Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “robust clustering”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

An Octacarboxylate-Linked Sodium Metal–Organic Framework with High Porosity

Alkali metal-based metal-organic frameworks (MOFs) with permanent porosity are scarce because of their high tendency to coordinate with solvents such as water. However, these MOFs are lightweight and bear gravimetric benefits for gas adsorption related applications. In this paper, we present the successful construction of a microporous MOF, designated as HIAM-111, built solely on sodium ions using an octacarboxylate linker. The structure of HIAM-111 is based on 8-connected Na4 clusters and exhibits a novel topology with an underlying 3 2 ,4 2 ,8-c net. Remarkably, HAM-111 possesses a robust and highly porous framework, with a BET surface area of 1561 m 2 /g, significantly surpassing that of the previously reported Na-MOFs. Further investigations demonstrate that HIAM-111 is capable of separating C 2 H 2 /CO 2 and purifying C 2 H 4 directly from C 2 H 4 /C 2 H 2 /C 2 H 6 with high adsorption capacities. The current work may shed light on the rational design of robust and porous MOFs based on alkali metals.

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

Effects of Subhalos on Interpreting Highly Magnified Sources Near Lensing Caustics

Large magnification factors near gravitational lensing caustics of galaxy-cluster lenses allow the study of individual stars or compact stellar associations at cosmological distances. We study how the presence of sub-galactic subhalos, an inevitable consequence of cold dark matter, can alter the property of caustics and hence change the interpretation of highly magnified sources that lie atop them. First, we consider a galaxy-cluster halo populated with subhalos sampled from a realistic subhalo mass function calibrated to N-body simulations. Then, we compare a semianalytical approximation and an adaptive ray-shooting method that we employ to quantify the property of the caustics. As a case study, we investigate Earendel, a z = 6.2 candidate of magnified single- or multiple-star system with a lone lensed image atop the critical curve in the Sunrise Arc. We find that the source size constraint (≲0.3 pc) previously derived from macrolens models should be relaxed by a factor of a few to 10 when subhalos are accounted for, therefore allowing the possibility of a compact star cluster. The subhalos could introduce an astrometric perturbation that is ≲0$^{"}_{.}$5, which does not contradict observation. These conclusions are largely robust to changes in the subhalo population. Subhalos therefore should be seriously accounted for when interpreting the astrophysical nature of similar highly magnified sources uncovered in recent high-z observations.

Caustic curve↗
DOE OSTI2022

Substructure in the stellar halo near the Sun: I. Data-driven clustering in integrals-of-motion space

Context. Merger debris is expected to populate the stellar haloes of galaxies. In the case of the Milky Way, this debris should be apparent as clumps in a space defined by the orbital integrals of motion of the stars. Aims. Our aim is to develop a data-driven and statistics-based method for finding these clumps in integrals-of-motion space for nearby halo stars and to evaluate their significance robustly. Methods. We used data from Gaia EDR3, extended with radial velocities from ground-based spectroscopic surveys, to construct a sample of halo stars within 2.5 kpc from the Sun. We applied a hierarchical clustering method that makes exhaustive use of the single linkage algorithm in three-dimensional space defined by the commonly used integrals of motion energy E, together with two components of the angular momentum, L z and L ⊥ . To evaluate the statistical significance of the clusters, we compared the density within an ellipsoidal region centred on the cluster to that of random sets with similar global dynamical properties. By selecting the signal at the location of their maximum statistical significance in the hierarchical tree, we extracted a set of significant unique clusters. By describing these clusters with ellipsoids, we estimated the proximity of a star to the cluster centre using the Mahalanobis distance. Additionally, we applied the HDBSCAN clustering algorithm in velocity space to each cluster to extract subgroups representing debris with different orbital phases. Results. Our procedure identifies 67 highly significant clusters (> 3σ), containing 12% of the sources in our halo set, and 232 subgroups or individual streams in velocity space. In total, 13.8% of the stars in our data set can be confidently associated with a significant cluster based on their Mahalanobis distance. Inspection of the hierarchical tree describing our data set reveals a complex web of relations between the significant clusters, suggesting that they can be tentatively grouped into at least six main large structures, many of which can be associated with previously identified halo substructures, and a number of independent substructures. This preliminary conclusion is further explored in a companion paper, in which we also characterise the substructures in terms of their stellar populations. Conclusions. Our method allows us to systematically detect kinematic substructures in the Galactic stellar halo with a data-driven and interpretable algorithm. The list of the clusters and the associated star catalogue are provided in two tables available at the CDS.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Psb27, a photosystem II assembly protein, enables quenching of excess light energy during its participation in the PSII lifecycle

