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Content

Abstract

Introduction

Analysis of LCLS data from imaging experiments requires precise coordinate definition of the photon detection spot.  In In imaging experiments at LCLS users want to know precise coordinates of photons reported by the detector. For pixel array detectors photon energy usually deposited in a single pixel and hence pixel location precision should be comparable with or better than its size, about 100μm.  Apparently, calibration of the detector and entire experiment experimental setup geometry with such a precision is a challenging task for many reasons; 

• position of the detector w.r.t. sensors relative to interaction point (IP)  of the photon beam with target is not well known,
• in some cases detector consists of a few is a composition of other sub-detectors arranged together and consisting of other sub-detectors and so on for a few layers in depth,
• sometimes sub-detectors may move w.r.t. of each layer may have stable positions or be moved by stepping motor relative to each other,
• final level sub-detectors (different in general) consist of precisely engineered sensors which positions are not well known and need to be calibrated. detector is represented by precisely engineered sensor(s) of particular type(s) which geometry needs to be tabulated.

To take into account this structure To describe such a geometry we may consider a variable length series of hierarchical objects like pixel → sensor → -> sub-detector → -> detector → -> setup, where each lowlower-level child object is included (s) is(are) embedded in its higher-level parent object. For each node of this hierarchical model low-level objects   Nodes/objects of this hierarchical model form the tree , which is convenient for recursionsnavigation and recursion algorithms. Each child object position location and orientation can be described in the parent frame. Tree-like structure can be kept in form of table saved in and retrieved from file. The last feature is practically convenient useful for calibration purpose; all .  All constants for detector/experiment geometry description can be saved saved  in a single file. Whenever Relevant parts of the hierarchical table can be calibrated  and updated whenever new geometry information is available, for example from optical measurement or dedicated runs with images of bright diffraction rings , particular part of the hierarchical table can be updated.or Bragg peaks.    

This note contains description of the implemented hierarchical geometry model, implemented coordinate transformation algorithms, parametrization tabulation of the hierarchical geometry in tableobjects and calibration file format, description of software interface in C++ and Python, details of calibration, etc.                                                           

Coordinate system for setup

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