Astronomers studying archival observations of powerful explosions called short gamma-ray bursts (GRBs) have detected light patterns indicating the brief existence of a superheavy neutron star shortly before it collapsed into a black hole. This fleeting, massive object likely formed from the collision of two neutron stars. 

“We looked for these signals in 700 short GRBs detected with NASA’s Neil Gehrels Swift Observatory, Fermi Gamma-ray Space Telescope, and the Compton Gamma Ray Observatory,” explained Cecilia Chirenti, a researcher at NASA’s Goddard Space Flight Center in Greenbelt, Maryland. “We found these gamma-ray patterns in two bursts observed by Compton in the early 1990s.”

A neutron star forms when the core of a massive star runs out of fuel and collapses. This produces a shock wave that blows away the rest of the star in a supernova explosion. Neutron stars typically pack more mass than our Sun into a ball about the size of a city, but above a certain mass, they must collapse into black holes. 

Both the Compton data and supercomputer simulations showed mega neutron stars tipping the scales by 20% more than the most massive, precisely measured neutron star known – dubbed J0740+6620 – which weighs in at nearly 2.1 times the Sun’s mass. Superheavy neutron stars also have nearly twice the size of a typical neutron star or about twice the length of Manhattan Island.

The mega neutron stars spin nearly 78,000 times a minute – almost twice the speed of J1748–2446ad, the fastest pulsar on record. This rapid rotation briefly supports the objects against further collapse, allowing them to exist for just a few tenths of a second, after which they proceed to form a black hole faster than the blink of an eye.

“We know that short GRBs form when orbiting neutron stars crash together, and we know they eventually collapse into a black hole, but the precise sequence of events is not well understood,” said Cole Miller, a professor of astronomy at UMCP and a co-author of the paper. “At some point, the nascent black hole erupts with a jet of fast-moving particles that emits an intense flash of gamma rays, the highest-energy form of light, and we want to learn more about how that develops.”

Short GRBs typically shine for less than two seconds yet unleash energy comparable to what’s released by all the stars in our galaxy over one year. They can be detected more than a billion light-years away. Merging neutron stars also produce gravitational waves, ripples in space-time that can be detected by a growing number of ground-based observatories.

Supercomputer simulations of these mergers show that gravitational waves exhibit a sudden jump in frequency – exceeding 1,000 hertz – as the neutron stars coalesce. These signals are too fast and faint for existing gravitational wave observatories to detect. But Chirenti and her team reasoned that similar signals could appear in the gamma-ray emission from short GRBs. 

Astronomers call these signals quasiperiodic oscillations, or QPOs for short. Unlike, say, the steady ringing of a tuning fork, QPOs can be composed of several close frequencies that vary or dissipate over time. Both the gamma-ray and gravitational wave QPOs originate in the maelstrom of swirling matter as the two neutron stars coalesce.

While no gamma-ray QPOs materialized in the Swift and Fermi bursts, two short GRBs recorded by Compton’s Burst And Transient Source Experiment (BATSE) on July 11, 1991, and Nov. 1, 1993, fit the bill.

The larger area of the BATSE instrument gave it the upper hand in finding these faint patterns – the tell-tale flickering that revealed the presence of mega neutron stars. The team rates the combined odds of these signals occurring by chance alone at less than 1 in 3 million.

“These results are very important as they set the stage for future measurements of hypermassive neutron stars by gravitational wave observatories,” said Chryssa Kouveliotou, chair of the physics department at George Washington University in Washington, who was not involved in the work.

By the 2030s, gravitational wave detectors will be sensitive to kilohertz frequencies, providing new insights into the short lives of supersized neutron stars. Until then, sensitive gamma-ray observations and supercomputer simulations remain the only available tools for exploring them. 

Compton’s BATSE instrument was developed at NASA's Marshall Space Flight Center in Huntsville, Alabama, and provided the first compelling evidence that gamma-ray bursts occurred far beyond our galaxy. After operating for almost nine years, the Compton Gamma Ray Observatory was deorbited on June 4, 2000, and destroyed as it entered Earth’s atmosphere.

