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Nearby Massive Star Cluster Yields Insights into Early Universe
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By NASA
NASA’s Dawn spacecraft captured this image of Vesta as it left the giant asteroid’s orbit in 2012. The framing camera was looking down at the north pole, which is in the middle of the image.NASA/JPL-Caltech/UCLA/MPS/DLR/IDA Known as flow formations, these channels could be etched on bodies that would seem inhospitable to liquid because they are exposed to the extreme vacuum conditions of space.
Pocked with craters, the surfaces of many celestial bodies in our solar system provide clear evidence of a 4.6-billion-year battering by meteoroids and other space debris. But on some worlds, including the giant asteroid Vesta that NASA’s Dawn mission explored, the surfaces also contain deep channels, or gullies, whose origins are not fully understood.
A prime hypothesis holds that they formed from dry debris flows driven by geophysical processes, such as meteoroid impacts, and changes in temperature due to Sun exposure. A recent NASA-funded study, however, provides some evidence that impacts on Vesta may have triggered a less-obvious geologic process: sudden and brief flows of water that carved gullies and deposited fans of sediment. By using lab equipment to mimic conditions on Vesta, the study, which appeared in Planetary Science Journal, detailed for the first time what the liquid could be made of and how long it would flow before freezing.
Although the existence of frozen brine deposits on Vesta is unconfirmed, scientists have previously hypothesized that meteoroid impacts could have exposed and melted ice that lay under the surface of worlds like Vesta. In that scenario, flows resulting from this process could have etched gullies and other surface features that resemble those on Earth.
To explore potential explanations for deep channels, or gullies, seen on Vesta, scientists used JPL’s Dirty Under-vacuum Simulation Testbed for Icy Environments, or DUSTIE, to simulate conditions on the giant asteroid that would occur after meteoroids strike the surface.NASA/JPL-Caltech But how could airless worlds — celestial bodies without atmospheres and exposed to the intense vacuum of space — host liquids on the surface long enough for them to flow? Such a process would run contrary to the understanding that liquids quickly destabilize in a vacuum, changing to a gas when the pressure drops.
“Not only do impacts trigger a flow of liquid on the surface, the liquids are active long enough to create specific surface features,” said project leader and planetary scientist Jennifer Scully of NASA’s Jet Propulsion Laboratory in Southern California, where the experiments were conducted. “But for how long? Most liquids become unstable quickly on these airless bodies, where the vacuum of space is unyielding.”
The critical component turns out to be sodium chloride — table salt. The experiments found that in conditions like those on Vesta, pure water froze almost instantly, while briny liquids stayed fluid for at least an hour. “That’s long enough to form the flow-associated features identified on Vesta, which were estimated to require up to a half-hour,” said lead author Michael J. Poston of the Southwest Research Institute in San Antonio.
Launched in 2007, the Dawn spacecraft traveled to the main asteroid belt between Mars and Jupiter to orbit Vesta for 14 months and Ceres for almost four years. Before ending in 2018, the mission uncovered evidence that Ceres had been home to a subsurface reservoir of brine and may still be transferring brines from its interior to the surface. The recent research offers insights into processes on Ceres but focuses on Vesta, where ice and salts may produce briny liquid when heated by an impact, scientists said.
Re-creating Vesta
To re-create Vesta-like conditions that would occur after a meteoroid impact, the scientists relied on a test chamber at JPL called the Dirty Under-vacuum Simulation Testbed for Icy Environments, or DUSTIE. By rapidly reducing the air pressure surrounding samples of liquid, they mimicked the environment around fluid that comes to the surface. Exposed to vacuum conditions, pure water froze instantly. But salty fluids hung around longer, continuing to flow before freezing.
The brines they experimented with were a little over an inch (a few centimeters) deep; scientists concluded the flows on Vesta that are yards to tens of yards deep would take even longer to refreeze.
The researchers were also able to re-create the “lids” of frozen material thought to form on brines. Essentially a frozen top layer, the lids stabilize the liquid beneath them, protecting it from being exposed to the vacuum of space — or, in this case the vacuum of the DUSTIE chamber — and helping the liquid flow longer before freezing again.
