fixing latex formatting

README.md

@@ -18,7 +18,7 @@ In this work, we present the first attempt to operationalize LLM-based agents wi
 
 ## Description of a Representative High Energy Physics Analysis
 
-In this paper, we use a cross-section measurement of the Higgs boson decaying to the diphoton channel at the Large Hadron Collider as an example. We employ collision data and simulation samples from the 2020 ATLAS Open Data release [ATLAS Collaboration, 2020](#ref-atlas-collab-2020). The data sample corresponds to **10 fb⁻¹** of proton-proton collisions collected in 2016 at $\sqrt{s} = 13$ TeV. Higgs boson production is simulated for gluon fusion, vector boson fusion, associated production with a vector boson, and associated production with a top-quark pair.
+In this paper, we use a cross-section measurement of the Higgs boson decaying to the diphoton channel at the Large Hadron Collider as an example. We employ collision data and simulation samples from the 2020 ATLAS Open Data release [ATLAS Collaboration, 2020](#ref-atlas-collab-2020). The data sample corresponds to **10 fb⁻¹** of proton-proton collisions collected in 2016 at \\(\sqrt{s} = 13\\) TeV. Higgs boson production is simulated for gluon fusion, vector boson fusion, associated production with a vector boson, and associated production with a top-quark pair.
 
 Our example analysis uses control samples derived from collision data and Higgs production simulation samples to design a categorized analysis with a machine-learning-based event classifier, similar to the one used by the CMS collaboration in their Higgs observation paper [CMS Collaboration, 2012](#ref-cms-collab-2012). The objective of this analysis is to maximize the expected significance of the Higgs-to-diphoton signal. Since the purpose of this work is to demonstrate the LLM-based agentic implementation of a HEP analysis, we do not report the observed significance. The workflow of this analysis is highly representative in HEP.