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By NASA
5 Min Read Webb Maps Full Picture of How Phoenix Galaxy Cluster Forms Stars
Spectroscopic data collected from NASA’s James Webb Space Telescope is overlayed on an image of the Phoenix cluster that combines data from NASA’s Hubble Space Telescope, Chandra X-ray Observatory and the Very Large Array (VLA) radio telescope. Credits:
NASA, CXC, NRAO, ESA, M. McDonald (MIT), M. Reefe (MIT), J. Olmsted (STScI) Discovery proves decades-old theory of galaxy feeding cycle.
Researchers using NASA’s James Webb Space Telescope have finally solved the mystery of how a massive galaxy cluster is forming stars at such a high rate. The confirmation from Webb builds on more than a decade of studies using NASA’s Chandra X-ray Observatory and Hubble Space Telescope, as well as several ground-based observatories.
The Phoenix cluster, a grouping of galaxies bound together by gravity 5.8 billion light-years from Earth, has been a target of interest for astronomers due to a few unique properties. In particular, ones that are surprising: a suspected extreme cooling of gas and a furious star formation rate despite a roughly 10 billion solar mass supermassive black hole at its core. In other observed galaxy clusters, the central supermassive black hole powers energetic particles and radiation that prevents gas from cooling enough to form stars. Researchers have been studying gas flows within this cluster to try to understand how it is driving such extreme star formation.
Image A: Phoenix Cluster (Hubble, Chandra, VLA Annotated)
Spectroscopic data collected from NASA’s James Webb Space Telescope is overlayed on an image of the Phoenix cluster that combines data from NASA’s Hubble Space Telescope, Chandra X-ray Observatory and the Very Large Array (VLA) radio telescope. Webb’s powerful sensitivity in the mid-infrared detected the cooling gas that leads to a furious rate of star formation in this massive galaxy cluster. Credit: NASA, CXC, NRAO, ESA, M. McDonald (MIT), M. Reefe (MIT), J. Olmsted (STScI) “We can compare our previous studies of the Phoenix cluster, which found differing cooling rates at different temperatures, to a ski slope,” said Michael McDonald of the Massachusetts Institute of Technology in Cambridge, principal investigator of the program. “The Phoenix cluster has the largest reservoir of hot, cooling gas of any galaxy cluster — analogous to having the busiest chair lift, bringing the most skiers to the top of the mountain. However, not all of those skiers were making it down the mountain, meaning not all the gas was cooling to low temperatures. If you had a ski slope where there were significantly more people getting off the ski lift at the top than were arriving at the bottom, that would be a problem!”
To date, in the Phoenix cluster, the numbers weren’t adding up, and researchers were missing a piece of the process. Webb has now found those proverbial skiers at the middle of the mountain, in that it has tracked and mapped the missing cooling gas that will ultimately feed star formation. Most importantly, this intermediary warm gas was found within cavities tracing the very hot gas, a searing 18 million degrees Fahrenheit, and the already cooled gas around 18,000 degrees Fahrenheit.
The team studied the cluster’s core in more detail than ever before with the Medium-Resolution Spectrometer on Webb’s Mid-Infrared Instrument (MIRI). This tool allows researchers to take two-dimenstional spectroscopic data from a region of the sky, during one set of observations.
“Previous studies only measured gas at the extreme cold and hot ends of the temperature distribution throughout the center of the cluster,” added McDonald. “We were limited — it was not possible to detect the ‘warm’ gas that we were looking for. With Webb, we could do this for the first time.”
Image B: Phoenix Cluster (Hubble, Chandra, VLA)
This image of the Phoenix cluster combines data from NASA’s Hubble Space Telescope, Chandra X-ray Observatory, and the Very Large Array radio telescope. X-rays from Chandra depict extremely hot gas in purple. Optical light data from Hubble show galaxies in yellow, and filaments of cooler gas where stars are forming in light blue. Outburst generated jets, represented in red, are seen in radio waves by the VLA radio telescope. NASA, CXC, NRAO, ESA, M. McDonald (MIT). A Quirk of Nature
Webb’s capability to detect this specific temperature of cooling gas, around 540,000 degrees Fahrenheit, is in part due to its instrumental capabilities. However, the researchers are getting a little help from nature, as well.
This oddity involves two very different ionized atoms, neon and oxygen, created in similar environments. At these temperatures, the emission from oxygen is 100 times brighter but is only visible in ultraviolet. Even though the neon is much fainter, it glows in the infrared, which allowed the researchers to take advantage of Webb’s advanced instruments.
“In the mid-infrared wavelengths detected by Webb, the neon VI signature was absolutely booming,” explained Michael Reefe, also of the Massachusetts Institute of Technology, lead author on the paper published in Nature. “Even though this emission is usually more difficult to detect, Webb’s sensitivity in the mid-infrared cuts through all of the noise.”
The team now hopes to employ this technique to study more typical galaxy clusters. While the Phoenix cluster is unique in many ways, this proof of concept is an important step towards learning about how other galaxy clusters form stars.The James Webb Space Telescope is the world’s premier space science observatory. Webb is solving mysteries in our solar system, looking beyond to distant worlds around other stars, and probing the mysterious structures and origins of our universe and our place in it. Webb is an international program led by NASA with its partners, ESA (European Space Agency) and CSA (Canadian Space Agency).