This phenomenon is similar to how on Earth lava flows farther in lava tubes than when exposed to cool surface temperatures. It also matches up with modeling research conducted around potential mud volcanoes on Mars and volcanoes that may have spewed icy material from volcanoes on Jupiter’s moon Europa.
“Our results contribute to a growing body of work that uses lab experiments to understand how long liquids last on a variety of worlds,” Scully said.
Find more information about NASA’s Dawn mission here:
https://science.nasa.gov/mission/dawn/
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Gretchen McCartney
Jet Propulsion Laboratory, Pasadena, Calif.
818-287-4115
gretchen.p.mccartney@jpl.nasa.gov
Karen Fox / Molly Wasser
NASA Headquarters, Washington
202-358-1600
karen.c.fox@nasa.gov / molly.l.wasser@nasa.gov
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Last Updated Dec 20, 2024 Related Terms
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By NASA
Download PDF: Statistical Analysis Using Random Forest Algorithm Provides Key Insights into Parachute Energy Modulator System
Energy modulators (EM), also known as energy absorbers, are safety-critical components that are used to control shocks and impulses in a load path. EMs are textile devices typically manufactured out of nylon, Kevlar® and other materials, and control loads by breaking rows of stitches that bind a strong base webbing together as shown in Figure 1. A familiar EM application is a fall-protection harness used by workers to prevent injury from shock loads when the harness arrests a fall. EMs are also widely used in parachute systems to control shock loads experienced during the various stages of parachute system deployment.
Random forest is an innovative algorithm for data classification used in statistics and machine learning. It is an easy to use and highly flexible ensemble learning method. The random forest algorithm is capable of modeling both categorical and continuous data and can handle large datasets, making it applicable in many situations. It also makes it easy to evaluate the relative importance of variables and maintains accuracy even when a dataset has missing values.
Random forests model the relationship between a response variable and a set of predictor or independent variables by creating a collection of decision trees. Each decision tree is built from a random sample of the data. The individual trees are then combined through methods such as averaging or voting to determine the final prediction (Figure 2). A decision tree is a non-parametric supervised learning algorithm that partitions the data using a series of branching binary decisions. Decision trees inherently identify key features of the data and provide a ranking of the contribution of each feature based on when it becomes relevant. This capability can be used to determine the relative importance of the input variables (Figure 3). Decision trees are useful for exploring relationships but can have poor accuracy unless they are combined into random forests or other tree-based models.
The performance of a random forest can be evaluated using out-of-bag error and cross-validation techniques. Random forests often use random sampling with replacement from the original dataset to create each decision tree. This is also known as bootstrap sampling and forms a bootstrap forest. The data included in the bootstrap sample are referred to as in-the-bag, while the data not selected are out-of-bag. Since the out-of-bag data were not used to generate the decision tree, they can be used as an internal measure of the accuracy of the model. Cross-validation can be used to assess how well the results of a random forest model will generalize to an independent dataset. In this approach, the data are split into a training dataset used to generate the decision trees and build the model and a validation dataset used to evaluate the model’s performance. Evaluating the model on the independent validation dataset provides an estimate of how accurately the model will perform in practice and helps avoid problems such as overfitting or sampling bias. A good model performs well on
both the training data and the validation data.
The complex nature of the EM system made it difficult for the team to identify how various parameters influenced EM behavior. A bootstrap forest analysis was applied to the test dataset and was able to identify five key variables associated with higher probability of damage and/or anomalous behavior. The identified key variables provided a basis for further testing and redesign of the EM system. These results also provided essential insight to the investigation and aided in development of flight rationale for future use cases.
For information, contact Dr. Sara R. Wilson. sara.r.wilson@nasa.gov
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By NASA
X-rays are radiated by matter hotter than one million Kelvin, and high-resolution X-ray spectroscopy can tell us about the composition of the matter and how fast and in what direction it is moving. Quantum calorimeters are opening this new window on the Universe. First promised four decades ago, the quantum-calorimeter era of X-ray astronomy has finally dawned.
