Tracks In Drift Chamber Research Articles

Neural network applications to improve drift chamber track position measurements

This paper describes applications of two neural networks to improve drift chamber position measurements. One network calculates a data-driven estimate of the drift cell time-to-distance relationship that is conventionally estimated by a numerical calculation based on the anode and cathode wire geometry, wire potentials, and gas properties. The second network additionally uses the full digital waveform of the signal in the drift chamber, hence accessing information on the full ensemble of ionization clusters. This network uses more information than the conventional position estimate that relies exclusively on the arrival time of the first drift electron. In principle, this technique improves resolution even when multiple ionization clusters cannot be separated, in contrast with a cluster-counting technique. The performance of both networks when applied to MEG II drift chamber data is reported and compared to that of a conventional approach.

BESIII Drift Chamber Tracking with Machine Learning

The tracking efficiency and the quality for the drift chamber of the BESIII experiment is essential to the physics analysis. The tracking efficiency of the drift chamber of BESIII is high for the high momentum tracks but still have room to improve for the low momentum tracks, especially for the tracks with multiple turn. A novel way to use a convolutional network called U-Net network is represented to solve the identification of the first turn’s hits for the multiple-turn tracks.

A drift chamber tracking system for muon scattering tomography applications

Muon scattering tomography (MST) allows the identification of shielded high atomic number (high-Z) materials by measuring the scattering angle of cosmic ray muons passing through an inspection region. Cosmic ray muons scatter to a greater degree due to multiple Coulomb scattering in high-Z materials than low-Z materials, which can be measured as the angular difference between the incoming and outgoing trajectories of each muon. Measurements of trajectory are achieved by placing position sensitive particle tracking detectors above and below the inspection volume. By localising scattering information, the point at which a series of muons scatter can be used to reconstruct an image, differentiating high, medium and low density objects.MST is particularly useful for differentiating between materials of varying density in volumes that are difficult to inspect visually or by other means. This paper will outline the experimental work undertaken to develop a prototype MST system based on drift chamber technology. The planar drift chambers used in this prototype measure the longitudinal interaction position of an ionising particle from the time taken for elections, liberated in the argon (92.5%), carbon dioxide (5%), methane (2.5%) gas mixture, to reach a central anode wire. Such a system could be used to enhance the detection of shielded radiological material hidden within regular shipping cargo.

Proposal for the upgrade of the tracking and trigger systems of the CMD-3 detector

Large cylindrical triple-GEM detector (CGEM) is proposed to upgrade the CMD-3 tracker subsystem. CGEM will be designed both for precise measurement of z-coordinate of tracks in drift chamber (DC) and for generating signals for the first level trigger. This chamber will have better spatial resolution, trigger segmentation and rate capability with respect to the present Z-chamber which is used in CMD-3 today. An end-cup discs with GEM-based detectors are also considered for the upgrade. This tracker will improve significantly the detection efficiency for multi-hadron events, will help to study processes with initial state radiation (ISR) and measure the cross section with double tagged electrons when two virtual photons radiated by initial electrons produced C-even states (π0,η).

Magnetic Field Mapping in the BESIII Solenoid

<para xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> The Beijing Spectrometer III (BESIII) superconducting solenoid magnet, which is running in the Beijing Electron Positron Collider II (BEPC-II), is an important part of BESIII and provides a 1 Tesla field in the main drift chamber. A 3-D mapping device with three 3-D probes was fabricated to measure the field components of <formula formulatype="inline"><tex Notation="TeX">$B_{z}$</tex> </formula>, <formula formulatype="inline"><tex Notation="TeX">$B_{r}$</tex> </formula> and <formula formulatype="inline"><tex Notation="TeX">$B_{\mit\Phi}$</tex> </formula>. The mapping of the magnetic field of the BESIII superconducting solenoid magnet is presented, with the accelerator interaction region magnets located inside the BESIII solenoid excited to different current values. A set of polynomials, and a few trigonometric-Bessel terms are used to fit the data. The measurements and the functional model agree to 5 Gauss within the main drift chamber tracking volume at nominal field values. </para>

