1.
Introduction
This document is intended to provide the LAT collaborators
with sufficient information to perform data analysis during LAT integration. It
is intended for users who are familiar with the LAT instrument,
however a brief overview is provided.
Most of the information in this document is
either copied from the website of Instrument Analysis Workshop presentations,
or existing LAT-DOCS. A list of references is provided in Resources, section 12.
The Large Array Telescope (LAT) is an
integrated instrument consisting of 16 towers set into a 4x4 grid. Each tower
consists of a Tracker (TKR), Calorimeter (CAL), and Tower Electronics Module
(TEM), as shown in Figure 1. The 16 towers are surrounded by an
Anti-Coincidence Detector (ACD) which is surrounded by an
micro-meteorite shield.
Micro-Meteorite Shield
ACD Tiles
TRK Layers
Grid
CAL
Modules
TEMs
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Figure 1: The LAT
The following paragraphs provide a brief
description of how the major components are used during pre-launch tests and
are shown in Figure
2.
The ACD is mostly used to either identify charged
particles for cosmic ray calibration runs, or to reject charged particles
during Van de Graaff photon calibration runs.
The TKR’s
function is to reconstruct the original direction of travel of either incoming
photons (from 18 MeV photons from a Van de Graaff generator) or of charged
particles (cosmic rays).
The CAL’s
function is to measure the energy deposited by incoming charged particles,
either from photon pair creation or cosmic rays.
The TEM assembles trigger primitives from the TKR and CAL (or simulated input)
to determine whether or not there has been an event in the LAT. If so, it
alerts the GLAST Electronics Module (GEM). It also communicates with the Event
Builder Module. Trigger parameters are stored in the TEM.
The GEM (also referred to as the GLAST LAT Trigger -
GLT) responds to a TEM’s message that an event has
been detected and decides whether or not to generate a trigger. The GEM is an
important component when performing Dead Time and Trigger analyses.
The Anti-Coincidence Detector Electronics
Module (AEM) performs the same
function for the ACD as the TEM does for the TKR and CAL detectors.
The Event Builder Module (EBM) communicates with the
GEM, TEM and AEM.
The
Global-trigger/ACD-module/Signal-distribution Unit (GASU) performs the highest
logic level of event decision making, and comprises the AEM, GEM and EBM.
The Power Distribution Unit (PDU) supplies DC current to
operate the electronics.
Figure 2: Principal LAT Components (Block Diagram)
NOTE: Real detectors (ACD, TKR,
CAL) can be replaced by simulated
input that mimics the behavior of the physical detectors beginning at the
cables that readout the detectors. However, the Front End Electronics (FEE) are
not simulated, but a pattern can be created to generate events.
Data taking with cosmic ray muons and low energy photons
using the Van de Graaff accelerator will occur with 1, 2, 4, 6, 8, 10, 12, 14
and 16 Flight Modules (FMs) installed in the LAT
grid. For mechanical reasons, the first position filled is position #8. The
second position filled is #9. 24 hours of cosmic ray data taking occurs every
time towers are added to the LAT. 24 hours of data taking with Van de Graaff
photons occurs when integrating 1, 2 and 16 towers into the grid. Please refer
to LAT-MD-00575 for detailed information on
data taking during integration. Figure 3 shows the tower positions filled in each
data taking configuration. Note that shaded squares indicate a tower
installed in the grid.
For each hardware configuration there will be
a baseline cosmic ray data-taking run for which the hardware is configured with
nominal settings (please refer to the Nominal Register Settings in section 5) for ground analysis for the integrated hardware
(towers).
Figure 3:
Tower Placement for Cosmic Ray Data Taking
Monte Carlo
simulations for Flight Modules will be performed for 1, 2, and 8 towers, and
the fully integrated LAT grid, as shown in Figure 4.
Figure 4: Grid
Tower Positions for Monte Carlo Simulations
The global instrument coordinate system for
the LAT is consistent with the coordinate system for the observatory. It is a
right-handed coordinate system with the Y-axis parallel to the
solar panel axis, the Z axis normal to the
planes of the TKR, CAL,
and Grid (i.e., parallel to the “bore sight”), and the X axis is mutually
perpendicular to Y and Z. The positive Z-axis points from the CAL to the TKR. Particles entering the
instrument at normal incidence are thus oriented along the -Z direction (please
see Figure
5).
The point X=Y=0 is at the center of the Grid.
The Z=0 plane is at the top face of the Grid, between the TKR and CAL units on the TKR side of the Grid. The
TKR silicon layer closest
to Z = 0 is at Z = +33 mm; the crystal layer closest to Z = 0 is at Z = -46 mm.
Figure 5: LAT
Tower Numbering and Grid
Coordinate System
2.1.
ACD Geometry and Numbering Scheme
The active elements of the ACD consist of 89
tiles and 9 ribbons. (A figure will be added later.)
The tracker is made up of 19 trays
comprising 36 layers as shown in Figure 6. It is important to note that layers are
numbered and labeled differently depending on whether the variable was
calculated in a digi or recon file. Please refer to Event Data
in section 7.
NOTE: In this document a “layer” is one side of a tray, only.
This is not always the convention used for TKR layers, but it is the convention
used throughout this document.
The TKR trays are numbered in increasing
order with increasing Z. Each tray has two active layers, except the top half
of the top tray (+Z) and bottom half of the bottom tray.
A tray measures in either the X or Y direction, i.e.,
has an X or Y view. To get X and Y
information, layers from two adjacent trays are electronically combined. X and
Y layers are about 2 mm apart. This arrangement leaves the top-most and
bottom-most layers without a partner and without silicon detectors.
A tray with detector
strips physically parallel to the Y axis is an X tray: it measures the X
coordinate (has an X view) and is called an X tray. Please see Figure 7. Most layers have an embedded tungsten
foil for g conversion: The
top 12 X and Y pairs have a thin foil (3% of X0),
the next four have a thick foil (18% of X0),
and the bottom two X and Y pairs have no tungsten.
The active regions of the TKR layers are
comprised of Silicon Strip Detectors (SSDs). Each SSD has 384 strips. Four SSDs
are end-joined to make a ladder with the four SSDs in a given ladder
electronically joined to make 384 long strips. With four ladders per layer,
there are a total of 1536 strips per layer. Each layer is about 360 mm2.
Figure 6: TKR Tower Numbering Scheme. (Note Difference between Digi and
Recon.)
