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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Vortices in low-density neutron matter and cold Fermi gases

Cold gas experiments can be tuned to achieve strongly-interacting regimes such as that of low-density neutron matter found in neutron-stars' crusts. We report T=0 diffusion Monte Carlo results (i) for the ground state of both spin-1/2 fermions with short-range interactions and low-density neutron matter in a cylindrical container, and (ii) properties of these systems with a vortex line excitation. We calculate the equation of state for cold atoms and low-density neutron matter in the bulk systems, and we contrast it to our results in the cylindrical container. We compute the vortex line excitation energy for different interaction strengths, and we find agreement between cold gases and neutron matter for very low densities. We also calculate density profiles, which allow us to determine the density depletion at the vortex core, which depends strongly on the short-ranged interaction in cold atomic gases, but it is of ≈25% for neutron matter in the density regimes studied in this work. Our results can be used to constrain neutron matter properties by using measurements from cold Fermi gases experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Auxiliary function approach for determining symmetry energy at suprasaturation densities

Nuclear symmetry energy E sym (ρ) at density ρ is normally expanded or simply parameterized as a function of χ = (ρ – ρ 0 )/3ρ 0 in the form of Esym(ρ) ≈ S + Lχ + 2 –1 K sym χ 2 + 6 –1 J sym χ 3 + … using its magnitude S, slope L, curvature K sym and skewness J sym at the saturation density ρ0 of nuclear matter. Much progress has been made in recent years in constraining especially the S and L parameters using various terrestrial experiments and astrophysical observations. Furthermore, such kind of expansions/parameterizations do not converge at supra-saturation densities where χ is not small enough, hindering an accurate determination of high-density E sym (ρ) even if its characteristic parameters at ρ0 are all well determined by experiments/observations. By expanding the E sym (ρ) in terms of a properly chosen auxiliary function Π sym (χ,Θ sym ) with a parameter Θsym fixed accurately by an experimental E sym (ρ r ) value at a reference density ρr, we show that the shortcomings of the χ-expansion can be completely removed or significantly reduced in determining the high-density behavior of E sym (ρ). In particular, using two significantly different auxiliary functions, we show that the new approach effectively incorporates higher χ-order contributions and converges to the same E sym (ρ) much faster than the conventional χ-expansion at densities ≲3ρ 0 . Several quantitative demonstrations using Monte Carlo simulations are given.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Higher-order nonequilibrium term: Effective power density quantifying evolution towards or away from local thermodynamic equilibrium

A common approach to assess the nature of energy conversion in a classical fluid or plasma is to compare power densities of the various possible energy conversion mechanisms. A leading research area is quantifying energy conversion for systems that are not in local thermodynamic equilibrium (LTE), as is common in a number of fluid and plasma systems. Here we introduce the “higher-order nonequilibrium term” (HORNET) effective power density, which quantifies the rate of change of departure of a phase space density from LTE. It has dimensions of power density, which allows for quantitative comparisons with standard power densities. We employ particle-in-cell simulations to calculate HORNET during two processes, magnetic reconnection and decaying kinetic turbulence in collisionless magnetized plasmas, that inherently produce non-LTE effects. We investigate the spatial variation of HORNET and the time evolution of its spatial average. By comparing HORNET with power densities describing changes to the internal energy (pressure dilatation, Pi − D , and divergence of the vector heat flux density), we find that HORNET can be a significant fraction of these other measures (8% and 35% for electrons and ions, respectively, for reconnection; up to 67% for both electrons and ions for turbulence), meaning evolution of the system towards or away from LTE can be dynamically important. Applications to numerous plasma phenomena are discussed. Published by the American Physical Society 2024

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2017

First-principles equation-of-state table of silicon and its effects on high-energy-density plasma simulations

