The Near Detector Purpose and Conceptual Design
A.5 Movable components of the ND and the DUNE-PRISM programprogram
A.5.3 Multipurpose Detector
A.5.3.2 MPD performance
A.5.3.2.1 Track Reconstruction and Particle Identification
The combination of very high resolution magnetic analysis and superb particle identification from the HPgTPC, coupled with a high-performance ECAL will lead to excellent event reconstruction capabilities and potent tools to use in neutrino event analysis. As an example of this capability, the top panel of Figure A.26 shows a νe+(N)Ar −→ e−+π++n+(N−1)Ar in the HPgTPC with automatically-reconstructed tracks. The same event was simulated in a FD SP module, and is shown in the bottom panel of Figure A.26.
Since important components of the hardware and design for the HPgTPC are taken from or duplicated from the ALICE detector, the ALICE reconstruction is a useful point of reference in this discussion. Track reconstruction in ALICE is achieved by combining hits recorded on the ROC pads into tracks following a trajectory that a charged particle traveled through the TPC drift volume. The HPgTPC is oriented so that the neutrino beam is perpendicular to the magnetic field, which is the most favorable orientation for measuring charged particles traveling along the neutrino beam direction.
The GArSoft simulation and reconstruction package borrows heavily from LArTPC, and is based on theart event processing framework and GEANT4. It is designed to be able to reconstruct tracks with a full 4π acceptance. GArSoft simulates a 10 atmosphere gaseous argon detector with readout chambers filling in the central holes in the ALICE geometry. GArSoft’s tracking efficiency has been evaluated in a large sample of GENIE νµ events interacting in the TPC gas at least 40 cm from the edges, generated using the optimized LBNF forward horn current beam spectra. The efficiency for reconstructing tracks associated with pions and muons as a function of track momentum p is shown in Figure A.27. The efficiency is above 90% for tracks with p >40 MeV/c, and it steadily rises with increasing momentum.
Also shown is the efficiency for reconstructing all charged particles with p > 200 MeV/c as a function ofλ, the track angle with respect to the center plane. The tracking efficiency for protons is shown in Figure A.28 as a function of kinetic energy, Tp. Currently, the tracking works well down toTp '20 MeV. ForTp <20 MeV, a machine-learning algorithm is in development, targeting short tracks near the primary vertex. This algorithm, although currently in a very early stage of development, is already showing good performance, and efficiency improvements are expected with more development. The machine learning algorithm is described in Section A.5.3.2.3.
The ALICE detector, as it runs at the LHC, typically operates with particle densities ranging from 2000 to 8000 charged particles per unit rapidity (dN/dy) for central Pb-Pb interactions [120]. The expected particle densities in the DUNE neutrino beam will be much lower and less of a challenge for the reconstruction.
ALICE chose to use neon, rather than argon, for the primary gas in their first run; the decision was driven by a number of factors, but two-track separation capability was one of the primary motivations due to the extremely high track multiplicities in the experiment. Neon performs better than argon in this regard. A better comparison for the HPgTPC’s operation in DUNE is the two- track separation that was obtained in PEP4 [117]. PEP4 ran an 80-20 mixture of Ar-CH4 at 8.5 atmospheres, yielding a two-track separation performance of 1 cm.
Figure A.26: (Top) Track-reconstructedνeCC event in the HPgTPC, simulated and reconstructed with GArSoft. The annotations are from Monte Carlo (MC) truth. (Bottom) The same νe CC event, but simulated in a SP module using Liquid Argon Software (LArSoft). The topmost blue panel shows the collection-plane view, the middle blue panel shows the V view, and the bottom blue panel shows the U view. Wire number increases on the horizontal axes and sample time along the vertical axes. The wire number in the collection view is labeled on the top of the panel, while theV and U wire numbers are below their respective panels. Simulated analog-to-digital converter (ADC) values are indicated by the colors. The curve in the bottom-most panel is a simulated waveform from a collection-plane wire.
The annotations are from MC truth.
Figure A.27: (Left) The efficiency to find tracks in the HPgTPC as a function of momentum, p, for tracks in a sample of GENIE events simulating 2 GeV and νµ interactions in the gas, using GArSoft.
(Right) The efficiency to find tracks as a function of λ, the angle with respect to the center plane, for tracks with p >200MeV/c.
Figure A.28: Tracking efficiency for protons in the HPgTPC as a function of kinetic energy.
In ALICE, the ionization produced by charged particle tracks is sampled by the TPC pad rows (there are 159 pad rows in the TPC) and a truncated mean is used for the calculation of the PID signal. Figure A.29 (left) shows the ionization signals of charged particle tracks in ALICE for pp collisions at √
s = 7 TeV. The different characteristic bands for various particles are clearly visible and distinct at momenta below a few GeV. When repurposing ALICE as the HPgTPC component of the MPD, better performance is expected for particles leaving the active volume, since the detector will be operating at higher pressure (10 atmospheres vs. the nominal ALICE 1 atmosphere operation), resulting in ten times more ionization per unit track length available for collection. Figure A.29 (right) shows the charged particle identification for PEP-4/9 [121], a higher pressure gas TPC that operated at 8.5 atmospheres, which is very close to the baseline argon gas mixture and pressure of the DUNE HPgTPC.
Figure A.29: Left: ALICE TPC dE/dx-based particle identification as a function of momentum (from [122]). Right: PEP-4/9 TPC (80:20 Ar-CH4, operated at 8.5 Atm, from [121]) dE/dx-based particle identification.