arXiv subjects

Manuchehr Taghizadeh-Popp

Publications and source records attributed to Manuchehr Taghizadeh-Popp.

6 recordsLinked to original sources

arXiv2026

Surveying the Universe in 4D: Beating Cosmic Variance with Wide-Field Slitless Spectroscopy from HST, JWST, Euclid, Roman, and Beyond

We summarize strategies, lessons learned, and future directions from the Space Telescope Science Institute workshop Surveying the Universe in 4D: Beating Cosmic Variance with Wide-Field Slitless Spectroscopy from HST, JWST, Euclid, Roman, and Beyond, held August 24--28, 2026. The workshop examined scientific results, observational and data analysis challenges, extraction tools, and future opportunities. Discussions highlighted (1) the transformative potential of WFSS for the study of transient phenomena, galaxy evolution --both spatially-resolved and within the broader context of the cosmic web--, and rare populations and (2) the synergies among Euclid and Roman surveys, Rubin-LSST monitoring, JWST WFSS, and high-resolution integral-field observations. Participants identified advances in forward modeling and physics-informed machine learning as essential for addressing spectral overlap, crowded fields, and upcoming, very large data volumes. Realizing WFSS's full potential will require community-wide infrastructure, science-ready data products, accessible cloud-based analysis tools, and robust benchmarking of reduction pipelines. Crucially, participants called for systemic changes to properly recognize early-career researchers who invest significant efforts in pipeline, code, and calibration developments that enable WFSS science, and stressed that progress requires collaborative, multidisciplinary practices that optimize the participation and benefits of the next generation.

astro-ph.GA↗

arXiv2026

Tomographer: End-to-end Redshift Distribution Estimation for Source Catalogs and Intensity Maps

Redshift information is central to nearly every extragalactic and cosmological application of sky surveys, yet only a small fraction of cataloged sources, and none of the photons forming diffuse backgrounds, have spectroscopic redshifts. Clustering-based redshift inference estimates the redshift distribution of an arbitrary dataset through spatial cross-correlation with a reference sample of known redshifts. It relies only on positional information, making it applicable to any tracer of large-scale structure, including source populations and diffuse intensity maps. Its broader adoption, however, has been limited by technical barriers: assembling and characterizing spectroscopic references, expensive pair-counting computations, theoretical corrections, and systematic control. To remove these barriers, we introduce Tomographer, an end-to-end clustering-redshift framework. The key design feature is a set of precomputed "activation maps" encoding the spatial pair information of 3 million SDSS spectroscopic galaxies and quasars up to $z\sim4$ over $10{,}000\,{\rm deg}^2$. This eliminates user-end pair counting, reducing computational scaling from $O(N\log N)$ to $O(1)$ map multiplications. Given a source catalog or intensity map, Tomographer returns the bias-weighted redshift distribution, $b(z)\,{\rm d}N/{\rm d}z(z)$ or $b(z)\,{\rm d}I/{\rm d}z(z)$. We validate the framework against samples with known redshifts, demonstrate accurate uncertainty estimates, and show robustness to survey footprint, spatially varying selection functions, beam smoothing, and foreground contamination. We showcase applications to source catalogs selected by flux, color, photometric redshift, morphology, or variability, and to intensity maps from radio to X-rays. Future Tomographer releases will incorporate additional wide-field spectroscopic reference samples as they become available.

astro-ph.CO↗

arXiv2020

SciServer: a Science Platform for Astronomy and Beyond

We present SciServer, a science platform built and supported by the Institute for Data Intensive Engineering and Science at the Johns Hopkins University. SciServer builds upon and extends the SkyServer system of server-side tools that introduced the astronomical community to SQL (Structured Query Language) and has been serving the Sloan Digital Sky Survey catalog data to the public. SciServer uses a Docker/VM based architecture to provide interactive and batch mode server-side analysis with scripting languages like Python and R in various environments including Jupyter (notebooks), RStudio and command-line in addition to traditional SQL-based data analysis. Users have access to private file storage as well as personal SQL database space. A flexible resource access control system allows users to share their resources with collaborators, a feature that has also been very useful in classroom environments. All these services, wrapped in a layer of REST APIs, constitute a scalable collaborative data-driven science platform that is attractive to science disciplines beyond astronomy.

