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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Estimating Terrestrial Snow Mass via Multi-sensor Assimilation of Synthetic AMSR-E Brightness Temperature Spectral Differences and Synthetic GRACE Terrestrial Water Storage Retrievals

This study explores multi-sensor data assimilation (DA) using synthetic Advanced Microwave Scanning Radiometer (AMSR-E) passive microwave brightness temperature spectral differences (∆T(B)) and synthetic Gravity Recovery and Climate Experiment (GRACE) terrestrial water storage (TWS) retrievals to improve estimates of snow water equivalent (SWE), subsurface water storage, and TWS across snow-covered terrain. Results show that multi-sensor DA improves SWE estimates by reducing the RMSE by 14.1% relative to a model-only simulation. Multi-sensor assimilation also yields the smallest TWS RMSE (reduced by 13.0% relative to a model-only simulation). However, multi-sensor DA does not always yield complementary updates, and can sometimes lead to conflicting changes to SWE, where the assimilation of synthetic ∆T(b) generates positive SWE increments while the assimilation of synthetic TWS removes SWE, which can ultimately degrade the posterior SWE estimates. This synthetic experiment provides useful insight for future DA experiments using real-world AMSR-E/AMSR-2 ∆T(b) observations and GRACE/GRACE-FO TWS retrievals to better characterize terrestrial freshwater storage across regional scales.

Jing Wang↗
DOE OSTI2026

Synthetic soils for ecological and synthetic biology applications

Soils are heterogeneous and dynamic systems characterized by complex physical, chemical, and biological interactions. Understanding these interactions is critical, as they influence plant productivity, global biogeochemical cycles, and ecosystem resilience. While ecologists have long studied soils in field, greenhouse, and laboratory settings, their complexity and heterogeneity make it challenging to pinpoint key properties driving biological processes and derive mechanistic insights. Advancements in synthetic biology, which seeks to engineer and control biological processes in soils, have increased the demand for standardized and controllable experimental platforms. These platforms, referred to here as ‘synthetic soils’, are systems designed to reproduce selected physicochemical characteristics of natural soils in a simplified and defined format, allowing scientists to systematically change soil physicochemical properties (i.e. texture, mineralogy, pH) to study how biological components (i.e. microbes, plants, soil fauna, etc.) respond to, modify, or interact within these controlled environments. This review explores existing synthetic soils, their advantages, limitations, and applications in ecology and synthetic biology, and discusses potential directions for their future development.

artificial soils↗
DOE OSTI2025

Initial Mobility Analysis for ORNL VA-EDH Synthetic Populations

Travel burdens are a major barrier to healthcare access among US Veteran patient populations, particularly those residing in rural areas. Spatial accessibility to points of care for US Veteran populations is commonly assessed in two ways. The first approach uses open data from the US Census to represent collective travel burdens, for example the distance between population-weighted census tract centroids and VHA points of care. The second approach uses restricted-access VHA patient data to measure travel costs (e.g., distance, time) for accessing points of care with respect to geolocated patient addresses and real or approximated transportation networks. While the advantage of the open data approach lies in its reproducibility, it has notable limitations in its tendency to infer individual travel behavior from aggregate population characteristics, a problem known as ecological fallacy. Conversely, while the patient data approach is able to account for individual travel behavior, its ability to account for localized access disparities (e.g., a neighborhood with exceptionally high transportation costs) and patient demographics is limited as protecting individual patient data requires their storage in closed systems with limited capacity for adequately modeling real-world travel patterns or for supplementing patient attributes. Additionally, the patient data approach cannot account for veterans who are not enrolled in the VHA system but who may be eligible for care. These challenges limit the ability to perform “what if” analyses on the effects of place-specific interventions on veteran populations with high access barriers to healthcare. To address these challenges, we explore the application of realistic synthetic populations to examine travel burdens and spatial accessibility issues among veteran patient populations. Synthetic populations provide a virtual, individually-resolved and cross-sectional representation of the veteran patient population that enables investigation of spatial access to points of care in ways in which aggregate data and patient data do not. First, synthetic populations allow one to directly assess how individuals access points of care, from synthesized residential locations to outpatient facilities on real-world transportation networks. Modeling access to points of care at the individual scale addresses the ecological fallacy problem associated with using aggregated census data to represent veteran populations and patterns of movement. Second, synthetic populations provide a means of completely representing an area’s veteran population using only publicly available, anonymized census microdata from the American Community Survey (ACS) to ensure the privacy of real-world individuals. Generating synthetic populations from the ACS also expands descriptive characteristics beyond what patient data typically offers to include socio-demographic, economic, housing, and mobility attributes. More detailed profiles of both VHA patient populations and veterans not enrolled in the VA system will provide a comprehensive picture of groups that may benefit from interventions or outreach. As an initial exercise for using synthetic populations to measure veteran travel burdens to VA care, we apply Oak Ridge National Laboratory’s (ORNL) UrbanPop capability to generate a series of synthetic VHA patient populations for 9 Veterans Integrated Services Networks (VISN) market areas in 9 Census Divisions across the continental United States, which are listed in Table 1. We use UrbanPop to produce synthetic populations for the VISN markets selected for each US Census Division, then assign VA outpatient clinic destinations to synthetic VHA patients based on travel about each VISN market’s road network. To demonstrate using the synthetic populations to evaluate healthcare travel burdens, we compare the time-based impedance between simulated home locations and VA outpatient clinics in each VISN market. We then perform validation exercises on the synthetic populations with respect to neighborhood (block group) demographic composition as well as patient mobility, comparing aggregate origin-destination statistics for the synthetic population to outpatient visits available in restricted patient data from the VA’s Corporate Data Warehouse (CDW) database.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2016

