Proposal for precise geometry parametrization of planar imaging detectors.

Content

 

Coordinate system for setup

Axes definition

Cartesian coordinate system of setup is defined by three mutually orthogonal right-hand-indexed axes with origin in the interaction point (IP) of the photon beam with target:

as shown in the plot:

                             

 

Each photon with sample collision happens in different place... IP is an abstract position of the crossing point of the "beam line" and "target", which both are not well defined... Is it really good definition?

 

Detector position

Detector coordinate system may have a translation and rotation with respect to the setup, which can be defined by the 3 vectors in the setup frame:

as shown in the plot:

                                         

Third unit vector ez – is assumed to be right-hand triplet component,

               ez=[ex × ey].

Components of these three unit vectors form the rotation matrix eij, where indexes "i" and "j" corresponds to the vector components in the setup and detector local coordinate frames, respectively. Within this definition 3-d pixel coordinate "c" in the detector frame can be transformed to the setup coordinate "C" using equation

                              Ci=eij·cj + Pi.

 

 

Coordinate system of the detector

In this note we assume that:

These assumptions are not necessary for most of algorithms. But, in many cases it may be convenient to use small angle approximation or ignore angular misalignment for image mapping between tiles and 2-d image array.

 

Tile ideal geometry

           

For any type of tile there should be a class or method returning pixel coordinates in this ideal geometry

            (x, y, z) = get_pixel_xyz(row,column),

or look-up tables for consecutive pixel indexes

              (xarr, yarr, zarr) = get_pixel_xyz_arrays().

 

 

Memory model

It is assumed that each tile is presented in DAQ or offline data by a consecutive block of memory.  Uniform matrix-type geometry of pixel array is preferable, but  other geometry can be handled.  For example, for CSPAD 2x1 sensor pixel index in the tile memory block of size (185,388) can be evaluated as

                         i = column + row*388.

 

Detector data record consists of consecutive tile-blocks, in accordance with numeration adopted in DAQ. For effective memory management, some of the tile-blocks may be missing due to current detector configuration. Available configuration of the detector tile-blocks should be marked in a  bit-mask word in position order (bit position from lower to higher is associated with the tile number in DAQ).

 

Optical measurements

Quality check

Quality check of optical measurement may include for each tile:

 

Position of tiles in the detector

Detector pixels' geometry in 3-d can be unambiguously derived from

The tile location and orientation can be defined by the table of records

Tile #Xc[µm]Yc[µm]Yc[µm]Rotation angle [degree]Tilt in X-Y[degree]Tilt in Y-Z[degree]Tilt in X-Z[degree]

where

Tile center coordinates are defined as an average over 4 corners.

Tilt angles are projected angles of the tile sides on relevant planes. Each angle is evaluated as an averaged angle for 2 sides.

Origin of the detector local frame is arbitrary. There are few preferable options for choosing coordinate frame origin:

 

                                            

 

Pixel coordinate reconstruction uses

             (x,y,z)in detector = (Xc,Yc,Zc) + Rotation(N·90+tilt) × (x,y,z)in tile.

 

 

Pixel coordinates in the detector should be accessed by method like

            (x, y, z) = get_pixel_xyz_in_detector(tile_number,row,column),

or look-up tables for consecutive pixel indexes

              (xarr, yarr, zarr) = get_pixel_xyz_arrays_in_detector().

 

Summary

Suggested method for imaging detector geometry description provides simple and unambiguous way of pixel coordinate parametrization. This method utilizes all available information from optical measurement and design of the detector and tiles. All geometry parameters are extracted without fitting technique and presented by natural intuitive way.