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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Physics-Based Machine Learning Methods for U-235 Forensics Signatures

Signatures of low-intensity U-235 sources have been recently studied by utilizing a variety of machine learning (ML) classifiers using features derived from gamma spectral measurements collectedunder structured campaigns. Several ML classifiers, such as ensemble of tress and classification trees, revealed misleadingly-optimistic training error due to over-fitting, and furthermore,their performance is not directly relatable to the physical properties due to their data-driven, opaque designs. We present a regression-based ML method that first estimates the inverse distanceto the source and then utilizes a threshold to infer its presence, by representing the background as a source located at an infinite distance. For the inverse distance estimation, we study the ensembleof trees and Gaussian process regression methods, and a hyper parameter auto-tuning and selection method that employs five regression estimators. These methods avoid the over-fittingobserved in several ML classifiers, while providing the classification error nearly comparable to them based on independent test data. Their error is directly related to estimates of the inversephysical distance to source, and the precision of error determines the seperability property that determines the false alarm and missed detection rates. The property of monotonic decrease of thesource strength with increasing detector distance combined with Poisson distribution of measurements is utilized to analytically validate these methods by deriving the generalization equations ofunderlying regression methods.

Rao, Nageswara↗
DOE OSTI2020

Planck 2018 results. VI. Cosmological parameters

In this paper, we present cosmological parameter results from the final full-mission Planck measurements of the cosmic microwave background (CMB) anisotropies, combining information from the temperature and polarization maps and the lensing reconstruction. Compared to the 2015 results, improved measurements of large-scale polarization allow the reionization optical depth to be measured with higher precision, leading to significant gains in the precision of other correlated parameters. Improved modelling of the small-scale polarization leads to more robust constraints on many parameters, with residual modelling uncertainties estimated to affect them only at the 0.5 σ level. We find good consistency with the standard spatially-flat 6-parameter ΛCDM cosmology having a power-law spectrum of adiabatic scalar perturbations (denoted “base ΛCDM” in this paper), from polarization, temperature, and lensing, separately and in combination. A combined analysis gives dark matter density Ω c h 2 = 0.120 ± 0.001, baryon density Ω b h 2 = 0.0224 ± 0.0001, scalar spectral index n s = 0.965 ± 0.004, and optical depth τ = 0.054 ± 0.007 (in this abstract we quote 68% confidence regions on measured parameters and 95% on upper limits). The angular acoustic scale is measured to 0.03% precision, with 100 θ * = 1.0411 ± 0.0003. These results are only weakly dependent on the cosmological model and remain stable, with somewhat increased errors, in many commonly considered extensions. Assuming the base-ΛCDM cosmology, the inferred (model-dependent) late-Universe parameters are: Hubble constant H 0 = (67.4 ± 0.5) km s –1 Mpc –1 ; matter density parameter Ω m = 0.315 ± 0.007; and matter fluctuation amplitude σ 8 = 0.811 ± 0.006. We find no compelling evidence for extensions to the base-ΛCDM model. Combining with baryon acoustic oscillation (BAO) measurements (and considering single-parameter extensions) we constrain the effective extra relativistic degrees of freedom to be N eff = 2.99 ± 0.17, in agreement with the Standard Model prediction N eff = 3.046, and find that the neutrino mass is tightly constrained to Σ m ν < 0.12 eV. The CMB spectra continue to prefer higher lensing amplitudes than predicted in base ΛCDM at over 2 σ , which pulls some parameters that affect the lensing amplitude away from the ΛCDM model; however, this is not supported by the lensing reconstruction or (in models that also change the background geometry) BAO data. The joint constraint with BAO measurements on spatial curvature is consistent with a flat universe, Ω K = 0.001 ± 0.002. Also combining with Type Ia supernovae (SNe), the dark-energy equation of state parameter is measured to be w 0 = –1.03 ± 0.03, consistent with a cosmological constant. We find no evidence for deviations from a purely power-law primordial spectrum, and combining with data from BAO, BICEP2, and Keck Array data, we place a limit on the tensor-to-scalar ratio r 0.002 < 0.06. Standard big-bang nucleosynthesis predictions for the helium and deuterium abundances for the base-ΛCDM cosmology are in excellent agreement with observations. The Planck base-ΛCDM results are in good agreement with BAO, SNe, and some galaxy lensing observations, but in slight tension with the Dark Energy Survey’s combined-probe results including galaxy clustering (which prefers lower fluctuation amplitudes or matter density parameters), and in significant, 3.6 σ , tension with local measurements of the Hubble constant (which prefer a higher value). Simple model extensions that can partially resolve these tensions are not favoured by the Planck data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

