About Krishna Kingkar Pathak
I work in high energy physics, QCD-inspired models, and quantum tunneling, focusing on universal scaling laws and analytical frameworks for complex quantum systems. My research connects fundamental theory with applications in molecular tunneling and meson spectroscopy. I also contribute to innovation with three design patents and six utility patents, particularly in quantum control and applied physics.
Popular Content
We develop an analytical–numerical framework for quantum tunnelling in hydrogen bonds, revealing a universal scaling law where tunnelling splitting depends exponentially on the square root of effective isotope mass, consistent across 1D models and multidimensional quantum calculations.
Mapping the Parameter Space of the Cornell Potential: Constraints on Strong Coupling and Confinement in QCD Models
Introduction
We analyse the parameter space of the Cornell potential, deriving constraints on the strong coupling αs and constant term c that ensure consistent perturbative treatment and convergence in QCD-inspired models of heavy–light mesons.
Resolving Meson Hyperfine Structure with a Smeared Cornell Potential Across Heavy–Light and Heavy–Heavy Systems
We revisit meson hyperfine splitting using a QCD-inspired Cornell potential with Gaussian smearing and analytic wavefunctions, achieving consistent predictions across D, B, and quarkonium systems while resolving short-distance divergences.
A Universal Scaling Law for Quantum Tunneling and Isotope Effects
Quantum tunneling allows particles to cross barriers classically forbidden. We show a universal law: tunneling decreases exponentially with the square root of isotope mass, explaining strong hydrogen–deuterium effects across physics, chemistry, and biology.
When First-Order Isn’t Enough: Understanding Perturbative Consistency in Confining Two-Body Systems
In physics, approximations are essential—but are they always reliable? In this work, I explore confining two-body systems and show that first-order corrections can fail for sensitive observables, making higher-order analysis necessary for consistent results.