CERN Accelerating science

Estimated CPU resources (in MHS06~\cite{hepspec}) needed for the 2020 to 2032 time frame for both data and simulation processing for the ATLAS experiment. Three different scenarios considered by ATLAS are shown ranging from the baseline to that in which the aggressive R\&D program is successful (blue points). The common scenario agreed between the different experiments as a reference is shown with red triangles. The black lines indicate the amount of CPU that can be expected based on current budget models. From Ref.~\cite{Calafiura:2729668}

Performance of the magnetic field lookup for a number of different scenarios. Results for the analytical solenoid field, and the interpolated magnetic field map are shown. Field queries at a fixed point, at a sequence of random points, and a sequence along a straight line are measured. Performance with and without field interpolation cell caching are shown.

The geometry of the ATLAS ITk (\subref{fig:det_geometry_itk}), the PANDA silicon detector (\subref{fig:det_geometry_panda}) and the sPHENIX silicon tracking detectors (\subref{fig:det_geometry_sphenix}), implemented with \acts. Colors indicate different subsystems, in the top image, the High Granularity Timing Detector (HGTD)~\cite{CERN-LHCC-2020-007} is shown in orange.

The geometry of the ATLAS ITk (\subref{fig:det_geometry_itk}), the PANDA silicon detector (\subref{fig:det_geometry_panda}) and the sPHENIX silicon tracking detectors (\subref{fig:det_geometry_sphenix}), implemented with \acts. Colors indicate different subsystems, in the top image, the High Granularity Timing Detector (HGTD)~\cite{CERN-LHCC-2020-007} is shown in orange.

The geometry of the ATLAS ITk (\subref{fig:det_geometry_itk}), the PANDA silicon detector (\subref{fig:det_geometry_panda}) and the sPHENIX silicon tracking detectors (\subref{fig:det_geometry_sphenix}), implemented with \acts. Colors indicate different subsystems, in the top image, the High Granularity Timing Detector (HGTD)~\cite{CERN-LHCC-2020-007} is shown in orange.

Geometries of Belle~II (\subref{fig:det_geometry_belle2}) and FASER (\subref{fig:det_geometry_faser}) implemented in ACTS. Colors indicate the different subsystems.

Geometries of Belle~II (\subref{fig:det_geometry_belle2}) and FASER (\subref{fig:det_geometry_faser}) implemented in ACTS. Colors indicate the different subsystems.

A projection of the magnetic field implemented with \acts for the ATLAS tracking system into the $x-y$ plane (\subref{fig:atlas_bfield_xy}). The strength of the magnetic field at each point is indicated in color. The $r-z$ coordinates of the intersections of propagated pion tracks with the ATLAS ITk detector elements, using the ATLAS magnetic field (\subref{fig:atlas_bfield_itk_prop}). Boundary intersections are shown in blue, while intersections with sensors are shown in orange. Green lines indicate a subset of extrapolated particle tracks. Grey points are the intermediate integration steps, required within a predefined tolerance threshold.

A projection of the magnetic field implemented with \acts for the ATLAS tracking system into the $x-y$ plane (\subref{fig:atlas_bfield_xy}). The strength of the magnetic field at each point is indicated in color. The $r-z$ coordinates of the intersections of propagated pion tracks with the ATLAS ITk detector elements, using the ATLAS magnetic field (\subref{fig:atlas_bfield_itk_prop}). Boundary intersections are shown in blue, while intersections with sensors are shown in orange. Green lines indicate a subset of extrapolated particle tracks. Grey points are the intermediate integration steps, required within a predefined tolerance threshold.

Comparison of the mapped material obtained from \acts material mapping tool (orange line) and the \texttt{Geant4} material (blue line) as a function of $\eta$ for the Open Data Pixel Detector. The ratio of the material in ACTS to Geant4 is indicated in the panel below and the statistical uncertainty is indicated with the gray band. Agreement is within about 2\%, with excellent agreement seen in the central part of the detector.

