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The question of whether or not red dwarf stars can support habitable planets has been subject to debate for decades. With the explosion in exoplanet discoveries in the past two decades, the debate has become all the more significant. For starters, M-type (red dwarf) stars are the most common in the Universe, accounting for 75% of the stars in our galaxy. Additionally, exoplanet surveys indicate that red dwarfs are particularly good at forming Earth-like rocky planets that orbit within their circumsolar habitable zones (CHZs).

Unfortunately, a considerable body of research has shown that planets orbiting red dwarf suns would be subject to lots of flare activity – including some so powerful they’re known as “superflares.” In a recent study led by the University of Hawai’i, a team of astrophysicists revealed that red dwarf stars can produce stellar flares with significantly more far-ultraviolet radiation than previously expected. Their findings could have drastic implications for exoplanet studies and the search for extraterrestrial life on nearby rocky planets.

The study was led by Vera L Berger, a Churchill Scholar and graduate student researcher currently at the University of Cambridge’s Cavendish Laboratory, formerly with the University of Hawai‘i’s Institute for Astronomy (UHIfA). She was joined by colleagues from UHIfA, the Center for Cosmology and Astroparticle Physics (CCAP) at Ohio State University, and the Sydney Institute for Astronomy (SIfA). Their findings appeared in a paper titled “Stellar flares are far-ultraviolet luminous,” which was recently published in the Monthly Notices of the Royal Astronomical Society.

Artist’s impression of Kepler-1649 c orbiting its host star, a red dwarf. Credit: NASA’s Ames Research Center/Daniel Rutter

In recent years, the debate regarding red dwarf habitability has focused on two major areas: tidal locking and flare activity. The former arises from the fact that rocky planets orbiting a red dwarf star’s CMZ are close enough that their rotation is perfectly timed with their orbit, meaning that one side is constantly facing toward the star. This also means that the sun-facing side would be subject to powerful solar flares, which are very with cooler, low-mass M-type stars. In the past, research has shown that a planet subjected to this powerful flare activity would likely be stripped of its atmosphere.

However, other research has indicated that planets with a magnetic field and a sufficiently dense atmosphere could still support life. Moreover, recent research has demonstrated that red dwarfs emit their most powerful flares (aka. “superflares”) from their poles, thus sparing the planets that orbit them. For their study, Berger and her team used archival data from NASA’s Galaxy Evolution Explorer (GALEX) – a UV space telescope decommissioned in 2013. Using new computational techniques, the team searched this data for evidence of flares from 300,000 nearby stars.

Overall, they detected 182 flares from 158 stars within about 326 light-years (100 parsecs) of the Sun in the near-ultraviolet (NUV) and far-ultraviolet (FUV) wavelengths. These results challenge existing models of stellar flares and exoplanet habitability, which predict that flares will produce more NUV than FUV radiation. However, their observations showed that the distribution of FUV radiation was three times more energetic (on average) and up to twelve times what current models predict. As Bergin explained in a recent UH press release:

“Few stars have been thought to generate enough UV radiation through flares to impact planet habitability. Our findings show that many more stars may have this capability… Our work puts a spotlight on the need for further exploration into the effects of stellar flares on exoplanetary environments. Using space telescopes to obtain UV spectra of stars will be crucial for better understanding the origins of this emission.”

Artist’s illustration of Proxima Centauri b. ESO/M. Kornmesser

On Earth, ultraviolet radiation has been vital to the development of life as we know it. Whereas near-UV (UV-A, 400 nm to 300 nm) plays an essential role in the formation of Vitamin D by the skin, prolonged exposure can lead to sunburn, increased risk of melanoma, and cataracts. Middle wavelength UV (UV-B, 300 to 200 nm) can cause damage at the molecular level, affecting deoxyribonucleic acid (DNA), the very building blocks of life. Thanks to Earth’s magnetic field and dense atmosphere, very little UV light below 290 nm reaches the surface.

However, as the team indicates in their study, exposure to Far-UV (200 nm to 10 nm) produced by stellar flares could severely impact planetary habitability, from eroding a planet’s atmosphere to threatening the formation of RNA building blocks. “A change of three is the same as the difference in UV in the summer from Anchorage, Alaska to Honolulu, where unprotected skin can get a sunburn in less than 10 minutes,” said co-author Benjamin J. Shappee from the University of Hawai’i.