On the Stochastic Stability of Deep Markov Models

Deep Markov models (DMM) are generative models which are scalable and expressive generalization of Markov models for representation, learning, and inference problems. DMMs using deep neural networks to parametrize the transition of Markov probability distributions have recently been shown to provide more expressiveness in modeling sequential data and dynamical system responses. However, the fundamental stochastic stability guarantees of such models have not been thoroughly investigated. In this paper, we present a rigorous analytical method to prove the necessary and sufficient conditions of DMM's stochastic stability. This task is achieved by spectral analysis of the efficiently computed Jacobians of probabilistic maps modeled by deep neural networks. We make theoretical connections between the eigenvalues of neural network's weights and the different activation function types used on the stability and overall dynamic behavior of DMMs with Gaussian distributions. We empirically substantiate our theoretical results on stochastic stability and eigenvalue spectra via several numerical experiments. Formal stability guarantees of DMMs can substantially improve their robustness and trustworthiness, necessary for reliable use in safety-critical real-world applications.

Drgona, Jan↗
DOE OSTI2024

Physics-Based Machine Learning Methods for U-235 Forensics Signatures

Signatures of low-intensity U-235 sources have been recently studied by utilizing a variety of machine learning (ML) classifiers using features derived from gamma spectral measurements collected under structured campaigns. Several ML classifiers, such as ensemble of tress and classification trees, revealed misleadingly-optimistic training error due to over-fitting, and furthermore, their performance is not directly relatable to the physical properties due to their data-driven, opaque designs. We present a regression-based ML method that first estimates the inverse distance to the source and then utilizes a threshold to infer its presence, by representing the background as a source located at an infinite distance. For the inverse distance estimation, we study the ensemble of trees and Gaussian process regression methods, and a hyper parameter auto-tuning and selection method that employs five regression estimators. These methods avoid the over-fitting observed in several ML classifiers, while providing the classification error nearly comparable to them based on independent test data. Their error is directly related to estimates of the inverse physical distance to source, and the precision of error determines the seperability property that determines the false alarm and missed detection rates. The property of monotonic decrease of the source strength with increasing detector distance combined with Poisson distribution of measurements is utilized to analytically validate these methods by deriving the generalization equations of underlying regression methods.

Rao, Nageswara↗
DOE OSTI2025

Overview of oxygen opacity experiments at the National Ignition Facility and investigation of potential systematic errors

Experiments to measure oxygen opacity at stellar interior conditions have been performed at the National Ignition Facility in a Discovery Science campaign. These experiments utilize the Opacity-on-NIF platform with a sample comprised of O, Mg, and Si. The spectral data from the Opacity Spectrometer cover the 1000–2000 eV photon energy range showing bound-free continuum absorption from O and line absorption from Mg and Si. DANTE and the Gated X-ray Detector are employed to measure the sample plasma’s temperature and density, respectively. Initial data show lower transmission than expected by theoretical models, raising questions of whether potential background or data uniformity concerns could produce systematic errors in the inferred transmission. Here, we investigate three concerns thought to be important for the oxygen opacity data, including instrumental scattered background, sample self-emission non-uniformity, and backlight continuum non-uniformity. Additionally, we show the effect of a recently developed method to account for 2nd order crystal reflection. The total effect of these concerns on one experiment is found to be small compared to the observed difference between the inferred transmission and a model calculation at the inferred temperature and density. Thus, we conclude that these potential sources of systematic error cannot account for the observed difference, increasing the likelihood of a real effect due to the high temperature and density conditions. However, because this is only a single experiment, we cannot make a firm conclusion. More experiments measuring the opacity and necessary calibrations are needed to assess the reproducibility and uncertainty of this result.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Characterizing laser preheat for laser-driven magnetized liner inertial fusion using soft x-ray emission

