Boosted four-top production at the LHC: A window to Randall-Sundrum or extended color symmetry

Scenarios seeking to address the issue of electroweak symmetry breaking often have heavy colored gauge bosons coupling preferentially to the top quark. Considering the bulk Randall-Sundrum as a typical example, we consider the prospects of the first Kaluza-Klein mode (<a:math xmlns:a="http://www.w3.org/1998/Math/MathML" display="inline"><a:msup><a:mi>G</a:mi><a:mrow><a:mo stretchy="false">(</a:mo><a:mn>1</a:mn><a:mo stretchy="false">)</a:mo></a:mrow></a:msup></a:math>) of the gluon being produced at the LHC in association with a <e:math xmlns:e="http://www.w3.org/1998/Math/MathML" display="inline"><e:mi>t</e:mi><e:mover accent="true"><e:mi>t</e:mi><e:mo stretchy="false">¯</e:mo></e:mover></e:math> pair. The enhanced coupling not only dictates that the dominant decay mode would be to a <i:math xmlns:i="http://www.w3.org/1998/Math/MathML" display="inline"><i:mi>t</i:mi><i:mover accent="true"><i:mi>t</i:mi><i:mo stretchy="false">¯</i:mo></i:mover></i:math> pair, but also to a very large <m:math xmlns:m="http://www.w3.org/1998/Math/MathML" display="inline"><m:msup><m:mi>G</m:mi><m:mrow><m:mo stretchy="false">(</m:mo><m:mn>1</m:mn><m:mo stretchy="false">)</m:mo></m:mrow></m:msup></m:math> width, necessitating the use of a renormalized <q:math xmlns:q="http://www.w3.org/1998/Math/MathML" display="inline"><q:msup><q:mi>G</q:mi><q:mrow><q:mo stretchy="false">(</q:mo><q:mn>1</q:mn><q:mo stretchy="false">)</q:mo></q:mrow></q:msup></q:math> propagator. This, along with the presence of large backgrounds (specially <u:math xmlns:u="http://www.w3.org/1998/Math/MathML" display="inline"><u:mi>t</u:mi><u:mover accent="true"><u:mi>t</u:mi><u:mo stretchy="false">¯</u:mo></u:mover><u:mi>j</u:mi><u:mi>j</u:mi></u:math>), renders a conventional cut-based analysis ineffective, yielding only marginal significances of only around <y:math xmlns:y="http://www.w3.org/1998/Math/MathML" display="inline"><y:mrow><y:mn>2</y:mn><y:mi>σ</y:mi></y:mrow></y:math>. The use of machine learning (ML) techniques alleviates this problem to a great extent. In particular, the use of artificial neural networks helps us identify the most discriminating observables, thereby allowing a significance in excess of <ab:math xmlns:ab="http://www.w3.org/1998/Math/MathML" display="inline"><ab:mrow><ab:mn>4</ab:mn><ab:mi>σ</ab:mi></ab:mrow></ab:math> for <cb:math xmlns:cb="http://www.w3.org/1998/Math/MathML" display="inline"><cb:msup><cb:mi>G</cb:mi><cb:mrow><cb:mo stretchy="false">(</cb:mo><cb:mn>1</cb:mn><cb:mo stretchy="false">)</cb:mo></cb:mrow></cb:msup></cb:math> masses of <gb:math xmlns:gb="http://www.w3.org/1998/Math/MathML" display="inline"><gb:mo>∼</gb:mo><gb:mn>4</gb:mn><gb:mtext> </gb:mtext><gb:mtext> </gb:mtext><gb:mi>TeV</gb:mi></gb:math>. Published by the American Physical Society 2024