Photosystem II (PSII), the enzyme responsible for oxidizing water into molecular oxygen, undergoes a complex lifecycle during which multiple assembly proteins transiently bind to and depart from PSII assembly intermediate complexes. Psb27 is one such protein. It associates with the CP43 chlorophyll-binding subunit of PSII to form a Psb27-PSII sub-complex that constitutes 7–10% of the total PSII pool. Psb27 remains bound to PSII assembly intermediates and dissociates prior to the formation of fully functional PSII. In this study, we compared a series of Psb27 mutant strains in the cyanobacterium Synechocystis sp. PCC 6803 with varied expression levels of Psb27: wild type (WT); psb27 genetic deletion (Del27), genetically complemented psb27 (Com27); and over-expressed Psb27 (OE27). The Del27 strain demonstrated decreased non-photochemical fluorescence quenching, while the OE27 strain showed increased non-photochemical quenching and tolerance to fluctuating light conditions. Multiple flashes and fluorescence decay analysis indicated that OE27 has the least affected maximum PSII quantum yield of the mutants. OE27 also displayed a minimal impact on the half-life of the fast component of QA – reoxidation over multiple flashes, indicating robust PSII function. Further, we propose that the close association between Psb27 and CP43, and the absence of a fully functional manganese cluster in the Psb27-PSII complex create a PSII sub-population that dissipates excitation energy prior to its recruitment into the functional PSII pool. Efficient energy dissipation prevents damage to this pre-PSII pool and allows for efficient PSII repair and maturation. Participation of Psb27 in the PSII life cycle ensures high-quality PSII assembly.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Unveiling the structural transformations in glassy solid electrolyte adapted to high-stress cycles

Brittleness of glass–ceramic and ceramic ion conductors is considered as a main roadblock for their implementation as electrolytes in solid-state batteries where the fractures often occur due to the pressure exerted by metallic lithium. In this regard, nano- and micro-scale ductility of the solid electrolyte allows reducing such pressure without formation of cracks. Among different types of solid state ion conductors, phosphate invert glasses seem to be promising in achieving such ductility. We report the mechanical behavior of lithium phosphorous oxynitride (LiPON) invert glass probed by static and cyclic nanoindentation. Repeated application of high intensity stress results in densification and shear deformation of material allowing LiPON to accommodate the ~ 22% nominal strain imposed by the nanoindenter without cracking. Ability to do this under repeated loading indicates robustness of LiPON when used in lithium metal batteries under cyclic charge and discharge. Using Raman spectroscopy with unsupervised K-means clustering we reveal pressure-induced formation of P 2 O 7 units which migrate to the periphery of the residual hardness impressions with cycling resulting in surface morphology of LiPON superficially similar to that of deformed bulk metallic glass.

36 MATERIALS SCIENCE↗
DOE OSTI2025

X-ray Absorption Spectroscopy of Dilute Metalloenzymes at X-ray Free-Electron Lasers in a Shot-by-Shot Mode

X-ray absorption spectroscopy (XAS) of 3d transition metals provides important electronic structure information for many fields. However, X-ray-induced radiation damage under physiological temperature has prevented using this method to study dilute aqueous systems, such as metalloenzymes, as the catalytic reaction proceeds. Here we present a new approach to enable operando XAS of dilute biological samples and demonstrate its feasibility with K-edge XAS spectra from the Mn cluster in photosystem II and the Fe–S centers in photosystem I. This approach combines highly efficient sample delivery strategies and a robust signal normalization method with high-transmission Bragg diffraction-based spectrometers at X-ray free-electron lasers (XFELs) in a damage-free, shot-by-shot mode. These photon-out spectrometers have been optimized for discriminating the metal Mn/Fe Kα fluorescence signals from the overwhelming scattering background present on currently available detectors for XFELs that lack suitable energy discrimination. We quantify the enhanced performance metrics of the spectrometer and discuss its potential applications for acquiring time-resolved XAS spectra of biological samples during their reactions at XFELs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Directional clogging and phase separation for disk flow through periodic and diluted obstacle arrays