Laser heating of a gas in a cylindrical liner held in by a thin foil window is a critical process in the MagLIF (magnetized liner inertial fusion) concept. Window burn-through and gas heating for OMEGA scale MagLIF cylinders as a function of time have been determined using spectrally integrated soft x-ray diagnostics. Window laser absorption is classified in terms of the emitted x-rays from the window plasma as a function of laser energy, and shows that laser energy absorbed is weakly dependent on incident intensity. Radiation-hydrodynamic simulations overestimate the amount of laser energy absorbed by the window as evidenced by the increase in x-ray radiation across several photon energy bands compared to experiments. Gas temperatures inferred from soft x-ray emission from the front 1 mm of the liner are shown to evolve in time in a similar manner to simulation predictions. In conclusion, soft x-ray emission from the gas within the region of the liner that is normally imploded is shown to meet the 100 eV requirements set by the initial point design for laser-driven MagLIF.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

GeoCarb Calibration Campaign Field Campaign Report

The GeoCarb Calibration Campaign, referred to as the Total Carbon Column Observing Network (TCCON) calibration campaign within this report for clarity, involved a series of single- and multiple-day Bruker EM27/SUN Fourier transform infrared (FTIR) spectrometer deployments at the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s Southern Great Plains (SGP) observatory in Oklahoma. The EM27/SUN instruments directly measure infrared solar radiation in a wavelength range from 4000 to 11000 cm -1 at a spectral resolution of 0.5 cm -1 and varied temporal resolution of approximately 15 seconds. The solar radiation observed by these spectrometers contains information about the concentrations of atmospheric constituents present between the instruments and the top of the atmosphere, as every gas and particle in the atmosphere absorbs solar radiation at different wavelengths depending on their physical and chemical makeup. Through retrieval algorithm processing, the solar radiation data collected by EM27/SUN instruments can be used to infer total column dry-air mole fractions, or total column concentrations, of different trace gases present in the atmosphere. These total column concentrations, denoted as Xgas , represent the concentration, in ppb or ppm, of a trace gas in the column of atmosphere between an instrument and the top of the atmosphere. EM27/SUN instruments are primarily used to infer total column concentrations of carbon dioxide (CO 2 ), carbon monoxide (CO), methane (CH 4 ), and water vapor.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Analysis of Spectral Lines in Large Databases of Synthetic Spectra for Massive Stars

In this paper, we describe a program that identifies in the optical spectrum the main parameters of a spectral line, namely the initial and final wavelengths, and the line depth. Moreover, using numerical calculations, it identifies and removes adjacent lines. Next, the program calculates the equivalent width and the FWHM. The software was tested in a sample of 300 lines in two databases of synthetic spectra generated by the CMFGEN and PoWR codes, and 300 lines in observed spectra from the IACOB database, showing a Gaussian distribution of relative errors, from which it is inferred that 80% of the measured lines have errors less than 17% and only 5% of the lines have errors greater than 26%. The program was also run on the entire database of 45,000 CMFGEN and 202 POWR synthetic spectra, generating a library of H i, He i, and He ii lines necessary to feed the FITspec code for the derivation of stellar parameters: effective temperature, surface gravity, and luminosity.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

Establishing robust correction schemes for improved and reliable ARM-AOS aerosol optical data products

Aerosol light absorption and scattering of solar radiation play an important role in the earth’s atmosphere in terms of direct and semi-direct radiative forcing. Optical parameters of importance to the US Department of Energy (DOE) climate models include absorption and scattering coefficients, single scattering albedo (SSA), absorption Angstrom exponents (AAE), and the asymmetry parameter (g). These parameters depend on aerosol size, shape and composition (refractive index), and are spectrally sensitive in the shortwave region. Additionally, these parameters have a complex dependency on the emission source, especially for carbonaceous aerosols. The DOE Atmospheric Radiation Measurement (ARM) user facility has deployed aerosol observing systems (AOS) containing several filter-based instruments to measure and constrain aerosol optical properties and related parameters at multiple sites worldwide. For measurement of aerosol light absorption, the AOS includes filter-based instruments (particle soot absorption photometer and tricolor absorption photometer) that infer particle-phase aerosol absorption coefficients at nominal red, green, and blue wavelength bands from the attenuation (ATN) of light passing through a particulate filter on which aerosols are deposited. Measurement of aerosol scattering is done in situ using nephelometers. By combining inferred absorption coefficients from filter-based ATN measurements and in situ scattering coefficients, value-added products (VAPs) such as SSA, AAE, and g are derived.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Automatic method of material identification for computed tomography

