The Roman Space Telescope (formerly WFIRST) is a NASA flagship mission currently under construction. One of its primary goals is to conduct a search for exoplanets using microlensing technique. This search will discover thousands of exoplanets with parameters that were not achivable for Kepler satellite. I will present a package that is aimed to be used for analysis of Roman microlensing data - MulensModel. This package is already allows deriving main parameters of exoplanets from simulated Roman data. Further MulensModel development will be discussed.

VBBinaryLensing is a library written in C++ and importable in Python for computation of microlensing light curves and astrometric shifts generated by single and binary/planetary lenses. It is based on contour integration optimized with several advanced methods. Higher order effects such as parallax, orbital motion and xallarap are also included. VBBinaryLensing has been adopted by several user-friendly microlensing modeling platforms and in the pipeline of the future Roman mission.

JWST offers high-contrast coronagraphic imaging in the near-IR (with NIRCam) and in the mid-IR (with MIRI) for the detection and characterization of exoplanets and circumstellar disks. spaceKLIP applies PCA-based PSF subtraction techniques based on the popular pyKLIP package to JWST coronagraphy data. It provides routines to compute contrast curves and forward model companion PSFs based on contemporary wavefront maps (obtained from MAST) for deriving accurate companion photometry and astrometry. spaceKLIP also enables reducing the raw (uncal) JWST data using the official JWST data reduction pipeline with several custom modifications to improve the quality of high-contrast imaging reductions and to better prepare the data for the KLIP workflow. Future upgrades will include the processing of non-coronagraphic imaging data, e.g., from NIRCam or NIRISS.

VIP (Vortex Image Processing) is a Python package providing the tools to reduce, post-process and analyze high-contrast imaging datasets, enabling the detection and characterization of directly imaged exoplanets, circumstellar disks, and stellar environments. It is a collaborative project which started at the University of Liège, aiming to integrate open-source, efficient, easy-to-use and well-documented implementations of state-of-the-art algorithms used in the context of high-contrast imaging. Since the first publication of the package (Gomez Gonzalez et al. 2017), a number of changes (new algorithms, new options, tutorials, etc.) have been made to the package, which will be summarized in this presentation (see also Christiaens et al. 2023).

EXOSIMS is an open source software framework for the simulation and analysis of space-based exoplanet imaging missions, which has been in active development since 2015. We present EXOSIMS's design philosophy and capabilities, as well as future development plans. We also discuss the particular challenges associated with maintaining this type of software, explicitly designed to serve multiple different external projects and communities, and the strategies the EXOSIMS team has adopted to ensure the project's continued success.

Eureka! is a data reduction and analysis pipeline for exoplanet time-series observations, with a particular focus on James Webb Space Telescope (JWST) data. The goal of Eureka! is to provide an end-to-end pipeline that starts with raw, uncalibrated FITS files and ultimately yields precise exoplanet transmission and/or emission spectra. The pipeline has a modular structure with six stages, and each stage uses a "Eureka! Control File" (ECF; these files use the .ecf file extension) to allow for easy control of the pipeline's behavior. We provide template ECFs for the MIRI, NIRCam, NIRISS, and NIRSpec instruments on JWST and the WFC3 instrument on the Hubble Space Telescope (HST). These templates give users a good starting point for their analyses, but Eureka! is not intended to be used as a black-box tool, and users should expect to fine-tune some settings for each observation in order to achieve optimal results. At each stage, the pipeline creates intermediate figures and outputs that allow users to compare Eureka!'s performance using different parameter settings or to compare Eureka! with an independent pipeline. Here we present a stage-by-stage breakdown of the Eureka! pipeline and its basic functionalities as well as the resources available to the community so they may further familiarize themselves with Eureka! and its uses.