While the exact cause of these stronger FUV emissions is unclear, the team believes that flare radiation could be concentrated at specific wavelengths, possibly due to elements like carbon and nitrogen in the star’s composition. They emphasize that more data is needed to determine the source of these emissions and to gain a better understanding of red dwarf UV luminosity. These findings could indicate that most stars in our galaxy cannot support life (as we know it), which could have drastic implications for astrobiology and might even be a possible answer to Fermi’s Paradox!

Further Reading: University of Hawai’i, MNRAS

The post Habitable Planet’s Orbiting Red Dwarf Suns Could at Risk from Far-Ultraviolet Radiation appeared first on Universe Today.

Mention the name Starlink among the astronomy community and you will often be greeted with a shudder. There are now thousands of Starlink satellites orbiting Earth providing internet connectivity to every corner of the Earth. Many believe they are making astronomy difficult but now, SpaceX is launching another service; ‘direct-to-cell’ technology that will allow mobile phones to use satellites to send text messages as early as this year. Voice and data services are likely to follow on quickly next year. With smaller antennae at a lower altitude what is their impact on astronomy?

The SpaceX Starlink satellite project provides high speed broadband to ever corner of the globe (I know globes don’t have corners but it’s a saying that I didn’t write, I’m just using it…. reluctantly.) Thousands of small satellites are now in low Earth orbit to achieve that aim. It’s great news to those that live in remote parts of Earth and it has massive benefits to communications and support applications like disaster relief, medicine and remote learning. To astronomers attempting to study the faintest light from distant objects across the cosmos the satellites are problematic, having a negative impact on many observations. 

This diagram and artist illustration demonstrates how sunlight reflects off a Starlink version 1.5 satellite. (Credit: SpaceX)

SpaceX have gone to great lengths to minimise the impact from their satellites but now they are launching more to service direct messaging from mobile phones, via satellite. With even more satellites in orbit, at a lower orbit too, concerns are mounting of their impact on astronomical observations. The new satellites will have a mean magnitude of 4.62, this is 4.9 times brighter than other Starlink Mini spacecraft! Currently there are only 6 ‘direct-to-cell’ satellites in orbit but the plan is for over 7,000 to join them.

Four researchers; Anthony Mallama, Richard E. Cole, Scott Harrington and J. Respler from the International Astronomical Union have studied the new suite of satellites to see what impact they may have on future observations. In their paper they describe just how they analysed the visibility and how they estimated the brightness of the new mini satellites.

The analysis process began with electronic and visual observations of the 6 test satellites. The electronic observations were taken using the MMT9 (Mini-MegaTORTORA) system at the Special Astrophysical Observatory in Russia. It is made up of 9 x 71mm diameter lenses and 2160 x 2560 CMOS detectors. The brightness observations were recorded along with the satellite distance and phase angle of which both would impact brightness. 

The visual observations techniques is similar to that which is familiar to variable star observers. Brightness estimates are made using nearby reference stars whose brightness is known. They then characterise them before reassessing the impact on the new DTC satellites and the existing internet satellites. 

Despite having arrived at an estimate of brightness 4.9 times brighter than the existing satellites, they are unable to conclude how the different attitudes and operations will impact their brightness. Taking into account their expected operations the brightness is more likely to be just 2.6 times brighter than the existing. They will however, spend far more of their time in Earth’s shadow so will be less visible.  

Source : Brightness Characterization for Starlink Direct-to-Cell Satellites

The post Starlink Direct-to-Cell Satellites are Coming. What Will Be Their Impact on Astronomy? appeared first on Universe Today.

Countries are starting to take steps to cut human sources of methane emissions, but climate change is increasing emissions of the potent greenhouse gas from wetlands

A groundbreaking study has revealed that red dwarf stars can produce stellar flares that carry far-ultraviolet (far-UV) radiation levels much higher than previously believed.