Schematic layout of the TrackML detector showing the coverage of the pixel detector in blue, short strip detector in red and long strip detector in green.

The track reconstruction efficiency (top), fake rate (middle) and duplicate rate (bottom) for 1,000 $t\bar{t}$ events with \pu = 200 obtained using \acts CKF on the TrackML detector. The blue dots and orange triangles represent results using starting parameters based on truth track parameters and those estimated from seeds found the \acts seed finding algorithm, respectively. The truth particles used to calculate the track reconstruction efficiency are required to have $p_T>$ 1 \GeV and have nine measurements on the traversed detectors. The reconstructed tracks are required to have $p_T>$ 1 \GeV and have six measurements in the detectors.

The track reconstruction efficiency (top), fake rate (middle) and duplicate rate (bottom) for 1,000 $t\bar{t}$ events with \pu = 200 obtained using \acts CKF on the TrackML detector. The blue dots and orange triangles represent results using starting parameters based on truth track parameters and those estimated from seeds found the \acts seed finding algorithm, respectively. The truth particles used to calculate the track reconstruction efficiency are required to have $p_T>$ 1 \GeV and have nine measurements on the traversed detectors. The reconstructed tracks are required to have $p_T>$ 1 \GeV and have six measurements in the detectors.

The track reconstruction efficiency (top), fake rate (middle) and duplicate rate (bottom) for 1,000 $t\bar{t}$ events with \pu = 200 obtained using \acts CKF on the TrackML detector. The blue dots and orange triangles represent results using starting parameters based on truth track parameters and those estimated from seeds found the \acts seed finding algorithm, respectively. The truth particles used to calculate the track reconstruction efficiency are required to have $p_T>$ 1 \GeV and have nine measurements on the traversed detectors. The reconstructed tracks are required to have $p_T>$ 1 \GeV and have six measurements in the detectors.

The pull distributions of the six bound track parameters, $d_0$, $z_0$, $\phi$, $\theta$, $\frac{q}{p}$, and $t$, as obtained with the KF on the TrackML detector. The blue dots are the obtained pull values and the orange lines are the fitted Gaussian curves. For each Gaussian fit, the fitted values (with negligible uncertainties) for the parameters mean ($\mu$) and standard deviation ($\sigma$) are shown in the legend. Truth-generated seeds are used for the KF. A sample of 100,000 single muons with 500 \MeV $

Number of reconstructed primary vertices with the \acts AMVF for different numbers of true $pp$ collisions in simulated $t\bar{t}$ events. For reference, the gray dashed line indicates a $100\%$ vertex reconstruction efficiency and the blue dots indicate the vertex reconstruction efficiency given a detector acceptance of $|\eta|<2.5$ and $p_{T}>400$ \MeV

The fraction of wall time during which different numbers of threads were running simultaneously while running track propagation through the TrackML detector. Either a static (blue) or contextual (orange) geometry is used for 100,000 events with 1,000 pions per event using multi-threads on a Cori-Haswell node.

The mean number of propagation steps (top), propagation time for 1,000 pions (middle) and mean propagation time per step (bottom) of the track parameter propagation as a function of the $p_T$ of the pions ($|\eta|<2.5$) with the array-like math implementation (blue dots), the main Eigen-based stepper (orange triangles) and the straight-line stepper (green stars).

The CPU time of track fitting per event using \acts KF (blue dots) and combined track finding and track fitting (orange triangles) per event using the \acts CKF as a function of the \pu of the $t\bar{t}$ sample. Truth-generated seeds are used for both the KF and the CKF. Only simulated particles with $p_T>$ 500 \MeV and having at least nine measurements on the detector are considered.

The average CPU time for seed finding (blue dots) per event, and combined track finding and track fitting (orange triangles) per event with \acts CKF using reconstructed seeds as a function of \pu of the $t\bar{t}$ sample. Only seeds with $p_T>$ 500 MeV are considered.