Goddard manages both the Swift and Fermi missions.

Today in Paris, Alcatel-Lucent Enterprise has released a new AIOps service: OmniVista Network Advisor. It's an intelligent, autonomous system providing real-time network monitoring, alerts of potential risks, and instant mitigation of network issues.

The solution is built with ALE intelligence to provide new and existing customers with real-time network monitoring and alerts. OmniVista Network Advisor aims to simplify and accelerate the troubleshooting process, reducing network downtime and improving the Quality of Experience.

The technology provides proactive protection for network infrastructure, designed to significantly reduce the time from issue detection to resolution while simplifying the network administrator’s day-to-day operations.

OmniVista Network Advisor gives administrators a choice on who is notified and what measures should be taken to resolve the issue. Leveraging the unique capabilities of Alcatel-Lucent Enterprise’s Rainbow CPaaS platform, the application triggers a smart alerting system on an intuitive interface and proposes clear, immediate action as soon as a threat or anomaly is detected. The new system aims to fix network issues with one tap, detecting unexpected system errors and allowing network administrators to apply the solution instantaneously from any smart device, anywhere. With OmniVista Network Advisor, issues are resolved much faster, substantially reducing the need for engineers to be on site.

Through Artificial Intelligence (AI) and Machine Learning (ML) capabilities, OmniVista Network Advisor will gradually expand its capabilities to detect and anticipate issues/anomalies by reviewing historical data to understand network behavior. This means that even intermittent problems can be caught, logged, and resolved much faster. The system also aims to detect unknown patterns, employing automated log collection to aid the remediation of new problems without lengthy troubleshooting.

Michael See, CTO of Alcatel-Lucent Enterprise Network Business Division commented, “Enterprises increasingly rely on an Autonomous Network. OmniVista Network Advisor accelerates real-time reactions to anomalies so that our customers can have peace of mind that their connectivity and mission-critical operations will remain secure and uninterrupted. Typically, only 5% of issues reported to ALE Customer Support are new, so our experience and intelligence are built into the tool to immediately identify the root cause of any issues and provide solutions that can be implemented automatically.”

Overall, ALE’s OmniVista Network Advisor aims to improve the efficiency of network administrators’ teams, reducing the time between a problem occurring, and the problem is solved. It will be available to all customers using ALE OmniSwitches or OmniAccess Stellar access points.

The future evolution of OmniVista Network Advisor, associated with the Alcatel-Lucent Enterprise Rainbow CPaaS platform, facilitates integration with third-party systems. Examples of such integration include the automated creation of tickets in the company's IT Service Management system, collaboration in real-time with other specialists, or interfacing with other AI platforms. This powerful combination optimizes processes and enables faster resolution of threats or issues associated with the network.

In a new study, a team of astronomers led by Haojing Yan at the University of Missouri used data from NASA’s James Webb Space Telescope (JWST) Early Release Observations and discovered 87 galaxies that could be the earliest known galaxies in the universe.

The finding moves astronomers one step closer to finding out when galaxies first appeared in the universe — about 200-400 million years after the Big Bang, said Yan, associate professor of physics and astronomy at MU and lead author on the study. 

“Finding such a large number of galaxies in the early parts of the universe suggests that we might need to revise our previous understanding of galaxy formation,” Yan said. “Our finding gives us the first indication that a lot of galaxies could have been formed in the universe much earlier than previously thought.”

In the study, the astronomers searched for potential galaxies at “very high redshifts.” Yan said the concept of redshifts in astronomy allows astronomers to measure how far away distant objects are in the universe — like galaxies — by looking at how the colors change in the waves of light that they emit.

“If a light-emitting source is moving toward us, the light is being ‘squeezed,’ and that shorter wavelength is represented by blue light or blueshift,” Yan said. “But if that source [of light] is moving away from us, the light it produces is being ‘stretched,’ and changes to a longer wavelength that is represented by red light, or redshift.”

