arXiv subjects

Sanaz Vahidinia

Publications and source records attributed to Sanaz Vahidinia.

6 recordsLinked to original sources

arXiv2026

Emerging Technologies for Astrophysics Missions: Workshop Summary Report

NASA's Astrophysics Division convened the Emerging Technologies for Astrophysics Missions (ETAM) Workshop in March 2025 at the Ames Research Center in Silicon Valley, California. The workshop's goal was to identify emerging technologies that could critically impact or enable future space missions-including concepts previously considered unachievable. Four key technology areas were examined: Astrophotonics, Artificial Intelligence and Machine Learning, Advanced Materials, and Quantum Sensors. Approximately 60 participants from academia, industry, government laboratories, and NASA centers attended. The workshop fostered an inspiring and collaborative atmosphere that encouraged interaction among experts both within and across disciplines. The workshop's three-day novel format featured landscape presentations outlining the state of each field, followed by breakout sessions where participants, grouped in their own disciplines, identified high-impact technologies for astrophysics missions. Cross-pollination sessions then brought together experts from multiple technology domains to foster interdisciplinary insights. The event successfully identified several high-priority emerging technologies (summarized in subsequent sections of this report). In addition to the field-specific insights, the workshop also produced five key cross-cutting suggestions for the NASA Astrophysics Division to consider.

astro-ph.IM↗

arXiv2025

Fractal Aggregate Aerosols in the Virga Cloud Code I: Model Description and Application to a Benchmark Cloudy Exoplanet

We introduce new functionality to treat fractal aggregate aerosol particles within the Virga cloud modeling framework. Previously, the open source cloud modeling code Virga (Batalha et al. 2025), the Python version of EddySed (Ackerman & Marley, 2001), assumed spherical particles to compute particle mass and size distributions throughout the atmosphere. The initial release of Virga also assumed spherical particles to compute Mie scattering properties, which include the single scattering albedo, asymmetry parameter, and optical depth as a function of particle radius and composition. However, extensive evidence from Solar system aerosols, astrophysical disks and dust, and Earth climate studies suggests that non-spherical aggregate particles are common compared to idealized compact spherical particles. Following recent advances in microphysical and opacity modeling, we implement a simple parametrization for dynamical and optical (modified mean field theory) effects of fractal aggregate particles into Virga. We then use this new functionality to perform a case study using basic planetary parameters similar to the well-characterized, aerosol-laden mini-Neptune GJ 1214 b, using KCl clouds made of aggregate particles. We choose KCl to most directly explore comparisons to previous studies. We demonstrate 1) how our method compares to previous fractal aggregate particle treatments and 2) how our new fractal treatment affects theoretical spectra of cloudy atmospheres. Overall, our model is faster and more flexible for a wider range of parameter space than previous studies. We explore the limitations of our modeling set-up and offer guidance for future investigations using our framework.

astro-ph.EP↗

arXiv2024

INDUS: Effective and Efficient Language Models for Scientific Applications

Large language models (LLMs) trained on general domain corpora showed remarkable results on natural language processing (NLP) tasks. However, previous research demonstrated LLMs trained using domain-focused corpora perform better on specialized tasks. Inspired by this insight, we developed INDUS, a comprehensive suite of LLMs tailored for the closely-related domains of Earth science, biology, physics, heliophysics, planetary sciences and astrophysics, and trained using curated scientific corpora drawn from diverse data sources. The suite of models include: (1) an encoder model trained using domain-specific vocabulary and corpora to address NLP tasks, (2) a contrastive-learning based text embedding model trained using a diverse set of datasets to address information retrieval tasks and (3) smaller versions of these models created using knowledge distillation for applications which have latency or resource constraints. We also created three new scientific benchmark datasets, CLIMATE-CHANGE NER (entity-recognition), NASA-QA (extractive QA) and NASA-IR (IR) to accelerate research in these multi-disciplinary fields. We show that our models outperform both general-purpose (RoBERTa) and domain-specific (SCIBERT) encoders on these new tasks as well as existing tasks in the domains of interest. Furthermore, we demonstrate the use of these models in two industrial settings -- as a retrieval model for large-scale vector search applications and in automatic content tagging systems.

cs.CL↗

arXiv2024

Aggregate Cloud Particle Effects in Exoplanet Atmospheres

Aerosol opacity has emerged as a critical factor controlling transmission and emission spectra. We provide a simple guideline for the effects of aerosol morphology on opacity and residence time in the atmosphere, as it pertains to transit observations, particularly those with flat spectra due to high altitude aerosols. This framework can be used for understanding complex cloud and haze particle properties before getting into detailed microphysical modeling. We consider high altitude aerosols to be composed of large fluffy particles that can have large residence times in the atmosphere and influence the deposition of stellar flux and/or the emergence of thermal emission in a different way than compact droplet particles, as generally modeled to date for extrasolar planetary atmospheres. We demonstrate the important influence of aggregate particle porosity and composition on the extent of the wavelength independent regime. We also consider how such fluffy particles reach such high altitudes and conclude that the most likely scenario is their local production at high altitudes via UV bombardment and subsequent blanketing of the atmosphere, rather than some mechanism of lofting or transport from the lower atmosphere.

astro-ph.EP↗

arXiv2020

Enabling Effective Exoplanet / Planetary Collaborative Science

The field of exoplanetary science has emerged over the past two decades, rising up alongside traditional solar system planetary science. Both fields focus on understanding the processes which form and sculpt planets through time, yet there has been less scientific exchange between the two communities than is ideal. This white paper explores some of the institutional and cultural barriers which impede cross-discipline collaborations and suggests solutions that would foster greater collaboration. Some solutions require structural or policy changes within NASA itself, while others are directed towards other institutions, including academic publishers, that can also facilitate greater interdisciplinarity.

astro-ph.IM↗

arXiv2014

Cloud Base Signature in Transmission Spectra of Exoplanet Atmospheres

We present an analytical model for the transmission spectrum of a transiting exoplanet, showing that a cloud base can produce an observable inflection point in the spectrum. The wavelength and magnitude of the inflection can be used to break the degeneracy between the atmospheric pressure and the abundance of the main cloud material, however, the abundance still depends on cloud particle size. An observed inflection also provides a specific point on the atmospheric P-T profile, giving us a "thermometer" to directly validate or rule out postulated cloud species. We apply the model to the transit spectrum of HD 189733b.

astro-ph.EP↗