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NASA NTRS2020

Validation of Carbon Trace Gas Profile Retrievals from the NOAA-Unique Combined Atmospheric Processing System for the Cross-Track Infrared Sounder

This paper provides an overview of the validation of National Oceanic and Atmospheric Administration (NOAA) operational retrievals of atmospheric carbon trace gas profiles, specifically carbon monoxide (CO), methane (CH4) and carbon dioxide (CO2), from the NOAA-Unique Combined Atmospheric Processing System (NUCAPS), a NOAA enterprise algorithm that retrieves atmospheric profile environmental data records (EDRs) under global non-precipitating (clear to partly cloudy) conditions. Vertical information about atmospheric trace gases is obtained from the Cross-track Infrared Sounder (CrIS), an infrared Fourier transform spectrometer that measures high resolution Earth radiance spectra from NOAA operational low earth orbit (LEO) satellites, including the Suomi National Polar-orbiting Partnership (SNPP) and follow-on Joint Polar Satellite System (JPSS) series beginning with NOAA-20. The NUCAPS CO, CH4, and CO2 profile EDRs are rigorously validated in this paper using well-established independent truth datasets, namely total column data from ground-based Total Carbon Column Observing Network (TCCON) sites, and in situ vertical profile data obtained from aircraft and balloon platforms via the NASA Atmospheric Tomography (ATom) mission and NOAA AirCore sampler, respectively. Statistical analyses using these datasets demonstrate that the NUCAPS carbon gas profile EDRs generally meet JPSS Level 1 global performance requirements, with the absolute accuracy and precision of CO 5% and 15%, respectively, in layers where CrIS has vertical sensitivity; CH4 and CO2 product accuracies are both found to be within ±1%, with precisions of ≈1.5% and ⪅0.5%, respectively, throughout the tropospheric column.

satellite cal/val; error analysis; greenhouse gase↗
NASA NTRS2021

Radar-Based Bayesian Estimation of Ice Crystal Growth Parameters within a Microphysical Model

The potential for polarimetric Doppler radar measurements to improve predictions of ice microphysical processes within an idealized model–observational framework is examined. In an effort to more rigorously constrain ice growth processes (e.g., vapor deposition) with observations of natural clouds, a novel framework is developed to compare simulated and observed radar measurements, coupling a bulk adaptive-habit model of vapor growth to a polarimetric radar forward model. Bayesian inference on key microphysical model parameters is then used, via a Markov chain Monte Carlo sampler, to estimate the probability distribution of the model parameters. The statistical formalism of this method allows for robust estimates of the optimal parameter values, along with (non-Gaussian) estimates of their uncertainty. To demonstrate this framework, observations from Department of Energy radars in the Arctic during a case of pristine ice precipitation are used to constrain vapor deposition parameters in the adaptive habit model. The resulting parameter probability distributions provide physically plausible changes in ice particle density and aspect ratio during growth. A lack of direct constraint on the number concentration produces a range of possible mean particle sizes, with the mean size inversely correlated to number concentration. Consistency is found between the estimated inherent growth ratio and independent laboratory measurements, increasing confidence in the parameter PDFs and demonstrating the effectiveness of the radar measurements in constraining the parameters. The combined Doppler and polarimetric observations produce the highest-confidence estimates of the parameter PDFs, with the Doppler measurements providing a stronger constraint for this case.