Figure 7: TKR Layer Physical Details (X-View)
Each CAL module is made up of 96 crystals in
an 8 x 12 orthogonal layering of 12 crystals per layer and 8 layers. A CAL
crystal makes its coordinate measurement along its principal axis: an X crystal
has its principal axis along the X direction, as shown in Figure 8.
Each crystal has two PIN diodes at each end
for reading out the signal. Each PIN diode (at either end) reads out for either
the low or high energy measurement. The low energy PIN has an area four times
greater than the high energy PIN.
The CAL layers are numbered from 0 – 7 in
increasing order with decreasing Z. The CAL layer closest to the TKR is layer
0. CAL layer 0 has X crystals; CAL layer 7 has Y crystals. The CAL logs are
read from each end, and the log ends are either plus or minus: the end with the
larger value of the coordinate is the “plus” end and the end with the smaller
value of the coordinate is the “minus.”
Figure 8: CAL Crystal Layer Numbering and Orientation
Figure
10 shows an accurate representation of a CAL
module.
Figure 9: An Accurate
Representation of a CAL Module
Figure 10 shows a close-up view of the displacement of CAL
crystal ends of two adjacent CAL modules. It is important to note that crystal
ends that face each other are at a different spacing than the closest crystals
in adjacent modules that are parallel to each other.
Figure
10: Zoom of Region
between Two Adjacent CAL Modules Profile
The CAL
crystal profile is shown in Figure 11 along with the dimensions of a CAL
crystal, including its carbon fiber enclosure.
Figure
11: CAL
Crystal Dimensions
Table 1 lists the number of readout channels
(active elements) for the ACD, TKR and CAL in a 1, 2, 4, 8, and the full LAT
configuration. Note that the ACD front-end PCBs actually have 216 channels, but
because each tile is read by 2 PMTs that are assembled with a logical OR, the
number of tiles that can be read out is actually 108. With a total number
of 97 tiles and ribbons, some channels
are not used.
Table 1: Detector Readout Channels
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1 Tower
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36 / 55,296
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96 / 384
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2 Tower
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72 / 110,592
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192 / 768
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4 Tower
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144 / 221,184
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384 / 1536
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8 Tower
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288 / 442,368
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768 / 3072
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LAT
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89/178
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8/16
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576 / 884,736
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1536 / 6144
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To be written.
To be written.
3.2.
TKR Readout Sequence
Data from each silicon layer is read out by
24 GTFE ASICs located in a Multi-Chip-Module (MCM),
controlled by 2 GLAST Tracker Readout Controllers (GTRC). There are 2 (GTRC 0
and GTRC 1) per layer or 4 per tray (please see Figure 18). The two GTRCs
are situated at the edge of the layer. GTRC 0 (RC0) is defined as being closest
to where strip 0 is located. RC1 is defined as where strip 1535 is located. The
default mode is to read from both ends. The readouts of a TKR is carried
through eight cables (please see Figure 12).
If any shaper-out signal of a channel in a
GTFE chip is over threshold, a trigger request (TREQ) signal is issued and
transferred to the TEM, which then checks the trigger status. If a trigger
condition (3-in-a-row) is satisfied, the TEM sends the trigger request
acknowledge (TACK) signal to all layers to latch hit strip data into GTFE event
buffers. Each GTFE has 4 event buffers. Note
that it is not the TREQ but the TACK signal that starts the Time over Threshold
(ToT) counter in the GTRC.
The TEM sends the READ-OUT command and
transfers event data from GTFE event buffers to GTRC event buffers. A GTRC
event buffer is limited to 64 hit-strips. The GTRC has 2 buffers. The TEM sends
the TOKEN signal and transfers event data from the GTRC event buffers to the
TEM one layer at a time. The GTRC waits to send data until the process of the
READ-OUT command finishes, and the ToT counter terminates. The ToT counter
saturates at 1000 clock cycles (= 50 μs). In a case where the ToT counter overflows,
the GTRC will start to send data at the overflow point (1000 clock cycles).
The TKR mapping scheme is shown in Table
2. This table maps the TKR physical
information in LDF, digi and recon files. Figure 12 shows the four faces of the TKR. A
typical user does not need to know the information in electronics space. This table is intended to serve as a
reference for hardware-oriented people. Before using the Electronics Space
information, always verify that it is the latest information in the TEM manual.
Table 2: TKR Mapping between Physical and Electronics Space. Note
that “X” or “Y” Means Measured Coordinate.
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18/B
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35
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0
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Y
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4,5
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8
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17/T
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34
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0
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X
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6,7
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8
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17/B
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33
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1
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X
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2,3
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8
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16/T
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32
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1
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Y
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0,1
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8
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16/B
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31
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2
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Y
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4,5
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7
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15/T
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30
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2
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X
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6,7
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7
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15/B
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29
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3
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X
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2,3
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7
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14/T
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28
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3
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Y
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0,1
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7
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14/B
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27
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4
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Y
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4,5
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6
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13/T
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26
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4
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X
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6,7
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6
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13/B
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25
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5
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X
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2,3
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6
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12/T
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24
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5
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Y
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0,1
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6
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12/B
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23
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6
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Y
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4,5
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5
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11/T
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22
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6
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X
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6,7
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5
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11/B
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21
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7
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X
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2,3
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5
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10/T
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20
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7
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Y
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0,1
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5
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10/B
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19
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8
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Y
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4,5
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4
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9/T
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18
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8
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X
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6,7
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4
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9/B
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17
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9
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X
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2,3
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4
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8/T
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16
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9
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Y
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0,1
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4
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8/B
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15
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10
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Y
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4,5
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3
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7/T
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14
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10
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X
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6,7
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3
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7/B
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13
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11
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X
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2,3
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3
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6/T
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12
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11
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Y
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0,1
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3
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6/B
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11
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12
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Y
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4,5
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2
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5/T
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10
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12
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X
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6,7
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2
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5/B
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9
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13
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X
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2,3
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2
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4/T
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8
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13
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Y
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0,1
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2
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4/B
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7
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14
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Y
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4,5
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1
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3/T
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6
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14
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X
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6,7
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1
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3/B
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5
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15
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X
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2,3
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1
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2/T
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4
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15
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Y
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0,1
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1
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2/B
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3
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16
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Y
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4,5
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0
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1/T
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2
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16
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X
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6,7
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0
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1/B
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1
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17
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X
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2,3
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0
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0/T
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0
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17
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Y
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0,1
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0
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Figure
12:
The Four Sides of the TKR Tower with Cables. Note that “X” or “Y” Means
Measured Coordinate.