On Beyond Star Trek, the Role of Synthetic Biology in Nasa's Missions

The time has come to for NASA to exploit the nascent field of synthetic biology in pursuit of its mission, including aeronautics, earth science, astrobiology and notably, human exploration. Conversely, NASA advances the fundamental technology of synthetic biology as no one else can because of its unique expertise in the origin of life and life in extreme environments, including the potential for alternate life forms. This enables unique, creative "game changing" advances. NASA's requirement for minimizing upmass in flight will also drive the field toward miniaturization and automation. These drivers will greatly increase the utility of synthetic biology solutions for military, health in remote areas and commercial purposes. To this end, we have begun a program at NASA to explore the use of synthetic biology in NASA's missions, particularly space exploration. As part of this program, we began hosting an iGEM team of undergraduates drawn from Brown and Stanford Universities to conduct synthetic biology research at NASA Ames Research Center. The 2011 team (http://2011.igem.org/Team:Brown-Stanford) produced an award-winning project on using synthetic biology as a basis for a human Mars settlement and the 2012 team has expanded the use of synthetic biology to estimate the potential for life in the clouds of other planets (http://2012.igem.org/Team:Stanford-Brown; http://www.calacademy.org/sciencetoday/igem-competition/). More recent projects from the Stanford-Brown team have expanded our ideas of how synthetic biology can aid NASA's missions from "Synthetic BioCommunication" (http://2013.igem.org/Team:Stanford-Brown) to a "Biodegradable UAS (drone)" in collaboration with Spelman College (http://2014.igem.org/Team:StanfordBrownSpelman#SBS%20iGEM) and most recently, "Self-Folding Origami" (http://2015.igem.org/Team:Stanford-Brown), the winner of the 2015 award for Manufacturing.

miniaturization and automation↗
NASA NTRS2016

Misconceptions of Synthetic Biology: Lessons from an Interdisciplinary Summer School

In 2014, an international group of scholars from various fields analysed the "societal dimensions" of synthetic biology in an interdisciplinary summer school. Here, we report and discuss the biologists' observations on the general perception of synthetic biology by non-biologists who took part in this event. Most attendees mainly associated synthetic biology with contributions from the best-known public figures of the field, rarely mentioning other scientists. Media extrapolations of those contributions appeared to have created unrealistic expectations and irrelevant fears that were widely disconnected from the current research in synthetic biology. Another observation was that when debating developments in synthetic biology, semantics strongly mattered: depending on the terms used to present an application of synthetic biology, attendees reacted in radically different ways. For example, using the term "GMOs" (genetically modified organisms) rather than the term "genetic engineering" led to very different reactions. Stimulating debates also happened with participants having unanticipated points of view, for instance biocentrist ethicists who argued that engineered microbes should not be used for human purposes. Another communication challenge emerged from the connotations and inaccuracies surrounding the word "life", which impaired constructive debates, thus leading to misconceptions about the abilities of scientists to engineer or even create living organisms. Finally, it appeared that synthetic biologists tend to overestimate the knowledge of non-biologists, further affecting communication. The motivation and ability of synthetic biologists to communicate their work outside their research field needs to be fostered, notably towards policymakers who need a more accurate and technical understanding of the field to make informed decisions. Interdisciplinary events gathering scholars working in and around synthetic biology are an effective tool in addressing those issues.

