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The ATLAS Trigger Algorithms Upgrade and Performance in Run-2

The ATLAS trigger has been used very successfully for the online event selection during the first part of the second LHC run (Run-2) in 2015/16 at a center-of-mass energy of 13 TeV. The trigger system is composed of a hardware Level-1 trigger and a software-based high-level trigger; it reduces the event rate from the bunch-crossing rate of 40 MHz to an average recording rate of about 1 kHz. The excellent performance of the ATLAS trigger has been vital for the ATLAS physics program of Run-2, selecting interesting collision events for a wide variety of physics signatures with high efficiency. The trigger selection capabilities have been significantly improved compared to Run-1, in order to cope with the higher event rates and pile-up during Run-2. At the Level-1 trigger the undertaken improvements resulted in more pile-up robust selection efficiencies and event rates and in a reduction of fake candidate particles. A new hardware system, designed to analyze event-topologies, supports a more refined event selection at the Level-1. A hardware-based high-rate track reconstruction is currently being commissioned. Together with a re-design of the high-level trigger to deploy more offline-like reconstruction techniques, these changes improve the performance of the trigger selection turn-on and efficiency to nearly that of the offline reconstruction. In order to prepare for the anticipated further luminosity increase of the LHC in 2017/18, improving the trigger performance remains an ongoing endeavor. The large number of pile-up events is one of the most prominent challenges. This report gives a short review the ATLAS trigger system and its performance in 2015/16 before describing the significant improvements in selection sensitivity and pile-up robustness, which we implemented in preparation for the expected highest ever luminosities of the 2017/18 LHC.


The Run-ATLAS Trigger System
The Run-2 ATLAS Trigger and Data Acquisition (TDAQ) system consists of a hardware-based first level (Level-1) and a software-based high level trigger (HLT). Level-1 runs with a fixed latency of 2.5 µs and reduces the event rate from 40 MHz to 100 kHz. The Level-1 trigger decision is formed by the Central Trigger Processor, which receives information from the Level-1 calorimeter (Level-1 Calo) and the Level-1 muon (Level-1 Muon) triggers as well as from the topological trigger (L1Topo) which performs selections based on geometric or kinematic associations between trigger objects received from Level-1 Calo and/or Level-1 Muon. The HLT receives the input from Level-1 in the form of geometrical regions in η and φ, so-called regions of interest (RoI). It runs on a single farm of about 40000 processors, that accept or reject the event within 300 ms, and performs object reconstruction in the RoI using algorithms that are as close as possible to their counterparts used in offline reconstruction. The Fast Tracker (FTK) [4] which is currently being installed and commissioned will provide hardware-based tracking to the HLT.

Algorithm Upgrades and Performance
Events are selected based on physics signatures such as the presence of energetic leptons, photons, jets or large missing energy. Each one of these signatures is reconstructed and identified using different strategies. While there have been many improvements in the reconstruction and identification across all signatures, in the following selected improvements in the electron, muon, jet and missing transverse energy signature group will be described. A lot of work and effort has gone into improvements in the b-jet and B-physics trigger signatures which will not be discussed here.

Electrons
Many improvements were made in the electron and photon trigger signature. Highlighted here is the implementation of new Level-1 electromagnetic (EM) medium isolation cuts to reduce the rate of the lowest unprescaled Level-1 triggers while keeping the efficiency loss as low as possible in order to cope with the increasing luminosity in 2017. Reducing the trigger rate through isolation means that the single electron trigger thresholds can be kept low. Figure 1 (left) shows a comparison of the efficiency curves of the new isolation cuts (L1 EM24VHIM) with the default cuts (L1 EM24VHI) used for 2016 data taking. Figure 1 (right) shows the efficiency of a single electron trigger at the HLT as a function of the transverse energy (E T ) of the offline electron candidate in comparison with Monte Carlo simulation, showing good agreement and a sharp turn-on curve.

