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Pattern recognition and machine learning techniques are known to play anemerging role for studying underlying physics of light-matter interaction.While on the subject, photon condensation and Anti-Stokes cooling remaincompelling phenomena of laser-underdense plasma interaction. In this work, theinteraction of a 1064 nm continuum-wave laser with inductively-coupled plasma(ICP) of Mercury(Hg) has been studied by probabilistic pattern recognition overobserved time resolved spectral data.3D vector fields obtained by theprobabilistic pattern recognition over spectral database proficientlyilluminates the analogue black hole (ABH) and its sonic horizon in whichhomoclinic orbit Whistler waves are exited. Vector spectra show the collectivebehavior of condensation and anti-Stokes cooling is due to the electronictransitions of Hg1 trapped by the phonon sink of ABH of laser. Modeling ofsubsonic phonon vector spectrum obtained by the probabilistic lineardiscriminant analysis(PLDA) estimates the 0.70 nanoKelvin of temperature of thesink region of ABH.

Probabilistic principal component and linear discriminant analysis of  interaction of 1064 nm CW laser with ICP plasma: Anti-Stokes cooling due to  analogue black hole