Using density-functional theory–based molecular-dynamics simulations, we have investigated the equation of state for silicon in a wide range of plasma density and temperature conditions of ρ=0.001–500g/cm 3 and T=2000–10 8 K. With these calculations, we have established a first-principles equation-of-state (FPEOS) table of silicon for high-energy-density (HED) plasma simulations. When compared with the widely used SESAME-EOS model (Table 3810), we find that the FPEOS-predicted Hugoniot is ~20% softer; for off-Hugoniot plasma conditions, the pressure and internal energy in FPEOS are lower than those of SESAME EOS for temperatures above T ≈ 1–10 eV (depending on density), while the former becomes higher in the low- T regime. The pressure difference between FPEOS and SESAME 3810 can reach to ~50%, especially in the warm-dense-matter regime. Implementing the FPEOS table of silicon into our hydrocodes, we have studied its effects on Si-target implosions. When compared with the one-dimensional radiation-hydrodynamics simulation using the SESAME 3810 EOS model, the FPEOS simulation showed that (1) the shock speed in silicon is ~10% slower; (2) the peak density of an in-flight Si shell during implosion is ~20% higher than the SESAME 3810 simulation; (3) the maximum density reached in the FPEOS simulation is ~40% higher at the peak compression; and (4) the final areal density and neutron yield are, respectively, ~30% and ~70% higher predicted by FPEOS versus the traditional simulation using SESAME 3810. All of these features can be attributed to the larger compressibility of silicon predicted by FPEOS. Furthermore, these results indicate that an accurate EOS table, like the FPEOS presented here, could be essential for the precise design of targets for HED experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Accuracy of ab initio electron correlation and electron densities in vanadium dioxide

Here, diffusion quantum Monte Carlo results are used as a reference to analyze properties related to phase stability and magnetism in vanadium dioxide computed with various formulations of density functional theory. We introduce metrics related to energetics, electron densities and spin densities that give us insight on both local and global variations in the antiferromagnetic M1 and R phases. Importantly, these metrics can address contributions arising from the challenging description of the 3d orbital physics in this material. We observe that the best description of energetics between the structural phases does not correspond to the best accuracy in the charge density, which is consistent with observations made recently by Medvedev et~al. in the context of isolated atoms. However, we do find evidence that an accurate spin density connects to correct energetic ordering of different magnetic states in VO$_2$, although local, semilocal, and meta-GGA functionals tend to erroneously favor demagnetization of the vanadium sites. The recently developed SCAN functional stands out as remaining nearly balanced in terms of magnetization across the M1-R transition and correctly predicting the ground state crystal structure. In addition to ranking current density functionals, our reference energies and densities serve as important benchmarks for future functional development.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Nanoscale mapping of the electron density at Al grain boundaries and correlation with grain-boundary energy

Grain-boundary (GB) structures and energies are often calculated and have revealed correlations between the GB energy and change in electron density at the GB. In this work, the plasmon peak in valence electron energy-loss spectroscopy (VEELS) was used to determine the variation in electron density across four well-characterized GBs in Al, spanning a range of known GB energies. The results show that the plasmon energy is lower at the GB than in the adjacent grains due to a decrease in electron density, and the GB energy increases proportional to the density decrease. The decrease in electron density also extends further into adjacent grains with increasing GB energy, extending beyond the geometric changes, or physical width, revealed by electron microscopy. Plasmon damping also increases with increasing GB energy, indicative of increasing disruption of the electron density with increasing GB energy. These results demonstrate that VEELS can be a valuable tool for detecting small electron density changes at GBs, and this change clearly influences, and is correlated to, the GB energy.

36 MATERIALS SCIENCE↗
DOE OSTI2016

SU-F-T-136: Breath Hold Lung Phantom Study in Using CT Density Versus Relative Stopping Power Ratio for Proton Pencil Beam Scanning System

Purpose: To evaluate mass density effects of CT conversion table and its variation in current treatment planning system of spot scanning proton beam using an IROC proton lung phantom for this study. Methods: A proton lung phantom study was acquired to Imaging and Radiation Oncology Core Houston (IROC) Quality Assurance Center. Inside the lung phantom, GAF Chromic films and couples of thermal luminescent dosimeter (TLD) capsules embedded in specified PTV and adjacent structures to monitor delivered dosage and 3D dose distribution profiles. Various material such as cork (Lung), blue water (heart), Techron HPV (ribs) and organic material of balsa wood and cork as dosimetry inserts within phantom of solid water (soft tissue). Relative stopping power (RLSP) values were provided. Our treatment planning system (TPS) doesn’t require SP instead relative density was converted relative to water. However lung phantom was irradiated by planning with density override and the results were compared with IROC measurements. The second attempt was conducted without density override and compared with IROC’s. Results: The higher passing rate of imaging and measurement results of the lung phantom irradiation met the criteria by IROC without density override. The film at coronal plane was found to be shift due to inclined cylinder insertion. The converted CT density worked as expected to correlate relative stopping power. Conclusion: The proton lung phantom provided by IROC is a useful tool to qualify our commissioned proton pencil beam delivery with TPS within reliable confidence. The relative mass stopping power ratios of materials were converted from the relative physical density relative to water and the results were satisfied.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