Photo of the XRISM/Resolve quantum-calorimeter array in its storage container prior to integration into the instrument. The 6×6 array, 5 mm on a side, consists of independent detectors – each one a thermally isolated silicon thermistor with a HgTe absorber. The spectrometer consisting of this detector and other essential technologies separates astrophysical X-ray spectra into about 2400 resolution elements, which can be thought of as X-ray colors.NASA GSFC A quantum calorimeter is a device that makes precise measurements of energy quanta by measuring the temperature change that occurs when a quantum of energy is deposited in an absorber with low heat capacity. The absorber is attached to a thermometer that is somewhat decoupled from a heat sink so that the sensor can heat up and then cool back down again. To reduce thermodynamic noise and the heat capacity of the sensor, operation at temperatures less than 0.1 K is required.
The idea for thermal measurement of small amounts of energy occurred in several places in the world independently when scientists observed pulses in the readout of low-temperature thermometers and infrared detectors. They attributed these spurious signals to passing cosmic-ray particles, and considered optimizing detectors for sensitive measurement of the energy of particles and photons.
The idea to develop such sensors for X-ray astronomy was conceived at Goddard Space Flight Center in 1982 when X-ray astronomers were considering instruments to propose for NASA’s planned Advanced X-ray Astrophysics Facility (AXAF). In a fateful conversation, infrared astronomer Harvey Moseley suggested thermal detection could offer substantial improvement over existing solid-state detectors. Using Goddard internal research and development funding, development advanced sufficiently to justify, just two years later, proposing a quantum-calorimeter X-ray Spectrometer (XRS) for inclusion on AXAF. Despite its technical immaturity at the time, the revolutionary potential of the XRS was acknowledged, and the proposal was accepted.
The AXAF design evolved over the subsequent years, however, and the XRS was eliminated from its complement of instruments. After discussions between NASA and the Japanese Institute of Space and Astronautical Science (ISAS), a new XRS was included in the instrument suite of the Japanese Astro-E X-ray observatory. Astro-E launched in 2000 but did not reach orbit due to an anomaly in the first stage of the rocket. Astro-E2, a rebuild of Astro-E, was successfully placed in orbit in 2005 and renamed Suzaku, but the XRS instrument ceased operation before observations started due to loss of the liquid helium, an essential part of the detector cooling system, caused by a faulty storage system.
A redesigned mission, Astro-H, that included a quantum-calorimeter instrument with a redundant cooling system was successfully launched in 2016 and renamed Hitomi. Hitomi’s Soft X-ray Spectrometer (SXS) obtained high resolution spectra of the Perseus cluster of galaxies and a few other sources before a problem with the attitude control system caused the mission to be lost roughly one month after launch. Even so, Hitomi was the first orbiting observatory to obtain a scientific result using X-ray quantum calorimeters. The spectacular Perseus spectrum generated by the SXS motivated yet another attempt to implement a spaceborne quantum-calorimeter spectrometer.
The X-ray Imaging and Spectroscopy Mission (XRISM) was launched in September 2023, with the spectrometer aboard renamed Resolve to represent not only its function but also the resolve of the U.S./Japan collaboration to study the Universe through the window of this new capability. XRISM has been operating well in orbit for over a year.
Development of the Sensor Technology
Development of the sensor technology employed in Resolve began four decades ago. Note that an X-ray quantum-calorimeter spectrometer requires more than the sensor technology. Other technologies, such as the coolers that provide a
The sensors used from XRS through Resolve were all based on silicon-thermistor thermometers and mercury telluride (HgTe) X-ray absorbers. They used arrays consisting of 32 to 36 pixels, each of which was an independent quantum calorimeter. Between Astro-E and Astro-E2, a new method of making the thermistor was developed that significantly reduced its low-frequency noise. Other fabrication advances made it possible to make reproducible connections between absorbers and thermistors and to fit each thermistor and its thermal isolation under its X-ray absorber, making square arrays feasible.
Through a Small Business Innovation Research (SBIR) contract executed after the Astro-E2 mission, EPIR Technologies Inc. reduced the specific heat of the HgTe absorbers. Additional improvements made to the cooler of the detector heat sink allowed operation at a lower temperature, which further reduced the specific heat. Together, these changes enabled the pixel width to be increased from 0.64 mm to 0.83 mm while still achieving a lower heat capacity, and thus improving the energy resolution. From Astro-E through Astro-H, the energy resolution for X-rays of energy around 6000 eV improved from 11 eV, to 5.5 eV, to 4 eV. No changes to the array design were made between Astro-H and XRISM.
