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X-ray astronomy lacks high resolution spectra of interstellar dust analogues and molecules, severely hampering interstellar medium studies based on upcoming X-ray missions. Various theoretical approaches may be used to address this problem, but they must first be shown to reproduce reliable spectra compared to the experiment. In this work, we calculate the sulfur K edge X-ray absorption spectra of H2S, SO2, and OCS, whose spectra are already known from X-ray experiments and predict the X-ray spectrum of CS, which as far as we are aware has not been measured, thereby hampering its detection by X-ray telescopes. We chose these four molecules as the astrochemistry of sulfur is an unsolved problem and as the four molecules are already known to exist in space. We consider three types of methods for modeling the X-ray spectra: more accurate calculations with the algebraic-diagrammatic construction (ADC) and the CC2, CCSD, and CC3 coupled cluster (CC) approaches as well as more affordable ones with transition potential density functional theory (TP-DFT). A comparison of our computational results to previously reported experimental spectra shows that the core-valence separation (CVS) approaches CVS-ADC(2)-x and CVS-CC3 generally yield a good qualitative level of agreement with the experiment, suggesting that they can be used for interpreting measured spectra, while the TP-DFT method is not reliable for these molecules. However, quantitative agreement with the experiment is still outside the reach of the computational methods studied in this work.

Ubrzanim razvojem istraživanja i pregleda neba u srednjem i dalekom dijelu infracrvenog spektra, znanstvenici su uvidjeli da kozmička prašina nije samo smetnja prilikom opažanja nebeskih tijela. Pojavio se vrlo veliki broj slika nebeskih tijela, npr. mladih zvjezdanih objekata, aktivnih galaksijskih jezgri, planetarnih maglica i smeđih patuljaka. S pojavom tih slika nebeskih objekata pregledi neba ušli su u potpuno novo doba. Formalno istraživanje se ne može nositi s ovako brzim razvojem te astronomija počinje stvarati vlastiti problem „velikih podataka“. Brzi rast podataka odvija se u tako kratkom vremenskom intervalu da se čak niti tehnike strojnog učenja ne mogu dovoljno brzo razviti, a da ujedno uspijevaju kvalitetno analizirati sve slike. Male razlike u slikama, primjerice, mladih zvjezdanih objekta i aktivnih galaksijskih jezgara ne doprinose rješavanju ovog problema. Astronomiji su još uvijek potrebni postupci vizualne klasifikacije podataka. S ciljem rješavanja ovih problema, pokrenuti su projekti znanosti za građanstvo. Nakon kratkog uvoda u prvom poglavlju ovog rada, drugo poglavlje sadrži opise osnovnih ideja projekata znanosti za građanstvo. Predstavljeni su projekti u astronomiji. Čitatelj će se ukratko upoznati s najvećim astronomskim opažanjima od strane građana, kao i doprinosima strojnom učenju i modeliranju podataka. Iako pojedini stručnjaci smatraju Stardust prvim projektom znanosti za građanstvo u astronomiji, pravi razvoj astronomskih istraživanja u kojima sudjeluju građani započeo je Galaxy Zoo projektom, koji je u drugom poglavlju prikazan detaljnije. Nakon toga su opisana i najveća dostignuća Supernova Zoo projekta, a na kraju poglavlja predstavljen je Zooniverse projekt, koji koordinira većinu trenutno aktivnih projekata znanosti za građanstvo. Više informacija o znanosti za građanstvo u Europskoj Uniji nalazi se u Dodatku A. Treće poglavlje počinje opisom osnovnih svojstava, postanka i raspodjele prašine u Svemiru. Nakon toga, fokus je na diskovima kozmičke prašine oko mladih zvijezda, a posebno na uvjetima koji ove diskove čine pogodnima za stvaranje planeta. Čitatelj će se upoznati s teorijama koje nastoje objasniti procese nastanka planeta te s pregledima neba teleskopima i svemirskim letjelicama. Četiri istraživanja, prikazana u ovom poglavlju, odabrana su zbog važnosti informacija koje generiraju o kozmičkoj prašini, kao i zbog otkrića i promatranja egzoplaneta. Na kraju trećeg poglavlja predstavljena je fuzija svih prikazanih fenomena: Disk Detective projekt. Ovaj projekt znanosti za građanstvo oslanja se na volontere za otkrivanje diskova kozmičke prašine u blizini mladih zvijezda, a s ciljem pronalaska egzoplaneta i planetarnih sustava u blizini tih zvijezda. U ovom dijelu rada prikazani su detalji o projektu, dosadašnja dostignuća, kao i postupci određivanja dobrog kandidata za mladu zvijezdu s diskovima kozmičke prašine koji bi mogli sadržavati planetarne sustave. U četvrtom poglavlju prikazani su zanimljivi primjeri kandidata, odnosno naglašene su posebnosti u izgledu pojedinih objekata na slikama istraživanja koje sam pronašla tijekom rada na Disk Detective projektu. Također je prikazan udio pojedinih kriterija na postupak klasifikacije objekata kao dobrih kandidata za mladu zvijezdu s protoplanetarnim diskovima. Na kraju sam usporedila svoje rezultate s posljednjom objavom podataka od strane osnivača projekta. U posljednjem poglavlju su predstavljena zaključna razmatranja. With rapidly increasing development of sky surveys in the mid and far-infrared spectra, scientists have finally realized that the cosmic dust is not merely a nuisance during celestial body observations. An invaluable set of new images of celestial bodies emerged. Perhaps most interesting so far are images of young stellar objects, active galactic nuclei, planetary nebulae, and brown dwarfs. Sky surveys have entered a whole new era. The formal resarch cannot cope with this rapid evolvement and astronomy started to face its own „Big data“ problem. The growth of data happens in such a short time span that even machine learning techniques cannot evolve fast enough to be able to follow up and successfully analyze all images. Extremely small differences between pictures of, for instance, young stellar objects and active galactic nuclei surely do not contribute to solving this problem. Astronomy still needs processes of visual classifications by human eye. In the attempt of solving these issues, citizen science projects were initiated. After a brief introduction at the beginning of this thesis, the second chapter includes a description of basic concepts of "citizen science“ phenomena. After that, focus shifts to citizen science projects in astronomy. The reader is briefly introduced to some major astronomical observations made by citizens, as well as to their contributions to the machine learning and data modelling. Although Stardust project is considered to be the first citizen science project in astronomy, the true evolution of crowd-sourced projects in astronomy began with Galaxy Zoo. Therefore, this project is introduced in more details. Achievements of Supernova Zoo are described. Zooniverse, that coordinates most of the currently active citizen science projects, is presented. More information about citizen science in European Union can be found in Appendix A. The third chapter begins with the origin, properties, and distribution of dust in space. Afterwards, the focus will be on the disks of cosmic dust around young stars, and especially on conditions that make these disks suitable for planet formation. After a description of the formation of planets, the reader will be briefly introduced to sky surveys, chosen because of the importance of their contributions to cosmic dust explorations, as well as to the search, detections and observations of exoplanets. At the end of the third chapter, the fusion of all these phenomena is presented: the Disk Detective project. This crowd-sourced project uses volunteers for detecting young stellar object and debris disks in the vicinity of young stars, in the hope of finding exoplanets and planetary systems. The ideas behind the project, achievements made so far, and the process of determining good candidates for young star with a disk are presented. In the fourth chapter, I will show interesting cases with peculiarities in images that I found during my work on the Disk Detective project. I will also present overall influence of individual criteria in the process of determining good candidates. At the end, I am going to compare my results with the latest data release published by the project founders. In the last chapter, I will present some concluding remarks.