arXiv subjects

Giada N. Arney

Publications and source records attributed to Giada N. Arney.

At least 19 recordsLinked to original sources

arXiv2026

The Venus Benchmark: Resolving Degeneracies in Terrestrial Exoplanet Spectra with DAVINCI

The characterization of terrestrial exoplanets with thick, CO$_2$-dominated atmospheres via transmission and emission spectroscopy is limited by degeneracies between atmospheric composition, cloud structure, and surface conditions. These degeneracies are particularly acute for planets in or near the Venus Zone, where sulfuric acid aerosol layers and deep-atmosphere opacity render the lower atmosphere and surface spectroscopically inaccessible via many optical/IR wavelengths. Venus provides the only accessible analog to such worlds, yet current knowledge of its full atmospheric profile relies on decades-old in situ data with known limitations. Here we demonstrate that the forthcoming DAVINCI (Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging) mission will provide the comprehensive, high-fidelity atmospheric profile data necessary to resolve many of these degeneracies. We quantify how atmospheric profile uncertainties translate into uncertainties in modeled transmission and thermal emission spectra of CO$_2$-dominated terrestrial worlds, and show that the spread in the modeled Venus benchmark spectrum arising from current atmospheric profile uncertainties will decrease by factors of $\sim$4--5 for transmission and $\sim$5--15$\times$ for thermal emission after DAVINCI, providing a correspondingly improved benchmark and prior for the modeling of exoplanets with Venus-like atmospheres. We further demonstrate that these improvement factors are larger for the cloud-free atmospheric case, where the opacity floor is set by gas-phase processes rather than aerosols, because the pre-DAVINCI data are most discrepant in the sub-cloud region. Our results highlight the importance of Venus for the atmospheric characterization of rocky exoplanets in the JWST and HWO era, and demonstrate how DAVINCI measurements will directly improve exoplanet atmospheric modeling.

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arXiv2025

Polarized Signatures of the Earth Through Time: An Outlook for the Habitable Worlds Observatory

The search for life beyond the Solar System remains a primary goal of current and near-future missions, including NASA's upcoming Habitable Worlds Observatory (HWO). However, research into determining the habitability of terrestrial exoplanets has been primarily focused on comparisons to modern-day Earth. Additionally, current characterization strategies focus on the unpolarized flux from these worlds, taking into account only a fraction of the informational content of the reflected light. Better understanding the changes in the reflected light spectrum of the Earth throughout its evolution, as well as analyzing its polarization, will be crucial for mapping its habitability and providing comparison templates to potentially habitable exoplanets. Here we present spectropolarimetric models of the reflected light from the Earth at six epochs across all four geologic eons. We find that the changing surface albedos and atmospheric gas concentrations across the different epochs allow the habitable and non-habitable scenarios to be distinguished, and diagnostic features of clouds and hazes are more noticeable in the polarized signals. We also discuss how using Mie scattering for naturally non-spherical particles, which is a common simplification for exoplanet modeling, affects the resulting planetary signals. Finally, our results suggest that pushing the HWO planet-to-star flux contrast limit down to 1 $\times$ 10$^{-13}$ could allow for the characterization in both unpolarized and polarized light of an Earth-like planet at any stage in its history.

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arXiv2024

Venus

After decades of relative neglect, interest in Venus surges anew in the planetary science community and the public. New missions are planned and selected, and will pave the way to the decade of Venus, as new observations allow us to uncover some of the many mysteries our closest Solar System neighbor still harbors. Building on the legacy of past works, here, we discuss the state of our understanding of Venus, from both observation and modeling. We describe each of the envelopes of the planet, from its atmosphere to its interior with an eye for the most recent advances and current topics of interest. We then briefly discuss coupled modelling efforts to better constrain the evolution of the planet. Finally, we describe how the upcoming missions and concepts will further lift the veil on Venus' secrets.