Resolve detector scientist Caroline Kilbourne installing the flight Resolve quantum-calorimeter array into the assembly that provides its electrical, thermal, and mechanical interfaces.NASA GSFC Over the same period, other approaches to quantum-calorimeter arrays optimized for the needs of future missions were developed. The use of superconducting transition-edge sensors (TES) instead of silicon (Si) thermistors led to improved energy resolution, more pixels per array, and multiplexing (a technique that allows multiple signals to be carried on a single wire). Quantum-calorimeter arrays with thousands of pixels are now standard, such as in the NASA contribution to the future European New Advanced Telescope for High-ENergy Astrophysics (newAthena) mission. And quantum calorimeters using paramagnetic thermometers — which unlike TES and Si thermistors require no dissipation of heat in the thermometer for it to be read out — combined with high-density wiring are a promising route for realizing even larger arrays. (See Astrophysics Technology Highlight on these latest developments.)
The Resolve instrument aboard XRISM (X-ray Imaging and Spectroscopy Mission) captured data from the center of galaxy NGC 4151, where a supermassive black hole is slowly consuming material from the surrounding accretion disk. The resulting spectrum reveals the presence of iron in the peak around 6.5 keV and the dips around 7 keV, light thousands of times more energetic that what our eyes can see. Background: An image of NGC 4151 constructed from a combination of X-ray, optical, and radio light.Spectrum: JAXA/NASA/XRISM Resolve. Background: X-rays, NASA/CXC/CfA/J.Wang et al.; optical, Isaac Newton Group of Telescopes, La Palma/Jacobus Kapteyn Telescope; radio, NSF/NRAO/VLA Results from Resolve
So, what is Resolve revealing about the Universe? Through spectroscopy alone, Resolve allows us to construct images of complex environments where collections of gas and dust with various attributes exist, emitting and absorbing X-rays at energies characteristic of their various compositions, velocities, and temperatures. For example, in the middle of the galaxy known as NCG 4151 (see figure above), matter spiraling into the central massive black hole forms a circular structure that is flat near the black hole, more donut-shaped further out, and, according to the Resolve data, a bit lumpy. Matter near the black hole is heated up to X-ray-emitting temperatures and irradiates the matter in the circular structure. The Resolve spectrum has a bright narrow emission line (peak) from neutral iron atoms that must be coming from colder matter in the circular structure, because hotter material would be ionized, and would have a different emission signature. Nonetheless, the shape of the iron line needs three components to describe it, each coming from a different lump in the circular structure. The presence of absorption lines (dips) in the spectrum provides further detail about the structure of the infalling matter.
A second example is the detection of X-ray emission by Resolve from the debris of stars that have exploded, such as N132D (see figure below), that will improve our understanding of the explosion mechanism and how the elements produced in stars get distributed, and allow us to infer the type of star each was before ending in a supernova. Elements are identified by their characteristic emission lines, and shifts of those lines via the Doppler effect tell us how fast the material is moving.
XRISM’s Resolve instrument captured data from supernova remnant N132D in the Large Magellanic Cloud to create the most detailed X-ray spectrum of the object ever made. The spectrum reveals peaks associated with silicon, sulfur, argon, calcium, and iron. Inset at right is an image of N132D captured by XRISM’s Xtend instrument.JAXA/NASA/XRISM Resolve and Xtend These results are just the beginning. The rich Resolve data sets are identifying complex velocity structures, rare elements, and multiple temperature components in a diverse ensemble of cosmic objects. Welcome to the quantum calorimeter era! Stay tuned for more revelations!
Project Leads: Dr. Caroline Kilbourne, NASA Goddard Space Flight Center (GSFC), for silicon-thermistor quantum calorimeter development from Astro-E2 through XRISM and early TES development. Foundational and other essential leadership provided by Dr. Harvey Moseley, Dr. John Mather, Dr. Richard Kelley, Dr. Andrew Szymkowiak, Mr. Brent Mott, Dr. F. Scott Porter, Ms. Christine Jhabvala, Dr. James Chervenak (GSFC at the time of the work) and Dr. Dan McCammon (U. Wisconsin).
Sponsoring Organizations and Programs: The NASA Headquarters Astrophysics Division sponsored the projects, missions, and other efforts that culminated in the development of the Resolve instrument.
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