Continuously live image processor for drift chamber track segment triggering

The first portion of the BABAR experiment Level 1 Drift Chamber Trigger pipeline is the Track Segment Finder (TSF). Using a novel method incorporating both occupancy and drift-time information, the TSF system continually searches for segments in the supercells of the full 7104-wire Drift Chamber hit image at 3.7 MHz. The TSF was constructed to operate in a potentially high beam-background environment while achieving high segment-finding efficiency, deadtime-free operation, a spatial resolution of <0.7 mm and a per-segment event time resolution of <70 ns. The TSF system consists of 24 hardware-identical TSF modules. These are the most complex modules in the BABAR trigger. On each module, fully parallel segment finding proceeds in 20 pipeline steps. Each module consists of a 9U algorithm board and a 6U interface board. The 9U printed circuit board has 10 layers and contains 0.9 million gates implemented in 25 FPGAs, which were synthesized from a total of 50,000 lines of VHDL. The boards were designed from the top-down with state-of-the-art CAD tools, which included gate-level board simulation. This methodology enabled production of a flawless board with no intermediate prototypes. It was fully tested with basic test patterns and 10/sup 5/ simulated physics events.

CLEO III, a detector to measure rare B decays and CP violation

The symmetric e +e − collider CESR is undergoing a series of upgrades allowing for luminosities in excess of 2 × 10 33 cm −2s −1. The most important goals of the upgrade are precision measurement of standard model parameters V cb, V ub, V td V ts , f D s , and searching for CP violation and standard model violations in rare B decays. A new detector upgrade, called CLEO III, has started which includes a new silicon-wire drift chamber tracking system and a Ring Imaging Cherenkov Detector, RICH, using a LiF radiator and CH 4-TEA gas based photon detector.

Performance of drift chambers in a magnetic rigidity spectrometer for measuring the cosmic radiation

A drift chamber tracking system was developed and flown as part of the IMAX balloon-borne magnetic spectrometer. The drift chamber uses a hexagonal drift-cell structure and is filled with pure CO 2 gas. It operated with high efficiency in the strong and inhomogenous field of a superconducting magnet, demonstrating a spatial resolution of better than 100 μm over most of the drift path for singly charged particles, as well as for helium and lithium nuclei. The drift chamber portion of the spectrometer achieved a maximum detectable rigidity of 175 and 250 GV/ c for protons and helium respectively.

Drift chamber tracking with neural networks

Drift chamber tracking with a commercial analog VLSI neural network chip is discussed. Voltages proportional to the drift time in a four-layer drift chamber are presented to the Intel Electrically Trained Analog Neural Network chip. The network is trained to provide the intercept and slope of straight tracks traversing the chamber. The outputs are recorded and compared offline to conventional track fits. Two types of network architectures are studied. Application of neural network tracking to high energy physics detector triggers is discussed. >

A drift chamber track finder for the first level trigger of the H1 experiment

The information from the central drift chamber of the H1 experiment is used in a first level trigger to find and count charged tracks, originating from genuine ep collisions at the HERA storage ring. Background processes, predominantly from beam-wall and beam-gas interactions, are discriminated because their distance of closest approach to the collision vertex differs from good events. The track finder is designed in a pipelined fashion, producing decisions at the bunch crossing frequency of ⨍b = 10.4 MHz, however delayed by a fixed decision time of 2.3 μs. This operation is deadtime free but still uniquely related to the specific bunch crossing 24 cycles earlier. The hardware implementation relies on XILINX logic cell arrays which are programmable providing a high flexibility.

Vectorization of track finding and fitting algorithms for HEP

The applicability of vector computers toward solving the problems of drift chamber track finding and fitting is discussed. Particular attention is paid to the Mark III tracking program, which appears amenable to such vectorization. Progress in the field by other groups is also discussed, and an attempt is made to extrapolate from present experience to situations of higher multiplicity and drift chamber complexity.