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arXiv2023

Inferring Chemical Disequilibrium Biosignatures for Proterozoic Earth-Like Exoplanets

Chemical disequilibrium quantified via available free energy has previously been proposed as a potential biosignature. However, exoplanet biosignature remote sensing work has not yet investigated how observational uncertainties impact the ability to infer a life-generated available free energy. We pair an atmospheric retrieval tool to a thermodynamics model to assess the detectability of chemical disequilibrium signatures of Earth-like exoplanets, emphasizing the Proterozoic Eon where atmospheric abundances of oxygen-methane disequilibrium pairs may have been relatively high. Retrieval model studies applied across a range of gas abundances revealed that order-of-magnitude constraints on disequilibrium energy are achieved with simulated reflected-light observations at the high abundance scenario and signal-to-noise ratios (50) while weak constraints are found at moderate SNRs (20\,--\,30) for med\,--\,low abundance cases. Furthermore, the disequilibrium energy constraints are improved by modest thermal information encoded in water vapor opacities at optical and near-infrared wavelengths. These results highlight how remotely detecting chemical disequilibrium biosignatures can be a useful and metabolism-agnostic approach to biosignature detection.

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arXiv2023

Two Warm Super-Earths Transiting the Nearby M Dwarf TOI-2095

We report the detection and validation of two planets orbiting TOI-2095 (TIC 235678745). The host star is a 3700K M1V dwarf with a high proper motion. The star lies at a distance of 42 pc in a sparsely populated portion of the sky and is bright in the infrared (K=9). With data from 24 Sectors of observation during TESS's Cycles 2 and 4, TOI-2095 exhibits two sets of transits associated with super-Earth-sized planets. The planets have orbital periods of 17.7 days and 28.2 days and radii of 1.30 and 1.39 Earth radii, respectively. Archival data, preliminary follow-up observations, and vetting analyses support the planetary interpretation of the detected transit signals. The pair of planets have estimated equilibrium temperatures of approximately 400 K, with stellar insolations of 3.23 and 1.73 times that of Earth, placing them in the Venus zone. The planets also lie in a radius regime signaling the transition between rock-dominated and volatile-rich compositions. They are thus prime targets for follow-up mass measurements to better understand the properties of warm, transition radius planets. The relatively long orbital periods of these two planets provide crucial data that can help shed light on the processes that shape the composition of small planets orbiting M dwarfs.

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arXiv2023

A Second Earth-Sized Planet in the Habitable Zone of the M Dwarf, TOI-700

We report the discovery of TOI-700 e, a 0.95 R$_\oplus$ planet residing in the Optimistic Habitable Zone (HZ) of its host star. This discovery was enabled by multiple years of monitoring from NASA's Transiting Exoplanet Survey Satellite (TESS) mission. The host star, TOI-700 (TIC 150428135), is a nearby (31.1 pc), inactive, M2.5 dwarf ($V_{mag} = 13.15$). TOI-700 is already known to host three planets, including the small, HZ planet, TOI-700 d. The new planet has an orbital period of 27.8 days and, based on its radius (0.95 R$_\oplus$), it is likely rocky. TOI-700 was observed for 21 sectors over Years 1 and 3 of the TESS mission, including 10 sectors at 20-second cadence in Year 3. Using this full set of TESS data and additional follow-up observations, we identify, validate, and characterize TOI-700 e. This discovery adds another world to the short list of small, HZ planets transiting nearby and bright host stars. Such systems, where the stars are bright enough that follow-up observations are possible to constrain planet masses and atmospheres using current and future facilities, are incredibly valuable. The presence of multiple small, HZ planets makes this system even more enticing for follow-up observations.

