arXiv subjects

Arnav Agrawal

Publications and source records attributed to Arnav Agrawal.

3 recordsLinked to original sources

arXiv2026

Three outstanding physical questions for K2-18 b and other temperate sub-Neptunes

Recent transmission spectra of the temperate sub-Neptune K2-18 b obtained with JWST have attracted significant attention. Debates have quickly arisen over the interpretation of the spectral data, particularly the recent MIRI observation where dimethyl sulfide (DMS) and dimethyl disulfide (DMDS) are claimed. Here we revisit K2-18 b as a case study to examine several key questions that are also broadly relevant to the temperate sub-Neptune population: i) Can the low water abundance be reconciled with water clouds driven by orbital eccentricity? ii) Are the observed and non-observed atmospheric compositions mutually consistent? iii) Is it kinetically possible to produce DMS under sub-Neptune conditions? To address these questions, we couple climate and photochemical models to obtain self-consistent climate-photochemistry states for K2-18 b with a moderate orbital eccentricity of 0.2, as suggested by radial-velocity measurements. In addition, we present new laboratory measurements of DMS and DMDS infrared opacities by HFML-FELIX and compile updated C$_2$H$_6$ (ethane) opacities that include weak overtone bands. Our results support the interpretation of a sub-Neptune scenario without invoking DMS, and we do not find strong evidence for a water-rich interior.

astro-ph.EP↗

arXiv2024

Cthulhu: An Open Source Molecular and Atomic Cross Section Computation Code for Substellar Atmospheres

Atmospheric studies of exoplanets and brown dwarfs are a cutting-edge and rapidly evolving area of astrophysics research. Calculating models of exoplanet or brown dwarf spectra requires knowledge of the wavelength-dependent absorption of light (cross sections) by the molecules and atoms in the atmosphere. Here we introduce Cthulhu, a pure Python package that rapidly calculates cross sections from atomic and molecular line lists. Cthulhu includes modules to automatically download molecular line lists from online databases (e.g. ExoMol and HITRAN) and compute cross sections on a user-specified temperature, pressure, and wavenumber grid. Cthulhu requires only CPUs and can run on a user's laptop (for smaller line lists with < 100 million lines) or on a large cluster in parallel (for many billion lines). Cthulhu includes in-depth Jupyter tutorials in the online documentation. Finally, Cthulhu can be used as an educational tool to demystify the process of making cross sections for atmospheric models.

astro-ph.IM↗

arXiv2020

Authoritarian Governments Appear to Manipulate COVID Data

Because SARS-Cov-2 (COVID-19) statistics affect economic policies and political outcomes, governments have an incentive to control them. Manipulation may be less likely in democracies, which have checks to ensure transparency. We show that data on disease burden bear indicia of data modification by authoritarian governments relative to democratic governments. First, data on COVID-19 cases and deaths from authoritarian governments show significantly less variation from a 7 day moving average. Because governments have no reason to add noise to data, lower deviation is evidence that data may be massaged. Second, data on COVID-19 deaths from authoritarian governments do not follow Benford's law, which describes the distribution of leading digits of numbers. Deviations from this law are used to test for accounting fraud. Smoothing and adjustments to COVID-19 data may indicate other alterations to these data and a need to account for such alterations when tracking the disease.

econ.GN↗