Performance of Top Quark and W Boson Tagging in Run 2 with ATLAS

The performance of hadronically-decaying top-quark and $W$-boson taggers in $pp$ collisions at $\sqrt{s}$ = 13 TeV recorded by the ATLAS experiment at the Large Hadron Collider is presented. A set of techniques, including some new to the data recorded in 2015 and 2016, are studied to determine a set of optimal cut-based taggers for use in physics analyses. A further extension is made to study the utility of combinations of substructure observables as a multivariate tagger using boosted decision trees and deep neural networks in comparison with taggers based on two-variable combinations. The performance of these taggers is studied with the data collected during 2015 and 2016 in $t\bar{t}$, dijet and $\gamma$ + jet event topologies.