Robert S. Schrom↗
NASA NTRSDate not supplied

Osiris-Rex Post-Tag Observation Trajectory Design and Navigation Performance

NASA’s OSIRIS-REx spacecraft successfully collected a sample of asteroid regolith from the surface of near-Earth asteroid Bennu in October of 2020. Subsequent imaging of the sampler head showed material leaking from the collection mechanism, thus stowage of the sample precluded execution of any planned maneuvers in the following days. Optical navigation imaging also ceased in the days following sample collection. The desire to image the sample site to investigate the results of the spacecraft-to-surface interaction led to the Navigation team designing a trajectory to return to Bennu after several months in order to image the surface one final time. After several iterations a trajectory design was created that satisfied the numerous constraints that were levied in order to place utmost importance on the safety of the spacecraft and stowed sample, while also closely emulating previously obtained imaging conditions to provide a close comparison of site pre- and post-contact. Significant analysis was necessary in order to reliably reacquire the asteroid after several months without optical navigation imagery. The final design required five maneuvers to return the spacecraft to Bennu and perform a final flyby of the asteroid at a distance of 3.8 kilometers. Successful execution of the phase provided key insights regarding the performance of the sample collection activities and the subsurface composition of the asteroid.

Daniel R Wibben↗
NASA NTRS2021

The Dual-Rasp Sampling System Design with Closed Pneumatic Sample Transfer

The novel Dual-Rasp sampling system has been developed for landed missions to low gravity planetary bodies and is particularly well suited for the unique environment of Saturn’s moon Enceladus. The Dual-Rasp sampling system has two counter-rotating rasp cutters that remove material from the surface and direct it into a guide. The cuttings follow the guide into a sample collection cup. When the sampling collection completes, the tool reconfigures by rotating the guide to create a closed circuit for pneumatic sample transfer from the collection cup to science instruments on the lander. A valve opens a gas tank and the gas flows from that tank into the sample collection cup and down rigid tubing to the science instruments chamber on the lander. A two degree of freedom arm with base actuators is used to deploy the sampler and control its sampling location.

Heness, Andrew B.↗
NASA NTRSDate not supplied

Adding GPU Support to the Markov Chain Monte Carlo Code Catmip

In geophysics, we are confronted with many under-determined inverse problems. For example, all of our observations of earthquakes are made at the Earth’s surface. So, when we try to infer how slip during an earthquake evolves in space and time, we find that there are many potential slip histories that are consistent with our limited observations and our understanding of earthquake physics. One way to approach these problems is with Bayesian analysis which allows us to infer the ensemble of all potential slip models that satisfy the observations and our prior knowledge of earthquake physics. In Bayesian analysis, our prior knowledge is known as the prior probability density function or prior PDF, the fit to the data is known as the data likelihood, and the target PDF that satisfies both the prior PDF and data likelihood is known as the posterior PDF. However, simulating the posterior PDF typically requires using Markov Chain Monte Carlo (MCMC) to draw tens of billions of random realizations of earthquake slip models, which may not be computationally feasible. To make this and similar geophysical inversions computationally tractable, we developed the Cascading Adaptive Transitional Metropolis In Parallel (CATMIP) algorithm. CATMIP is an efficient parallel Markov Chain Monte Carlo (MCMC) sampler that is used for model fitting and uncertainty quantification in geophysics. Example use cases are earthquake rupture modeling, determining mineral composition on Mars, reconstructing the history of ocean salinity, and historical earthquake relocation. CATMIP employs many parallel instances of the Metropolis algorithm for sampling in a transitioning framework. Transitioning is a process in which a set of random samples at equilibrium with a known probability density function (PDF) are used as seeds for the Markov chains to sample successive target PDFs that incrementally move the distribution from the starting seeds to the final desired PDF that describes the relative plausibility of potential values for the model parameters. The algorithm is implemented as a Master-Worker model employing MPI for communication. The worker processes are loosely coupled with global parameters periodically optimized by the master process. This provides a very high amount of parallelism with little communication between updates. During the presentation we will discuss the history of the algorithm and elaborate the earthquake rupture modeling use case for the CATMIP package. Our first step toward GPU optimization was to optimize the code for the CPU. CPU profiling revealed that most of the compute time is spent in calls to level 2 BLAS routines and calls to GSL random number generators. We revised the algorithm to employ level 3 BLAS routines instead. In our presentation we will describe how this was accomplished. Adding GPU support to CATMIP consisted mostly of replacing the calls to GSL with calls to GPU vendor-provided library routines. A small number of loops were directly implemented in CUDA. In the presentation will provide implementation details. Finally, we will discuss methods for profiling and opportunities for further optimizing GPU execution. By creating a code with the flexibility to run on either a CPU or GPU architecture, CATMIP can be used on systems ranging from large CPU-based HPC environments to single servers with GPU acceleration and everything in between.

