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

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At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Some exact anisotropic solutions via Noether symmetry in f(R) gravity

We attempt to find exact solutions of the Bianchi I model in f(R) gravity using the Noether symmetry approach. For this purpose, we take a perfect fluid and formulate conserved quantities for the power-law f(R) model. We discuss some cosmological parameters for the resulting solution which are responsible for expanding behavior of the universe. We also explore Noether gauge symmetry and the corresponding conserved quantity. It is concluded that symmetry generators as well as conserved quantities exist in all cases and the behavior of cosmological parameters shows consistency with recent observational data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Probing the Neutrino-Mass Scale with the KATRIN Experiment

The absolute mass scale of neutrinos is an intriguing open question in contemporary physics. The as-yet-unknown mass of the lightest and, at the same time, most abundant massive elementary particle species bears fundamental relevance to theoretical particle physics, astrophysics, and cosmology. The most model-independent experimental approach consists of precision measurements of the kinematics of weak decays, notably tritium β decay. With the KATRIN experiment, this direct neutrino-mass measurement has entered the sub-eV domain, recently pushing the upper limit on the electron-based neutrino mass down to 0.8 eV (90% CL) on the basis of first-year data out of ongoing, multiyear operations. Here, we review the experimental apparatus of KATRIN, the progress of data taking, and initial results. While KATRIN is heading toward the target sensitivity of 0.2 eV, other scientific goals are pursued. We discuss the search for light sterile neutrinos and an outlook on future keV-scale sterile-neutrino searches as well as further physics opportunities beyond the Standard Model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

X-Ray Morphological Analysis of the Planck ESZ Clusters

X-ray observations show that galaxy clusters have a very large range of morphologies. The most disturbed systems, which are good to study how clusters form and grow and to test physical models, may potentially complicate cosmological studies because the cluster mass determination becomes more challenging. Thus, we need to understand the cluster properties of our samples to reduce possible biases. This is complicated by the fact that different experiments may detect different cluster populations. For example, Sunyaev–Zeldovich (SZ) selected cluster samples have been found to include a greater fraction of disturbed systems than X-ray selected samples. In this paper we determine eight morphological parameters for the Planck Early Sunyaev–Zeldovich (ESZ) objects observed with XMM-Newton . We found that two parameters, concentration and centroid shift, are the best to distinguish between relaxed and disturbed systems. For each parameter we provide the values that allow selecting the most relaxed or most disturbed objects from a sample. We found that there is no mass dependence on the cluster dynamical state. By comparing our results with what was obtained with REXCESS clusters, we also confirm that the ESZ clusters indeed tend to be more disturbed, as found by previous studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Toward Rate Estimation for Transient Surveys. I. Assessing Transient Detectability and Volume Sensitivity for iPTF

The past couple of decades have seen an emergence of transient detection facilities in various avenues of time-domain astronomy that have provided us with a rich data set of transients. The rates of these transients have implications in star formation, progenitor models, evolution channels, and cosmology measurements. The crucial component of any rate calculation is the detectability and spacetime volume sensitivity of a survey to a particular transient type as a function of many intrinsic and extrinsic parameters. Fully sampling that multidimensional parameter space is challenging. Instead, we present a scheme to assess the detectability of transients using supervised machine learning. The data product is a classifier that determines the detection likelihood of sources resulting from an image subtraction pipeline associated with time-domain survey telescopes, taking into consideration the intrinsic properties of the transients and the observing conditions. We apply our method to assess the spacetime volume sensitivity of type Ia supernovae (SNe Ia) in the intermediate Palomar Transient Factory (iPTF) and obtain the result, ⟨ VT ⟩ Ia = (2.93 ± 0.21) × 10 -2 Gpc 3 yr. With rate estimates in the literature, this volume sensitivity gives a count of 680-1160 SNe Ia detectable by iPTF, which is consistent with the archival data. With a view toward wider applicability of this technique we do a preliminary computation for long-duration type IIp supernovae (SNe IIp) and find ⟨ VT ⟩ IIa = (7.80 ± 0.76) × 10 -4 Gpc 3 yr. This classifier can be used for computationally fast spacetime volume sensitivity calculation of any generic transient type using their light-curve properties. Hence, it can be used as a tool to facilitate calculation of transient rates in a range of time-domain surveys, given suitable training sets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Simultaneous Estimation of Large-scale Structure and Milky Way Dust Extinction from Galaxy Surveys

The high cosmological precision offered by the next generation of galaxy surveys hinges on improved corrections for Galactic dust extinction. We explore the possibility of estimating both the dust extinction and large-scale structure from a single photometric galaxy survey, making use of the predictable manner in which Milky Way dust affects the measured brightness and colors of galaxies in a given sky location in several redshift bins. To test our method, we use a synthetic catalog from a cosmological simulation designed to model the Vera C. Rubin Observatory Legacy Survey of Space and Time. At high Galactic latitude (|b| ≳ 20°) and a resolution of 1° (7'), we predict the uncertainty in the measurement of dust extinction, E(B - V), to be 0.005 mag (0.015 mag). This is similar to the uncertainty of existing dust maps, illustrating the feasibility of our method. Simultaneous estimation of large-scale structure is predicted to recover the galaxy overdensity δ with a precision of ~0.01 (~0.05) at 1° (7') resolution. Finally, we also introduce a Bayesian formalism that combines prior information from existing dust maps with the likelihood of Galactic dust extinction determined from the excursion of observed galaxy properties.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1977

