The ATLAS experiment relies on real-time hadronic jet reconstruction and b-tagging to record fully hadronic events containing b-jets. These algorithms require track reconstruction, which is computationally expensive and could overwhelm the high-level-trigger farm, even at the reduced event rate that passes the ATLAS first stage hardware-based trigger. In LHC Run 3, ATLAS has mitigated these computational demands by introducing a fast neural-network-based b-tagger, which acts as a low-precision filter using input from hadronic jets and tracks. It runs after a hardware trigger and before the remaining high-level-trigger reconstruction. This design relies on the negligible cost of neural-network inference as compared to track reconstruction, and the cost reduction from limiting tracking to specific regions of the detector. In the case of Standard Model HH → bb̅bb̅, a key signature relying on b-jet triggers, the filter lowers the input rate to the remaining high-level trigger by a factor of five at the small cost of reducing the overall signal efficiency by roughly 2%.

<jats:p>This paper presents the observation of four-top-quark (<jats:inline-formula><jats:alternatives><jats:tex-math>$$t\bar{t}t\bar{t}$$</jats:tex-math><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>t</mml:mi> <mml:mover> <mml:mrow> <mml:mi>t</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>¯</mml:mo> </mml:mrow> </mml:mover> <mml:mi>t</mml:mi> <mml:mover> <mml:mrow> <mml:mi>t</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>¯</mml:mo> </mml:mrow> </mml:mover> </mml:mrow> </mml:math></jats:alternatives></jats:inline-formula>) production in proton-proton collisions at the LHC. The analysis is performed using an integrated luminosity of 140 <jats:inline-formula><jats:alternatives><jats:tex-math>$$\hbox {fb}^{-1}$$</jats:tex-math><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msup> <mml:mtext>fb</mml:mtext> <mml:mrow> <mml:mo>-</mml:mo> <mml:mn>1</mml:mn> </mml:mrow> </mml:msup> </mml:math></jats:alternatives></jats:inline-formula> at a centre-of-mass energy of 13 TeV collected using the ATLAS detector. Events containing two leptons with the same electric charge or at least three leptons (electrons or muons) are selected. Event kinematics are used to separate signal from background through a multivariate discriminant, and dedicated control regions are used to constrain the dominant backgrounds. The observed (expected) significance of the measured <jats:inline-formula><jats:alternatives><jats:tex-math>$$t\bar{t}t\bar{t}$$</jats:tex-math><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>t</mml:mi> <mml:mover> <mml:mrow> <mml:mi>t</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>¯</mml:mo> </mml:mrow> </mml:mover> <mml:mi>t</mml:mi> <mml:mover> <mml:mrow> <mml:mi>t</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>¯</mml:mo> </mml:mrow> </mml:mover> </mml:mrow> </mml:math></jats:alternatives></jats:inline-formula> signal with respect to the standard model (SM) background-only hypothesis is 6.1 (4.3) standard deviations. The <jats:inline-formula><jats:alternatives><jats:tex-math>$$t\bar{t}t\bar{t}$$</jats:tex-math><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>t</mml:mi> <mml:mover> <mml:mrow> <mml:mi>t</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>¯</mml:mo> </mml:mrow> </mml:mover> <mml:mi>t</mml:mi> <mml:mover> <mml:mrow> <mml:mi>t</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>¯</mml:mo> </mml:mrow> </mml:mover> </mml:mrow> </mml:math></jats:alternatives></jats:inline-formula> production cross section is measured to be <jats:inline-formula><jats:alternatives><jats:tex-math>$$22.5^{+6.6}_{-5.5}$$</jats:tex-math><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>22</mml:mn> <mml:mo>.</mml:mo> <mml:msubsup> <mml:mn>5</mml:mn> <mml:mrow> <mml:mo>-</mml:mo> <mml:mn>5.5</mml:mn> </mml:mrow> <mml:mrow> <mml:mo>+</mml:mo> <mml:mn>6.6</mml:mn> </mml:mrow> </mml:msubsup> </mml:mrow> </mml:math></jats:alternatives></jats:inline-formula> fb, consistent with the SM prediction of <jats:inline-formula><jats:alternatives><jats:tex-math>$$12.0 \pm 2.4$$</jats:tex-math><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>12.0</mml:mn> <mml:mo>±</mml:mo> <mml:mn>2.4</mml:mn> </mml:mrow> </mml:math></jats:alternatives></jats:inline-formula> fb within 1.8 standard deviations. Data are also used to set limits on the three-top-quark production cross section, being an irreducible background not measured previously, and to constrain the top-Higgs Yukawa coupling and effective field theory operator coefficients that affect <jats:inline-formula><jats:alternatives><jats:tex-math>$$t\bar{t}t\bar{t}$$</jats:tex-math><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>t</mml:mi> <mml:mover> <mml:mrow> <mml:mi>t</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>¯</mml:mo> </mml:mrow> </mml:mover> <mml:mi>t</mml:mi> <mml:mover> <mml:mrow> <mml:mi>t</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>¯</mml:mo> </mml:mrow> </mml:mover> </mml:mrow> </mml:math></jats:alternatives></jats:inline-formula> production.</jats:p>

A search is presented for a heavy resonance $Y$ decaying into a Standard Model Higgs boson $H$ and a new particle $X$ in a fully hadronic final state. The full Large Hadron Collider Run 2 dataset of proton-proton collisions at $\sqrt{s}= 13$ TeV collected by the ATLAS detector from 2015 to 2018 is used, and corresponds to an integrated luminosity of 139 fb$^{-1}$. The search targets the high $Y$-mass region, where the $H$ and $X$ have a significant Lorentz boost in the laboratory frame. A novel signal region is implemented using anomaly detection, where events are selected solely because of their incompatibility with a learned background-only model. It is defined using a jet-level tagger for signal-model-independent selection of the boosted $X$ particle, representing the first application of fully unsupervised machine learning to an ATLAS analysis. Two additional signal regions are implemented to target a benchmark $X$ decay into two quarks, covering topologies where the $X$ is reconstructed as either a single large-radius jet or two small-radius jets. The analysis selects Higgs boson decays into $b\bar{b}$, and a dedicated neural-network-based tagger provides sensitivity to the boosted heavy-flavor topology. No significant excess of data over the expected background is observed, and the results are presented as upper limits on the production cross section $\sigma(pp \rightarrow Y \rightarrow XH \rightarrow q\bar{q}b\bar{b}$) for signals with $m_Y$ between 1.5 and 6 TeV and $m_X$ between 65 and 3000 GeV.