synthetic biology↗
NASA NTRS2019

The Role of Synthetic Biology in NASA's Missions

The time has come to for NASA to exploit the nascent field of synthetic biology in pursuit of its mission, including aeronautics, earth science, astrobiology and notably, human exploration. Conversely, NASA advances the fundamental technology of synthetic biology as no one else can because of its unique expertise in the origin of life and life in extreme environments, including the potential for alternate life forms. This enables unique, creative "game changing" advances. NASA's requirement for minimizing upmass in flight will also drive the field toward miniaturization and automation. These drivers will greatly increase the utility of synthetic biology solutions for military, health in remote areas and commercial purposes. To this end, we have begun a program at NASA to explore the use of synthetic biology in NASA's missions, particularly space exploration. As part of this program, we began hosting an iGEM team of undergraduates drawn from Brown and Stanford Universities to conduct synthetic biology research at NASA Ames Research Center. The 2011 team (http://2011.igem.org/Team:Brown-Stanford) produced an award-winning project on using synthetic biology as a basis for a human Mars settlement and the 2012 team has expanded the use of synthetic biology to estimate the potential for life in the clouds of other planets (http://2012.igem.org/Team:Stanford-Brown; http://www.calacademy.org/sciencetoday/igem-competition/). More recent projects from the Stanford-Brown team have expanded our ideas of how synthetic biology can aid NASA's missions from "Synthetic BioCommunication" (http://2013.igem.org/Team:Stanford-Brown) to a "Biodegradable UAS (drone)" in collaboration with Spelman College (http://2014.igem.org/Team:StanfordBrownSpelman#SBS%20iGEM) and most recently, "Self-Folding Origami" (http://2015.igem.org/Team:Stanford-Brown), the winner of the 2015 award for Manufacturing.

Rothschild, Lynn J.↗
NASA NTRS2002

Synthetic Jet Interaction With A Turbulent Boundary Layer Flow

Perhaps one of the more notable advances to have occurred in flow control technology in the last fifteen years is the application of surface-issuing jets for separation control on aerodynamic surfaces. The concept was introduced by Johnston and Night (1990) who proposed using circular jets, skewed and inclined to the wall, to generate streamwise vortices for the purpose of mitigating boundary layer separation. The skew and inclination angles have subsequently been shown to affect the strength and sign of the ensuing vortices. With a non-circular orifice, in addition to skew and inclination, the yaw angle of the major axis of the orifice can influence the flow control effectiveness of the jet. In particular, a study by Chang arid Collins (1997) revealed that a non-circular orifice, yawed relative to the freestream, can be used to control the size and strength of the vortices produced by the control jet. This early work used jets with only a steady injection of mass. Seifert et al. revealed that an unsteady blowing jet, could be as effective at separation control as a steady jet but with less mass flow. Seifert et al. showed that small amplitude blowing oscillations superimposed on a low momentum steady jet Was the most effective approach to delaying separation on a NACA 0015 airfoil at post-stall angles of attack. More recent work suggests that perhaps the most efficient jet control effect comes from a synthetic (oscillatory) jet where the time-averaged mass flux through the orifice is zero, but the net wall normal momentum is non-zero. The control effectiveness of synthetic jets has been demonstrated for several internal and external flow fields used synthetic jet control on a thick, blunt-nosed airfoil to delay stall well beyond the stall angles for the uncontrolled airfoil and with a dramatic increase in the lift-to-drag performance. Amitay et al. used an array of synthetic jets to mitigate flow separation in curved and diffusing ducts. While the control effectiveness of synthetic jet actuators in an application setting has been confirmed through a number of studies, the fluid dynamic mechanism by which control is effected is not well understood. Issues like yaw angle arid velocity ratio that have been studied for steady control jets have not been investigated for synthetic jets. Moreover, the role played by the inherently unsteady nature of a synthetic jet in the interaction with the controlled flow is not known. Some recent work by Rinehart and Glazer and Smith suggests that away from tile immediate vicinity of the jet orifice the flow field is steady in the mean, and that the interaction of a synthetic jet and a boundary layer creates a secondary flow in the boundary layer consisting primarily of streamwise vortices.