Interpretation of observed cosmic microwave background radiation

It is argued that the 'surface of last scattering' of the observed microwave background radiation corresponds to the distribution of dust in galaxies or protogalaxies with a temperature of about 110 K at the epoch corresponding to Z roughly equal to 40. This is in contrast with the plasma temperature of over 3,000 K at an earlier epoch (Z greater than about 1,000), as given by the canonical model of big bang cosmologies. In view of this, the claim that the microwave background radiation lends strong support to hot big bang cosmologies is without foundation.

Alfven, H.↗
NASA NTRS1990

Curvature-squared cosmology in the first-order formalism

Variation of the R + alpha-R-squared action with respect to independent metric and connection fields is shown to be equivalent to the metric-compatible fourth-order gravity coupled to a vector defined as a function of the trace of the energy-momentum tensor. The field equations are second order. The Friedmann cosmology based on this model is studied and it is shown to include nonsingular solutions at t = 0.

Shahid-Saless, Bahman↗
NASA NTRS1992

Galaxy clusters and cold dark matter - A low-density unbiased universe?

Large-scale simulations of a universe dominated by cold dark matter (CDM) are tested against two fundamental properties of clusters of galaxies: the cluster mass function and the cluster correlation function. We find that standard biased CDM models are inconsistent with these observations for any bias parameter b. A low-density, low-bias CDM-type model, with or without a cosmological constant, appears to be consistent with both the cluster mass function and the cluster correlations. The low-density model agrees well with the observed correlation function of the Abell, Automatic Plate Measuring Facility (APM), and Edinburgh-Durham cluster catalogs. The model is in excellent agreement with the observed dependence of the correlation strength on cluster mean separation, reproducing the measured universal dimensionless cluster correlation. The low-density model is also consistent with other large-scale structure observations, including the APM angular galaxy-correlations, and for lambda = 1-Omega with the COBE results of the microwave background radiation fluctuations.

Bahcall, Neta A.↗
DOE OSTI2024

Multiscale Flow for robust and optimal cosmological analysis

We propose Multiscale Flow, a generative Normalizing Flow that creates samples and models the field-level likelihood of two-dimensional cosmological data such as weak lensing. Multiscale Flow uses hierarchical decomposition of cosmological fields via a wavelet basis and then models different wavelet components separately as Normalizing Flows. The log-likelihood of the original cosmological field can be recovered by summing over the log-likelihood of each wavelet term. This decomposition allows us to separate the information from different scales and identify distribution shifts in the data such as unknown scale-dependent systematics. The resulting likelihood analysis can not only identify these types of systematics, but can also be made optimal, in the sense that the Multiscale Flow can learn the full likelihood at the field without any dimensionality reduction. We apply Multiscale Flow to weak lensing mock datasets for cosmological inference and show that it significantly outperforms traditional summary statistics such as power spectrum and peak counts, as well as machine learning–based summary statistics such as scattering transform and convolutional neural networks. We further show that Multiscale Flow is able to identify distribution shifts not in the training data such as baryonic effects. Finally, we demonstrate that Multiscale Flow can be used to generate realistic samples of weak lensing data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Bridging the Gap between Cosmological Simulations with Graph Neural Networks and Domain Adaptation

Deep learning models have been shown to outperform methods that rely on summary statistics, like the power spectrum, in extracting information from complex cosmological data sets. However, due to differences in the subgrid physics implementation and numerical approximations across different simulation suites, models trained on data from one cosmological simulation show a drop in performance when tested on another. Similarly, models trained on any of the simulations would also likely experience a drop in performance when applied to observational data. Training on data from two different suites of the CAMELS hydrodynamic cosmological simulations, we examine the generalization capabilities of Domain Adaptive Graph Neural Networks (DA-GNNs). By utilizing GNNs, we capitalize on their capacity to capture structured scale-free cosmological information from galaxy distributions. Moreover, by including unsupervised domain adaptation via Maximum Mean Discrepancy (MMD), we enable our models to extract domain-invariant features. We demonstrate that DA-GNN achieves higher accuracy and robustness on cross dataset tasks (up to 28% better relative error and up to almost an order of magnitude better χ 2 ). Using data visualizations, we show the effects of domain adaptation on proper latent space data alignment. This shows that DA-GNNs are a promising method for extracting domain-independent cosmological information, a vital step toward robust deep learning for real cosmic survey data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Can assembly bias explain the lensing amplitude of the BOSS CMASS sample in a Planck cosmology?