We model collective disk flow though a square array of obstacles as the flow direction is changed relative to the symmetry directions of the array. At lower disk densities there is no clogging for any driving direction, but as the disk density increases, the average disk velocity decreases and develops a drive angle dependence. For certain driving angles, the flow is reduced or drops to zero when the system forms a heterogeneous clogged state consisting of high density clogged regions coexisting with empty regions. The clogged states are fragile and can be unclogged by changing the driving angle. For large obstacle sizes, we find a uniform clogged state that is distinct from the collective clogging regime. Within the clogged phases, depinning transitions can occur as a function of increasing driving force, with intermittent motion appearing just above the depinning threshold. The clogging is robust against the random removal or dilution of the obstacle sites, and the disks are able to form system-spanning clogged clusters even under increasing dilution. If the dilution becomes too large, however, the clogging behavior is lost.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Cosmological constraints from a joint DESI DR1 Full-Shape and DR2 BAO

We present a cosmological analysis combining full-shape (FS) clustering measurements from the Dark Energy Spectroscopic Instrument (DESI) DR1 with baryon acoustic oscillation (BAO) measurements from DESI DR2. To achieve a robust combination that accounts for the correlation between the two data releases, we employ the ShapeFit compression method and estimate the joint covariance using EZmocks. This compressed approach inherently mitigates the prior volume effects that have previously dominated Bayesian constraints from DESI data with minimal external priors. Consequently, we obtain — for the first time within a Bayesian framework — reliable DESI-only constraints on extensions to ΛCDM using only a Big Bang Nucleosynthesis prior on the baryon density and a wide prior on the spectral index. In flat ΛCDM, we find Ω m = 0.3035 ± 0.0085, h = 0.6876 ± 0.0059, and σ 8 = 0.822 ± 0.034. For the w 0 w a CDM dynamical dark energy model, we measure w 0 = -0.49 ± 0.25 and w a = -1.52 ± 0.77, improving constraints by ∼ 30% relative to the analogous DR1 measurement and reducing the discrepancy with ΛCDM to 1.4σ when compared to BAO only analyses. We also report competitive limits on the sum of neutrino masses and spatial curvature. This work demonstrates that the ShapeFit compression provides a prior-robust and computationally efficient pathway to constrain beyond-ΛCDM physics with large-scale structure.

baryon acoustic oscillations↗
DOE OSTI2023

Optical telecommunications-band clock based on neutral titanium atoms

Here, we propose an optical clock based on ultranarrow transitions in neutral titanium, which exhibit small blackbody radiation and quadratic Zeeman shifts and have wavelengths in the S-, C-, and L-telecommunications fiber bands, allowing for integration with robust laser technology. We calculate relevant properties using a high-precision relativistic hybrid method that combines configuration interaction and coupled-cluster approaches. To identify magic wavelengths, we have completed the largest-to-date direct dynamical polarizability calculations. Finally, we identify challenges that arise from magnetic dipole-dipole interactions and describe an approach to overcome them. A telecommunications-band atomic frequency standard will aid the deployment of optical clock networks and clock comparisons over long distances.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2022

Combining biomarker and virus phylogenetic models improves HIV-1 epidemiological source identification