In a recent ApJL by Corrales & Gavilan et al. (2023), we showcase opacities for three sets of lab-grown tholins formed in different C/O ratio environments. The optical constants and resulting cross-sections are publicly available on Zenodo in ascii and FITS formats. I will present the general spectroscopic properties of the tholins and their effects on a model GJ 1214b transmission spectrum. These optical properties provide a necessary advancement over the templates available from Khare et al. 1984, and are particularly well-suited for modeling the observable properties of terrestrial planetary atmospheres. I will discuss the format of our data products and invite community feedback for making the data products most useful for incorporation into open source simulation tools.

In Cycle 1, JWST will be taking spectra for over 70 different transiting planets at a variety of sizes and temperatures, in transit and at secondary eclipse. In order to simplify the process of knowledge extraction and initial comparison to models, I have been working to create a variety of atmosphere models and spectra for each of the exoplanets that are set to be observed in cycle 1. For each planet, I use the Planetary Intensity Code for Atmospheric Spectroscopy Observations (PICASO) code, an open-source 1D python model, to create a mini-grid of model atmospheres and spectra. I examine the role of changing metallicity, C/O ratio, energy redistribution, and other factors. These simulations will serve an important baseline, both for the initial comparison to JWST spectra, and as a starting point to more detailed models, which may include non-equilibrium chemistry or dynamics. These models will be posted online as a community resource for the initial comparison to JWST spectra.

The recent progress in observational capabilities of exoplanets has increased the requirements of theoretical models in terms of accuracy and robustness. A number of models are thus turning to multi-dimensional simulations to that aim. Pytmosph3R is an open-source Python package that can generate synthetic emission and transmission spectra using 3D atmospheric simulations (such as GCMs). It is designed as a post-process tool which offers the possibility of changing atmospheric properties (temperature, composition) before the computation of the spectrum. Pytmosph3R has been used in a number of studies (Caldas et al. 2019, Falco et al. 2022, Pluriel et al. 2022, McDonald et al. 2022) and in hands-on sessions or summer schools (ARES school, tutorials). Future developments include the computation of lightcurves, phasecurves, with the inclusion of rotation effects such as the Doppler shift, and limb darkening.

Over the past two decades, atmospheric characterization of exoplanets and brown dwarfs has been dramatically increasing - particularly, observations with HST, Spitzer, and various ground-based telescopes both with low to moderate-resolution spectroscopy and high-resolution cross-correlation approaches. Additionally, with the Transiting Exoplanet Survey Satellite (TESS), in conjunction with the launch of the James Webb Space Telescope (JWST), we can expect hundreds of planet detections followed by detailed spectroscopic characterization of their atmospheres. The compositional and temperature diversity of these worlds provide a unique opportunity to gain insight into planetary atmospheric chemical processes and formation pathways. One of NASA's primary goals is to observationally characterize exoplanet atmospheres, understand the chemical and physical processes of exoplanets and improve the understanding of the origins of exoplanetary systems. In the coming decade, starting with JWST, we will work towards achieving these goals by interpreting a diverse set of exoplanet atmosphere observations, ranging from hot gas giants to small temperate rocky worlds. Our understanding and interpretation of this full gamut of data will hinge on our ability to link observations to theoretical models, and then our ability to link those models to fundamental molecular and atomic opacities. Opacities serve as a fundamental input to all models used for exoplanet atmospheric characterization. The limitation of pressure-broadening data in the current opacities for HST/JWST resolutions, as well as the critical need for accurate spectral line position for cross-correlation technique could lead to serious uncertainties and biases on the observables including uncertainty in the C/O ratio, thermal structure, and atmospheric composition. Hence, a thorough assessment of opacities is instrumental to achieving a full understanding of exo-atmospheres across several measurement techniques. In this talk, we will give an overview of the current status of a set of key atmospheric absorbers relevant to late-type stellar, brown dwarf, and planetary atmospheres, to give the community intuition for selecting line lists for different measurement techniques. For example, H2O has four different "current" opacities which have different line positions, intensities, and transitions. We will discuss their impact on low-to-medium resolution HST/JWST spectroscopy and cross-correlation functions to illustrate the importance of opacity choices. We will focus on molecules that have been the subject of recent observation campaigns. This includes the noticeable disagreements between different TiO and VO line lists and their impact on synthetic emission/transmission spectra, as well as CH4 and FeH. In sum, an overview of the current challenges in opacity data and their practical influence on radiative transfer modeling will be outlined, and motivated. Lastly, our team's endeavors at NASA Ames research center to leverage these disagreements and concerns on opacity data and the lack of sufficient pre-computed and evaluated datasets will be addressed. Our comprehensive opacity database, MAESTRO, will be introduced as a means to alleviate community access to opacities.