3.3.
CAL Readout Sequence
The CAL crystals are normally read from both
ends through a total of four cables – each crystal is read out by two cables.
Each crystal end has two PIN diodes, one large and one small, for low and high
energy, respectively. Each crystal end (left and right ) has its own FEE
pre-amplifier electronics assembly. Both low and high energy signals go through
a pre amp and shaper then a Track and Hold gain multiplier and into an analog
multiplexer and finally to the Analog to Digital Converter (ADC). A simplified
schematic diagram is shown in Figure 13. The calibration charge injection
signal is fed to the front end of these pre amps.
Figure 13: CAL FEE Simplified Schematic Diagram
Table 3 shows the gain stages.
Table 3: CAL FEE Signal Gain Characteristics
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Low Energy
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X 6
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X 64
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X 1
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LEX1
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64
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X 8
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LEX8
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512
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High Energy
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X 1
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X 1
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X 1
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HEX1
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8
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X 8
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HEX8
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1
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Figure 14 shows how the energy ranges overlap.
During cosmic ray data taking on the ground most of the events fall within the
low range diodes.
Figure 14: CAL Channel Signal Range Energy Overlap
Table 4 maps the locations of layers and
crystal ends between the electronics space and the physical space. A typical
user does not need to know the information in electronics space. This table is intended to serve as a
reference for hardware-oriented people. Before using the Electronics Space
information, always verify that it is the latest information in the TEM manual.
Table 4: CAL Mapping between Physical and Electronics Space
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0 / X
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0
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0
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0,2
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0
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1 / Y
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1
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1
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1,3
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0
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2 / X
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2
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2
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0,2
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1
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3 / Y
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3
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3
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1,3
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1
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4 / X
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4
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4
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0,2
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2
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5 / Y
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5
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5
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1,3
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2
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6 / X
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6
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6
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0,2
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3
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7 / Y
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7
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7
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1,3
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3
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The CAL readout cables and the associated GCCC are
shown in Figure
15.
Figure 15: The Four Sides of the CAL Module with
Cables
The Trigger inputs from the ACD, CAL and TKR
are processed by the GEM. The GEM decides whether to read out an event or not
based on all inputs received. Therefore trigger primitives can be issued but
may lead to no data latched if the GEM decides that all necessary conditions
have not been met.
Any of the three detectors (ACD, CAL and
TKR) can issue a trigger request (TREQ) but data is only latched from the
detector buffers if the GEM logic is satisfied that a trigger acknowledge
(TACK) is warranted.
The ACD signals are usually used as a veto
for charged particles. However, the CNO signal can be used to trigger on heavy
nuclei (mostly used for calibrations). During ground testing we can only test
the CNO signal through charge injection. Another useful concept one has to keep
in mind is that Regions Of Interest (ROI) can be defined using the ACD tiles.
So a number of tiles can be logically grouped for trigger/veto purposes.
The TKR trigger logic requires at least one
hit above a predetermined threshold in three consecutive XY layers (six
layers).
The CAL trigger logic requires at least one
hit above a predetermined threshold in any of the crystals. One can have a low energy trigger and a high
energy trigger. For ground testing with cosmic rays the nominal CAL low-energy trigger
is already too high and one must lower the discriminator thresholds or use the
TKR trigger, instead.
During ground testing there will be a
pattern generator (software) that will produce several trigger rates from a few
Hz to tens of kHz. These solicited triggers will be overlaid with the
nominal trigger conditions (e.g. TKR trigger) to study the behavior of the
trigger and data flow system.
To trigger on a set of trigger inputs coming
from different detectors, they must all fall within the same time coincidence
window, but the system must not be busy (already reading an event). Note that
during ground testing in order to cope with rates greater then 1.5 kHz one may
have to prescale (discard) events.
For the TKR, the hit threshold is also the trigger
threshold. The threshold is that six consecutive layers must be fired. Nominal
trigger rate on the ground (no ACD) is roughly 25 Hz (TBR) for each TKR tower
for cosmic ray analysis.
All three subsystems have preamps that put
out shaped pulses that peak at different times after the entrance time (t0) for
the particle into the LAT.
Any one of the three detectors can cause the
GEM to issue a TACK which latches the buffered data of all three detectors
regardless of whether or not they issued a trigger request. The purpose of the
time delays is to ensure that the trigger window is open at the correct time to
receive data from all the detectors at the peak of the input pulses for a given
detector. Table
5 shows the different delays for the ACD,
CAL and TKR. The table is for the entire ACD but just one of the 16 tower
modules.
Table 5: Detector Timing Delay Registers
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ACD
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12 TREQ Delays
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12 TACK Delays
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CAL High
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4 TREQ Cable Delays
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1 TREQ Delay (OR of 4 inputs)
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1 TACK Delay (applied to all 4 cables)
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4 TACK Cable Delays
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CAL Low
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1 TREQ Delay (OR of 4 inputs)
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TKR
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8 TREQ Cable Delays
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1 TREQ Delay (OR of 8 inputs)
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1 TACK Delay (applied to all 8 cables)
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8 TACK Cable Delays
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Figure 16 shows the various time
delay registers that are available at the input to the GEM. CAL low and CAL
high come in on the same four cables, each with a cable delay. CAL high and CAL
low are then split into two lines with each line having a TREQ delay as input
to the GEM. The TKR signals come in on eight cables, each with a delay
register. The eight signals are OR’d into one line
which has a delay register before input into the GEM. The ACD signals come in
through 12 lines, each with a delay in the GEM input.
Figure 16: Conceptual Trigger Delay Adjustments
Diagram (GEM Inputs)
The GASU output (please see Figure 17) has an adjustable Trigger Window Width
register that feeds all three detectors with a single signal line. For the CAL
it passes through a TACK delay register before being split into four lines,
each with a CAL TACK cable delay. Likewise, the GASU output signal passes
through a TKR TACK delay before being split into eight lines, each with a TKR
TACK cable delay. For the ACD the GASU output signal splits into 12 lines, each
with an ACD TACK delay register.
Figure 17: Conceptual Trigger Delay Adjustments Diagram
(GEM Outputs)
To be written.
There are hundreds of registers in the LAT.
Here we discuss only a few registers that one need be aware for data analysis.
5.1.
ACD Nominal Register Settings
To be written.
To be written.
To be written.