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arXiv2022

Revealing the Mysteries of Venus: The DAVINCI Mission

The Deep Atmosphere Venus Investigation of Noble gases, Chemistry, and Imaging (DAVINCI) mission described herein has been selected for flight to Venus as part of the NASA Discovery Program. DAVINCI will be the first mission to Venus to incorporate science-driven flybys and an instrumented descent sphere into a unified architecture. The anticipated scientific outcome will be a new understanding of the atmosphere, surface, and evolutionary path of Venus as a possibly once-habitable planet and analog to hot terrestrial exoplanets. The primary mission design for DAVINCI as selected features a preferred launch in summer/fall 2029, two flybys in 2030, and descent sphere atmospheric entry by the end of 2031. The in situ atmospheric descent phase subsequently delivers definitive chemical and isotopic composition of the Venus atmosphere during a cloud-top to surface transect above Alpha Regio. These in situ investigations of the atmosphere and near infrared descent imaging of the surface will complement remote flyby observations of the dynamic atmosphere, cloud deck, and surface near infrared emissivity. The overall mission yield will be at least 60 Gbits (compressed) new data about the atmosphere and near surface, as well as first unique characterization of the deep atmosphere environment and chemistry, including trace gases, key stable isotopes, oxygen fugacity, constraints on local rock compositions, and topography of a tessera.

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arXiv2022

Accurate Machine Learning Atmospheric Retrieval via a Neural Network Surrogate Model for Radiative Transfer

Atmospheric retrieval determines the properties of an atmosphere based on its measured spectrum. The low signal-to-noise ratio of exoplanet observations require a Bayesian approach to determine posterior probability distributions of each model parameter, given observed spectra. This inference is computationally expensive, as it requires many executions of a costly radiative transfer (RT) simulation for each set of sampled model parameters. Machine learning (ML) has recently been shown to provide a significant reduction in runtime for retrievals, mainly by training inverse ML models that predict parameter distributions, given observed spectra, albeit with reduced posterior accuracy. Here we present a novel approach to retrieval by training a forward ML surrogate model that predicts spectra given model parameters, providing a fast approximate RT simulation that can be used in a conventional Bayesian retrieval framework without significant loss of accuracy. We demonstrate our method on the emission spectrum of HD 189733 b and find good agreement with a traditional retrieval from the Bayesian Atmospheric Radiative Transfer (BART) code (Bhattacharyya coefficients of 0.9843--0.9972, with a mean of 0.9925, between 1D marginalized posteriors). This accuracy comes while still offering significant speed enhancements over traditional RT, albeit not as much as ML methods with lower posterior accuracy. Our method is ~9x faster per parallel chain than BART when run on an AMD EPYC 7402P central processing unit (CPU). Neural-network computation using an NVIDIA Titan Xp graphics processing unit is 90--180x faster per chain than BART on that CPU.

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arXiv2021

The Fundamental Connections Between the Solar System and Exoplanetary Science

Over the past several decades, thousands of planets have been discovered outside of our Solar System. These planets exhibit enormous diversity, and their large numbers provide a statistical opportunity to place our Solar System within the broader context of planetary structure, atmospheres, architectures, formation, and evolution. Meanwhile, the field of exoplanetary science is rapidly forging onward towards a goal of atmospheric characterization, inferring surface conditions and interiors, and assessing the potential for habitability. However, the interpretation of exoplanet data requires the development and validation of exoplanet models that depend on in-situ data that, in the foreseeable future, are only obtainable from our Solar System. Thus, planetary and exoplanetary science would both greatly benefit from a symbiotic relationship with a two-way flow of information. Here, we describe the critical lessons and outstanding questions from planetary science, the study of which are essential for addressing fundamental aspects for a variety of exoplanetary topics. We outline these lessons and questions for the major categories of Solar System bodies, including the terrestrial planets, the giant planets, moons, and minor bodies. We provide a discussion of how many of these planetary science issues may be translated into exoplanet observables that will yield critical insight into current and future exoplanet discoveries.