We present the second generation of ROCKE-3D (Resolving Orbital and Climate Keys of Earth and Extraterrestrial Environments with Dynamics), a generalized 3-dimensional General Circulation Model (GCM) for use in Solar System and exoplanetary simulations of rocky planet climates. ROCKE-3D version 2.0 is a descendant of ModelE2.1, the flagship GCM of the NASA Goddard Institute for Space Studies (GISS) used in the most recent Intergovernmental Panel for Climate Change (IPCC) assessments. ROCKE-3D is a continuous effort to expand the capabilities of GISS ModelE to handle a broader range of atmospheric conditions, including different atmospheric planet sizes, gravities, pressures, rotation rates, more diverse chemistries and atmospheric compositions, diverse ocean and land distributions and topographies, and potential basic biosphere functions. In this release we present updated physics, and many more supported configurations which can serve as starting points to simulate the atmospheres of rocky terrestrial planets of interest. Two different radiation schemes are supported, the GISS radiation, valid only for atmospheres similar to that of modern Earth, and SOCRATES, which is more generalized but more computationally expensive. Three different atmospheric composition options are supported (preindustrial Earth, the atmosphere used in ROCKE-3D 1.0, and an anoxic atmosphere with no aerosols), three ocean configurations (prescribed, Q-flux, and dynamic), and two resolutions: the medium resolution (4x5 degrees in latitude and longitude, previously used in ROCKE-3D 1.0), and the fine resolution, which has double the resolution in the atmosphere and 4 times the horizontal and 3 times the vertical resolution in the ocean. Finally, for the land surface hydrology, we have introduced generalized physics for arbitrary topography in the pooling and evaporation of water and river transport of water between grid cells, and for the vertical stratification of temperature in dynamic lakes. We quantify how the different component choices affect model results, and discuss strengths and limitations of using each component, together with how one can select which component to use. ROCKE-3D is publicly available and tutorial sessions are available for the community, greatly facilitating its use by any interested group.

New-generation spectrographs dedicated to the study of exoplanetary atmospheres, require a higher precision in the atmospheric models to better interpret the new spectra. Thanks to future space missions like JWST, ARIEL and Twinkle, indeed, the observed spectra will be precise enough to reveal features which cannot be modeled with a one-dimensional plane parallel atmosphere, especially in the case of Ultra Hot Jupiters. Bayesian frameworks are computationally intensive and prevent us from using complete three-dimensional self-consistent models to retrieve an exoplanetary atmosphere, and, they constrain us to use simplified models to converge to a set of atmospheric parameters. We propose the TauREx2D retrieval code, which uses two-dimensional atmospheric models as a good compromise between computational power and model precision to better infer exoplanetary atmospheres. Finally, we apply such a model on synthetic spectrum computed from a GCM simulation of WASP-121b and show the parameters retrieved bythe new TauREx 2D retrieval code.

The characterization of a diverse set of atmospheres, ranging from brown dwarfs to hot gas giants to small temperate rocky worlds will be part of the legacy of JWST and future NASA missions. These technological innovations will enable a plethora of discoveries, unveiling a variety of new chemical and physical regimes that could even point to the first detection of life beyond Earth. However, our ability to fully interpret these results hinge on how well we can link observations to complex theoretical models that describe, for example, the chemistry and climate. These kinds of models have immense potential to enable transformative discoveries, but only if the broader community has unfettered access to them, as well as the data they rely on. Here, I will talk about the developments we have made to model the climate, clouds, and spectra of exoplanets and brown dwarfs. I will also talk about the steps we have taken to ensure our software supports the principles of findability, accessibility, interoperability, and reusability.