A method is provided for isolating and labeling discrete features in a spectral radiographic image recorded as a set of images in different energy channels. The disclosed method involves creating a profile for each of at least some pixels in the spectral radiographic image. The profiles are sequences of pixel values, in which each pixel value is a photon count or a similar radiographic exposure value indicative of the attenuation of a portion of the scanning beam in a respective energy channel. Iterative hierarchical clustering is used to cluster the pixels on the basis of their respective profiles. Labels are assigned to one or more of the resulting clusters. In implementations, each label can be associated with an inferred material composition or with an inference that the material composition is unknown.

Jimenez, Jr., Edward Steven↗
DOE OSTI2023

Disentangling the AGN and Star formation Contributions to the Radio–X-Ray Emission of Radio-loud Quasars at 1 < Z < 2

We constrain the emission mechanisms responsible for the prodigious electromagnetic output generated by active galactic nuclei (AGNs) and their host galaxies with a novel state-of-the-art AGN radio-to-X-ray spectral energy distribution model fitting code (ARXSED). ARXSED combines multiple components to fit the spectral energy distributions (SEDs) of AGNs and their host galaxies. Emission components include radio structures such as lobes and jets, infrared emission from the AGN torus, visible-to-X-ray emission from the accretion disk, and radio-to-ultraviolet emission from the host galaxy. Applying ARXSED to the radio SEDs of 20 3CRR quasars at 1 < z < 2 verifies the need for more than a simple power law when compact radio structures are present. The nonthermal emission contributes 91%–57% of the observed-frame 1.25 mm to 850 μm flux, and this component must be accounted for when using these wavelengths to estimate star formation properties. We predict the presence of strong radio-linked X-ray emission in more than half the sample sources. ARXSED estimates median (and the associated first and third quartile ranges) BH mass of ${2.9}_{1.7}^{6.0}\times {10}^{9}\,{M}_{\odot }$ , logarithm of Eddington ratio of $-{1.0}_{-1.2}^{-0.6}$ , and spin of ${0.98}_{0.94}^{0.99}$ for our sample. The inferred AGN torus and accretion disk parameters agree with those estimated from spectroscopic analyses of similar samples in the literature. We present the median intrinsic SED of the luminous radio-loud quasars at 1 < z ≲ 2; this SED represents a significant improvement in the way each component is modeled.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

$\mathrm{SageNet}$: Fast Neural Network Emulation of the Stiff-amplified Gravitational Waves from Inflation

Accurate modeling of the inflationary gravitational waves (GWs) requires time-consuming, iterative numerical integrations of differential equations to take into account their backreaction on the expansion history. To improve computational efficiency while preserving accuracy, we present the Stiff-amplified Gravitational-wave Emulator Network (SageNet), a deep learning framework designed to replace conventional numerical solvers (code available at https://github.com/YifangLuo/SageNet). SageNet employs a long short-term memory architecture to emulate the present-day energy density spectrum of the inflationary GWs with possible stiff amplification, Ω GW (f). Trained on a data set of 25,689 numerically generated solutions, SageNet allows accurate reconstructions of Ω GW (f) and generalizes well to a wide range of cosmological parameters; 90.9% of the test emulations with randomly distributed parameters exhibit errors of under 4%. In addition, SageNet demonstrates its ability to learn and reproduce the artificial, adaptive sampling patterns in numerical calculations, which implement denser sampling of frequencies around changes in spectral indices in Ω GW (f). The dual capability of learning both physical and artificial features of the numerical GW spectra establishes SageNet as a robust alternative to exact numerical methods. Finally, our benchmark tests show that SageNet reduces the computation time from tens of seconds to milliseconds, achieving a speedup of ∼10 4 times over standard CPU-based numerical solvers with the potential for further acceleration on GPU hardware. These capabilities make SageNet a powerful tool for accelerating Bayesian inference procedures for extended cosmological models. In a broad sense, the SageNet framework offers a fast, accurate, and generalizable solution to modeling cosmological observables whose theoretical predictions demand costly differential equation solvers.