HECC↗
NASA NTRSDate not supplied

A Study of the Curation Protocol by Sample Analysis Working Team (SAWT) in Martian Moons eXploration (MMX) Project

Japan Aerospace Exploration Agency (JAXA) will launch a spacecraft in 2024 for a sample return mission from Phobos (Martian Moons eXploration: MMX). The major scientific goals of MMX are to constrain (1) the origin of Phobos and Deimos and (2) the evolution of the Mars-moon system [1]. The touchdown operations are planned to be performed twice at different landing sites on the Phobos surface to collect > 10 g of the surface materials [2]. After the return to the Earth, the Phobos samples will be collected from the individual sample canisters and introduced to the clean chamber installed at ISAS (Institute of Space and Astronautical Science). The Sample Analysis Working Team (SAWT) of MMX designed the procedure of Phobos sample analysis mainly conducted by the initial analysis teams [3]. For the next step, the SAWT will define the procedure of the curation process (mostly non-destructive analysis) of the Phobos samples, which will be presented here. The protocols of the Phobos sample curation is illustrated in figure 1. First, the headspace gas from the sample container will be collected during the Quick Analysis phase. The Quick Analysis will be operated by the sampler and curation teams in ISAS/JAXA. The terrestrial leak and contamination from the sampling systems will be tested using a quadrupole mass spectrometer equipped with a gas sampling system. Second, the bulk Phobos sample will be observed in the clean chamber under purified-N2 gas with an ambient condition (Pre-basic Characterization). This phase will be operated by the curation team in ISAS/JAXA and the instrument team of the MMX mission. The consistency between the data from the instruments in the clean chamber and the spacecraft will then be evaluated. Subsequently, the curation will distribute the small amount of Phobos samples to the Initial analysis team of MMX to conduct the "Preliminary Examination". The objectives of the preliminary examination are to provide (1) feedback on the subsequent sample allocation process, (2) preliminary scientific results that will address parts of MMX mission goals, and (3) evaluation of the sampling system and terrestrial alteration on Phobos samples. Because multiple models are proposed for the origin of Phobos [1] (e.g., giant impact, the capture of asteroids), the chemical and mineralogical characteristics of Phobos must be assessed before the allocation of the samples to the individual initial analysis teams. Simultaneously, the curation team in JAXA will observe the individual grains and aliquots of the samples in the clean chamber (Basic Characterization).

R Fukai↗
NASA NTRS2022

Source and Chemistry of Hydroxymethanesulfonate (HMS) in Fairbanks, Alaska

Fairbanks, Alaska is a subarctic city with fine-particle (PM 2.5 ) concentrations that exceed air quality regulations in winter due to weak dispersion caused by strong atmospheric inversions, local emissions, and the unique chemistry occurring under the cold and dark conditions. Here we report on observations from the winters of 2020 and 2021, motivated by our pilot study which showed exceptionally high concentrations of fine particle hydroxy methane sulfonate (HMS) or related sulfur (IV) species (e.g., sulfite and bisulfite). We deployed an online Particle-Into-Liquid Sampler-Ion Chromatography (PILS-IC) in conjunction with a suite of instruments to determine HMS precursors (HCHO, SO 2 ) and aerosol composition in general, with the goal to characterize the sources and sinks of HMS in wintertime Fairbanks. PM 2.5 HMS comprised a significant fraction of PM 2.5 sulfur (26-41%) and overall PM 2.5 mass concentration (2.8-6.8%) during pollution episodes, substantially higher than what has been observed in other regions, likely due to the exceptionally low temperatures. HMS peaked in January, with lower concentrations in December and February, resulting from changes in precursors as well as meteorological conditions. Strong correlations with inorganic sulfate and organic mass during pollution events suggest HMS is linked to processes responsible for poor air quality episodes. These findings demonstrate unique aspects of air pollution formation in cold and humid atmospheres.