astro-ph.IM↗

arXiv2020

Sequencing seismograms: A panoptic view of scattering in the core-mantle boundary region

Scattering of seismic waves can reveal subsurface structures but usually in a piecemeal way focused on specific target areas. We used a manifold learning algorithm called "the Sequencer" to simultaneously analyze thousands of seismograms of waves diffracting along the core-mantle boundary and obtain a panoptic view of scattering across the Pacific region. In nearly half of the diffracting waveforms, we detected seismic waves scattered by three-dimensional structures near the core-mantle boundary. The prevalence of these scattered arrivals shows that the region hosts pervasive lateral heterogeneity. Our analysis revealed loud signals due to a plume root beneath Hawaii and a previously unrecognized ultralow-velocity zone beneath the Marquesas Islands. These observations illustrate how approaches flexible enough to detect robust patterns with little to no user supervision can reveal distinctive insights into the deep Earth.

physics.geo-ph↗

arXiv2015

Simulating Deep Hubble Images With Semi-empirical Models of Galaxy Formation

We simulate deep images from the Hubble Space Telescope (HST) using semi-empirical models of galaxy formation with only a few basic assumptions and parameters. We project our simulations all the way to the observational domain, adding cosmological and instrumental effects to the images, and analyze them in the same way as real HST images ("forward modeling"). This is a powerful tool for testing and comparing galaxy evolution models, since it allows us to make unbiased comparisons between the predicted and observed distributions of galaxy properties, while automatically taking into account all relevant selection effects. Our semi-empirical models populate each dark matter halo with a galaxy of determined stellar mass and scale radius. We compute the luminosity and spectrum of each simulated galaxy from its evolving stellar mass using stellar population synthesis models. We calculate the intrinsic scatter in the stellar mass-halo mass relation that naturally results from enforcing a monotonically increasing stellar mass along the merger history of each halo. The simulated galaxy images are drawn from cutouts of real galaxies from the Sloan Digital Sky Survey, with sizes and fluxes rescaled to match those of the model galaxies. The distributions of galaxy luminosities, sizes, and surface brightnesses depend on the adjustable parameters in the models, and they agree well with observations for reasonable values of those parameters. Measured galaxy magnitudes and sizes have significant magnitude-dependent biases, with both being underestimated near the magnitude detection limit. The fraction of galaxies detected and fraction of light detected also depend sensitively on the details of the model.

astro-ph.GA↗

arXiv2009

Probing Spectroscopic Variability of Galaxies & Narrow-Line Active Galactic Nuclei in the Sloan Digital Sky Survey

Under the unified model for active galactic nuclei (AGNs), narrow-line (Type 2) AGNs are, in fact, broad-line (Type 1) AGNs but each with a heavily obscured accretion disk. We would therefore expect the optical continuum emission from Type 2 AGN to be composed mainly of stellar light and non-variable on the time-scales of months to years. In this work we probe the spectroscopic variability of galaxies and narrow-line AGNs using the multi-epoch data in the Sloan Digital Sky Survey (SDSS) Data Release 6. The sample contains 18,435 sources for which there exist pairs of spectroscopic observations (with a maximum separation in time of ~700 days) covering a wavelength range of 3900-8900 angstrom. To obtain a reliable repeatability measurement between each spectral pair, we consider a number of techniques for spectrophotometric calibration resulting in an improved spectrophotometric calibration of a factor of two. From these data we find no obvious continuum and emission-line variability in the narrow-line AGNs on average -- the spectroscopic variability of the continuum is 0.07+/-0.26 mag in the g band and, for the emission-line ratios log10([NII]/Halpha) and log10([OIII]/Hbeta), the variability is 0.02+/-0.03 dex and 0.06+/-0.08 dex, respectively. From the continuum variability measurement we set an upper limit on the ratio between the flux of varying spectral component, presumably related to AGN activities, and that of host galaxy to be ~30%. We provide the corresponding upper limits for other spectral classes, including those from the BPT diagram, eClass galaxy classification, stars and quasars.

astro-ph↗