Smith, Douglas R.↗
DOE OSTI2024

Data-Informed Synthetic Networks of Water Distribution Systems for Resilience Analysis in Puerto Rico

The increasing potential of infrastructure disruptions calls for high-quality infrastructure models to be used in resilience analysis and decision making. Unfortunately, many utilities and communities do not have access to accurate and detailed models due to a lack of data and resources. Furthermore, security restrictions on sharing infrastructure models present roadblocks to research, analysis, and decision making. Recent advances in the development of synthetic water distribution models provide a potential solution to this problem. There is an opportunity to improve these methods by leveraging incomplete pipe datasets to aid synthetic network generation. To address this gap, we developed a methodology for synthetic network generation that incorporates partial pipe data using a modification of the minimum cost flow algorithm for network generation and pipe sizing. This methodology demonstrates how partial pipe data can be leveraged to improve site-specific synthetic network generation. For the study area of Mayagüez, Puerto Rico, a synthetic model generated using 50% of real pipe data matches the pressure of the validation system with an average error of 23.5 m of head, which improves upon the average error of 31.6 m of head produced by a synthetic model generated using no data of the real pipes. Additionally, synthetic networks are shown to replicate the pressure response under a disruption scenario of the validation network, suggesting potential use in resilience analysis.

resilience analysis↗
NASA NTRS1995

Distributed and collaborative synthetic environments

Fast graphics workstations and increased computing power, together with improved interface technologies, have created new and diverse possibilities for developing and interacting with synthetic environments. A synthetic environment system is generally characterized by input/output devices that constitute the interface between the human senses and the synthetic environment generated by the computer; and a computation system running a real-time simulation of the environment. A basic need of a synthetic environment system is that of giving the user a plausible reproduction of the visual aspect of the objects with which he is interacting. The goal of our Shastra research project is to provide a substrate of geometric data structures and algorithms which allow the distributed construction and modification of the environment, efficient querying of objects attributes, collaborative interaction with the environment, fast computation of collision detection and visibility information for efficient dynamic simulation and real-time scene display. In particular, we address the following issues: (1) A geometric framework for modeling and visualizing synthetic environments and interacting with them. We highlight the functions required for the geometric engine of a synthetic environment system. (2) A distribution and collaboration substrate that supports construction, modification, and interaction with synthetic environments on networked desktop machines.

Bajaj, Chandrajit L.↗
NASA NTRS2017

Monitoring Land Surface Albedo and Vegetation Dynamics Using High Spatial and Temporal Resolution Synthetic Time Series from Landsat and the MODIS BRDF/NBAR/Albedo Product

Seasonal vegetation phenology can significantly alter surface albedo which in turn affects the global energy balance and the albedo warmingcooling feedbacks that impact climate change. To monitor and quantify the surface dynamics of heterogeneous landscapes, high temporal and spatial resolution synthetic time series of albedo and the enhanced vegetation index (EVI) were generated from the 500-meter Moderate Resolution Imaging Spectroradiometer (MODIS) operational Collection V006 daily BRDF (Bidirectional Reflectance Distribution Function) / NBAR (Nadir BRDF-Adjusted Reflectance) / albedo products and 30-meter Landsat 5 albedo and near-nadir reflectance data through the use of the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). The traditional Landsat Albedo (Shuai et al., 2011) makes use of the MODIS BRDFAlbedo products (MCD43) by assigning appropriate BRDFs from coincident MODIS products to each Landsat image to generate a 30-meter Landsat albedo product for that acquisition date. The available cloud free Landsat 5 albedos (due to clouds, generated every 16 days at best) were used in conjunction with the daily MODIS albedos to determine the appropriate 30-meter albedos for the intervening daily time steps in this study. These enhanced daily 30-meter spatial resolution synthetic time series were then used to track albedo and vegetation phenology dynamics over three Ameriflux tower sites (Harvard Forest in 2007, Santa Rita in 2011 and Walker Branch in 2005). These Ameriflux sites were chosen as they are all quite nearby new towers coming on line for the National Ecological Observatory Network (NEON), and thus represent locations which will be served by spatially paired albedo measures in the near future. The availability of data from the NEON towers will greatly expand the sources of tower albedometer data available for evaluation of satellite products. At these three Ameriflux tower sites the synthetic time series of broadband shortwave albedos were evaluated using the tower albedo measurements with a Root Mean Square Error (RMSE) less than 0.013 and a bias within the range of 0.006. These synthetic time series provide much greater spatial detail than the 500 meter gridded MODIS data, especially over more heterogeneous surfaces, which improves the efforts to characterize and monitor the spatial variation across species and communities. The mean of the difference between maximum and minimum synthetic time series of albedo within the MODIS pixels over a subset of satellite data of Harvard Forest (16 kilometers by 14 kilometers) was as high as 0.2 during the snow-covered period and reduced to around 0.1 during the snow-free period. Similarly, we have used STARFM to also couple MODIS Nadir BRDF-Adjusted Reflectances (NBAR) values with Landsat 5 reflectances to generate daily synthetic times series of NBAR and thus Enhanced Vegetation Index (NBAR-EVI) at a 30-meter resolution. While normally STARFM is used with directional reflectances, the use of the view angle corrected daily MODIS NBAR values will provide more consistent time series. These synthetic times series of EVI are shown to capture seasonal vegetation dynamics with finer spatial and temporal details, especially over heterogeneous land surfaces.