The ACD has 12 ACD TREQ delay registers
feeding into the GEM. There are also 12 ACD TACK delay registers applied to the
output of the GEM for ACD hold. Table 6 lists the nominal settings for the ACD
delays. Until test are performed assume that all 12 delays for the input or
output are equal.
Table 6: ACD Delay Register Nominal Settings
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12 TREQ Delays
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12 TACK Delays
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To be written.
Nominal settings for the registers of
interest are described here. The registers
of interest are the GTFE registers MODE, DAC and MASK, and the GTRC registers
for GTFE_CNT, SIZE, and TOT_EN and time delays.
The GTFE threshold setting defines an energy
value above which the preamplifier in each channel integrates the charge
collected until the charge signal re-crosses the threshold. The time the signal
remains above the threshold is the ToT. Please see Figure 19.
Each strip hit in a silicon layer
contributes with a ToT value. A logical OR of all strips in the layer is used
to determine the value of the ToT per layer. ToT can be used to crudely
determining the amount of energy deposited on the TKR because its value is
dominated by the strip with the highest energy deposited. Channel-to-channel
variations exist and this is discussed further in the Calibrations Section, 6.2.
Each layer generates two ToT values because
it can be read out by 2 GTRC chips (please see Figure 18). The default configuration is to read 12 GTFEs with each GTRC: 12 GTFE chips read out by GTRC0 and
12 GTFE chips read out by GTRC1. If a GTFE fails it can be by-passed and the
split is modified from the usual 12/12. Every data analysis run includes a
report that states what the GTRC split is, which is important for Timing and
Trigger studies.
Figure 18: TKR FEE Readout Channel Splitting
The hit threshold can be set individually
for each GTFE with a default value of 0.25 of that of a Minimum Ionizing
Particle (MIP). The goal for the data taking with cosmic rays and VDG
accelerator is to have a uniform set of thresholds across all readout chips.
These are determined by measuring both the trigger capture efficiency and the
noise rate as a function of the discriminator DAC settings.
Figure 19: Shaper Output Time over Threshold
The GTFE and GTRC registers of interest are
shown in Table
7.
Table 7: TKR GTFE and GTRC Registers
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GTFE
(Please refer to LAT-SS-00169 for further
details.)
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Mode
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2-bit
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Left or Right mode (Is the GTFE read out
by the left or right GTRC)
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Deaf mode ON / OFF (Is the GTFE deaf to
the GTFE beside it?)
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DAC
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7-bit +
7-bit
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THR_DAC: (0-2 MIPS) Sets the threshold
level of the comparator. Range: about 0.05 -10 fC
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CAL_DAC: (0-8 MIPS) Sets pulse height of
calibration strobe signal. Range: about 0.072-43 fC
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Mask
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64-bit
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Channel mask
Trigger mask
Calibration mask
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GTRC
(Please refer to LAT-SS-00170 for further
details.)
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GTRC_CNT
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Sets the number of GTFEs
to read by defining the LEFT/RIGHT split point. Range: 0-24. The default is
12 LEFT and 12 RIGHT. Please see Figure 18.
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Size
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Sets the maximum number of hits to get
from the GTFEs. Range: 0-64. The default is 64.
NOTE: Max hits/layer: 128 can be read using both LEFT and
RIGHT sides.
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TOT_EN
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1-bit
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ENABLE TOT (1) or DISABLE TOT (0). The
default is 1.
|
Each TKR has a total of nine TREQ
delays. Each TKR has a total of nine
TACK delays. Table
8 lists the TKR delay register nominal
settings. Until test are performed assume that the cable delays for an input or
output are equal.
Table 8: TKR Delay Registers Nominal Settings
|
|
|
|
TREQ (8 – 1 per cable)
|
|
|
OR’d TREQ (1)
|
|
|
TACK (1 – applied to all 8 cables)
|
|
|
TACK (8 – 1 per cable)
|
|
Some known features for the TKR electronics
are shown in Table
9.
Table 9: TKR Electronics Known Features
|
|
|
|
Limit of TOT
Counter
|
The
TOT counter saturates at 1000 count, corresponding to 50 μs.
(c.f. 1 MIP ~ 10 μs.)
|
|
Limitation of Calibration-Strobe
Signal in GTFE
|
The
calibration strobe signal of GTFE used in charge-injection tests is a signal
with a duration of 512 clock cycles = 25.6 μs. Thus, we cannot simulate TRIG signal longer
than 25.6 μs with the internal calibration
system.
|
|
TACK Too Late in a
Small Signal
|
Small
signal events with the pulse height very close to threshold will be missed at
the TACK time, which causes the event with a trigger but no hit. The
probability of such events was 10-5 in EM1 tower.
|
|
2 TACKs in One TREQ Signal
|
If
multiple TACK signals are sent within one long trigger signal, TOT in the
second readout event shows an illegal number (2044).
|
CAL Nominal register settings are divided
into the three categories of Gain, Triggering and Data Volume as shown in Table 10.
Table 10: CAL Registers for Gain, Triggering and Data Volume
|
|
|
|
|
|
Gain
|
LE
|
8 programmable settings for a x3
gain-range.
|
One setting per CAL face (= 16 towers x 4
faces)
|
|
HE
|
9 programmable settings, x3 in gain plus
test gain for muons.
|
One setting per CAL face (= 16 towers x 4
faces)
|
|
Time to Peak
|
Adjustable so that track-and-hold occurs
at the peak of the shaped signal.
|
One setting per tower with different
settings for muons and charge injection.
|
|
Triggering
|
FLE
|
Threshold adjustable for every CAL crystal
end (1536/crystal x 2 faces) with 64 fine and 64 coarse programmable DAC
settings that cover about 200 MeV
|
Fast Low Energy (FLE) and Fast High Energy
(FHE) have a timing constant of .5 μs,
important for timing and analysis.
(For reference, the Slow Low Energy shaper
has a timing constant of about 3.5 μs.)
|
|
FHE
|
Threshold is adjustable for every CAL
crystal end (1536/LAT x 2 faces) with 64 fine and 64 coarse programmable DAC
settings that cover about 25 GeV.
|
|
Data Volume
|
Range Read
|
Range Readout can be either commanded or
run in Auto-range. The range modes are one range or four ranges.
|
In Auto-range, the appropriate energy
channel is selected and read out.
|
Table 11 shows the nominal register settings for
the different modes of data taking, of which there are two: flight and ground.
Flight mode tests flight operations with a
best guess at on orbit configuration. Ground mode tests high gain in the HE
channels to see muons and VDG photons, and with thresholds low enough for CAL
to trigger on muons and VDG photons.