Mission development studies often need rapid assessments of detection feasibility, especially as related to proposed instrument specifications. Originally designed to enable the HabEx and LUVOIR concept studies, rfast is a publicly-available, Python-based tool for rapidly exploring planetary spectra and atmospheric retrievals. Using a simple collection of commands, users can simulated a noise-free spectrum of a world, add instrument noise to generate a faux observations, and perform inverse analysis to understand how the spectral and noise properties map to atmospheric and planetary constraints. The rfast tool can be applied to transit, emission, and reflected-light spectra, and can be run on a personal laptop or small number of cluster cores.

ExoCAM is an independently curated exoplanet branch of the National Center for Atmospheric Research Community Earth System Model (CESM), version 1.2.1. ExoCAM has been used for studying the Earth through time, and the atmospheres of terrestrial extrasolar planets around a variety of stars. Here we describe ExoCAM and what makes it unique from standard configurations of CESM. In this presentation I will briefly review how the code is structured, supported configurations, metrics on community use, as well in progress model development efforts as we blaze on towards an ExoCAM 2.0.

Observations of extrasolar planetary systems have revealed a wide diversity of properties. This makes it necessary to understand how the processes thought to shape Earth's atmospheric composition might operate on exo-Earths (here defined as terrestrial planets with surface liquid water) whose size and bulk composition may differ. As a first step, the ExoCcycleGeo code allows investigation of how variations in planet size and the chemical (mineral) composition of its upper mantle and surface affects key processes involved in the carbonate-silicate cycle, which is thought to have regulated the composition of Earth's atmosphere and its surface temperature over its geological history. ExoCcycleGeo couples a simple model of thermal evolution with widely used geochemical codes, called as subroutines, that compute solid-melt equilibria for silicate rocks (MELTS) and equilibria and kinetics of water-rock interactions (PHREEQC). Outputs include, as a function of geologic time: reservoirs and fluxes of carbon; mantle temperature and convective velocity; lithospheric heat flux and thickness; surface pressure, temperature, and mixing ratios of CO2, N2, H2O, CH4, and O2; rainwater, river, and ocean pH; ocean redox; and detailed river and ocean compositions such as abundances of key soluble species (Na, Mg, Ca, Cl, sulfate, Fe, Si, oxidized and reduced carbon species, etc.). The code's calculations of outgassing and weathering fluxes are validated against modern and Archean Earth conditions. The source in C language is available at https://github.com/MarcNeveu/ExoCcycleGeo.

The community uses a variety of models to characterize the interior structure of small planets. Underlying these models are multiple computational techniques, numerous experimental measurements and theoretical estimates of the equations of state for planet-building materials, and differing treatments of temperature. MAGRATHEA is an open-source interior structure solver which can be customized to user-defined planet models. Our code features adaptable phase diagrams for the core, mantle, hydrosphere, and atmosphere and transparent storage for equations of state. I will demonstrate how the community can use and contribute to the code.

Magma ocean might exist in the dayside of tidally-locked planets where the temperature could exceed the melting temperature of solid silicates. Many previous studies suggest that the magma ocean depth can reach tens of to hundreds of kilometers by assuming adiabatic or vertically constant temperature profiles. The effect of ocean dynamics has not been considered yet. In our study, we try to simulate the magma ocean depth using a 2D(x-z) Matlab model written by ourselves. Our simulation results show that the magma ocean depth considering ocean dynamics is much shallower than that not considering within-pool ocean overturning circulation. Consistent to the scaling theory, the magma ocean depth is strongly determined by the magnitude of vertical diffusivity. The effect of wind stress is evident only when the wind stress is hundreds to thousands of times that on Earth, which could make the magma ocean depth even shallower.