Ancient plants, seeds and insects preserved beneath Greenland’s ice sheet reveal that it once melted completely, raising concerns about sea level rise if it happens again

Modern astronomy would struggle without AI and machine learning (ML), which have become indispensable tools. They alone have the capability to manage and work with the vast amounts of data that modern telescopes generate. ML can sift through large datasets, seeking specified patterns that would take humans far longer to find.

The search for biosignatures on Earth-like exoplanets is a critical part of contemporary astronomy, and ML can play a big role in it.

Since exoplanets are so distant, astronomers pay close attention to the ones that allow transmission spectroscopy. When starlight passes through a planet’s atmosphere, spectroscopy can split the light into different wavelengths. Astronomers then examine the light for the telltale signs of particular molecules. However, chemical biosignatures in exoplanet atmospheres are tricky because natural abiogenic processes can generate some of the same signatures.

This is a model JWST transmission spectrum for an Earth-like planet. It shows the wavelengths of sunlight that molecules like ozone (O3), water (H2O), carbon dioxide (CO2), and methane (CH4) absorb. The y-axis shows the amount of light blocked by Earth’s atmosphere rather than the brightness of sunlight that travels through the atmosphere. The brightness decreases from bottom to top. An understanding of Earth’s spectrum helps scientists interpret spectra from exoplanets. Image Credit: NASA, ESA, Leah Hustak (STScI)

Though the method is powerful, it faces some challenges. Stellar activity like starspots and flares can pollute the signal, and the light from the atmosphere can be very weak compared to the star’s light. If there are clouds or haze in the exoplanet’s atmosphere, that can make it difficult to detect molecular absorption lines in the spectroscopic data. Rayleigh scattering adds to the challenge, and there can also be multiple different interpretations of the same spectroscopic signal. The more of these types of ‘noise’ there is in the signal, the worse the signal-to-noise ratio (SNR) is. Noisy data—data with a low SNR—is a pronounced problem.

We’re still discovering different types of exoplanets and planetary atmospheres, and our models and analysis techniques aren’t complete. When combined with the low SNR problem, the pair comprise a major hurdle.

But machine learning can help, according to new research. “Machine-assisted classification of potential biosignatures in earth-like exoplanets using low signal-to-noise ratio transmission spectra” is a paper under review by the Monthly Notices of the Royal Astronomical Society. The lead author is David S. Duque-Castaño from the Computational Physics and Astrophysics Group at the Universidad de Antioquia in Medellin, Colombia.

The JWST is our most powerful transmission spectroscopy tool, and it’s delivered impressive results. But there’s a problem: observing time. Some observing efforts take an enormous amount of time. It can take a prohibitively high number of transits to detect things like ozone. If we had unlimited amounts of observing time, it wouldn’t matter so much.

One study showed that in the case of TRAPPIST-1e, it can take up to 200 transits to obtain statistically significant detections. The transit number becomes more reasonable if the search is restricted to methane and water vapour. “Studies have demonstrated that using a reasonable number of transits, the presence of these atmospheric species, which are typically associated with a global biosphere, can be retrieved,” the authors write. Unfortunately, methane isn’t as robust a biosignature as ozone.

Given the time required to detect some of these potential biomarkers, the researchers say that it might be better to use the JWST to conduct signal-to-noise ratio (SNR) surveys. “Although this may not allow for statistically significant retrievals, it would at least enable planning for future follow-up observations of interesting targets with current and future more powerful telescopes (e.g., ELT, LUVOIR, HabEx, Roman, ARIEL),” the authors write, invoking the names of telescopes that are in the building or planning stages.

The researchers have developed a machine-learning tool to help with this problem. They say it can fast-track the search for habitable worlds by leveraging the power of AI. “In this work, we developed and tested a machine-learning general methodology intended to classify transmission spectra with low Signal-to-Noise Ratio according to their potential to contain biosignatures,” they write.

Since much of our exoplanet atmosphere spectroscopy data is noise, the ML tool is designed to process it, figure out how noisy it is, and classify atmospheres that may contain methane, ozone, and/or water or as interesting enough for follow-up observations.