Table 11: CAL Registers Nominal Settings
|
|
|
|
|
Flight
|
Ground test of flight operations
|
TKR:
trigger enabled
FLE:
~ 100 MeV but disabled
FHE:
~ 1 GeV enabled
LE
rails: ~ 1.6 GeV
HE
rails: ~ 100 GeV
Auto
Range: one range readout
Zero-suppression:
enabled
LAC
threshold ~ 2 MeV or below
|
|
Ground
|
Muons visible in HE ranges. Muon runs to test
stability.
|
Flight
Trigger
TKR: trigger enabled
FLE:
~ 100 MeV but disabled
FHE:
~ 1 GeV, enabled
Muon
Gain:
LE
rails: ~1.6 GeV
HE
rails: ~4 GeV
Intermediate
Data Volume:
Auto-range,
four-range readout
Zero-suppression:
enabled
LAC
threshold ~ 2 MeV or below
|
|
Ground
|
Muons visible in HE ranges. Ground test of
CAL self-trigger.
|
CAL
Trigger
TKR
trigger: disabled
FLE:
~2 MeV and FHE ~ 1 GeV (trigger on FLE)
FLE:
~ 100 MeV and FLE < 10 MeV (trigger on FHE)
Auto-range,
four-range readout
Zero-suppression:
enabled
LAC
threshold ~ 2 MeV or below
|
Each CAL has a total of six TREQ delays. Each
CAL has a total of five TACK delays. Table 12 lists the delay register nominal
settings. Until test are performed assume that the cable delays for an input or
output are equal.
Table 12: CAL Delay Registers Nominal Settings
|
|
|
|
TREQ (4 – 1 per cable)
|
|
|
CAL Low TREQ (1)
|
|
|
CAL High TREQ (1)
|
|
|
TACK (1 – applied to all 4 cables)
|
|
|
TACK (4 – 1 per cable)
|
|
Table 13 below lists some of the known features of
the CAL electronics.
Table 13: CAL Known Features
|
|
|
|
Readout time can be
long
|
In
a case with 4-range, unsuppressed CAL readout of ~ 600 μs:
Because
of the TEM readout buffer logic, one of these events does indeed paralyze the
entire system for ~ 600 us. FIFO has space for less than 2 of these events,
and readout is paralyzed if space for less than 1 remains.
|
|
Solicited triggers
with zero suppression enabled
|
Readout
time is a function of the CAL data volume. Either set the LAC threshold low
so that some pedestals sneak through, or inject charge in some specific
channels, or CAL data will be null. Tests with high-rate, Poisson solicited
triggers must be carefully posed.
|
|
CAL can retrigger
|
If
CAL self-trigger is enabled with a low threshold and zero suppression is
enabled, CAL may double-trigger because the trigger gets re-enabled before it
settles.
Retrigger
does not occur with zero supp disabled (i.e. large CAL data volume) because
TEM readout is slow enough that FLE has had time to settle.
|
|
CAL trigger biases
energy
|
If
the FLE fires (whether or not it’s enabled) about 2 MeV gets added to LEX8
and LEX1 signals. Don’t calibrate gain scale with FLE set low for CAL
self-trigger on muons or VDG photons. There is a similar effect for FHE
firing which adds ~ 20 MeV.
|
Instrument calibrations consist of:
·
Creation of response maps for all detectors;
·
Determination of nominal instrumental settings
for astrophysical science observations, and;
·
Determination of energy scales.
The program is divided into electronic
calibrations (using charge injection) and calibrations using cosmic rays
(selected muons). These will have calibration trends characterized during the
LAT integration. For details, please refer to LAT-MD-00575.
The user should be aware that data taking
will occur with zero suppression ON and OFF at several stages of
integration.
ACD, TKR and CAL electronic calibrations are
performed using charge injection and with EGSE scripts and/or Flight Software.
Whenever appropriate EGSE output calibration files will be used as input to the
reconstruction code. Be aware that the trigger behavior may be different when
triggering with cosmic rays and with charge injection. Data from charge
injection will be available in digi format but this primer is not intended to
guide general users to analyze those data.
Calibrations will be performed after
particle data is taken using offline analysis of the L1 data converted into
digitized data analysis files. Calibration data is then used as input to
generate reconstructed data analysis files.
6.1.
ACD Calibration
The ACD electronic calibration suite
establishes the calibration tables for the following features of each GAFE.
These calibration tables give the correspondence between relevant DAC settings
and output ADC bin or energy, as appropriate.
Units of calibration tables can be converted
to MeV in all gain settings. The ACD calibration will determine:
·
Pedestals for all energy ranges in all gain
settings. An estimate of the electronic noise can be derived from the pedestal
width;
·
FEE transfer function for all energy ranges,
i.e., the integral non-linearity of the analog and digital chain for each
energy range. The electronic gain of each energy range is given by the linear
term of the correspondence between injected charge and output ADC bin;
·
Calibration of the veto (hit) threshold
discriminator DAC; and
·
Calibration of the zero-suppression
threshold DAC.
The ACD calibrations with cosmic rays
determine pedestals and measure the muon peaks in the ACD tiles. Data for pedestal calibration shall be taken
with ACD zero suppression OFF.
The TKR calibration will determine:
·
The list of bad channels (open, dead, noisy)
·
Calibration of the hit discriminator DAC;
·
The GTFE will scan the hit thresholds for a
fixed charge injection DAC, noise can be extracted from these measurements;
and,
·
The response of the time-over-threshold to
injected charge up to saturation. The appropriate function will be used to fit
the charging injection curve and extract the necessary constants that will be
used for the SAS reconstruction.
The TKR muon calibrations of the TOT scale
for a MIP are made at two levels: read out chip-level and strip-level. (This in
turn provides the calibration of the charge injection scale, which is essential
to adjust the threshold using the charge injection.) It also part of
verification of bad channels with cosmic rays, measurement of trigger and
detection efficiencies and collection of necessary data for the hit resolution
measurement.
NOTE: Although alignment procedures produce calibration
“constants,” these will be treated as a performance measure.
The CAL electronic calibration suite
establishes the calibration tables for the following features of each GCFE.
These calibration tables give the correspondence between relevant DAC setting
and output ADC bin or energy, as appropriate. Also calibrated is light
asymmetry (the ratio of signals from the two ends of one crystal). There are
two basic types of calibration: Charge Injection, Cosmic Muons.