Fine-particle↗
NASA NTRSDate not supplied

Curation protocol of Phobos sample returned by the Martian Moon Exploration (MMX)

The Martian Moons Exploration (MMX) aims to return the regolith samples from the Martian moon, Phobos. After the topographic and spectroscopic observation, the spacecraft will land on the surface of Phobos to conduct the sampling operation[1–2]. Pneumatic and coring samplers will collect ≥10 g Phobos grains from two different sites. The collected samples will be retrieved from the capsule and transferred to the curation facility in 2029.

R Fukai↗
NASA NTRS2023

Prototype Global Analysis of LISA Data with Multiple Source Types

The novel data analysis challenges posed by the Laser Interferometer Space Antenna (LISA) arise from the overwhelmingly large number of astrophysical sources in the measurement band and the density with which they are found in the data. Robust detection and characterization of the numerous gravitational wave sources in LISA data can not be done sequentially, but rather through a simultaneous global fit of a data model containing the full suite of astrophysical and instrumental features present in the data. While previous analyses have focused on individual source types in isolation, here we present the first demonstration of a LISA global fit analysis containing combined astrophysical populations. The prototype pipeline uses a blocked Metropolis Hastings algorithm to alternatingly fit to a population of ultra compact galactic binaries, known “verification binaries” already identified by electromagnetic observations, a population of massive black hole mergers, and an instrument noise model. The Global LISA Analysis Software Suite (GLASS) is assembled from independently developed samplers for the different model components. The modular design enables flexibility to future development by defining standard interfaces for adding new, or updating additional, components to the global fit without being overly prescriptive for how those modules must be internally designed. The GLASS pipeline is demonstrated on data simulated for the LISA Data Challenge 2b. Results of the analysis and a road-map for continued development are described in detail.

Gravitational Waves↗
NASA NTRSDate not supplied

Insights From Routine Microbiological Monitoring of Air in Astromaterials Curation Cleanrooms

NASA maintains nine separate cleanrooms at the Johnson Space Center to curate and preserve astromaterials samples. Routine microbial monitoring of the surfaces in these cleanrooms began in 20181. Until recently, materials compatibility requirements prevented monitoring airborne biological particles in all but one of these cleanrooms. New astromaterials collections from carbon rich asteroids are more susceptible to biological degradation than previous collections. Therefore, it is important to monitor the bioburden in the air and on surfaces in these labs. Establishing a comprehensive microbial monitoring program will help inform the monitoring and curation plans for Mars sample return which will include samples that are extremely biologically sensitive. In April of 2022 we began routinely collecting air samples in seven of the nine curation cleanrooms (Meteorite ISO 7 equivalent, Lunar ISO 6 equivalent, Stardust, Hayabusa2, OSIRIS-REx ISO 5 equivalent, and Genesis ISO 4 equivalent) using a sampling device that collects airborne biological particles on an electret filter instead conventional sampler that collect cells in a liquid media or onto organic rich Petri dishes. Electret is a generic term for electrostatically charged media. The charge on these materials increases particle trapping when compared to non-charged filters of similar thickness. N95 respirators also use electret filters. This dry sample collection method allows us to meet materials requirements for all the curation labs and reduces the risk of inadvertently introducing contamination as part of our monitoring effort. This method also allows us to preserve a portion of each sample for DNA extraction and next generation sequencing. DNA sequencing helps us to characterize the portion of the cleanroom microbiome that we cannot culture. We will present the results of our first 8 months of monitoring, compare these results to particle counts in the labs and to measurements made directly onto Petri dishes when possible. We will also make recommendations for modifications to the sampling method to improve sampling efficiency and preserve diversity.