Significant DBSCAN+: Statistically Robust Density-based Clustering

Cluster detection is important and widely used in a variety of applications, including public health, public safety, transportation, and so on. Given a collection of data points, we aim to detect density-connected spatial clusters with varying geometric shapes and densities, under the constraint that the clusters are statistically significant. The problem is challenging, because many societal applications and domain science studies have low tolerance for spurious results, and clusters may have arbitrary shapes and varying densities. As a classical topic in data mining and learning, a myriad of techniques have been developed to detect clusters with both varying shapes and densities (e.g., density-based, hierarchical, spectral, or deep clustering methods). However, the vast majority of these techniques do not consider statistical rigor and are susceptible to detecting spurious clusters formed as a result of natural randomness. On the other hand, scan statistic approaches explicitly control the rate of spurious results, but they typically assume a single “hotspot” of over-density and many rely on further assumptions such as a tessellated input space. To unite the strengths of both lines of work, we propose a statistically robust formulation of a multi-scale DBSCAN, namely Significant DBSCAN+, to identify significant clusters that are density connected. As we will show, incorporation of statistical rigor is a powerful mechanism that allows the new Significant DBSCAN+ to outperform state-of-the-art clustering techniques in various scenarios. We also propose computational enhancements to speed-up the proposed approach. Experiment results show that Significant DBSCAN+ can simultaneously improve the success rate of true cluster detection (e.g., 10–20% increases in absolute F1 scores) and substantially reduce the rate of spurious results (e.g., from thousands/hundreds of spurious detections to none or just a few across 100 datasets), and the acceleration methods can improve the efficiency for both clustered and non-clustered data.

Computer Science↗
DOE OSTI2019

Does Breast Density Increase the Risk of Re-excision for Women with Breast Cancer Having Breast-Conservation Therapy?

Background: Women with dense breasts may have less-accurate preoperative evaluation of extent of disease, potentially affecting the achievement of negative margins. The goal of this study is to examine the association between breast density and re-excision rates in women having breast-conserving surgery for invasive breast cancer. Patients and Methods: Women with stage I/II invasive breast cancer treated with breast-conserving surgery between 1/1/2014 and 10/31/2014 were included. Breast density was assessed by two radiologists. The association between breast density and re-excision was examined using logistic regression. Results: Seven hundred and one women were included. Overall, 106 (15.1%) women had at least one re-excision. Younger age at diagnosis was associated with increased breast density (p < 0.001). On univariable analysis, increased breast density was associated with significantly increased odds of re-excision (odds ratio [OR] 1.38, 95% confidence interval [CI] 1.04–1.83), as was multifocal disease, human epidermal growth factor receptor 2 (HER2) positive status, and extensive intraductal component (EIC) (all p < 0.05). On multivariable analysis, breast density remained significantly associated with increased odds of re-excision (OR 1.37, 95% CI 1.00–1.86), as did multifocality and EIC. HER2 positive status was not significantly associated with re-excision on multivariable analysis. Conclusions: Women with dense breasts are more likely to need additional surgery (re-excision after breast-conserving surgery), but increased breast density did not adversely affect disease-free survival in our study. Our findings support the need for further study in developing techniques that can help decrease re-excisions for women with dense breasts who undergo breast-conserving surgery.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2021

A representation-independent electronic charge density database for crystalline materials

In addition to being the core quantity in density functional theory, the charge density can be used in many tertiary analyses in materials sciences from bonding to assigning charge to specific atoms. The charge density is data-rich since it contains information about all the electrons in the system. With increasing utilization of machine-learning tools in materials sciences, a data-rich object like the charge density can be utilized in a wide range of applications. The database presented here provides a modern and user-friendly interface for a large and continuously updated collection of charge densities as part of the Materials Project. In addition to the charge density data, we provide the theory and code for changing the representation of the charge density which should enable more advanced machine-learning studies for the broader community.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Entanglement, partial set of measurements, and diagonality of the density matrix in the parton model