Units of calibration tables can be converted
to MeV in all gain settings. The CAL calibration determine:
·
Pedestals for all energy ranges in all gain
settings. An estimate of the electronic noise can be derived from the pedestal
width;
·
FEE transfer function for all energy ranges,
i.e., the integral non-linearity of the analog and digital chain for each
energy range;
·
Calibration of the low-energy discriminator
(FLE) DAC;
·
Calibration of the high-energy discriminator
(FHE) DAC;
·
Calibration of the zero-suppression threshold
(LAC) DAC; and
·
Calibration of the auto-ranging discriminator
(ULD) DAC.
NOTE: The electronic gain of each energy range is given by the
linear term of the correspondence between injected charge and output ADC bin.
The CAL muon calibration suite is primarily
the calibration of the “optical gain” of each photodiode to establish the correspondence
between ADC bin and energy deposited. From this calibration the following are
achieved:
·
Optimization of the time delay between trigger
and peak hold to give maximal light yield for the ensemble of CDEs in a module;
·
Verification of the calibration in energy units
of the FLE and FHE tables generated in the electronic calibration;
·
Fitting of the muon peak in each LE and HE
photodiode in muon analysis gain setting. From the muon peak, a calibration table (correspondence between ADC
values and energy) is created; and,
·
Mapping of the light taper and light asymmetry
in each CDE as a function of position.
There are two trigger types used: CAL
internally triggering (“self-triggering”) on muons, and with an ancillary
detector generating external triggers for the CAL Tower Module. The CAL
self-triggering is simpler and requires no additional hardware, but it results
in a modestly biased energy calibration. By contrast, the externally triggered
muons do not create a biased calibration, and therefore are used to generate
the final energy calibration of each channel. During LAT integration the
tracker trigger can be used by CAL to provide unbiased calibrations. An
externally triggered system shall be available as a reference system.
Monte
Carlo “truth,” raw and reconstructed data are held in a Transient Data Storage
(TDS). Data analysis files (Merit and SVAC) are produced from TDS. Please see Figure
20.
Figure
20: TDS Input
and Output
An
event has several contributions: the TEM (AEM) carries the contributions from
TKR and CAL (ACD) and corresponding trigger primitives while the GEM contains
trigger and deadtime related information. All contributions are assembled in
the Event Builder that lives inside the GASU.
To be written.
Each
TEM receives detailed trigger primitive information for its
through the cable controllers: eight GTCCs from the
TKR (please refer to TKR Readout, section 3.2) and four from the CAL (please refer to
CAL Readout, section 3.3). CAL and TKR trigger primitives come
from each layer end. Please refer to Table 14.
Table
14: CAL and
TKR Trigger Primitive Data
|
|
|
|
CAL LE and HE trigger request for:
·
Each layer
·
Each end
·
A bit to tell whether a signal was above zero
suppression
|
3-in-a-row trigger request information for:
·
Each layer
·
Each view (X and Y)
·
Each end (GTRC0 and GTRC1)
|
TEM
trigger primitive data is present in: TDS, digi root files and SVAC ntuples. Each
cable controller can transmit trigger primitives to the GEM – the presence or
absence of data is indicated by a bit in the event summary. Each TEM can
contribute up to12 32-bit words – one word of 32-bits per layer.
The
GEM receives the aggregate trigger information from all the TEMs
as well as from the ACD. All event entries are sampled at window closing. The system clock is 20 MHz, i.e., one tick is 50 ns.
The
GEM event contributions are shown in Table 15.
Table
15: GEM
Event Contribution
|
|
|
|
TKR
Vector
|
16
bits containing TKR trigger signals - One per tower
|
|
ACD
ROI Vector
|
16
bits to define Regions of Interest
Format
depends on whether used
|
|
CAL
Low Energy Vector
|
16
bits containing CAL low energy trigger signals
|
|
CAL
High Energy Vector
|
16
bits containing CAL high energy trigger signals
|
|
ACD
CNO Vector
|
12
bits containing CNO trigger signals
|
|
Tile
List
|
State
of all the ACD tiles
|
|
Livetime
|
·
1/Deadtime
·
24-bit counter (rolls over at 0.8 sec)
|
|
Prescale Count
|
·
Number of triggered events not passing the prescaler
·
24-bit counter (1 GHz)
|
|
Discarded
Count
|
·
Number of triggered events passing prescaler but lost to LAT busy.
·
24-bit counter (1 GHz)
|
|
Sent
Count
|
·
Number of triggered events read out (TAMs sent by the GEM)
·
16-bit counter
(65 K)
|
|
Trigger
time
|
·
Free running counter incrementing at the
system clock
·
Count from when it was reset to the event was
declared.
·
25-bits
(rolls over at 7.6 sec)
|
|
1-PPS
time:
|
·
Seconds:
·
Number of seconds since the GEM was reset
·
7-bits
(128 sec)
·
1-PPS time:
·
Time in 50ns ticks of the last arrived 1-PPS
signal
·
25-bits
(7.6 sec)
|
|
Delta
event time
|
·
Time from event (n-1) to event n
·
16-bits
(3 ms)
|
The
data files are:
LDF.FITS
– binary format readable by online tools not used for data analysis
digi.root,
recon.root and
mc.root – ROOT trees
Merit.root and SVAC.root. –
ntuple files
A ROOT
tree file stores a snapshot of the compiler internal data structures at the end
of a successful compilation. It contains all the syntactic and semantic
information for the compiled unit and all the units upon which it depends
semantically. Trees are very efficient for storing the complex structure of the
LAT event but retrieval of data from trees requires some basic knowledge of
C++.
An
Ntuple is like a table where X
variables from data collection are the columns, and each event is a row. The
storage requirement is proportional to the number of columns in one event and
can become significant for large event samples. Ntuples are flat files which
are easy to access with minimal knowledge of ROOT.
The
LDF.FITS file is a binary file wrapped with a FITS header. All event
contributions are included and information is stored in electronics parameter
space. For details please refer to the GEM (LAT-TD-01545) and TEM
(LAT-TD-00605) manuals.
It is important to realize that for data analysis, events that have errors
and cannot be written by the online are discarded. If events are written but contents are corrupted a flag is set in the
next step in the digi.root file. For details, please refer to the SAS workbook.