Vegetation Index↗
NASA NTRS2016

The Role of Synthetic Biology in NASA's Missions

The time has come to for NASA to exploit synthetic biology in pursuit of its missions, including aeronautics, earth science, astrobiology and most notably, human exploration. Conversely, NASA advances the fundamental technology of synthetic biology as no one else can because of its unique expertise in the origin of life and life in extreme environments, including the potential for alternate life forms. This enables unique, creative "game changing" advances. NASA's requirement for minimizing upmass in flight will also drive the field toward miniaturization and automation. These drivers will greatly increase the utility of synthetic biology solutions for military, health in remote areas and commercial purposes. To this end, we have begun a program at NASA to explore the use of synthetic biology in NASA's missions, particular space exploration. As part of this program, we began hosting an iGEM team of undergraduates drawn from Brown and Stanford Universities to conduct synthetic biology research at NASA Ames Research Center. The 2011 team (http://2011.igem.org/Team:Brown-Stanford) produced an award-winning project on using synthetic biology as a basis for a human Mars settlement.

synthetic biology↗
DOE OSTI2026

Generalizing synthetic data-trained acoustic predictive models to real-world measurements

Acoustic Resonance Spectroscopy (ARS) is highly sensitive to structural properties such as material, geometry, and environmental conditions; as a consequence, it can noninvasively measure internal properties that are unobservable by most other methods. Because of its sensing capabilities and low implementation cost and complexity, ARS has potential as a paradigm shift in noninvasive sensing, characterization, and monitoring applications. However, extracting specific properties from ARS measurements, comprising the vibration spectrum of a test object, is challenging due to the sensitivity of the spectra to other structural changes not being measured, e.g. manufacturing tolerances, component coupling, environmental variation, etc. Neural Networks are promising tools for identifying trends in ARS measurements, but their training typically requires large datasets, which are often impractical to obtain for real-world systems. Synthetic data can be simulated efficiently, but discrepancies between synthetic and real-world data frequently lead to poor generalization when testing on the real-world data. We propose a novel ARS model training framework that enables networks trained exclusively on synthetic ARS data to generalize effectively to real-world measurements. Our approach leverages the Correlation Alignment (CORAL) technique to enforce the extraction of features common to both synthetic and real-world domains. As a case study, we demonstrate noninvasive ARS-based pressure measurements in sealed systems. Finite element method (FEM) simulations were used to generate synthetic training data across diverse vessel configurations and pressure conditions, and model performance was then tested on real-world measurements. We demonstrate that robust machine learning models for ARS can be developed without large real-world datasets, significantly broadening the applicability of ARS for noninvasive sensing. Moreover, the approach is extensible to other sensing modalities where synthetic data are abundant but real-world data are limited.