The extreme ultraviolet photons incident on an exoplanet become deposited in its upper atmosphere. The most energetic of these photons eject one or more electrons from the heavy particles in the gas. The nascent photoelectrons carry away as kinetic energy the excess of the photon energy over the ionization threshold, and can induce transformations in the gas that are often inhibited for thermal electrons. The transformations include excitation and ionization of atoms and molecules, which affect the detectability of these gases and constrain the fraction of incident stellar radiation that transforms into heat and may therefore affect the long-term stability of the atmosphere. We have built a Monte Carlo model that solves the slowing down of photoelectrons in a gas with arbitrary amounts of H, He and O atoms, and thermal electrons. The novel multi-score scheme differs from other Monte Carlo approaches in that it efficiently handles rare collisional channels, as in the case of low-abundance excited atoms that undergo superelastic and inelastic collisions. The Monte Carlo model, which is freely available, has been extensively demonstrated in a recent paper (https://doi.org/10.1016/j.icarus.2022.115373). The presentation will focus on the working principles of the Monte Carlo model and its possibilities to investigate the atmospheres of exoplanets.

The photoevaporation model is one of the leading explanations for the evolution of small, close-in planets and the origin of the radius-valley. However, without planet mass measurements, it is challenging to test the photoevaporation scenario. EvapMass predicts the minimum masses of planets in multi-planet systems using the photoevaporation-driven evolution model. The planetary system requires both a planet above and below the radius gap to be useful for this test. EvapMass can be used to identify transiting systems that warrant radial-velocity follow-up to further test the photoevaporation model. In this talk, I will walk you through the physics of the problem and how you can use EvapMass to test any multitransiting system for photoevaporation.

In planetary magnetospheres, charged particle distributions are often solved from kinetic equations in the form of a diffusion equation (Fokker-Planck equation) or an advection-diffusion equation using various curvilinear coordinates of physical convenience. Solving these equations is usually not a trivial task. In this presentation, we introduce a numerical solver that can solve the general form of an advection-diffusion equation in arbitrarily provided coordinate systems in multiple dimensions, with user-specified boundary geometry, boundary conditions, and equation terms. The solver is based upon the mathematical theory of stochastic differential equations, whose computational accuracy and efficiency are greatly enhanced by specially designed adaptive algorithms and variance reduction technique. The solver also applies to problems with jumping particle transport. Versatility and robustness of the solver is exhibited in example problems. The solver is an open-source software, and is publicly available from GitHub and GSFC-EMAC repository.

Software is an integral enabler of observation, experiment, theory, and computation and a primary modality for realizing discoveries and innovations. The ongoing explosion of activity in multi-messenger astronomy powers theoretical and computational developments, in particular the evolution of the community-driven software instrument Modules for Experiments in Stellar Astrophysics (MESA) for research and education. We will share how and why MESA established a dominant international market position, probable future directions for the MESA project, and the more general relationship between money and sustainability for community-driven, open-knowledge software instruments that enable transformative research.

PyLightcurve is an open-source python package dedicated to the modelling of exoplanet transit and eclipse light-curves. The aim of the package it to provide an integrated and user-friendly framework to analyse light-curves of exoplanets. It offers flexible fitting of multi-epoch and multi-colour light-curves, allowing for custom de-trending. Moreover, PyLightcurve includes wrappers for: ExoTETHyS (for easy calculation of limb-darkening coefficients for photometric and spectroscopic instruments); the Exoplanet Characterisation Catalogue, developed and maintained by the ExoClock project (for easy access to validated and up-to-date transit parameters); and SIMBAD (for easy access to stellar parameters). In PyLightcurve, the integration of the planetary orbit and of the stellar flux are performed in a fully vectorised way, allowing for efficient scaling-up even for more complex limb-darkening law (4-coefficient). With this implementation, the transit model can also be used in deep learning applications, through the pylightcurve-torch package, developed in Pytorch, which also offers GPU compatibility.