The
digi.root file is a ROOT tree which contains the same data from LDF.FITS but in
a representation that is better suited for SAS reconstruction code (physical
space instead of electronics space). For mapping between spaces see the mapping
sections in the section on geometry. If the process of parsing information from
LDF to digi generates “bad” events, these are not reconstructed and the flag
BadEvt is set to 1 in digi.root.
The Recon.root file is a ROOT tree file which contains
reconstructed data using digi.root and calibration constants as input. During initial phase of ground testing one
may produce recon files without calibration, but in general, energy scales in
recon files are usually calibrated.
The MC.root file is a ROOT tree which contains the MC true
information and is only available for simulated data. The MC.root
file does not contain all events from MC
The Merit.root file is a ROOT ntuple which contains about 240
variables in five classes: ACD, TKR, CAL, MC and Run. Scripting is available
through ROOT in C++. Integration & Test provides Hippodraw as an additional
visualization tool for data analysis, with scripting via Python.
A
ROOT file which contains most of the low level instrument variables
(hits/layer, trigger primitives, GEM information) which are stored in arrays.
Storage is less efficient than root Trees but access is as simple as from a
flat file. Scripting is available through ROOT in C++. Integration & Test
provides Hippodraw as an additional visualization tool for data analysis, with
scripting via Python.
SVAC
and Merit can be loaded into root at the same time and data display cuts can be
applied in each one through the ROOT “friends” class.
Raw
data sets (LDF.FITS), derived from the hardware, are parsed to create another
representation of the data in a format that is readable by the SAS
reconstruction software (digi.root). Digi.root is processed with SAS
calibration software to generate the calibration constants files. These are
loaded into the primary (SAS) database which provides a format-independent
interface to allow the reconstruction software to retrieve constants when
needed. With these constants the SAS reconstruction software produces
calibrated data files (recon.root). After processing
with analysis software, recon.root is used to create
the analysis files.
A
separate process queries the SAS database to retrieve calibration constants and
store them in a SVAC database whose design is optimized for trending.
In a
parallel path using Monte Carlo simulations, the LDF.FITS file is replaced by
simulated input from a model that contains a description of the detector
geometry and physics processes relevant to the LAT. The entire analysis chain
follows the recipe described in the previous paragraphs until final MC analysis
files are produced.
Results
from the hardware analysis files can then be compared to Monte Carlo simulation
results to validate the MC simulations. Data files and reports described above
will be generated using an automated data processing facility, hereafter
pipeline.
Figure 21 shows the data analysis flow.
Figure
21: Data
Analysis Process Flow
TKR reconstruction
is an iterative process using information from both the CAL and TKR. The TKR
reconstruction method adopts the following four-step procedure (please see Figure 22 and Figure 23)
1.
Form “Cluster Hits”
Done by converting the hit strips to
positions. Adjacent hit strips are merged to form a single hit.
2.
Pattern Recognize individual tracks
Done by associating cluster hits
into candidate tracks. Individual track energies are assigned to aid in track recognition.
3.
“Fit” Track to obtain track parameters
Inherently two-dimensional cluster
locations are processed to determine three-dimensional position and direction. The errors are estimated then
the energy calculations are used to help with track fitting.
4.
“Vertex” fit tracks
The common intersection point of fit
tracks is determined, and a position and direction is calculated.
For cosmic rays, the first hit layer determines the “vertex” location. The diagrams
presented in Figure
23 illustrate how a cosmic ray event can have more than one track and even
multiple vertices.
Figure
22: Four TKR Reconstruction
Steps (Block Diagram)
Figure
23:
Four Steps of TKR
Reconstruction (Illustrated)
Iterative
Recon allows parts of the TKR Reconstruction software to be called more than
once per event. The overview is shown in Figure 24. In particular, existing pattern
recognition tracks can be refit and the vertex algorithm re-run.
The
Iterative Recon provides the CAL Recon with sufficient tracking information to
get an improved energy estimate, which can be fed back to the track fit and
vertexing algorithms. The process can be repeated as many times as the user
likes (in principal) but the default is two passes.
Figure
24: Iterative
TKR Reconstruction Algorithms (Block Diagram)
The
clustering algorithms group strips with adjacent hits to form a cluster. TkrClusterAlg takes the strip hits to calculate the
center position to use in track fitting. The digi.root file (please refer to Digi.root in section 7.2.2) provides clustering the hit strip numbers, and Time
over Threshold (ToT).
The
clustering algorithms apply the TKR calibration data to account for
hot/dead/sick strips and merges clusters with known dead strips between them.
It also decides whether to add known hot strips to clusters.
The
result of TkrClusterAlg is a list of clusters
in TDS with associated XYZ coordinates and the value of ToT associated with
these strips. This information is used in the next step by TkrFindAlg.
The
output of track finding is an ordered list of candidate tracks to be fit. TkrPatCand, contained in a TkrPatCandCol Gaudi object vector outputs:
·
Estimated track parameters for the candidate
track (position, direction);
·
The energy assigned to the track;
·
Track candidate “quality” estimates, and;
·
Starting tower / layer information.
TkrPatCand contains
the Gaudi object vector of TkrPatCandHits for each hit (cluster) associated with the
candidate track. Any cluster associated to this hit is needed for the fit
stage.
All
are stored in the TDS.
TkrFindAlg associates clusters into candidate
tracks. Three approaches exist within the TkrRecon
package, as described in Table 16.
Table
16: TKR
Reconstruction Clustering Methods
|
|
|
|
|
|
Combo
|
Track
by track. Combinatoric search through space points
to find candidates.
|
Simple
to understand (although details add complications)
|
Finding
“wrong” tracks early in the process throws off the rest of the track finding
by mis-associating hits. Can be quite time
consuming depending upon the depth of the search.
|
|
Link
and Tree
|
Global
pattern recognition. Associate hits into a tree like structure.
|
Optimized
to find tracks in entire event, less susceptible to miss associating hits.
|
Can
be quite time consuming.
|
|
Neural
Net
|
Global
pattern recognition. Links nearby space points forming “neurons.”
|
Optimized
to find tracks in entire event, less susceptible to miss associating hits.
|
Can
be quite time consuming. Operates in 2D and then requires mating to get 3D
track.
|
Also:
“Monte Carlo” pattern recognition exists for testing fitting and vertexing.
There
are two basic Combinatoric strategies for track
finding: CAL based or Blind search. CAL based is used when there is enough CAL
energy present use energy centroid. When there is too little CAL energy we use
only Track Hits, and make a “Blind” search.