To study quantum properties of the hadron wavefunction at small x, we derived the reduced density matrix for soft gluons in the CGC framework. We explicitly showed that the reduced density matrix is not diagonal in the particle number basis. The off-diagonal components are usually ignored in the conventional parton model. We thus defined the density matrix of ignorance by keeping only the part of the reduced density matrix which can be probed in a limited set of experimental measurements. We calculated Von Neumann entropy for both the reduced and ignorance density matrices. The entropy of ignorance is always greater than the entanglement entropy (computed drom the reduced density matrix) of gluons. Finally, we showed that the CGC reduced density matrix for soft gluons can be diagonalized in a thermal basis with Boltzmann weights suggesting thermalization of new quasi-particle states which we dubbed entangolons.

Duan, Haowu↗
DOE OSTI2018

Solid Oxide Based Electrolysis and Stack Technology with Ultra-High Electrolysis Current Density (>3A/cm 2 ) and Efficiency

Hydrogen, a valuable commodity gas, is increasingly recognized as an important fuel and energy storage pathway of the future. This project aims to develop an innovative solid oxide based electrolysis cell and stack technology with ultra-high steam electrolysis current (>3A/cm 2 ) for potentially ultra-low-cost, highly efficient hydrogen production from diverse renewable sources. In this project, solid oxide based high power density cells (HiPoD cells) were developed. Those cells demonstrated capability of operating at ultra-high electrolysis current density of 6 A/cm 2 at 1.67V. During a long term steady state electrolysis test, a HiPoD cell was operated for more than 1000 hours at 3 A/cm 2 with a low degradation rate of 1.8% per 1000 hours. A 20-cell electrolysis stack was built using HiPoD cells and an ultra-compact, low-cost stack design platform. This stack was used to explore the boundaries of high current density electrolysis operation and achieved an incredible stack current density of 3 A/cm 2 with an average cell voltage of only 1.493 V. The stack was further operated in steady-state electrolysis at 2 A/cm 2 for more than 1000 hours with an overall degradation of 0.57% per 1000 hours. With an improved understanding of electrolysis operation at ultra-high current density, a new compact stack architecture (CSA) design with scalability up to 55 kW (or 38 kg H 2 per day) was tested. A number of 45-cell CSA stack was built and demonstrated 10 kW and 245 g/hr hydrogen production at 1.8 A/cm 2 electrolysis current density. In addition to cell and stack development, a preliminary system design was developed by integrating the inputs from electrochemistry, cell/stack performance data, and system level implications of configuration and operational parameters. A module design was created based on a circular array of six stacks surrounded in a cool pressure vessel. Further architectural and controls strategies such as stack power control and instrumentation were determined through the development of the module. A comprehensive techno-economic study of an ultra-high current density SOEC system integrated with renewable energy sources has been conducted. To determine the estimated cost of hydrogen for the system, the H2A Current Distributed Hydrogen Production Model version 3.101 was applied. Annual system production cases at both commercial and industrial electricity rates as per the H2A model was analyzed. The option of meeting DOE 2020 Advanced Electrolysis Technologies targets were discussed. Feedstock electricity represents the bulk of projected hydrogen cost with either electricity rate. At an annual production volume of 250 units, H2A hydrogen cost of $2.3/kg can be achieved at electricity cost around 3.5¢/kWh.

08 HYDROGEN↗
DOE OSTI2020

Room Temperature Quasi-static Characterization and Constitutive Model Parametrization of Flexible Polyurethane Foams of Different Densities Loaded in Different Orientations