In recent years the number of planets, in which atmospheric signatures were detected using space and ground-based telescopes, grew significantly. I would like to present ExoAtmospheres - IAC community database for exoplanet atmospheric observations. The Exoplanet Atmospheres Database is built for the community and maintained by the community. Exoplanet atmospheres is an exciting and vibrant field of research, where new discoveries and publications occur at a very fast pace, and it is easy to miss many interesting results. The main purpose of ExoAtmospheres is to become an easy tool to quickly find out how many planets of a given type have had their atmospheres characterized. It is also a great tool to easily explore the bibliography on your specific research subject. The main purpose of this database is to become a quick and useful repository of all available exoplanet atmospheres observations, and also to help in the gathering of useful references for a given planet or planet types.

In the field of exoplanetary science, observations often lead to 2D images, reduced into photometric and spectroscopic time-series later analysed to characterise exoplanetary systems. To process these images, scientists generally make use of pipelines: a set of processing units sequentially executed on each image before being combined into exploitable products. While requiring a large effort, pipelines developed by scientists are usually instrument-specific, poorly maintainable, and yield products suffering from a low-level of reproducibility and portability. In this talk I present prose, a Python package allowing scientists to build robust, modular and transparent pipelines, focusing on what matters. By providing a set of pre-implemented blocks, one can easily assemble and test processing sequences, and only develop the blocks they need. This approach not only yields reproducible tools, it allows for rapid iteration towards pipelines with optimal scientific products. I will present the main concepts behind prose, and its use in various projects, among which are the TESS follow-up effort from the TRAPPIST telescope, the photometric pipeline of the ASTEP telescope (searching for transits from Antartcica), and the measurement of a planetary transmission spectrum from Hubble spectroscopic observations.

PyTransit is a transit modeling library aiming to make modeling complex heterogeneous light curve data sets in CPU and GPU fast and easy. The package has been under continuous development since 2009 and in “production” use since 2010. Some of its recent new features include a transit model capable of using any radially symmetric function to model stellar limb darkening while still being faster to evaluate than the analytical transit model for quadratic limb darkening, and significantly accelerated orbit computation routines. In this presentation I briefly introduce PyTransit, some of its more advanced features, and new features that will be added in the near future.

I will describe the kima package, and how it has been used to detect some of the lightest exoplanets in high-precision data from the ESPRESSO spectrograph. The code allows for a principled and robust statistical analysis of radial velocity datasets. In particular, it estimates the posterior distribution for the number of detected planets and allows for stellar activity models based on Gaussian processes, including the use of activity indicators for additional information.

Exoplanet Watch's EXOplanet Transit Interpretation Code (EXOTIC) is a Python 3 package for analyzing photometric data of transiting exoplanets into lightcurves and retrieving transit epochs and planetary radii. EXOTIC relies upon the transit method for exoplanet detection. This method detects exoplanets by measuring the dimming of a star as an orbiting planet transits, which is when it passes between its host star and the Earth. If we record the host star's emitted light, known as the flux, and observe how it changes as a function of time, we should observe a small dip in the brightness when a transit event occurs. A graph of host star flux vs. time is known as a lightcurve, and it holds the key to determining how large the planet is, and how long it will be until it transits again.