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arXiv2021

Claimed detection of PH$_3$ in the clouds of Venus is consistent with mesospheric SO$_2$

The observation of a 266.94 GHz feature in the Venus spectrum has been attributed to PH$_3$ in the Venus clouds, suggesting unexpected geological, chemical or even biological processes. Since both PH$_3$ and SO$_2$ are spectrally active near 266.94 GHz, the contribution to this line from SO$_2$ must be determined before it can be attributed, in whole or part, to PH$_3$. An undetected SO$_2$ reference line, interpreted as an unexpectedly low SO$_2$ abundance, suggested that the 266.94 GHz feature could be attributed primarily to PH$_3$. However, the low SO$_2$ and the inference that PH$_3$ was in the cloud deck posed an apparent contradiction. Here we use a radiative transfer model to analyze the PH$_3$ discovery, and explore the detectability of different vertical distributions of PH$_3$ and SO$_2$. We find that the 266.94 GHz line does not originate in the clouds, but above 80 km in the Venus mesosphere. This level of line formation is inconsistent with chemical modeling that assumes generation of PH$_3$ in the Venus clouds. Given the extremely short chemical lifetime of PH$_3$ in the Venus mesosphere, an implausibly high source flux would be needed to maintain the observed value of 20$\pm$10 ppb. We find that typical Venus SO$_2$ vertical distributions and abundances fit the JCMT 266.94 GHz feature, and the resulting SO$_2$ reference line at 267.54 GHz would have remained undetectable in the ALMA data due to line dilution. We conclude that nominal mesospheric SO$_2$ is a more plausible explanation for the JCMT and ALMA data than PH$_3$.

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arXiv2020

Deep Atmosphere of Venus Probe as a Mission Priority for the Upcoming Decade

This is a white paper submitted to the Planetary Science and Astrobiology Decadal Survey. The deep atmosphere of Venus is largely unexplored and yet may harbor clues to the evolutionary pathways for a major silicate planet with implications across the solar system and beyond. In situ data is needed to resolve significant open questions related to the evolution and present-state of Venus, including questions of Venus' possibly early habitability and current volcanic outgassing. Deep atmosphere "probe-based" in situ missions carrying analytical suites of instruments are now implementable in the upcoming decade (before 2030), and will both reveal answers to fundamental questions on Venus and help connect Venus to exoplanet analogs to be observed in the JWST era of astrophysics.

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arXiv2020

The Hubble Space Telescope's near-UV and optical transmission spectrum of Earth as an exoplanet

We observed the 2019 January total lunar eclipse with the Hubble Space Telescope's STIS spectrograph to obtain the first near-UV (1700-3200 $Å$) observation of Earth as a transiting exoplanet. The observatories and instruments that will be able to perform transmission spectroscopy of exo-Earths are beginning to be planned, and characterizing the transmission spectrum of Earth is vital to ensuring that key spectral features (e.g., ozone, or O$_3$) are appropriately captured in mission concept studies. O$_3$ is photochemically produced from O$_2$, a product of the dominant metabolism on Earth today, and it will be sought in future observations as critical evidence for life on exoplanets. Ground-based observations of lunar eclipses have provided the Earth's transmission spectrum at optical and near-IR wavelengths, but the strongest O$_3$ signatures are in the near-UV. We describe the observations and methods used to extract a transmission spectrum from Hubble lunar eclipse spectra, and identify spectral features of O$_3$ and Rayleigh scattering in the 3000-5500 Å region in Earth's transmission spectrum by comparing to Earth models that include refraction effects in the terrestrial atmosphere during a lunar eclipse. Our near-UV spectra are featureless, a consequence of missing the narrow time span during the eclipse when near-UV sunlight is not completely attenuated through Earth's atmosphere due to extremely strong O$_3$ absorption and when sunlight is transmitted to the lunar surface at altitudes where it passes through the O$_3$ layer rather than above it.

