still under construction, realistic experimental data are generated by using Monte Carlo techniques and then polluted by noise hits. These simulated experiment data are used to test the reconstruction, which converts hits to trajectories to full event. Thus Atlantis can be used to check simulation and reconstruction programs and eventually to check real events for physics phenomena. Apart from standard operations (zoom, move, rotate, rubberband, pick, select, scale, etc.), Atlantis has a choice of projections and transformations that can be applied to the data. Those projections and transformations make use of the specific properties of detector subsystems and of the curved trajectories of electrically charged particles that cross magnetic fields. See reference [1] Coordinates Two coordinate systems are used in Atlantis. Cartesian coordinates (X,Y,Z) are used as follows: the Z axis coincides with the beam axis, i.e. the direction of the incoming particles, the X axis runs horizontally and the Y axis runs vertically. Additionally a (φ, η, ρ) coordinate system

3 is used with ρ= X 2 + Y 2, φ=arctan(y/x), η=arctan(ρ/z) Projections Some typical projections that are used in Atlantis are described. An intuitive, orthogonal projection along the beam axis is given by the Y/X projection, which projects data on the plane through X and Y axes. See figure 3. Figure 4: The φ/η projection for calorimeter data: top left shows the V s of the V-plot, others show the energy deposits in the successive calorimeter layers with V s superimposed. Data from 3D tracking chambers may be shown in a very special projection in φ and η, called the V-plot. For one point in space (with coordinates φ, η, ρ) a pair of points is displayed. In the case of particles moving in a solenoidal magnetic field the two displayed points get the same φ as vertical position and get two different horizontal positions namely η ± k (ρ max ρ). The value of the gradient k is set by default but may be changed interactively. The parameter ρ max is set automatically depending on the selected view. As k and ρ max are known, φ, η and ρ may be recalculated from the coordinates of a pair of displayed points, which means that the V-plot is a true 3D image. Figure 3: ATLAS detector and simple event with Y/X projection applied. The detector is represented by the central Inner Tracker (black), the Calorimeter System (green, red) and the outer Muon System (black and blue). Both hits (white, red) and reconstructed trajectories (green, yellow) are shown. A similar orthogonal projection on the plane through Y and Z axes, is not very useful. More useful is a special projection, the ρ/z projection, which projects the planes through the Z axis with variable angle ρ onto a plane through the Z axis with fixed angle ρ. Calorimeter data can be shown in the φ/η projection as energy deposits of the particles in the calorimeter layers. See figure 4. Figure 5: Creation of a V-plot: top left shows event with Y/X projection applied; top center shows event with zooming applied; top right has φ/η projection applied for both hits and reconstructed trajectories and shows rubberband selection; bottom left has φ/η pro-

4 jection applied for reconstructed trajectories; bottom center shows area selected by rubberband with both hits and reconstructed trajectories; bottom right shows selected area with reconstructed trajectories only. a selected azimuthal region to be shown in detail while still displaying the full See reference [5] Transformations Two useful transformations are described, the fisheye and the clock transformation. Since so many trajectories originate from one small center point, it is hard to see the trajectories near the center point. A circular fisheye transformation can be applied, which means that the area near the center point is enlarged and the faraway area of the muon system is shrunken. Circles around the center point are transformed into circles with a different radius. Close to the center the radius increases, far from the center the radius decreases. Straight lines through the center remain straight. Note that this transformation, with blown-up Inner Tracker and shrunken Muon System, allows to scrutinize the area around the center point without losing sight of how trajectories continue into the Muon System. See figure 6. Figure 7: As figure 3 but with both fisheye and clock transformation applied Interactions The canvas that shows the pictures generated by the visualization tool can be divided in one or more subwindows. Thus it is possible to have different projections visible simultaneously in the subwindows. Synchro cursors allow the same cursor position to be shown in all projections. By defining a point in one of the subwindows it can be displayed in the other subwindows. This concept makes it possible to find the hit or trajectory you located in one subwindow in the multitude of hits and trajectories in another subwindow with a different projection, transformation and zooming applied. 3. Combined Test Beam Figure 6: As figure 3 but with additional fisheye transformation applied. Another transformation that can be used e.g. to untie close trajectories, is the clock transformation, an angular fisheye transformation which allows Since the construction of a detector in the LHC isn t a simple job, a lot of testing is required both in hardware and in software. This is done for detector components and computer programs seperately, but in 2004 a Combined Test Beam of the ATLAS subdetector systems was constructed to be able to test the working of all types of detector components together. Using finished and prototype hardware, a full section of the new detector was built above ground and tested with various particle beams.

5 Atlantis was used as the primary visualization tool for this setup and has already booked some remarkable successes, e.g. detector components that were positioned wrongly in the software, connections that were exchanged in the hardware. 4. References 1. Atlantis website 2. ATLAS websites CERN website Figure 8: Checking the calibration of TRT hits in the Combined Test Beam: left without calibration, right with calibration. (pictures by Thijs Cornelissen, NIKHEF) 4. LHC website 5. H. Drevermann, D. Kuhn, B.S. Nilsson, Event Display: Can We See What We Want to See?, CERN/ECP 95-25, Geneva, 19 October 1995.