A New Paradigm in X-ray Spectral Fitting

While the field of X-ray spectral analysis has burgeoned over the last two decades, the intrinsic spectrum of targets has eluded astronomers; rather than observing the true spectrum, the observed spectrum is a convolution of the true spectrum with the instrumental response function. Using a class of neural networks known as a Recurrent Inference Machine (RIM), we have successfully deconvolved the source's intrinsic spectrum from the instrumental response function for the first time. In his presentation, we will discuss the intricacies of fitting X-ray spectra, how RIMs can be used to deconvolve them, and the implications of this deconvolution to several domains of X-ray astronomy.