This report describes the efforts to characterize and model General Plastics TF6070 and EF4000 flexible polyurethane foams under room temperature, large deformation quasi-static cyclic mechanical loading conditions. Densities from three to fifteen pound per cubic foot (PCF) are examined, which correspond to relative densities of approximately 4 to 20%. These foams are open cell structured and flexible at room temperature with a glass transition transition less than -30°C, and they fully recover their original shape when unloaded (at room temperature). Uniaxial compression tests were conducted with accompanying lateral image series for Digital Image Correlation (DIC) analysis with the goal of extracting transverse strain responses. Due to difficulties with DIC analysis at large strains, lateral strains were instead extracted for each test via edge tracking. The experimental results exhibit a nonlinear elastic response and anisotropic material behavior (particularly for the lower densities). Some hysteresis is observed that is different between the first and subsequent cycles of deformation indicating both a small degree of permanent damage (reduced stiffness during reloading) and viscoelasticity. These inelastic mechanisms are not considered in the modeling and calibration in this report. This work considers only the rate independent, room temperature foam behavior. Individual foam densities were calibrated for loading in two directions, parallel and perpendicular to the foam bubble rise direction, since the mechanical behavior is different in these two directions. The Flex Foam constitutive model was used for all parameterizations despite the fact that the model is isotropic. A review of the constitutive model is given as well as necessary data reduction procedures to parameterize it for each foam density and orientation are discussed. Finally, two different parameterizations are developed that take the undeformed foam density as an input that span all densities considered. These two parameterized models represent foams loaded in the rise and transverse directions respectively. We summarize the assumptions and limitations of the parameterizations provided in this report to guide analysis choices with them. All parameterizations presented herein have the following traits, room temperature, rate independent, damage-free, and non-dissipative . Isotropy (even if they are representing anisotropic data). Supplied Sierra Solid Mechanics Flex Foam Model Inputs are in units: pounds, inches, Celsius, and seconds

36 MATERIALS SCIENCE↗
DOE OSTI2021

(U) A Linear Response Model Predicts Reactivity From a Density Profile

We tested the ability to predict the system reactivity, described by alpha, given a density profile using a simple linear system response. We generated a suite of 1-dimensional density profiles that consisted of nominal density, a discontinuity, and a decay. These profiles were prescribed a functional form and the mass was conserved in all cases. From these density profiles, we calculated the alpha value of the 3-dimensional system.We calculated a linear response function given a training set of the 1-dimensional density profiles, and the system reactivity described by alpha. We tested the robustness of the response function using the remaining test data. Our results showed very good agreement between the predicted and calculated test values, where the distribution of alpha differences was centered about zero and had a standard deviation of 0.005 gens/shake. The predicted and calculated alpha values did not significantly differ (t=-0.0009 p<0.99). We used Singular Value Decomposition (SVD) to reduce the matrix rank by retaining95% of the cumulative singular value contributions. This reduced the matrix rank by 91.7%. We generated the linear response matrix and calculated the difference between the predicted and calculated alpha values. Using the reduced order matrix, we showed good agreement between the predicted and calculated alpha values where the distribution of differences was centered near zero, the standard deviation was 0.006 gens/shake, and the statistical t-test showed good agreement (t=0.02, p<0.98). These results show a linear relationship between a series of 1-dimensional density profiles,where the mass was conserved, and the system reactivity. The next steps of this work will be to investigate the linear response using 2-dimensional density profiles.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

High Flux Isotope Reactor Low-Enriched Uranium Low Density Silicide Fuel Design Parameters

High Flux Isotope Reactor (HFIR) highly enriched uranium (HEU) to low-enriched uranium (LEU) conversion activities are ongoing as part of the Department of Energy (DOE) National Nuclear Security Administration (NNSA)’s nuclear nonproliferation mission. Design activities studying the conversion of HFIR from HEU to LEU fuel explored different fuel design features and shapes with a low density uranium-silicide dispersion (U 3 Si 2 -Al) fuel, which has a uranium density of 4.8 gU/cm 3 . The goal of these studies is to generate several HFIR LEU fuel designs of varying fuel fabrication complexity that meet the current HEU performance metrics and safety requirements. The documented designs will serve as references for fuel fabrication and qualification activities. Recent advancements in modeling and simulation tools enable quick prototyping of fuel designs. Shift, a Monte Carlo neutron transport and depletion tool optimized for high-performance computing (HPC) architectures, is used for efficient fuel cycle and performance metrics calculations. The HFIR Steady State Heat Transfer Code (HSSHTC) is used to vet the thermal safety margin. Also, a new automation tool that connects all fuel design analysis steps, named Python HFIR Analysis and Measurement Engine (PHAME), has been developed to expedite the design study in an efficient and reproducible manner. Leveraging these tools, several candidate fuel designs were selected for varying fabrication complexity. This report provides design feature details for four selected HFIR LEU low density U 3 Si 2 -Al fuel designs and their corresponding performance and safety metrics. Nominal, best-estimate design parameters and irradiation conditions, including fission rate densities, power densities, heat fluxes, and cumulative fission densities are provided for candidate fuel designs relevant to framing irradiation experiments to support fuel qualification efforts. Simulations show that the low density U 3 Si 2 -Al, with design features to enhance safety, can meet HEU core performance metrics and safety requirements if the reactor power is increased from 85 MW (HEU) to 95 MW (LEU) and if the active fuel length is increased from 50.80 cm (HEU) to 55.88 cm (LEU).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

