# Temporal Evolution of Photon Energy emitted from Two Component Advective Flows: Origin of Time Lag

## TL;DR

This study uses Monte Carlo simulations within the Two Component Advective Flow model to analyze photon energy evolution and time lags in black hole accretion, reproducing observed trends related to spectral states and QPOs.

## Contribution

It introduces a detailed simulation approach to explain the origin of time lags in black hole systems using the TCAF model with relativistic ray-tracing.

## Key findings

- Time lag behavior varies with accretion rate, CENBOL size, and inclination.
- Simulated time lags match observed trends with QPO frequency and energy.
- The model explains the energy-dependent time lag phenomena in black hole accretion.

## Abstract

X-Ray time lag of black hole candidates contains important information regarding the emission geometry. Recently, study of time lags from observational data revealed very intriguing properties. To investigate the real cause of this lag behavior with energy and spectral states, we study photon paths inside a Two Component Advective Flow (TCAF) which appears to be a satisfactory model to explain the spectral and timing properties. We employ the Monte-Carlo simulation technique to carry out the Comptonization process. We use a relativistic thick disk in Schwarzschild geometry as the CENtrifugal pressure supported BOundary Layer (CENBOL) which is the Compton cloud. In TCAF, this is the post-shock region of the advective component. Keplerian disk on the equatorial plane which is truncated at the inner edge i.e., at the outer boundary of the CENBOL, acts as the soft photon source. Ray-tracing code is employed to track the photons to a distantly located observer. We compute the cumulative time taken by a photon during Comptonization, reflection and following the curved geometry on the way to the observer. Time lags between various hard and soft bands have been calculated. We study the variation of time lags with accretion rates, CENBOL size and inclination angle. Time lags for different energy channels are plotted for different inclination angles. The general trend of variation of time lag with QPO frequency and energy as observed in satellite data is reproduced.