The team generated one million synthetic atmospheric spectra based on the well-known TRAPPIST-1 e planet and then trained their ML models on them. TRAPPIST-1e is similar in size to Earth and is a rocky planet in the habitable zone of its star. “The TRAPPIST-1 system has gained significant scientific attention
in recent years, especially in planetary sciences and astrobiology, owing to its exceptional features,” the paper states.

Artist’s impression of TRAPPIST-1e, a rocky exoplanet similar in size to Earth. Credit: NASA/JPL-Caltech

The TRAPPIST-1 star is known for hosting the highest number of rocky planets of any system we’ve discovered. For the researchers, it’s an ideal candidate for training and testing their ML models because astronomers can get favourable SNR readings in reasonable amounts of time. The TRAPPIST-1e planet is likely to have a compact atmosphere like Earth’s. The resulting models were successful and correctly identified transmission spectra with suitable SNR levels.

The researchers also tested their models on realistic synthetic atmospheric spectra of modern Earth. Their system successfully identified synthetic atmospheres that contained methane and/or ozone in ratios similar to those of the Proterozoic Earth. During the Proterozoic, the atmosphere underwent fundamental changes because of the Great Oxygenation Event (GOE).

The GOE changed everything. It allowed the ozone layer to form, created conditions for complex life to flourish and even led to the creation of vast iron ore deposits that we mine today. If other exoplanets developed photosynthetic life, their atmospheres should be similar to the Proterozoic Earth’s, so it’s a relevant marker for biological life. (The recent discovery of dark oxygen has serious implications for our understanding of oxygen as a biomarker in exoplanet atmospheres.)

In their paper, the authors describe the detection of oxygen or ozone as the ‘Crown Jewel’ of exoplanet spectroscopy signatures. But there are abiotic sources as well, and whether or not oxygen or ozone are biotic can depend on what else is in the signature. “To distinguish between biotic and abiotic O2, one can look for specific spectral fingerprints,” they write.

To evaluate the performance of their model, they need to know more than which exoplanet atmospheres are correctly identified (True) and which exoplanet atmospheres are falsely identified (False.)

The results also need to be categorized as either True Positives (TP) or True Negatives (TN), which are related to accuracy, or False Positives (FP) or False Negatives (FN), which are errors. To organize their data they created a classification system they call a Confusion Matrix.

“In the diagram, we introduce the category interesting to distinguish planets that deserve follow-up observations or in-depth analysis,” the authors explain. “We should recall again that is the focus of this work: we do not aim at detecting biosignatures using ML but at labelling planets that are interesting or not.”

The Confusion Matrix has four classifications.

One of the models was successful in identifying likely biosignatures in Proterozoic Earth spectra after only a single transit. Based on their testing, they explain that the JWST would successfully detect most “inhabited terrestrial planets observed with the JWST/NIRSpec PRISM around M-dwarfs located at distances similar or smaller than that of TRAPPIST-1 e.” If they exist, that is.

These results can refine the JWST’s future efforts. The researchers write that “machine-assisted strategies similar to those presented here could significantly optimize the usage of JWST resources for biosignature searching.” They can streamline the process and maximize the chances that follow-up observations can discover promising candidates. The telescope is already two years and seven months into its planned five-and-a-half-year primary mission. (Though the telescope could last for up to 20 years overall.) Anything that can optimize the space telescope’s precious observing time is a win.

All in all, the study presents a machine-learning model that can save time and resources. It quickly sifts through the atmospheric spectra of potentially habitable exoplanets. While it doesn’t identify which ones contain biomarkers, it can identify the best candidates for follow-up after only 1 to 5 transits, depending on the type of atmosphere. Some types would require more transits, but the model still saves time.

“Identifying a planet as interesting will only make the allocation of observing time of valuable resources such as JWST more efficient, which is an important goal in modern astronomy,” they write.

The post Fast-Tracking the Search for Habitable Worlds appeared first on Universe Today.

A research team developed artificial intelligence technology that could find ways to improve researchers' understanding of the chemical reactions involved in ammonia production and other complex chemical reactions.

A research team developed artificial intelligence technology that could find ways to improve researchers' understanding of the chemical reactions involved in ammonia production and other complex chemical reactions.

Using state of the art techniques, researchers use vibrations from traffic to measure underground soil moisture.