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arXiv2020

Exoplanets in our Backyard: A report from an interdisciplinary community workshop and a call to combined action

This is a white paper submitted to the Planetary Science and Astrobiology Decadal Survey. The Exoplanets in our Backyard meeting was born out of a recognition of the value and potential of interdisciplinary, cross-divisional exoplanet and solar system research, and to encourage and grow the community of researchers working at this intersection. This first-ever inter-assessment group (AG) meeting (organized by members of the Venus Exploration, Outer Planets, and Exoplanet AGs, or VEXAG, OPAG, and ExoPAG, respectively), successfully brought together solar system and exoplanetary scientists from different backgrounds and NASA divisions, fostered communication between researchers whose paths had never crossed at a meeting before, and spurred new collaborations. The meeting was held at the Lunar and Planetary Institute in Houston, TX on February 5-8, 2020 immediately following the OPAG meeting hosted at the same location. The meeting was attended by approximately 110 scientists on site, and 20-30 online participants. The success of this meeting should be capitalized upon and its momentum carried forward to promote fruitful scientific and programmatic discussion, partnerships, and research going forward. This white paper summarizes the meeting, and discusses the findings and action items that resulted.

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arXiv2020

The First Habitable Zone Earth-sized Planet from TESS. I: Validation of the TOI-700 System

We present the discovery and validation of a three-planet system orbiting the nearby (31.1 pc) M2 dwarf star TOI-700 (TIC 150428135). TOI-700 lies in the TESS continuous viewing zone in the Southern Ecliptic Hemisphere; observations spanning 11 sectors reveal three planets with radii ranging from 1 R$_\oplus$ to 2.6 R$_\oplus$ and orbital periods ranging from 9.98 to 37.43 days. Ground-based follow-up combined with diagnostic vetting and validation tests enable us to rule out common astrophysical false-positive scenarios and validate the system of planets. The outermost planet, TOI-700 d, has a radius of $1.19\pm0.11$ R$_\oplus$ and resides in the conservative habitable zone of its host star, where it receives a flux from its star that is approximately 86% of the Earth's insolation. In contrast to some other low-mass stars that host Earth-sized planets in their habitable zones, TOI-700 exhibits low levels of stellar activity, presenting a valuable opportunity to study potentially-rocky planets over a wide range of conditions affecting atmospheric escape. While atmospheric characterization of TOI-700 d with the James Webb Space Telescope (JWST) will be challenging, the larger sub-Neptune, TOI-700 c (R = 2.63 R$_\oplus$), will be an excellent target for JWST and beyond. TESS is scheduled to return to the Southern Hemisphere and observe TOI-700 for an additional 11 sectors in its extended mission, which should provide further constraints on the known planet parameters and searches for additional planets and transit timing variations in the system.

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arXiv2020

The K Dwarf Advantage for Biosignatures on Directly Imaged Exoplanets

Oxygen and methane are considered to be the canonical biosignatures of modern Earth, and the simultaneous detection of these gases in a planetary atmosphere is an especially strong biosignature. However, these gases may be challenging to detect together in the planetary atmospheres because photochemical oxygen radicals destroy methane. Previous work has shown that the photochemical lifetime of methane in oxygenated atmospheres is longer around M dwarfs, but M dwarf planet habitability may be hindered by extreme stellar activity and evolution. Here, we use a 1-D photochemical-climate model to show that K dwarf stars also offer a longer photochemical lifetime of methane in the presence of oxygen compared to G dwarfs. For example, we show that a planet orbiting a K6V star can support about an order of magnitude more methane in its atmosphere compared to an equivalent planet orbiting a G2V star. In the reflected light spectra of worlds orbiting K dwarf stars, strong oxygen and methane features could be observed at visible and near-infrared wavelengths. Because K dwarfs are dimmer than G dwarfs, they offer a better planet-star contrast ratio, enhancing the signal-to-noise (SNR) possible in a given observation. For instance, a 50 hour observation of a planet at 7 pc with a 15-m telescope yields SNR = 9.2 near 1 um for a planet orbiting a solar-type G2V star, and SNR = 20 for the same planet orbiting a K6V star. In particular, nearby mid-late K dwarfs such as 61 Cyg A/B, Epsilon Indi, Groombridge 1618, and HD 156026 may be excellent targets for future biosignature searches.