A. B. Regberg↗
NASA NTRSDate not supplied

Nanopore Sequencing-Based Microbial Air Profiling Method for Crewed Spacecraft

Microbial monitoring of the International Space Station (ISS) atmosphere is vital to maintaining the health of the spacecraft and crew. Key to NASA’s microbial risk assessment is the identity of contaminating microorganisms in the environment. Historically, this has been achieved through impaction-based air sampling followed by culture. Identification of the microorganisms present requires sample return to Earth and lab-based analyses. While this culture-based approach has served to provide alerts to anomalies and overall confidence in the controls in place, it is not suitable for exploration missions with no sample return. Recently, significant advancements in molecular-based microbial monitoring via nanopore sequencing have been implemented onboard the ISS. Building on this work, multiple commercially available air samplers, compatible with downstream molecular analysis, were evaluated for use in the spaceflight environment. Through this assessment, the Coriolis Compact (Bertin Technologies), which uses cyclonic technology to collect bioaerosols onto the surface of a sterile cone, was selected for a larger-scale comparison to the current culture-based monitoring method. Using the Coriolis Compact, 1000 L of air was collected from the breakroom of an office building and a fitness center. The buffer used to dissociate the microbial cells from the surface of the cone was split between the NASA Microbiology Laboratory’s standard culture and Sanger sequencing-based method and the culture-independent nanopore sequencing method. The bacteria identified through culture were present in the nanopore data, with Micrococcus, Staphylococcus, and Moraxella being the most common cultured isolates, which is expected based on the media and growth conditions. Not surprisingly, the nanopore data yielded much higher diversity and paralleled that of previous atmospheric microbiome studies of human-occupied built environments. As compared to the culture-based data where the breakroom and fitness center data sets cluster in proximity, the nanopore data depicts the contrast of these atmospheric microbiomes. Moreover, the nanopore data were sufficient to meet NASA’s risk assessment needs and noted the culturable isolates routinely observed. This nanopore-based atmospheric microbial profiling method will enable near real-time environmental monitoring of crewed spacecraft as future missions extend beyond low-Earth orbit.

Brandon Dunbar↗
NASA NTRSDate not supplied

Heating and Sampling Efficiency Evaluation for the Nephele Venus Cloud Sampling Mission Concept

Nephele [1] is a descent probe concept with a unique combination of entry (3D-CC+HEEET), sampling (flow-through passive impactors), and optics (laser-induced breakdown spectroscopy, or LIBS, and surface-enhanced Raman spectroscopy, or SERS), technologies with two key innovations (Figure 1). The first is the integration of the aerosol sampling inlet into the aeroshell body, allowing the possibility of sampling during passive descent without separation. The second is the use of the aerosol capture surface as an optical analysis substrate, allowing fast-cadence aerosol analysis via a dual optical spectrometer instead of mass spectrometry. Although this concept shares some features with other efforts such as Cupid’s Arrow [1] (single-body sample capture system), DAVINCI [2] and Venera-D [3] (use of an optical spectrometer), Nephele is unique in its physical integration of the sonde body, aerosol and gas sampler, and analysis instrumentation. This innovation is designed to eliminate the need for a controlled descent to achieve a detailed atmospheric aerosol transect, which offers in situ planetary science in a small spacecraft envelope. Aeroshell designs with inlets for free-falling sondes are well-understood, though not yet assessed for aerosol capture efficiency. A HEEET aeroshell with a specialized nose inlet material comprised of Carbon-Carbon is proposed for this mission concept.