Muons
Until recently, the muon stand-alone trigger algorithm (FastMuonSA) which determines the transverse momentum, p T , had not included information from the ATLAS muon Cathode Strip Chamber (CSC) system, located in the forward region of the  Figure 1: Efficiency of the Level-1 (left) and of the HLT triggers (right) as a function of the offline electron candidate E T . The Level-1 triggers require an isolated electromagnetic (EM) cluster with E T > 24 GeV. "I" ("IM") stands for the isolation applied for EM clusters with E T < 50 GeV where the E T in an annulus of calorimeter towers around the EM candidate relative to the EM cluster E T is required to be less than max{2 GeV, E T /8−1.8 GeV} (max{2 GeV, E T /8−2.0 GeV}). The HLT trigger requires an electron candidate with E T > 28 GeV satisfying the likelihood-based tight identification without applying transverse impact parameter requirements but applying variable-size cone isolation [5].
ATLAS detector between 2.0 < |η| < 2.7. In 2017 it has been shown that including hits from the CSCs results in an improvement of the 1/p T,offline resolution in all p T ranges. Figure 2 shows the inverse p T resolution as a function of the offline muon p T with and without using hits from the CSC chambers. The resolution is extracted by taking the σ of a Gaussian fit to the distribution of the fractional residual of inverse p T , i.e. (1/p T,FastMuonSA − 1/p T,offline )/(1/p T,offline ). The fractional residual of the inverse p T,offline for all η ranges is shown in Figure 3.

Taus
Various improvements and changes were made to e.g. the online tau energy scale corrections and online tau identification using a Boosted Decision Tree to reflect changes made to the offline reconstruction methods. Additionally, L1Topo trigger items are now used for triggering on di-τ and lepton + τ signatures.

Jets
To determine the jet energy scale, its uncertainty, and to achieve an optimal jet energy resolution, several calibration schemes have been developed in ATLAS. The global sequential calibration (GSC) [7] corrects jets according to global jet observables such as the longitudinal structure of the energy depositions within the calorimeters, tracking information associated to the jet, and information related to the activity in the muon chambers behind a jet without changing the overall energy scale. They can be split into parts involving calorimeter-based variables, and parts involving trackbased variables. Since tracking is not guaranteed to be available for all jet thresholds, options are provided with and without the track-based corrections. The data-driven η-intercalibration correction [8] is the most important in situ correction added, and fixes differences in jet response as a function of η. Figure 4 compares the efficiencies for a single jet trigger for the calibration applied in 2016, the updated calibration applied in 2017 using only calorimeter information and the updated calibration additionally with track information. The additional corrections applied to the jets reconstructed at the HLT allow for improved agreement between the scale of trigger and offline jets as a function of both η and p T , and thus the trigger efficiency rises much more rapidly.
Large jets, i.e. reconstructed with the anti-k T algorithm with a radius parameter R = 1, are more susceptible to pile-up. Applying offline grooming techniques like trimming [10] can help to reduce the effect of pile-up by removing soft and wide    angle radiation from the jet clustering history which significantly pushes the mass distribtuion for light jets towards zero while having only a minimal effect on jets from heavy particle decays. In 2017, trimming has been implemented in large-R jet triggers at the HLT. Jet constituents are re-clustered with R = 0.2 to form sub-jets, and are removed if p T,sub−jet /p T,jet < 4 %. This is slightly altered from what is applied offline (5 %) to recover efficiency losses. As trimming produces a stable distribution of the jet mass as a function of pile-up, applying a mass cut significantly suppresses the QCD di-jet background, allowing a lower p T threshold, while retaining nearly all signal-like jets. This is shown in Figure 5 which compares the efficiencies for triggers with and without applying a mass cut for large-R single jet triggers at the HLT as a function of the leading (left) and second-leading (right) jet p T .

Missing Transverse Energy
The missing transverse energy (E miss T ) trigger rates are severely affected by detector noise, mis-measurements and increase non-linearly with the number of pile-up interactions. In 2016, the mht algorithm, which reconstructs E miss T as the negative of the transverse momentum (p T ) vector sum of all jets reconstructed from calorimeter topological clusters at the HLT, was used as the default reconstruction algorithm. In 2017, the PUFit algorithm which calculates the E miss T as the negative p T sum of all calorimeter topological clusters corrected for pile-up has been chosen as the default algorithm given its better performance in high pile-up regions. Figure 6 shows a comparison of the trigger cross-section as a function of the pile-up for both algorithms and Figure 7 show the efficiencies of the mht and PUFit algorithms versus E miss T (left) and pile-up (right).

Summary
The LHC conditions and performance pose a continuous challenge to the ATLAS trigger system throughout the ongoing Run-2. To maintain the efficient and reliable event selections of the trigger, many improvements in algorithm performance and robustness across all signatures have been made to deal with increasing trigger rates due to the increase in luminosity and pile-up in 2017. Only a few selected improvements were highlighted here, however the changes made in the various signatures have already shown great improvements and performance. Further improvements to the ATLAS trigger system in terms of hardware additions are planned for with the commissioning of FTK.