Yan said Edwin Hubble’s discovery in the late 1920s that our universe is ever-expanding is key to understanding how redshifts are used in astronomy.

“Hubble confirmed that galaxies external to our Milky Way galaxy are moving away from us, and the more distant they are, the faster they are moving away,” Yan said. “This relates to redshifts through the notion of distances — the higher the redshift an object is at, such as a galaxy, the further away it is from us.”

Therefore, Yan said the search for galaxies at very high redshifts gives astronomers a way to construct the early history of the universe.

“The speed of light is finite, so it takes time for light to travel over a distance to reach us,” Yan said. “For example, when we look at the sun, we aren’t looking at it as what it looks like in the present, but rather what it looked like some eight minutes ago. That’s because that’s how long it takes for the sun’s radiation to reach us. So, when we are looking at galaxies which are very far away, we are looking at their images from a long time ago.” 

Using this concept, Yan’s team analyzed the infrared light captured by the JWST to identify the galaxies.

“The higher the redshift a galaxy is at, the longer it takes for the light to reach us, so a higher redshift corresponds to an earlier view of the universe,” Yan said. “Therefore, by looking at galaxies at higher redshifts, we are getting earlier snapshots of what the universe looked like long ago.”

Deep overturning circulation collapses with strong warming

Climate-driven heating of seawater is causing a slowdown of deep circulation patterns in the Atlantic and Southern oceans, according to University of California, Irvine Earth system scientists, and if this process continues, the ocean’s ability to remove carbon dioxide from the atmosphere will be severely limited, further exacerbating global warming.

In a recent study, these researchers analyzed projections from three dozen climate models and found that the Atlantic Meridional Overturning Circulation and the Southern Meridional Overturning Circulation will slow by as much as 42 percent by 2100. The supercomputer simulations suggest that under worst-case warming, the SMOC could cease entirely by 2300.

"Analysis of the projections from 36 Earth system models over a range of climate scenarios shows that unchecked global warming could lead to a shutdown of the ocean deep circulation,” said co-author J. Keith Moore, UCI professor of Earth system science. “This would be a climate disaster similar in magnitude to the complete melting of the ice sheets on land.”

The importance of overturning circulation

In the Atlantic, as warm water flows northwards on the surface, it cools and evaporates, making it saltier and denser. This heavier water sinks into the deep ocean and proceeds to the south where it eventually rises back up, carrying from the depths the nutrients that are the food foundation of marine ecosystems.

In addition, globe-spanning ocean circulation creates a powerful factory for the processing of atmospheric carbon dioxide. The basic physical and chemical interaction of seawater and air – what Moore and his colleagues call a “solubility pump” – draws CO₂ into the ocean. While ocean circulation sends some carbon back to the sky, the net amount is sequestered in the ocean’s depths.

Additionally, a “biological pump” occurs as phytoplankton use CO₂ during photosynthesis and in forming carbonate shells. When the plankton and larger animals die, they sink, slowly decomposing and releasing the carbon and nutrients at depth. Some come back up with circulation and upwelling, but a portion remains banked beneath the waves.

“A disruption in circulation would reduce ocean uptake of carbon dioxide from the atmosphere, intensifying and extending the hot climate conditions,” Moore said. “Over time the nutrients that support marine ecosystems would increasingly become trapped in the deep ocean, leading to declining global-ocean biological productivity.”

Humans depend on the solubility pump and the biological pump to help remove some of the CO₂ emitted into the air through fossil fuel burning, land use practices, and other activities, according to Moore.

“Our analysis also shows that reducing greenhouse gas emissions now can prevent this complete shutdown of the deep circulation in the future,” he said.

Joining Moore on this project, which was funded by the U.S. Department of Energy, were lead author Yi Liu, a UCI Ph.D. student in Earth system science; Francois Primeau, professor and chair of UCI’s Department of Earth System Science; and Wei-Lei Wang, professor of ocean and Earth sciences at Xiamen University in China. The study depended substantially on simulations developed by the Coupled Model Intercomparison Project phase 6 (CMIP6) project used to inform the IPCC climate assessments.