Venus↗
NASA NTRSDate not supplied

Heating and Sampling Efficiency Evaluation for the Nephele Venus Cloud Sampling Mission Concept

Nephele is a descent probe concept with a unique combination of entry (3D-CC+HEEET), sampling (flow-through passive impactors), and optics (laser-induced breakdown spectroscopy, or LIBS, and surface-enhanced Raman spectroscopy, or SERS), technologies with two key innovations. The first is the integration of the aerosol sampling inlet into the aeroshell body, allowing the possibility of sampling during passive descent without separation. The second is the use of the aerosol capture surface as an optical analysis substrate, allowing fast-cadence aerosol analysis via a dual optical spectrometer instead of mass spectrometry. Although this concept shares some features with other efforts such as Cupid’s Arrow (single-body sample capture system), DAVINCI and Venera-D (use of an optical spectrometer), Nephele is unique in its physical integration of the sonde body, aerosol and gas sampler, and analysis instrumentation. This innovation is designed to eliminate the need for a controlled descent to achieve a detailed atmospheric aerosol transect, which offers in situ planetary science in a small spacecraft envelope. Aeroshell designs with inlets for free-falling sondes are well-understood, though not yet assessed for aerosol capture efficiency. A HEEET aeroshell with a specialized nose inlet material comprised of Carbon-Carbon is proposed for this mission concept.

Venus↗
NASA NTRSDate not supplied

Optical Spectroscopy of Venus Aerosol Analogs and Substrate Survivability

Aerosol Rapid Analysis Combined Entry Probe/Sonde Technology (AERACEPT) is a dual descent probe and in-situ sampler of cloud and aerosol particles, used as part of the Nephele mission concept to study Venus cloud layers. Various optical spectroscopic characterization methods, including Raman spectroscopy and Surface Enhanced Raman Spectroscopy (SERS), Laser induced Breakdown Spectroscopy (LIBS), and absorbance and fluorescence spectroscopy are being assessed for viability for compatibility with AERACEPT. Specifically, the detection limits, sensitivity, specificity, and analysis cadence of these techniques for a set of Venus aerosol analogs and their mixtures are tested. We report on preliminary optical spectroscopy results of the Venus aerosol analogs, as well as optical substrate survivability in heated and acidic conditions, substrate physical robustness, and analyte wettability on substrates.

Venus↗
NASA NTRS2023

DES Y3 + KiDS-1000: Consistent Cosmology Combining Cosmic Shear Surveys

We present a joint cosmic shear analysis of the Dark Energy Survey (DES Y3) and the Kilo-Degree Survey (KiDS-1000) in a collaborative effort between the two survey teams. We find consistent cosmological parameter constraints between DES Y3 and KiDS-1000 which, when combined in a joint-survey analysis, constrain the parameter S 8 =σ 8 √(Ω m /0.3) with a mean value of 0.790 +0.018 −0.014. The mean marginal is lower than the maximum a posteriori estimate, S 8 =0.801, owing to skewness in the marginal distribution and projection effects in the multi-dimensional parameter space. Our results are consistent with S 8 constraints from observations of the cosmic microwave background by Planck, with agreement at the 1.7 σ level. We use a Hybrid analysis pipeline, defined from a mock survey study quantifying the impact of the different analysis choices originally adopted by each survey team. We review intrinsic alignment models, baryon feedback mitigation strategies, priors, samplers and models of the non-linear matter power spectrum.

cosmology↗
NASA NTRS2024

The Peregrine Ion Trap Mass Spectrometer (PITMS) Investigation Development and Pre-Flight Planning

