DustRover v1.0.0: A Tool to Model Cosmic Dust Extinction in GRBs and Quasars

Abstract DustRover: A Tool to Model Cosmic Dust in GRBs and Quasars Tayyaba Zafar*, Amir Ebadati Bazkiaei, Nuria P. F. Lorente *School of Mathematical and Physical Sciences, Macquarie University, NSW 2109, Australia ([email protected]) DustRover is a new online tool designed to fit intrinsic dust extinction in gamma-ray burst (GRB) and quasar sightlines by modelling their spectral energy distributions (SEDs). It combines photometry, spectroscopy, and Xray data to constrain dust properties beyond the assumptions of canonical Local Group (Milky Way and Magellanic Clouds) extinction laws. Users input source redshift and Galactic extinction, and DustRover applies an MCMC-based fitting routine to model the intrinsic extinction curve, capturing both wavelength-dependent attenuation and total dust content. Developed under the Australian Astronomical Optics (AAO)'s RDS initiative, DustRover supports rapid analysis of dusty extragalactic environments and helps disentangle the role of dust in early galaxy evolution and high-redshift sightlines. This tool is particularly useful for GRB and quasar researchers aiming to characterise dust in complex, distant environments with multi-wavelength data. DustRover v1.0.0 provides automated, physically motivated extinction curve fitting for GRB and quasar sightlines by simultaneously correcting for both foreground Galactic and intrinsic host-galaxy dust extinction. The framework employs Markov Chain Monte Carlo (MCMC) optimisation to model multi-wavelength (X-ray to near-infrared) SEDs and derive key extinction intrinsic slope parameters. Multi-component fitting:Implements single or broken power-law underlying continua for GRBs and template-based spectral models for quasars, ensuring accurate recovery of intrinsic source spectra. Extinction decomposition:Corrects spectro-photometric data for user provided Milky Way foreground extinction from intrinsic host extinction to derive environment-specific extinction curves. Benchmark validation:Tested on >50 sources, including GRB 221009A at z=0.151 (Fig. 1), which demonstrates precise fitting of an unusually high visual extinction (AV(Host+Gal) ≈ 4.9 mag) with AV Gal = 4.5 mag, and quasar HAQ J0151+0618 at z=0.95 (Fig. 2), where the model successfully reproduces extinction curves using featureless power laws. Efficiency:Achieves a >90% runtime reduction relative to legacy IDL routines while maintaining parameter accuracy and robust uncertainty estimation. These results confirm DustRover’s reliability and scalability for population-level analyses of dust extinction across cosmic epochs. Background Workflow Results Fig. 1: The X-ray (Swift-XRT to near-infrared) SED of GRB 221009A showing VLT/X-shooter data in red, Swift in black, and photometric datapoints in black diamonds. The black dashed and solid lines are intrinsic double power-law and absorbed and extinguished law, respectively. The GRB shows dust (foreground and GRB) of AV=4.94±0.04. Conclusions DustRover establishes a new benchmark for automated, data-driven extinction curve modelling for GRBs and quasars. By moving beyond fixed empirical laws, it provides direct, physically constrained measurements of dust characteristics across diverse galactic environments and cosmic epochs. The framework’s robust performance and validated accuracy demonstrate its suitability for both individual-source analysis and large-scale population studies. Phase I development confirms DustRover’s efficiency and reproducibility, with a >90 % reduction in runtime relative to IDL implementations while maintaining full model precisions. The next phase will focus on extending its capabilities toward grain composition, enabling decomposition of extinction curves into carbonaceous, silicate, PAH, and iron-bearing components. This expansion will establish quantitative links between extinction signatures, dust chemistry, metallicity, and star-formation processes, providing key diagnostics for understanding dust evolution from the local interstellar medium to the earliest galaxies. Ultimately, DustRover will serve as a cornerstone tool for tracing the physical lifecycle of cosmic dust across cosmic time. Fig. 2: SED fitting for quasar HAQ J0151+0618. The spectrum, phometry and best fit are indicated by orange curve, purple symbols, and red curve and points. The best-fit intrinsic extinction model derived from MCMC optimisation over 1000 iterations, yielding AV = 0.5 mag. The pink-shaded region marks the Lyα and continuum shortward of 1216Å. Phase I validation achieves a >90 % reduction in runtime relative to legacy IDL implementations. A QR code (right) links directly to the repository for software access and documentation. Multi-wavelength observations GRB X-rayà NIR spectrophotometric data Quasar UVà NIR spectrophotometric data DustRover v1.0.0 Automated single and broken powerlaw SED fitting Automated SED fitting using Quasar UVàNIR templates MCMC parameter estimation Intrinsic extinction curves (RV, AV and 2175Å bump detection) Outputs Extinction curves Fitted parameters with 1𝜎 uncertainties Visualization plots Interstellar dust shapes the observable universe by absorbing, scattering, and reemitting radiation across all wavelengths, yet its intrinsic composition and evolution remain only partially understood. This ubiquitous presence of dust, intertwined with gas, forms the building blocks of stars in galaxies. While interstellar extinction has been recognised since 1930, current empirical laws based on Milky Way and Magellanic Cloud analogues cannot capture the full diversity of dust properties seen in distant galaxies.Dust grains form primarily in the outflows of evolved stars and supernovae and are subsequently processed in the interstellar medium through accretion, destruction, and coagulation, leading to substantial variation in size distribution and chemical composition across environments. Elemental depletion studies indicate that over 50% of refractory elements such as iron, silicon, and carbon are locked into solid dust phases, yet their precise mineralogical forms remain uncertain. DustRover is created to address this limitation by deriving intrinsic extinction curves for gamma-ray burst (GRB) and quasar sightlines using multi-wavelength data spanning X-ray to near-infrared regimes. The framework integrates established methods for spectral energy distribution (SED) fitting and extinction analysis (Zafar et al. 2015, 2018a, b, c) within an MCMC-based parameter estimation routine, providing robust determinations of total and selective extinction, extinction-curve shapes, and the 2175 Å bump. In the next phase of DustRover, by incorporating physically motivated grain models, including graphite, silicates, polycyclic aromatic hydrocarbons (PAHs), and iron, DustRover delivers a nextgeneration automated platform for quantifying dust properties and tracing their evolution from nearby galaxies to the epoch of reionization. Flux (erg/cm2/s/Å) The DustRover (https://dev.aao.org.au/rds/dustrover/-/releases/v1.0.0) framework is designed as a fully automated, modular pipeline. The workflow integrates data ingestion, Galactic extinction correction, continuum modelling, and intrinsic extinction fitting through an MCMC-based optimisation. Separate processing branches accommodate GRB and quasar inputs, before converging on a unified fitting engine that produces extinction curves. The flowchart below illustrates the complete processing pathway.