To identify and stop active HIV transmission chains new epidemiological techniques are needed. Here, we describe the development of a multi-biomarker augmentation to phylogenetic inference of the underlying transmission history in a local population. HIV biomarkers are measurable biological quantities that have some relationship to the amount of time someone has been infected with HIV. To train our model, we used five biomarkers based on real data from serological assays, HIV sequence data, and target cell counts in longitudinally followed, untreated patients with known infection times. The biomarkers were modeled with a mixed effects framework to allow for patient specific variation and general trends, and fit to patient data using Markov Chain Monte Carlo (MCMC) methods. Subsequently, the density of the unobserved infection time conditional on observed biomarkers were obtained by integrating out the random effects from the model fit. This probabilistic information about infection times was incorporated into the likelihood function for the transmission history and phylogenetic tree reconstruction, informed by the HIV sequence data. To critically test our methodology, we developed a coalescent-based simulation framework that generates phylogenies and biomarkers given a specific or general transmission history. Testing on many epidemiological scenarios showed that biomarker augmented phylogenetics can reach 90% accuracy under idealized situations. Under realistic within-host HIV-1 evolution, involving substantial within-host diversification and frequent transmission of multiple lineages, the average accuracy was at about 50% in transmission clusters involving 5–50 hosts. Realistic biomarker data added on average 16 percentage points over using the phylogeny alone. Using more biomarkers improved the performance. Shorter temporal spacing between transmission events and increased transmission heterogeneity reduced reconstruction accuracy, but larger clusters were not harder to get right. More sequence data per infected host also improved accuracy. We show that the method is robust to incomplete sampling and that adding biomarkers improves reconstructions of real HIV-1 transmission histories. The technology presented here could allow for better prevention programs by providing data for locally informed and tailored strategies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Hydrogen Dispersion Modeling for Development of Smart Distributed Monitoring

Studying hydrogen dispersion is crucial for ensuring the safe and effective deployment of hydrogen as an energy carrier. This study presents a comprehensive CFD modeling framework for simulating hydrogen dispersion at a real-world hydrogen production, storage, and utilization facility. Utilizing the Hydrogen Research Facility under the Advanced Research on Integrated Energy Systems (ARIES) at the National Renewable Energy Laboratory's (NREL) Flatirons campus, controlled hydrogen releases at 27 kg-H2/hr were simulated. The model incorporated site-specific atmospheric conditions, including hourly wind speeds and temperatures recorded between 8 AM and 8 PM from October to December 2023. To reduce computational demands, a statistical reduction technique was applied to condense the dataset to 100 representative scenarios, validated by statistical tests for wind speeds and power law coefficients. Simulations were conducted using the Reynolds-Averaged Navier-Stokes equations. Results demonstrated that wind speed substantially influences hydrogen dispersion, with low wind conditions forming concentrated clouds and higher wind speeds stretching the plume. Additionally, clustering analysis informed optimal sensor placement at various elevations with up to 10 sensor locations on each elevation. This framework offers a robust approach for understanding hydrogen behavior in ambient conditions and informing detection strategies.

08 HYDROGEN↗
DOE OSTI2024

Cluster cosmology without cluster finding

ABSTRACT We propose that observations of supermassive galaxies contain cosmological statistical constraining power similar to conventional cluster cosmology, and we provide promising indications that the associated systematic errors are comparably easier to control. We consider a fiducial spectroscopic and stellar mass complete sample of galaxies drawn from the Dark Energy Spectroscopic Instrument (DESI) and forecast how constraints on Ωm–σ8 from this sample will compare with those from number counts of clusters based on richness λ. At fixed number density, we find that massive galaxies offer similar constraints to galaxy clusters. However, a mass-complete galaxy sample from DESI has the potential to probe lower halo masses than standard optical cluster samples (which are typically limited to λ ≳ 20 and Mhalo ≳ 1013.5 M⊙ h−1); additionally, it is straightforward to cleanly measure projected galaxy clustering wp for such a DESI sample, which we show can substantially improve the constraining power on Ωm. We also compare the constraining power of M*-limited samples to those from larger but mass-incomplete samples [e.g. the DESI Bright Galaxy Survey (BGS) sample]; relative to a lower number density M*-limited samples, we find that a BGS-like sample improves statistical constraints by 60 per cent for Ωm and 40 per cent for σ8, but this uses small-scale information that will be harder to model for BGS. Our initial assessment of the systematics associated with supermassive galaxy cosmology yields promising results. The proposed samples have a ∼10 per cent satellite fraction, but we show that cosmological constraints may be robust to the impact of satellites. These findings motivate future work to realize the potential of supermassive galaxies to probe lower halo masses than richness-based clusters and to potentially avoid persistent systematics associated with optical cluster finding.