ABSTRACT In this paper, we investigate whether galaxy assembly bias can reconcile the 20–40 ${{\ \rm per\ cent}}$ disagreement between the observed galaxy projected clustering signal and the galaxy–galaxy lensing signal in the Baryon Oscillation Spectroscopic Survey CMASS galaxy sample. We use the suite of abacuscosmos lambda cold dark matter simulations at Planck best-fitting cosmology and two flexible implementations of extended halo occupation distribution (HOD) models that incorporate galaxy assembly bias to build forward models and produce joint fits of the observed galaxy clustering signal and the galaxy–galaxy lensing signal. We find that our models using the standard HODs without any assembly bias generalizations continue to show a 20–40 ${{\ \rm per\ cent}}$ overprediction of the observed galaxy–galaxy lensing signal. We find that our implementations of galaxy assembly bias do not reconcile the two measurements at Planck best-fitting cosmology. In fact, despite incorporating galaxy assembly bias, the satellite distribution parameter, and the satellite velocity bias parameter into our extended HOD model, our fits still strongly suggest a $\sim \! 34{{\ \rm per\ cent}}$ discrepancy between the observed projected clustering and galaxy–galaxy lensing measurements. It remains to be seen whether a combination of other galaxy assembly bias models, alternative cosmological parameters, or baryonic effects can explain the amplitude difference between the two signals.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Multi-component Dark Matter and small scale structure formation

We consider the evolution of non-thermal dark matter perturbations in models which contain both Weakly Interacting Massive Particles (WIMPs) and axions. Using constraints from existing observations we examine the percentage of WIMPs and axions that may comprise the cosmological dark matter budget in models with an Early Matter Dominated Epoch (EMDE) — where entropy production is important. After carefully tracking the thermal evolution of the various species by solving the Boltzmann equations, we consider the enhancement of perturbations that may have led to early structure formation for axions and WIMPs. We investigate the impact of enhanced perturbations on the parameter space of both species, after imposing existing constraints from indirect detection experiments. Given these constraints we establish the feasibility of axions to form miniclusters in the early universe in EMDEs for a given percentage of allowed WIMPs. We find that EMDEs with low reheat temperatures near the BBN limit are preferred for axion minicluster formation. When the EMDE is caused by string moduli, the WIMP contribution to the relic density is set by the moduli branching to dark matter at the level of ≲ $\mathcal{O}$ (10 −4 ).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Completely dark matter from rapid-turn multifield inflation

We study cosmological gravitational particle production as applied to “rapid-turn” models of inflation involving two scalar fields. We are interested in the production of massive spin-0 particles that only interact gravitationally and provide a candidate for the dark matter. Specifically, we study two models of rapid-turn multifield inflation, motivated in part by the de Sitter swampland conjecture, that are distinguished by the curvature of field space and the presence or absence of field space ‘angular momentum’ conservation. We find that one of these models leads to insufficient particle production and cannot explain the observed dark matter relic abundance. The second model is able to explain the origin of spin-0 dark matter via gravitational production, and we identify the relevant region of parameter space that is consistent with measurements of the dark-matter relic abundance, the dark-matter-photon isocurvature perturbations, and the spectrum of curvature perturbations that is probed by cosmological observations. Our work demonstrates the compatibility of the de Sitter swampland conjecture with completely dark matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

CFTs blueshift tensor fluctuations universally

The strong constraints of conformal symmetry cause any nearly-conformal sector to blueshift tensor fluctuations in cosmology. Hidden sectors with approximate conformal symmetry, which may be quite large, are a well-motivated extension of physics beyond the Standard Models of particle physics and cosmology. They can therefore lead to a detectable shift in the tensor tilt for next-generation CMB and gravitational wave experiments. Here, we compute the leading-order contribution to the in-in graviton two-point function from virtual loops in such sectors to demonstrate this universal effect. In units where a single conformally-coupled scalar is 1, limits from Stage-IV CMB experiments could bound the size of this extra sector to be smaller than ~10 15 , under a plausible calculational assumption backed by a simple power counting argument. This would be sufficient to rule out N-Naturalness as a complete resolution of the hierarchy problem.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Debiasing with Diffusion: Probabilistic Reconstruction of Dark Matter Fields from Galaxies with CAMELS

Abstract Galaxies are biased tracers of the underlying cosmic web, which is dominated by dark matter (DM) components that cannot be directly observed. Galaxy formation simulations can be used to study the relationship between DM density fields and galaxy distributions. However, this relationship can be sensitive to assumptions in cosmology and astrophysical processes embedded in galaxy formation models, which remain uncertain in many aspects. In this work, we develop a diffusion generative model to reconstruct DM fields from galaxies. The diffusion model is trained on the CAMELS simulation suite that contains thousands of state-of-the-art galaxy formation simulations with varying cosmological parameters and subgrid astrophysics. We demonstrate that the diffusion model can predict the unbiased posterior distribution of the underlying DM fields from the given stellar density fields while being able to marginalize over uncertainties in cosmological and astrophysical models. Interestingly, the model generalizes to simulation volumes ≈500 times larger than those it was trained on and across different galaxy formation models. The code for reproducing these results can be found athttps://github.com/victoriaono/variational-diffusion-cdm✎.

Astronomy & Astrophysics↗