The SPLASH Survey: Quiescent galaxies are more strongly clustered but are not necessarily located in high-density environments

We use the stellar-mass-selected catalog from the Spitzer Large Area Survey with Hyper-Suprime-Cam (SPLASH) in the COSMOS field to study the environments of galaxies via galaxy density and clustering analyses up to z∼2.5. The clustering strength of quiescent galaxies exceeds that of star-forming galaxies, implying that quiescent galaxies are preferentially located in more massive halos. When using local density measurement, we find a clear positive quiescent fraction–density relation at z<1, consistent with earlier results. However, the quiescent fraction–density relation reverses its trend at intermediate redshifts (1 1.5, the quiescent fraction depends little on the local density, even though clustering shows that quiescent galaxies are in more massive halos. We argue that at high redshift the typical halo size falls below 10{sup 13} , where intrinsically the local density measurements are so varied that they do not trace the halo mass. Our results thus suggest that in the high-redshift universe, halo mass may be the key in quenching the star formation in galaxies, rather than the conventionally measured galaxy density.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Quantifying How Density Gradients and Front Curvature Affect Carbon Detonation Strength during SNe Ia

Accurately reproducing the physics behind the detonations of SNe Ia and the resultant nucleosynthetic yields is important for interpreting observations of spectra and remnants. The scales of the processes involved span orders of magnitudes, making the problem computationally impossible to ever fully resolve in full-star simulations in the present and near future. In the lower density regions of the star, the curvature of the detonation front will slow the detonation, affecting the production of intermediate mass elements. We find that shock strengthening due to the density gradient present in the outer layers of the progenitor is essential for understanding the nucleosynthesis there, with burning extending well below the density at which a steady-state detonation is extinct. We show that a complete reaction network is not sufficient to obtain physical detonations at high densities and modest resolution due to numerical mixing at the unresolved reaction front. At low densities, below 6 × 10 5 g cm -3 , it is possible to achieve high enough resolution to separate the shock and the reaction region, and the abundance structure predicted by fully resolved quasi-steady-state calculations is obtained. For our best current benchmark yields, we utilize a method in which the unresolved portion of Lagrangian histories are reconstructed based on fully resolved quasi-steady-state detonation calculations. These computations demonstrate that under-resolved simulations agree approximately, ~10% in post-shock values of temperature, pressure, density, and abundances, with expected detonation structures sufficiently far from the under-resolved region, but that there is still room for some improvement in the treatment of subgrid reactions in the hydrodynamics to before better than 1% can be achieved at all densities.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

A measurement of $H_0$ from DESI DR1 using energy densities

We present a new measurement of the Hubble constant, independent of standard rulers and robust to pre-recombination modifications such as Early Dark Energy (EDE), obtained by calibrating the total energy density of the Universe. We start using the present-day photon density as an anchor, and use the baryon-to-photon ratio from Big Bang Nucleosynthesis based measurements and the baryon-to-matter ratio from the baryons' imprint on galaxy clustering to translate to a physical matter density at present day. We then compare this to measurements of the ratio of the matter density to the critical density ($Ω_{\mathrm{m}}$), calculated using the relative positions of the baryon acoustic oscillations, to measure the critical density of the universe and hence $H_0$. The important measurements of the evolution of the energy density all happen at low redshift, so we consider this a low-redshift measurement. We validate our method both on a suite of $N$-body mocks and on noiseless theory vectors generated across a wide range of Hubble parameters in both $Λ$CDM and EDE cosmologies. Using DESI DR1 data combined with the angular CMB acoustic scale and the latest BBN constraints, we find $H_0 = 69.0 \pm 2.5$ km s$^{-1}$ Mpc$^{-1}$, consistent with existing early and late-time determinations of the Hubble constant. We consider the impact of non-standard dark energy evolution on our measurement. Future data, including that from further iterations of DESI and from Euclid, will add to these results providing a powerful test of the Hubble tension.

Krolewski, Alex [U. Waterloo (main); Waterloo U., ↗