(cosmology): large-scale structure of Universe↗
DOE OSTI2022

Dark Energy Survey Year 3 results: Cosmological constraints from galaxy clustering and weak lensing

We present the first cosmology results from large-scale structure using the full 5000 deg 2 of imaging data from the Dark Energy Survey (DES) Data Release 1. We perform an analysis of large-scale structure combining three two-point correlation functions ( 3 × 2 pt ): (i) cosmic shear using 100 million source galaxies, (ii) galaxy clustering, and (iii) the cross-correlation of source galaxy shear with lens galaxy positions, galaxy–galaxy lensing. To achieve the cosmological precision enabled by these measurements has required updates to nearly every part of the analysis from DES Year 1, including the use of two independent galaxy clustering samples, modeling advances, and several novel improvements in the calibration of gravitational shear and photometric redshift inference. The analysis was performed under strict conditions to mitigate confirmation or observer bias; we describe specific changes made to the lens galaxy sample following unblinding of the results and tests of the robustness of our results to this decision. We model the data within the flat Λ CDM and w CDM cosmological models, marginalizing over 25 nuisance parameters. We find consistent cosmological results between the three two-point correlation functions; their combination yields clustering amplitude S 8 = 0.77 6 - 0.017 + 0.017 and matter density Ω m = 0.33 9 - 0.031 + 0.032 in Λ CDM , mean with 68% confidence limits; S 8 = 0.77 5 - 0.024 + 0.026 , Ω m = 0.35 2 - 0.041 + 0.035 , and dark energy equation-of-state parameter w = - 0.9 8 - 0.20 + 0.32 in w CDM . These constraints correspond to an improvement in signal-to-noise of the DES Year 3 3 × 2 pt data relative to DES Year 1 by a factor of 2.1, about 20% more than expected from the increase in observing area alone. This combination of DES data is consistent with the prediction of the model favored by the Planck 2018 cosmic microwave background (CMB) primary anisotropy data, which is quantified with a probability-to-exceed p = 0.13 –0.48. We find better agreement between DES 3 × 2 pt and Planck than in DES Y1, despite the significantly improved precision of both. When combining DES 3 × 2 pt data with available baryon acoustic oscillation, redshift-space distortion, and type Ia supernovae data, we find p = 0.34 . Combining all of these datasets with Planck CMB lensing yields joint parameter constraints of S 8 = 0.81 2 - 0.008 + 0.008 , Ω m = 0.30 6 - 0.005 + 0.004 , h = 0.68 0 - 0.003 + 0.004 , and ∑ m ν < 0.13 eV (95% C.L.) in Λ CDM ; S 8 = 0.81 2 - 0.008 + 0.008 , Ω m = 0.30 2 - 0.006 + 0.006 , h = 0.68 7 - 0.007 + 0.006 , and w = - 1.03 1 - 0.027 + 0.030 in w CDM .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Reward Driven Workflows for Unsupervised Explainable Analysis of Phases and Ferroic Variants From Atomically Resolved Imaging Data

Rapid progress in aberration corrected electron microscopy necessitates development of robust methods for the identification of phases, ferroic variants, and other pertinent aspects of materials structure from imaging data. While unsupervised methods for clustering and classification are widely used for these tasks, their performance can be sensitive to hyperparameter selection in the analysis workflow. In this study, the effects of descriptors and hyperparameters are explored on the capability of unsupervised ML methods to distill local structural information, exemplified by the discovery of polarization and lattice distortion in Sm − dopped BiFeO 3 (BFO) thin films. It is demonstrated that a reward-driven approach can be used to optimize these key hyperparameters across the full workflow, where rewards are designed to reflect domain wall continuity and straightness, ensuring that the analysis aligns with the material's physical behavior. This approach allows the discovery of local descriptors that are best aligned with the specific physical behavior, providing insight into the fundamental physics of materials. The reward driven workflow is further extended to disentangle structural factors of variation via an optimized variational autoencoder (VAE). Lastly, the importance of well-defined rewards is explored as a quantifiable measure of the success of the workflow.