The Peregrine Ion Trap Mass Spectrometer (PITMS) is a mass spectrometer instrument that operated during the Astrobotic Peregrine Mission-1 as part of the NASA Commercial Lunar Payload Services (CLPS) initiative. This paper describes the instrument and investigation design, development, and planning conducted by the PITMS team consisting of a successful partnership between NASA Goddard Space Flight Center (GSFC), The Open University (OU), NASA, and ESA. PITMS was designed to measure the abundance and temporal variability of volatile species in the near-surface lunar exosphere from a landed platform on the lunar surface. The PITMS instrument consisted of an ESA-provided Exospheric Mass Spectrometer (EMS; including sensor, electronics, controller, power supply boards) and a GSFC wrapper that provided structural elements, thermal control, and a deployable dust cover. PITMS was designed to operate as a passive sampler, where ambient gases would enter PITMS through an aperture, diffuse around the mass analyzer cavity, become ionized by electron impact and trapped in a radiofrequency field, then sequentially released to a detector to build a mass spectrum. PITMS was capable of measuring species with a massto-charge ratio (m/z) from 10 to 150 Da, with a mass resolution of approximately 0.5 amu. The PITMS science investigation was planned to be operated by GSFC with an international team of scientists. Though the mission did not achieve its lunar landing, information about the PITMS instrument and planning is provided to be able to understand and effectively use data that will be forthcoming from the investigation.

Barbara Cohen↗
NASA NTRS2025

An Efficient GPU-Accelerated Multi-Source Global Fit Pipeline for LISA Data Analysis

The large-scale analysis task of deciphering gravitational wave signals in the LISA data stream will be difficult, requiring a large amount of computational resources and extensive development of computational methods. Its high dimensionality, multiple model types, and complicated noise profile require a global fit to all parameters and input models simultaneously. In this work, we detail our global fit algorithm, called “Erebor,” designed to accomplish this challenging task. It is capable of analysing current state-of-the-art datasets and then growing into the future as more pieces of the pipeline are completed and added. We describe our pipeline strategy, the algorithmic setup, and the results from our analysis of the LDC2A Sangria dataset, which contains Massive Black Hole Binaries, compact Galactic Binaries, and a parameterized noise spectrum whose parameters are unknown to the user. The Erebor algorithm includes three unique and very useful contributions: GPU acceleration for enhanced computational efficiency; ensemble MCMC sampling with multiple MCMC walkers per temperature for better mixing and parallelized sample creation; and special online updates to reversible-jump (or trans-dimensional) sampling distributions to ensure sampler mixing and accurate initial estimates for detectable sources in the data. We recover posterior distributions for all 15 (6) of the injected MBHBs in the LDC2A training (hidden) dataset. We catalog ∼12000 Galactic Binaries (∼8000 as high confidence detections) for both the training and hidden datasets. All of the sources and their posterior distributions are provided in publicly available catalogs.

LISA global fit↗
NASA NTRS2025

Efficient GPU-Accelerated MultiSource Global Fit Pipeline for LISA Data Analysis

The large-scale analysis task of deciphering gravitational-wave signals in the LISA data stream will be difficult, requiring a large amount of computational resources and extensive development of computational methods. Its high dimensionality, multiple model types, and complicated noise profile require a global fit to all parameters and input models simultaneously. In this work, we detail our global fit algorithm, called “Erebor,” designed to accomplish this challenging task. It is capable of analyzing current state-of-the-art datasets and then growing into the future as more pieces of the pipeline are completed and added. We describe our pipeline strategy, the algorithmic setup, and the results from our analysis of the LDC2A Sangria dataset, which contains massive black hole binaries, compact galactic binaries, and a parametrized noise spectrum whose parameters are unknown to the user. The Erebor algorithm includes three unique and very useful contributions: GPU acceleration for enhanced computational efficiency; ensemble Markov Chain Monte Carlo (MCMC) sampling with multiple MCMC walkers per temperature for better mixing and parallelized sample creation; and special online updates to reversible-jump (or transdimensional) sampling distributions to ensure sampler mixing and accurate initial estimates for detectable sources in the data.We recover posterior distributions for all 15 (6) of the injected massive black hole binaries (MBHB) in the LDC2A training (hidden) dataset. We catalog ∼12000 galactic binaries (∼8000 as high confidence detections) for both the training and hidden datasets. All of the sources and their posterior distributions are provided in publicly available catalogs.

LISA↗