Searcharxiv⌕ Search

arXiv subjects

Shravan Hanasoge

Publications and source records attributed to Shravan Hanasoge.

38 records · Page 3Linked to original sources
arXiv2011

Transient solar oscillations driven by primordial black holes

Stars are transparent to the passage of primordial black holes (PBHs) and serve as seismic detectors for such objects. The gravitational field of a PBH squeezes a star and causes it to ring acoustically. We calculate the seismic signature of a PBH passing through the Sun. The background for this signal is the observed spectrum of solar oscillations excited by supersonic turbulence. We predict that PBHs more massive than 10^21 g (comparable in mass to an asteroid) are detectable by existing solar observatories. The oscillations excited by PBHs peak at large scales and high frequencies, making them potentially detectable in other stars. The discovery of PBHs would have profound implications for cosmology and high-energy physics.

astro-ph.CO↗
arXiv2011

The Adjoint Method Applied to Time-Distance Helioseismology

For a given {\it misfit function}, a specified optimality measure of a model, its gradient describes the manner in which one may alter properties of the system to march towards a stationary point. The adjoint method, arising from partial-differential-equation-constrained optimization, describes a means of extracting derivatives of a misfit function with respect to model parameters through finite computation. It relies on the accurate calculation of wavefields that are driven by two types of sources, namely the average wave-excitation spectrum, resulting in the {\it forward wavefield}, and differences between predictions and observations, resulting in an {\it adjoint wavefield}. All sensitivity kernels relevant to a given measurement emerge directly from the evaluation of an interaction integral involving these wavefields. The technique facilitates computation of sensitivity kernels (Fréchet derivatives) relative to three-dimensional heterogeneous background models, thereby paving the way for non-linear iterative inversions. An algorithm to perform such inversions using as many observations as desired is discussed.

astro-ph.SR↗