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arXiv2019

An Ensemble of Bayesian Neural Networks for Exoplanetary Atmospheric Retrieval

Machine learning is now used in many areas of astrophysics, from detecting exoplanets in Kepler transit signals to removing telescope systematics. Recent work demonstrated the potential of using machine learning algorithms for atmospheric retrieval by implementing a random forest to perform retrievals in seconds that are consistent with the traditional, computationally-expensive nested-sampling retrieval method. We expand upon their approach by presenting a new machine learning model, \texttt{plan-net}, based on an ensemble of Bayesian neural networks that yields more accurate inferences than the random forest for the same data set of synthetic transmission spectra. We demonstrate that an ensemble provides greater accuracy and more robust uncertainties than a single model. In addition to being the first to use Bayesian neural networks for atmospheric retrieval, we also introduce a new loss function for Bayesian neural networks that learns correlations between the model outputs. Importantly, we show that designing machine learning models to explicitly incorporate domain-specific knowledge both improves performance and provides additional insight by inferring the covariance of the retrieved atmospheric parameters. We apply \texttt{plan-net} to the Hubble Space Telescope Wide Field Camera 3 transmission spectrum for WASP-12b and retrieve an isothermal temperature and water abundance consistent with the literature. We highlight that our method is flexible and can be expanded to higher-resolution spectra and a larger number of atmospheric parameters.

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arXiv2019

The remote detectability of Earth's biosphere through time and the importance of UV capability for characterizing habitable exoplanets

Thousands of planets beyond our solar system have been discovered to date, dozens of which are rocky in composition and are orbiting within the circumstellar habitable zone of their host star. The next frontier in life detection beyond our solar system will be detailed characterization of the atmospheres of potentially habitable worlds, resulting in a pressing need to develop a comprehensive understanding of the factors controlling the emergence and maintenance of atmospheric biosignatures. Understanding Earth system evolution is central to this pursuit, and a refined understanding of Earth's evolution can provide substantive insight into observational and interpretive frameworks in exoplanet science. Using this framework, we argue here that UV observations can help to effectively mitigate 'false positive' scenarios for oxygen-based biosignatures, while 'false negative' scenarios potentially represent a significant problem for biosignature surveys lacking UV capability. Moving forward, we suggest that well-resolved UV observations will be critical for near-term volume-limited surveys of habitable planets orbiting nearby Sun-like stars, and will provide the potential for biosignature detection across the most diverse spectrum of reducing, weakly oxygenated, and oxic habitable terrestrial planets.

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arXiv2018

Bayesian Deep Learning for Exoplanet Atmospheric Retrieval

Over the past decade, the study of extrasolar planets has evolved rapidly from plain detection and identification to comprehensive categorization and characterization of exoplanet systems and their atmospheres. Atmospheric retrieval, the inverse modeling technique used to determine an exoplanetary atmosphere's temperature structure and composition from an observed spectrum, is both time-consuming and compute-intensive, requiring complex algorithms that compare thousands to millions of atmospheric models to the observational data to find the most probable values and associated uncertainties for each model parameter. For rocky, terrestrial planets, the retrieved atmospheric composition can give insight into the surface fluxes of gaseous species necessary to maintain the stability of that atmosphere, which may in turn provide insight into the geological and/or biological processes active on the planet. These atmospheres contain many molecules, some of them biosignatures, spectral fingerprints indicative of biological activity, which will become observable with the next generation of telescopes. Runtimes of traditional retrieval models scale with the number of model parameters, so as more molecular species are considered, runtimes can become prohibitively long. Recent advances in machine learning (ML) and computer vision offer new ways to reduce the time to perform a retrieval by orders of magnitude, given a sufficient data set to train with. Here we present an ML-based retrieval framework called Intelligent exoplaNet Atmospheric RetrievAl (INARA) that consists of a Bayesian deep learning model for retrieval and a data set of 3,000,000 synthetic rocky exoplanetary spectra generated using the NASA Planetary Spectrum Generator. Our work represents the first ML retrieval model for rocky, terrestrial exoplanets and the first synthetic data set of terrestrial spectra generated at this scale.

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