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Abstract

There are many different tracers of circumstellar disk physics, most notably, micrometer to millimeter-sized dust, and one of the most abundant molecules, CO. Formylium (HCO+) is another commonly observed species. Its chemistry is more complex than CO chemistry, and more interpretation steps are necessary to build the bridge between the disk structure and observed emission. Its isotopologs DCO+ and H13CO+ complement the picture and allow a more precise understanding of the disk structure. In this thesis, I present my results achieved by combining and developing physical modeling, chemical kinetics, and radiative transfer methods to understand circumstellar disks' physical properties through formylium isotopologs observations. I explain the observed DCO+ increase in the protoplanetary disk gap and use it as proof of the reduced amount of gas in the gaps. I show that HCO+ should be the brightest molecule after CO isotopologs in the gas-rich debris disks, and its brightness would reveal the elemental composition, but a next-generation observatory is needed to detect it. Then I present an application of the machine learning approach to predict the modeled disk chemistry instantaneously based on the pre-computed disk models' data set, allowing the replacement of computationally expensive thermo-chemical models in the fitting pipelines. Finally, I demonstrate the data which will be analyzed using this approach.