Astronomy data modeling↗
DOE OSTI2021

Hybrid simulations of sub-cyclotron compressional and global Alfven Eigenmode stability in spherical tokamaks

A comprehensive numerical study has been conducted in order to investigate the stability of beam-driven, sub-cyclotron frequency compressional (CAE) and global (GAE) Alfven Eigenmodes in low aspect ratio plasmas for a wide range of beam parameters. The presence of CAEs and GAEs has previously been linked to anomalous electron temperature profile flattening at high beam power in NSTX experiments, prompting further examination of the conditions for their excitation. Linear simulations are performed with the hybrid MHD-kinetic initial value code HYM in order to capture the general Doppler-shifted cyclotron resonance that drives the modes. Three distinct types of modes are found in simulations -- co-CAEs, cntr-GAEs, and co-GAEs -- with differing spectral and stability properties. The simulations reveal that unstable GAEs are more ubiquitous than unstable CAEs, consistent with experimental observations, as they are excited at lower beam energies and generally have larger growth rates. Local analytic theory is used to explain key features of the simulation results, including the preferential excitation of different modes based on beam injection geometry and the growth rate dependence on the beam injection velocity, critical velocity, and degree of velocity space anisotropy. The background damping rate is inferred from simulations and estimated analytically for relevant sources not present in the simulation model, indicating that co-CAEs are closer to marginal stability than modes driven by the cyclotron resonances.

Compressional Alfven Eigenmodes↗
DOE OSTI2026

Dynamical Dark Energy Imprints in the Lyman-Alpha Forest

The nature of dark energy (DE) remains elusive, even though it constitutes the dominant energy-density component of the Universe and drives the late-time acceleration of cosmic expansion. By combining measurements of the expansion history from baryon acoustic oscillations, supernova surveys, and cosmic microwave background data, the Dark Energy Spectroscopic Instrument (DESI) Collaboration has inferred that the DE equation of state may evolve over time. The profound implications of a time-variable, ``dynamical" DE (DDE) that departs from a cosmological constant motivate the need for independent observational tests. In this work, we use cosmological hydrodynamical simulations of structure formation to investigate how DDE affects the properties of the Lyman-Alpha ``forest'' of absorption features produced by neutral hydrogen in the cosmic web. We find that DDE models consistent with the DESI constraints induce a spectral tilt in the forest transmitted flux power spectrum, imprinting a scale- and redshift-dependent signature relative to standard Lambda-CDM cosmologies. These models also yield higher intergalactic medium temperatures and reduced Lyman-Alpha opacity compared to Lambda-CDM. We discuss the observational implications of these trends as potential avenues for independent confirmation of DDE.

Garza, Diego [UC, Santa Cruz, Inst. Part. Phys.] (↗
DOE OSTI2021

Hybrid simulations of sub-cyclotron compressional and global Alfvén eigenmode stability in spherical tokamaks

A comprehensive numerical study has been conducted in order to investigate the stability of beam-driven, sub-cyclotron-frequency compressional Alfvén eigenmodes (CAEs) and global Alfvén eigenmodes (GAEs) in low-aspect-ratio plasmas for a wide range of beam parameters. The presence of CAEs and GAEs has previously been linked to anomalous electron temperature profile flattening at high beam powers in NSTX experiments, prompting a further examination of the conditions necessary for their excitation. Linear simulations have been performed with the hybrid MHD–kinetic initial value code HYM in order to capture the general Doppler-shifted cyclotron resonance that drives the modes. Additionally, three distinct types of modes were found in the simulations—co-CAEs, cntr-GAEs, and co-GAEs—with differing spectral and stability properties. The simulations revealed that unstable GAEs are more ubiquitous than unstable CAEs, which is consistent with experimental observations, as they are excited at lower beam energies and generally have larger growth rates. Local analytic theory is used to explain key features of the simulation results, including the preferential excitation of different modes based on beam injection geometry and the growth rate dependence on the beam injection velocity, critical velocity, and degree of velocity space anisotropy. The background damping rate is inferred from the simulations and analytically estimated for relevant sources absent from the simulation model, indicating that co-CAEs are closer to marginal stability than modes driven by the cyclotron resonances.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Testing AGN outflow and accretion models with C IV and He II emission line demographics in z ≈ 2 quasars