Barakati, Kamyar [University of Tennessee, Knoxvil↗
DOE OSTI2026

Revealing the Hidden Third Dimension of Point Defects in Two-Dimensional MXenes

Point defects govern many important functional properties of two-dimensional (2D) materials. However, resolving the three-dimensional (3D) arrangement of these defects in multi-layer 2D materials remains a fundamental challenge, hindering rational defect engineering. Here, we overcome this limitation using an artificial intelligence-guided electron microscopy workflow to map the 3D topology and clustering of atomic vacancies in Ti3C2TX MXene. Our approach reconstructs the 3D coordinates of vacancies across hundreds of thousands of lattice sites, generating robust statistical insight into their distribution that can be correlated with specific synthesis pathways. This large-scale data enables us to classify a hierarchy of defect structures-from isolated vacancies to nanopores-revealing their preferred formation and interaction mechanisms, as corroborated by molecular dynamics simulations. This work provides a generalizable framework for understanding and ultimately controlling point defects across large volumes, paving the way for the rational design of defect-engineered functional 2D materials.

2D materials↗
DOE OSTI2021

Climate warming enhances microbial network complexity and stability

Unravelling the relationships between network complexity and stability under changing climate is a challenging topic in theoretical ecology that remains understudied in the field of microbial ecology. Here, we examined the effects of long-term experimental warming on the complexity and stability of molecular ecological networks in grassland soil microbial communities. Warming significantly increased network complexity, including network size, connectivity, connectance, average clustering coefficient, relative modularity and number of keystone species, as compared with the ambient control. Molecular ecological networks under warming became significantly more robust, with network stability strongly correlated with network complexity, supporting the central ecological belief that complexity begets stability. Furthermore, warming significantly strengthened the relationships of network structure to community functional potentials and key ecosystem functioning. Furthermore, these results indicate that preserving microbial ‘interactions’ is critical for ecosystem management and for projecting ecological consequences of future climate warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Characterizing the target selection pipeline for the Dark Energy Spectroscopic Instrument Bright Galaxy Survey

ABSTRACT We present the steps taken to produce a reliable and complete input galaxy catalogue for the Dark Energy Spectroscopic Instrument (DESI) Bright Galaxy Survey (BGS) using the photometric Legacy Survey DR8 DECam. We analyse some of the main issues faced in the selection of targets for the DESI BGS, such as star–galaxy separation, contamination by fragmented stars and bright galaxies. Our pipeline utilizes a new way to select BGS galaxies using Gaia photometry and we implement geometrical and photometric masks that reduce the number of spurious objects. The resulting catalogue is cross-matched with the Galaxy And Mass Assembly (GAMA) survey to assess the completeness of the galaxy catalogue and the performance of the target selection. We also validate the clustering of the sources in our BGS catalogue by comparing with mock catalogues and the Sloan Digital Sky Survey (SDSS) data. Finally, the robustness of the BGS selection criteria is assessed by quantifying the dependence of the target galaxy density on imaging and other properties. The largest systematic correlation we find is a 7 per cent suppression of the target density in regions of high stellar density.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Cosmological preference for a negative neutrino mass

The most precise determination of the sum of neutrino masses from cosmological data, derived from analysis of the cosmic microwave background (CMB) and baryon acoustic acoustic oscillations (BAO) from the Dark Energy Spectroscopic Instrument (DESI), favors a value below the minimum inferred from neutrino flavor oscillation experiments. We explore which data is most responsible of this puzzling aspect of the current constraints on neutrino mass and whether it is related to other anomalies in cosmology. We demonstrate conclusively that the preference for negative neutrino masses is a consequence of larger than expected lensing of the CMB in both the two- and four-point lensing statistics. Furthermore, we show that this preference is robust to changes in likelihoods of the BAO and CMB optical depth analyses given the available data. We then show that this excess clustering is not easily explained by changes to the expansion history and is likely distinct from the preference for for dynamical dark energy in DESI BAO data. Finally, we discuss how future data may impact these results, including an analysis of Planck CMB with mock DESI 5-year data. Here, we conclude that the negative neutrino mass preference is likely to persist even as more cosmological data is collected in the near future.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