Search NASA⌕ Search

SEARCH · Search NASA

Results for “POPULATION”

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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

The Extended Field-Aligned Suprathermal Proton Beam and Long-Lasting Trapped Energetic Particle Population Observed Upstream of a Transient Interplanetary Shock

The properties of the suprathermal particle distributions observed upstream of interplanetary shocks depend not only on the properties of the shocks but also on the transport conditions encountered by the particles as they propagate away from the shocks. The confinement of particles in close proximity to the shocks, as well as particle scattering processes during propagation to the spacecraft, lead to the common observation of upstream diffuse particle distributions. We present observations of a rare extended anisotropic low-energy(≤30 keV)proton beam together with a trapped ≥500 keV proton population observed in association with the arrival of an oblique interplanetary shock at the Advanced Composition Explorer, the Interplanetary Monitoring Platform-8, and the Wind spacecraft on 2001 January 31. Continuous injection of particles by the traveling shock into a smooth radial magnetic field region formed in the tail of a modest high-speed solar wind stream produced an extended foreshock region of energetic particles. The absence of enhanced magnetic field fluctuations upstream of the shock results in the observation of a prolonged anisotropic field-aligned beam of ≤30 keV protons as well as a population of higher-energy(≥500 keV)protons with small pitch-angle cosine(μ∼0)extending far from the shock.

D. Lario↗
NASA NTRS2024

Tracing Presolar Grain Populations Through Matrix Alteration Histories

Primitive meteorites preserve remnants of evolved stars as presolar grains, from asymptotic and red giant branch stars, novae and supernovae. These grains retain records of the formation mechanisms of the stellar environment from which they condensed, as well as physical and chemical processes in the interstellar medium (ISM), solar nebula and the parent bodies in which they are found. Consequently, their study can refine our understanding of the solar system and external stellar and planetary systems. However, presolar grains and their records can be altered, re-equilibrated with the surrounding matrix, and eventually lost through aqueous and thermal processing on the meteorite parent body. NanoSIMS is the most rapid and effective method for in situ identification of presolar grains via their highly anomalous isotopic ratios. Previous studies have measured variations in presolar grain populations between different matrix regions within the same meteorite thin section. However, most of these studies do not identify if there are any ties between these variations in presolar grain populations and the chemical and mineralogical differences in measured matrix regions. Therefore, the goal of this study is to determine if there is measurable variations in the degree of alteration of different matrix regions within the same thin section, and if mineralogical and chemical changes in matrix regions can be used as indicators for presolar grain preservation. Such a correlation could improve the efficiency of presolar grain identification during searches across large surface areas. To do this, we carried out coordinated scanning electron microscope (SEM) and NanoSIMS analyses, using a new SEM method which measures the ppm concentration of 100 nm to 5 μm sized Mg-, S-, Al-, C- and Ca-rich matrix grains.

presolar grains↗
NASA NTRS2024

SupportU: Smart UAS Program for the Population by Offering Resources and Tools to the Unhoused

Global warming, challenging economic conditions, the opioid epidemic, and other widespread problems, have impacted people globally, particularly over the past several years. Preventable diseases like the common cold and the effects of heat stroke have become increasingly prevalent due to these issues. It is estimated that 150 million people of the world’s population are unhoused globally, with many dwelling in unsafe and unsanitary conditions while lacking access to basic hygienic items and other essentials. Unsanitary conditions coupled with this lack of access exacerbates and prolongs health problems and harms quality of life. Traditional methods of aid, such as homeless shelters and meal programs, face numerous challenges such as having limited reach and resources. To address these problems, the Smart UAS Program for the Population by Offering Resources and Tools to the Unhoused (SUPPORT U) utilizes Uncrewed Aircraft Systems (UAS) to deliver resources to the unhoused and those in need of basic aid, prior to and during extreme temperature conditions, and after natural disasters in rural, suburban, and urban areas. The UA is envisioned to be an autonomous aircraft capable of efficiently distributing essential supplies, including blankets, water, food, and medicine. The UAS fleet relies on advanced navigation and communication technologies to accurately identify unhoused people and efficiently and safely distribute materials to them. This will be done through a machine learning algorithm. By focusing on identified “homeless clusters”, places where unhoused individuals are concentrated, the UAS network increases access to critical resources, thereby helping to mitigate some of the external risks to the health of unhoused individuals. The UA can also be used during crises, such as by transporting supplies to medical tents that are stationed in difficult-to-reach areas suffering from natural disasters.

Samuel Beard↗
DOE OSTI2024

Population-level Dark Energy Constraints from Strong Gravitational Lensing using Simulation-Based Inference

In this work, we present a scalable approach for inferring the dark energy equation-of-state parameter ($w$) from a population of strong gravitational lens images using Simulation-Based Inference (SBI). Strong gravitational lensing offers crucial insights into cosmology, but traditional Monte Carlo methods for cosmological inference are computationally prohibitive and inadequate for processing the thousands of lenses anticipated from future cosmic surveys. New tools for inference, such as SBI using Neural Ratio Estimation (NRE), address this challenge effectively. By training a machine learning model on simulated data of strong lenses, we can learn the likelihood-to-evidence ratio for robust inference. Our scalable approach enables more constrained population-level inference of $w$ compared to individual lens analysis, constraining $w$ to within $1\sigma$. Our model can be used to provide cosmological constraints from forthcoming strong lens surveys, such as the 4MOST Strong Lensing Spectroscopic Legacy Survey (4SLSLS), which is expected to observe 10,000 strong lenses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Population-level Dark Energy Constraints from Strong Gravitational Lensing using Simulation-Based Inference

In this work, we present a scalable approach for inferring the dark energy equation-of-state parameter ($w$) from a population of strong gravitational lens images using Simulation-Based Inference (SBI). Strong gravitational lensing offers crucial insights into cosmology, but traditional Monte Carlo methods for cosmological inference are computationally prohibitive and inadequate for processing the thousands of lenses anticipated from future cosmic surveys. New tools for inference, such as SBI using Neural Ratio Estimation (NRE), address this challenge effectively. By training a machine learning model on simulated data of strong lenses, we can learn the likelihood-to-evidence ratio for robust inference. Our scalable approach enables more constrained population-level inference of $w$ compared to individual lens analysis, constraining $w$ to within 1$\sigma$. Our model can be used to provide cosmological constraints from forthcoming strong lens surveys, such as the 4MOST Strong Lensing Spectroscopic Legacy Survey (4SLSLS), which is expected to observe 10,000 strong lenses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Coherent population trapping and spin relaxation of a silicon vacancy center in diamond at millikelvin temperatures

Here, we report experimental studies of coherent population trapping (CPT) and spin relaxation in a temperature range 4 K–100 mK in a silicon vacancy (SiV) center subject to a transverse magnetic field. The spin linewidth, which is determined by spin dephasing, is extracted from power dependent CPT linewidths. Near and below 1 K, phonon-induced spin dephasing becomes negligible compared with that induced by the spin bath of naturally abundant 13 C atoms. The temperature dependence of the spin dephasing rates agrees with the theoretical expectation that phonon-induced spin dephasing arises primarily from orbital relaxation induced by first order electron-phonon interactions. A nearly 100-fold increase in spin lifetime is observed when the temperature is lowered from 4 K to slightly below 1 K, indicating that two-phonon spin-flip transitions play an essential role in the spin relaxation of SiV ground states.

36 MATERIALS SCIENCE↗