Using ≈190 000 spectra from the 17th data release of the Sloan Digital Sky Survey (SDSS), we investigate the ultraviolet emission line properties in z ≈ 2 quasars. Specifically, we quantify how the shape of C IV λ1549 and the equivalent width (EW) of He II λ1640 depend on the black hole mass and Eddington ratio inferred from Mg II λ2800. Above L/L Edd ≳ 0.2, there is a strong mass dependence in both C IV blueshift and He II EW. Large C IV blueshifts are observed only in regions with both high mass and high accretion rate. Including X-ray measurements for a subsample of 5000 objects, we interpret our observations in the context of AGN accretion and outflow mechanisms. The observed trends in He II and 2 keV strength are broadly consistent with theoretical qsosed models of AGN spectral energy distributions (SEDs) for low spin black holes, where the ionizing SED depends on the accretion disc temperature and the strength of the soft excess. High spin models are not consistent with observations, suggesting SDSS quasars at z ≈ 2 may in general have low spins. We find a dramatic switch in behaviour at L/L Edd ≲ 0.1: the ultraviolet emission properties show much weaker trends, and no longer agree with qsosed predictions, hinting at changes in the structure of the broad line region. Overall, the observed emission line trends are generally consistent with predictions for radiation line driving where quasar outflows are governed by the SED, which itself results from the accretion flow and hence depends on both the SMBH mass and accretion rate.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Neutron-Resonance Transmission Analysis with a Compact Deuterium-Tritium Neutron Generator

Neutron Resonance Transmission Analysis (NRTA) is a spectroscopic technique which uses the resonant absorption of neutrons in the epithermal range to infer the isotopic composition of an object. This spectroscopic technique has relevance in many traditional fields of science and nuclear security. NRTA in the past made use of large, expensive accelerator facilities to achieve precise neutron beams, significantly limiting its applicability. Here, we describe a series of NRTA experiments where we use a compact, low-cost deuterium-tritium (DT) neutron generator to produce short neutron beams (2.6 m) along with a 6 Li-glass neutron detector. The time-of-flight spectral data from five elements – silver, cadmium, tungsten, indium, and 238 U – clearly show the corresponding absorption lines in the 1-30 eV range. The experiments show the applicability of NRTA in this simplified configuration, and prove the feasibility of this compact and low-cost approach. This could significantly broaden the applicability of NRTA, and make it practical and applicable in many fields, such as material science, nuclear engineering, and arms control.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2026

Comparability of Liquid Chromatography Tandem Mass Spectrometry Analysis of Dissolved Organic Matter across Laboratories

Non-targeted liquid chromatography tandem highresolution mass spectrometry (LC−MS/MS) is increasingly applied for the structure-resolved chemical analysis of dissolved organic matter (DOM). With new developments in MS instrumentation and analysis software, the approach has gained substantial momentum over the past decade. However, achieving high-quality analytical data that is reproducible and comparable across laboratories can be a bottleneck in non-targeted metabolomics and organic matter chemical analysis, especially for data reuse in repository-scale analyses. Understanding the capabilities as well as challenges of comparing LC−MS/MS data from different laboratories is necessary for inferring global trends from public data sets. To illuminate instrumentation factors that drive differences and variability, we used a standardized data analysis pipeline, including classical (CMN) and featurebased molecular networking (FBMN), to analyze data from a ring trial by 24 laboratories on identical sample sets of algal and DOM extracts that were mixed in predefined concentrations and spiked with standards. Our results showed that data sets from similar mass spectrometer types with unified instrument parameters were qualitatively comparable, resolving the same general trends and shared mass spectral features. Interlaboratory comparability was best for high-intensity features, while low-intensity features showed greater detection variability. Our analysis also highlights challenges when comparing data from instruments with different acquisition rates or operating with less standardized methods. Lastly, we provide recommendations for data integration, public data sharing, standardization, and best practices for standardized LC−MS/MS data acquisition, which will be critical for long-term time series and intercomparability of DOM chemical analyses.

DOM↗