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Media Contacts
Laura Betz – laura.e.betz@nasa.gov
NASA’s Goddard Space Flight Center, Greenbelt, Md.
Hannah Braun hbraun@stsci.edu
Space Telescope Science Institute, Baltimore, Md.
Christine Pulliam – cpulliam@stsci.edu
Space Telescope Science Institute, Baltimore, Md.
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By European Space Agency
After years of meticulous development, ESA’s next Earth Explorer satellite, Biomass, is ready to be packed up for transport to Europe’s Spaceport in French Guiana, where it will launch aboard a Vega-C rocket this spring.
Before final preparations and shipment, media representatives had the exclusive opportunity today to see the satellite up close in the cleanroom at Airbus’ facilities in Toulouse, France.
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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
4 min read
Preparations for Next Moonwalk Simulations Underway (and Underwater)
The Aerostar Thunderhead balloon carries the STRATO payload into the sky to reach the stratosphere for flight testing. The balloon appears deflated because it will expand as it rises to higher altitudes where pressures are lower.Credit: Colorado Division of Fire Prevention and Control Center of Excellence for Advanced Technology Aerial Firefighting/Austin Buttlar NASA is participating in a collaborative effort to use high-altitude balloons to improve real-time communications among firefighters battling wildland fires.
The rugged and often remote locations where wildland fires burn mean cell phone service is often limited, making communication between firefighters and command posts difficult.
The flight testing of the Strategic Tactical Radio and Tactical Overwatch (STRATO) technology brought together experts from NASA’s Ames Research Center in California’s Silicon Valley, the U.S. Forest Service, high-altitude balloon company Aerostar, and Motorola to provide cell service from above. The effort was funded by the NASA Science Mission Directorate’s Earth Science Division Airborne Science Program and the agency’s Space Technology Mission Directorate Flight Opportunities program.
“This project leverages NASA expertise to address real problems,” said Don Sullivan, principal investigator for STRATO at NASA Ames. “We do a lot of experimental, forward-thinking work, but this is something that is operational and can make an immediate impact.”
Flying High Above Wildland Fires
Soaring above Earth at altitudes of 50,000 feet or more, Aerostar’s Thunderhead high-altitude balloon systems can stay in operation for several months and can be directed to “station keep,” staying within a radius of few miles. Because wildland fires often burn in remote, rugged areas, firefighting takes place in areas where cell service is not ideal. Providing cellular communication from above, from a vehicle that can move as the fire changes, would improve firefighter safety and firefighting efficiency.
The STRATO project’s first test flight took place over the West Mountain Complex fires in Idaho in August and demonstrated significant opportunities to support future firefighting efforts. The balloon was fitted with a cellular LTE transmitter and visual and infrared cameras. To transmit between the balloon’s cell equipment and the wildland fire incident command post, the team used a SpaceX Starlink internet satellite device and Silvus broadband wireless system.
When tested, the onboard instruments provided cell coverage for a 20-mile radius. By placing the transmitter on a gimbal, that cell service coverage could be adjusted as ground crews moved through the region.
The onboard cameras gave fire managers and firefighters on the ground a bird’s-eye view of the fires as they spread and moved, opening the door to increased situational awareness and advanced tracking of firefighting crews. On the ground, teams use an app called Tactical Awareness Kit (TAK) to identify the locations of crew and equipment. Connecting the STRATO equipment to TAK provides real-time location information that can help crews pinpoint how the fire moves and where to direct resources while staying in constant communication.
Soaring Into the Future
The next steps for the STRATO team are to use the August flight test results to prepare for future fire seasons. The team plans to optimize balloon locations as a constellation to maximize coverage and anticipate airflow changes in the stratosphere where the balloons fly. By placing balloons in strategic locations along the airflow path, they can act as replacements to one another as they are carried by airflow streams. The team may also adapt the scientific equipment aboard the balloons to support other wildland fire initiatives at NASA.
As the team prepares for further testing next year, the goal is to keep firefighters informed and in constant communication with each other and their command posts to improve the safety and efficiency of fighting wildland fires.
“Firefighters work incredibly hard saving lives and property over long days of work,” said Sullivan. “I feel honored to be able to do what we can to make their jobs safer and better.”
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Last Updated Nov 14, 2024 Related Terms
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By NASA
Since its launch in 2014, the Physical Sciences Informatics (PSI) system has served as NASA’s online repository for physical science data. Now, the PSI system is live with new updates to further align with NASA’s open data policy.
With its first significant update in over five years, the data repository has been completely redesigned, featuring a new layout, improved structure, and enhanced search functionalities. This updated system was created with a focus on user experience, and more updates are anticipated as new features are introduced.
A key new feature of the system is, the PSI Submission Portal. This tool is designed to streamline the processes of collecting, curating, and publishing new data by enabling Principal Investigators and scientific teams to upload files directly to the system with the support of a data curator. The Portal also offers a dedicated workspace for data submitters, assigns a unique digital object identifier to each dataset, and standardizes the documentation and data structure for each investigation.
Both the updated PSI system and Submission Portal can be accessed at PSI.NASA.gov.
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