Table 17 differentiates between to the types of combinatoric track finding methods available to ComboFindTrackTool. In either case its starting layer is
always the one furthest from the CAL. It works to combine clusters in adjacent
X-Y layers to form 3D space points.
Table
17: TKR
Reconstruction Combinatoric Track Finding Methods
|
|
|
|
|
CAL
Energy Present
|
Sufficient
CAL energy, about 42 MeV.
|
Track fit uses the CAL centroid by first
attempting to connect the hit with CAL centroid. It connects the first two
hits, then projects and adds hits along the track within the search reason.
The search region is set by propagating the track errors through the GLAST
geometry. Please see Figure
25.
|
|
Blind
search
|
Insufficient
CAL energy.
|
The first hit found is tried in combinatoric order. The 2nd hit is selected in combinatoric order. The first two hits are used to
project into next layer, and a 3rd Hit is searched for. If a 3rd hit is found
the track is built by “finding – following.”
|
Figure
25: Combinatoric Pattern Recognition: ComboFindTrack
Tool
The
next step is for the TkrReconAlg to fit the
candidate tracks using the parameters of X, Y and the slopes of X and Y. It
tracks the parameter error matrix (parameter errors and correlations) and
measures of the quality of the track fit using the Kalman filter method.
The
filter process starts at the conversion point, but we want the best estimate of
the track parameters at the conversion point. This requires propagating the
influence of all the subsequent hits backwards to the beginning of the track,
essentially running the filter in reverse. This is called the smoother, and the
linear algebra is similar:
Residuals: r(k) = X(k) -Pm(k)
Covariance of r(k): Cr(k) = V(k)
-C(k)
Then: X2 =
r(k)TCr(k)-1r(k)
for the kth step
A
pair conversion results in 2 primary tracks,
but one track could be lost due to:
·
Low energy (track must cross three planes);
·
Tracks from pair conversion don’t separate for
several layers; and,
·
Track separation due to multiple scattering.
In
addition, wrong vertex associations could occur because secondary tracks may be
associated with primary tracks but are not part of the g conversion process.
The
vertexing algorithm attempts to associate “best” track (from track finding)
with one of the other found tracks by finding “the” vertex and returning
unassociated (“isolated”) tracks as single prong vertices. It determines the
reconstructed position of the conversion and the reconstructed direction of the
conversion. Currently two methods available, as listed in Table 18.
In
the presence of charged particles only, the vertex is considered to be at the
first layer hit.
Table
18: TKR
Reconstruction Vertexing Tools
|
|
|
|
|
“Combo”
(default)
|
Uses track Distance of Closest Approach
(DOCA) to associate tracks.
|
1. The vertex is determined at two tracks’
Distance of Closest Approach (DOCA).
2. The first track is the “best” track from
track finding/fitting algorithms.
3. It is looped through “other” tracks
looking for best match:
·
Smallest DOCA
·
Weighting factors:
·
Separation between the starting points of the
two tracks
·
Track energy
·
Track quality
4. It calculate vertex quantities:
·
Vertex Position: Midpoint of DOCA vector
·
Vertex Direction: Weighted vector sum of
individual track directions
Not a true HEP Vertex Fit
|
|
Kalman
Filter
|
Kalman
Filter
|
|
The
output from the vertexing algorithms is an ordered list of vertices with the
following TkrVertex
objects contained in a Gaudi Object Vector:
·
The vertex track parameters (x, mx, y, my);
·
The vertex track parameter covariance matrix;
·
The vertex energy;
·
The vertex quality;
·
The first tower/layer information; and,
·
Gaudi reference vector to the tracks in the
vertex.
The
first vertex in the list is the “best” vertex, and the rest are mostly
associated with “isolated” track.
MC
simulations are run for both simulated cosmic rays at sea level and photons
generated by a Van De Graaff generator.
MC
simulations on thresholds and noise are taken for data analysis purposes, and
are also described here.
Simulated
g photons are derived from real proton / Lithium 7
collisions according to Figure 26.
Figure
26:
Simulation of VDG Gammas – Simulated Particle Source Generation
For
MC simulation, there is no Li target – only the g are simulated, with an energy spectrum having the main
distribution at 14.6 MeV and a 17.6 MeV line spectrum. The ratio of numbers of
events at 17.6 MeV / number of events at 14.6 MeV is 2:1.
The
shielding is defined as a simulated iron cylinder with radius of 26 mm and
thickness of 1.25 mm (7% X0). The X position = -200
mm; the Y position = 200 mm; the Z position = 636 mm, ~ 3mm above the TKR. The
energy spectrum is angular-dependent.
Note
that g photons which convert in
the Fe shield generate an unwanted experimental background of charged
particles.
The
default scenario program name is surface_muons. It
models energy / angle correlations and has a spectrum to include events below 1
GeV. It can produce a small number of unphysical, low energy events that are
platform dependent.
Figure 27 shows the distribution of kinetic
energy vs particle flux for surface_muons.
Figure
27: Particle Flux
vs Kinetic Energy for surface_muon Source
The
TKR occupancy in MC is usually set at 510 -5 /
strip, meaning that one should expect about 3 noisy hits per tower, on average
(510 -5
/strip x 1536 strips x 36 layers per tower).
This section is intended to guide users in
the usage of the existing data analysis variables. There is no way to provide a
recipe for data analysis, but the idea is to illustrate how to use the
information in the data analysis files.
A MIP selection can involve information from
TKR, CAL and ACD.
It would be naïve to search for a single
straight track, with one hit in each TKR layer, that when extrapolated to the
CAL, deposits about 11 MeV in each crystal layer.
The SVAC file has hits per layer and
clusters per layer for every tower while the Merit ntuple has clusters
associated to tracks for all towers.
Care needs to be exercised when selecting
variables such as TkrTrackLength. This
variable measures an extrapolated length from the first hit layer to the grid
by dividing Tkr1Z0 (Z position at first hit of track1) by Tkr1ZDir
(direction cosine for track1). Thus, for a situation illustrated in Figure
28, both track lengths are equal.
Figure 28: TrkTrackLength
Example of Easily Misinterpreted Data
11.2. CALTowerGap
Note
that when extrapolating a track into the CAL sometimes the track will go
traverse different amounts of material even if it is a straight track. The
reason is depicted in Figure 29. One clearly sees the there is an
offset between successive CAL layers, so a on-axis muon, contrary to a naive
intuition, may hit every other layer.
Figure
29: A Charged
Particle’s Path is Parallel to the Z Axis and only
Strikes Every Other Crystal