Stellar photometric variability and instrumental effects, like cosmic ray hits, data discontinuities, data leaks, instrument aging etc. cause difficulties in the characterization of exoplanets and have an impact on the accuracy and precision of the modelling and detectability of transits, occultations and phase curves. This work aims to make an attempt to improve the transit, occultation and phase-curve modelling in the presence of strong stellar variability and instrumental noise. We invoke the wavelet-formulation to reach this goal. We explore the capabilities of the software package Transit and Light Curve Modeller (TLCM). It models the RV-curve + light curve: transit, occultation, beaming, ellipsoidal and reflection effects in the light curves (including the gravity darkening effect, too). The red-noise, the stellar variability and instrumental effects are modelled via wavelets. The wavelet-fit is constrained by prescribing that the final white noise level must be equal to the average of the uncertainties of the photometric data points. This helps to avoid the overfit and regularizes the noise model. The approach was tested by injecting synthetic light curves into Kepler's short cadence data and then modelling them. We give limits in terms of signal-to-noise ratio for every studied system parameter which is needed to accurate parameter retrieval. The wavelet-approach is able to manage and to remove the impacts of data discontinuities, cosmic ray events, long-term stellar variability and instrument ageing, short term stellar variability and pulsation and flares among others. Precise light curve models combined with the wavelet-method and with well prescribed constraints on the white noise are able to retrieve the planetary system parameters, even when strong stellar variability and instrumental noise including data discontinuities are present.

The Planetary Spectrum Generator is a free-to-use tool that can synthesize exoplanet's transmission and emission spectra. It includes a 3D ephemeris calculator that interfaces with NASAs Exoplanet Archive to obtain geometric parameters to compute spectroscopic fluxes. The atmospheric and surface compositions can be specified or adopted from templates. Finally, the noise calculator enables realistic simulations of different observatories and instruments. In this talk, we explain the different modules of PSG and highlight some of the work that has been done using the tool.

In this talk we will introduce the atmos model, explain its capabilities, and discuss exciting new improvements coming soon.

Panelists:

• NASA HQ - Steve Crawford
• NSF - Martin Still
• CUNY - Kelle Cruz

Future direct imaging missions aiming to detect and characterize Earth-like planets around Sun-like stars may encounter a "confusion" problem when imaging a multi-planet system. Previous work has shown that planets in multi-planet systems can be “confused” in direct images taken over multiple epochs due to lack of prior knowledge about the planet's orbital parameters or planetary characteristics. Here, we consider a system to be confused when it has multiple possible orbit combinations for the planets that describe the data equally well and it's not obvious which detection belongs to which planet. We address the confusion problem with a publicly available "deconfusion" algorithm, which leverages astrometric information to fit orbits to planets and help differentiate between multiple planets in an image. The deconfusion algorithm accepts unlabeled planet detections with astrometric information and generates orbit matches. The matches are ranked based on their consistency with the presented data and the number of matched observations. We also introduce the inclusion of photometric considerations in the deconfusion algorithm to help differentiate between possible orbits. We are investigating the utility of orbital phase information for each planet in simulated planetary systems to reduce the rate of confusion in a multi-planet system. We aim to ultimately provide updated estimated confusion rates for planetary systems and a useful tool for direct imaging surveys.

I will give an overview of EXOFASTv2 and detail one of its major advantages: the simultaneous modeling of the star and planet(s). It has long been understood that the light curve of a transiting planet constrains the density of its host star. That fact is routinely used to improve measurements of the stellar surface gravity and has been argued to be an independent check on the stellar mass. I'll discuss how the stellar density from a transit light curve can also provide meaningful constraints on the radius and effective temperature of the star. This additional constraint is especially significant when we account for systematic errors in stellar modeling, but only when the planet, star, and systematic floors are simultaneously modeled.

We present allesfitter: an open-source astronomical software for modeling photometric and radial velocity data that can be used to characterize a gravitationally bound system of stars and planets including phenomena such as transits, flares, and spots. We highlight the capabilities of allesfitter and benchmark its performance by illustrating its use on a few confirmed exoplanetary systems. Given some time-series data, allesfitter takes fair samples from the posterior and enables robust model selection via Bayesian evidence. As the field of transiting exoplanets enters an era of detailed characterization following the successful Kepler and TESS surveys, allesfitter will remain a versatile community tool for modeling high-precision photometry from missions such as JWST, CHEOPS, and Pandora as well as all ongoing and upcoming precise radial velocity surveys.