Demonstrating a Potential Method for Black Hole Information Recovery via Simulated Hawking Radiation
ISEF · 2026 Physics and Astronomy
Overview
This project modeled the effects of Hawking radiation on black hole evolution and investigated whether black hole initial conditions can be inferred from radiation temperature data. A numerical simulation was developed in Python to reproduce black hole evaporation dynamics using recursive equations to compute mass, temperature, radius, and spin across discrete timesteps. The model calculates decay time by integrating the evaporation process until mass approaches zero, with visualization tools implemented to analyze temporal behavior. Rotational effects were incorporated using the Kerr solutions to Einstein's field equations, and Gaussian noise was added to approximate realistic observational uncertainty. An inverse modeling prediction algorithm was constructed to estimate the initial black hole mass by comparing simulated radiation emission curves against generated reference data across a bounded search range. The results demonstrate that the initial mass of a non-rotating black hole can be estimated using radiation emission data within the constraints of the numerical simulation model.
Competition history
- ISEF 2026
Resources
Related projects
ISEF · 2019
Modelling Energy Extraction via the Penrose Process in Analog Black Holes
CYSF · 2025
Hawking Radition Produced By Black Holes As A Sourse For Dark Energy
ISEF · 2016
Shear Heating of Black Hole Accretion Disks
ISEF · 2018
The Effect of Varied Surface Gravity on the Gravitational Radiation (Luminosity) Produced by a Binary System of Black Holes
ISEF · 2023
Simulating the Dynamics, Collisions, and Morphology of Galactic Ultralight Dark Matter Haloes
ISEF · 2025
Analytically Modeling the Gravitational Radiation Generated From a Quasistar System
CWSF · 2026
ΛCDM+S - Thermodynamic Cosmology: Simulating The Universe's Expansion Without Dark Energy
ISEF · 2026
Perceived Negative Energy Density Hawking Radiation Near Black Holes: A Tensorial Derivation
Closest projects by meaning, across every fair and year in the corpus.
Browse more like this
Source: Regeneron International Science and Engineering Fair