36 MATERIALS SCIENCE↗
NASA NTRS1996

The Information Content of Interferometric Synthetic Aperture Radar: Vegetation and Underlying Surface Topography

This paper first gives a heuristic description of the sensitivity of Interferometric Synthetic Aperture Radar to vertical vegetation distributions and underlying surface topography. A parameter estimation scenario is then described in which the Interferometric Synthetic Aperture Radar cross-correlation amplitude and phase are the observations from which vegetation and surface topographic parameters are estimated. It is shown that, even in the homogeneous-layer model of the vegetation, the number of parameters needed to describe the vegetation and underlying topography exceeds the number of Interferometric Synthetic Aperture Radar observations for single-baseline, single-frequency, single-incidence-angle, single-polarization Interferometric Synthetic Aperture Radar. Using ancillary ground-truth data to compensate for the underdetermination of the parameters, forest depths are estimated from the INSAR data. A recently-analyzed multibaseline data set is also discussed and the potential for stand-alone Interferometric Synthetic Aperture Radar parameter estimation is assessed. The potential of combining the information content of Interferometric Synthetic Aperture Radar with that of infrared/optical remote sensing data is briefly discussed.

Treuhaft, Robert N.↗
NASA NTRS2010

A Powerful Toolkit for Synthetic Biology: Over 3.8 Billion Years of Evolution

The combination of evolutionary with engineering principles will enhance synthetic biology. Conversely, synthetic biology has the potential to enrich evolutionary biology by explaining why some adaptive space is empty, on Earth or elsewhere. Synthetic biology, the design and construction of artificial biological systems, substitutes bio-engineering for evolution, which is seen as an obstacle. But because evolution has produced the complexity and diversity of life, it provides a proven toolkit of genetic materials and principles available to synthetic biology. Evolution operates on the population level, with the populations composed of unique individuals that are historical entities. The source of genetic novelty includes mutation, gene regulation, sex, symbiosis, and interspecies gene transfer. At a phenotypic level, variation derives from regulatory control, replication and diversification of components, compartmentalization, sexual selection and speciation, among others. Variation is limited by physical constraints such as diffusion, and chemical constraints such as reaction rates and membrane fluidity. While some of these tools of evolution are currently in use in synthetic biology, all ought to be examined for utility. A hybrid approach of synthetic biology coupled with fine-tuning through evolution is suggested

Rothschild, Lynn J.↗
DOE OSTI2025

In Crystallo Photochemistry: Reimagining Synthetic Tractability with Transparent Single-Crystalline Flasks

Expanding the boundaries of synthetic tractability of what molecules can be synthesized and isolated is an eternal challenge for synthetic chemists. The development of new synthetic methods and strategies enables the properties and potential functions of novel molecular targets to be experimentally evaluated. In the context of catalysis, predictable synthetic strategies are often available to access kinetically persistent intermediates such as catalyst resting states. In contrast, synthesis and characterization of the reactive intermediates are often not possible due to the fleeting lifetimes of these species. In crystallo photochemistry combines single-crystal matrix isolation with cryogenic photochemistry to enable reactive intermediates to be synthesized under conditions in which they are persistent and can be (crystallographically) characterized. This Outlook highlights key achievements of in crystallo photochemistry as well as discusses opportunities and challenges that confront realization of the potential of in crystallo synthesis to redefine the boundaries of synthetic tractability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Validation of the DESI 2024 Lyα forest BAO analysis using synthetic datasets

The first year of data from the Dark Energy Spectroscopic Instrument (DESI) contains the largest set of Lyman-α (Lyα) forest spectra ever observed. This data, collected in the DESI Data Release 1 (DR1) sample, has been used to measure the Baryon Acoustic Oscillation (BAO) feature at redshift z = 2.33. In this work, we use a set of 150 synthetic realizations of DESI DR1 to validate the DESI 2024 Lyα forest BAO measurement presented in [1]. The synthetic data sets are based on Gaussian random fields using the log-normal approximation. We produce realistic synthetic DESI spectra that include all major contaminants affecting the Lyα forest. The synthetic data sets span a redshift range 1.8 < z < 3.8, and are analyzed using the same framework and pipeline used for the DESI 2024 Lyα forest BAO measurement. To measure BAO, we use both the Lyα auto-correlation and its cross-correlation with quasar positions. We use the mean of correlation functions from the set of DESI DR1 realizations to show that our model is able to recover unbiased measurements of the BAO position. We also fit each mock individually and study the population of BAO fits in order to validate BAO uncertainties and test our method for estimating the covariance matrix of the Lyα forest correlation functions. Finally, we discuss the implications of our results and identify the needs for the next generation of Lyα forest synthetic data sets, with the top priority being to simulate the effect of BAO broadening due to non-linear evolution.

79 ASTRONOMY AND ASTROPHYSICS↗