Scholarlink

Abstract <p>This paper presents a comprehensive quantum mechanical tunnelling framework for black-hole evaporation, integrating semiclassical, numerical and deep learning-based methodologies. Using the Wentzel–Kramers–Brillouin (WKB) approximation and Hamilton–Jacobi formalism, the study examines particle tunnelling across the gravitational potentials of Schwarzschild and rotating black holes. Quantum gravity effects are incorporated through corrections from the generalised uncertainty principle (GUP), leading to modified Hawking temperatures and predictions of remnant formation. A central advancement lies in the application of Physics Informed Neural Networks (PINNs) to estimate tunnelling probabilities across dynamically structured potentials. The PINN-based results are benchmarked against classical Runge–Kutta (RK4) numerical integration and analytical WKB solutions, demonstrating excellent consistency and computational robustness, particularly in complex or non-perturbative regimes. Enhanced tunnelling rates are observed for small and rotating black holes due to super-radiance and backreaction effects, resulting in a non-thermal Hawking spectrum with implications for information recovery. The study also explores holographic interpretations via the AdS/CFT correspondence and evaluates grey-body factors, quasi-normal modes and mass-loss rates under quantum gravitational corrections. The proposed framework offers novel insights into black-hole thermodynamics, supports the theoretical existence of stable remnants and indicates possible observational signatures in high-energy astrophysical environments. Furthermore, the implications of this framework extend to dark matter interaction scenarios near compact objects and to the cosmological evolution of black holes in a universe dominated by dark energy.</p> Graphical abstract <p></p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Quantum gravitational tunnelling and black-hole evaporation: a multimodal approach using WKB, RK4 and physics-informed neural networks

  • 期刊论文

  • 发表日期：

    2026年4月15日

查看全文
  • A Stanley Raj,
  • Adityan,
  • Josephine Usha,
  • K C Praveen Kumar

摘要

Abstract

This paper presents a comprehensive quantum mechanical tunnelling framework for black-hole evaporation, integrating semiclassical, numerical and deep learning-based methodologies. Using the Wentzel–Kramers–Brillouin (WKB) approximation and Hamilton–Jacobi formalism, the study examines particle tunnelling across the gravitational potentials of Schwarzschild and rotating black holes. Quantum gravity effects are incorporated through corrections from the generalised uncertainty principle (GUP), leading to modified Hawking temperatures and predictions of remnant formation. A central advancement lies in the application of Physics Informed Neural Networks (PINNs) to estimate tunnelling probabilities across dynamically structured potentials. The PINN-based results are benchmarked against classical Runge–Kutta (RK4) numerical integration and analytical WKB solutions, demonstrating excellent consistency and computational robustness, particularly in complex or non-perturbative regimes. Enhanced tunnelling rates are observed for small and rotating black holes due to super-radiance and backreaction effects, resulting in a non-thermal Hawking spectrum with implications for information recovery. The study also explores holographic interpretations via the AdS/CFT correspondence and evaluates grey-body factors, quasi-normal modes and mass-loss rates under quantum gravitational corrections. The proposed framework offers novel insights into black-hole thermodynamics, supports the theoretical existence of stable remnants and indicates possible observational signatures in high-energy astrophysical environments. Furthermore, the implications of this framework extend to dark matter interaction scenarios near compact objects and to the cosmological evolution of black holes in a universe dominated by dark energy.

Graphical abstract