Understanding neutrino interactions is crucial for obtaining a complete picture of particle physics and the universe. To date, neutrino interaction cross sections have not been measured at high energy above some hundred gigaelectronvolts at particle colliders. Now, researchers have obtained the first direct observation of electron and muon neutrino interactions in the Teraelectronvolt range at CERN's Large Hadron Collider, using the FASER detector. This study marks a significant step for particle physics research.

With GROVER, a new large language model trained on human DNA, researchers could now attempt to decode the complex information hidden in our genome. GROVER treats human DNA as a text, learning its rules and context to draw functional information about the DNA sequences.

A growing body of AI tools screen how people talk, searching for subtle changes that could indicate mental health concerns like depression or anxiety. A study finds that these tools don't perform consistently across people from different genders and races.

New findings on how sharks achieve drag reduction could inspire the design of riblets for more efficient aircraft and boats. In their investigation of great white shark denticles, researchers found that ridge height and spacing play crucial roles in drag reduction at different swimming speeds. Higher middle ridges aid sharks in efficient cruising at slower speeds, while the lower side ridges become more critical for drag reduction during high-speed hunting bursts. The analysis also suggests that the speeds of an extinct giant shark, megalodon, may not much differ from those of the white shark.

Researchers send entangled photons and laser pulses of the same color over a single optical fiber for the first time.

A team developed a new microscopy technique that uses electrical pulses to track the nanosecond dynamics within a material that is known to form charge density waves. Controlling these waves may lead to faster and more energy-efficient electronics.

A team developed a new microscopy technique that uses electrical pulses to track the nanosecond dynamics within a material that is known to form charge density waves. Controlling these waves may lead to faster and more energy-efficient electronics.

A low-carbohydrate ketogenic diet is linked to greater fat loss than a low-sugar diet, but also higher cholesterol levels

Over 5,000 exoplanets have been discovered around distant star systems. Protoplanetary disks have been discovered too and it’s these, out of which all planetary systems form. Such disks have recently been found in two binary star systems. The stellar components in one have a separation of 14 astronomical units (the average distance between the Earth and Sun is one astronomical unit) and the other system has a separation of 22 astronomical units. Studying systems like these allow us to see how the stars of a binary system interact and how they can distort protoplanetary disks.

The discovery of planetary systems around other stars has changed our view of the universe and how stellar systems evolve. The first confirmed detection occurred in 1995 and since then, advanced telescopes and detection techniques have enabled the detection of thousands of exoplanets. Space missions like Kepler and TESS have helped to categorise the planets and have identified large gas planets to Earth-sized rocky worlds, some in their star’s habitable zone. Protoplanetary disks have also been studied and so our understanding of the formation of planetary systems has improved markedly since. 

Artist’s impression of a young star surrounded by a protoplanetary disc made of gas and dust. According to new research, ring-shaped, turbulent disturbances (substructures) in the disk lead to the rapid formation of several gas and ice giants. Credit: LMU / Thomas Zankl, crushed eyes media

The disks of gas and dust around stars have been known to be the precursor to planetary systems for some years. What has been uncertain is the conditions that allow the disk to remain long enough for planets to form and what can lead to their early dissipation. 

An announcement of protoplanetary disks around young binary stars was announced at a meeting of the American Astronomical Society by a team of researchers from National Radio Observatory. They used the Atacama Large Millimetre/sub-millimetre Array otherwise known as ALMA and the near-infrared capability of the Keck II 10 metre telescope. ALMA has been setup in the Atacama Desert at an altitude of 5,000 metres so that the air is clear and dry. It’s composed of 66 antennae all working together as an interferometer to study the coldest and most distant objects in the universe.

Two of the Atacama Large Millimeter/submillimeter Array (ALMA) 12-metre antennas (Credit : Iztok Bon?ina/ESO)

The disks around pre-main sequence binary stars as announced provides an excellent opportunity to study the disks and try to find answers to the questions. The team explored the disk sizes, structure and inclination in relation to the star’s rotation speed and magnetic field strength to try and understand the complex processes at play. Binary and multiple star systems like the DF Tau and FO Tau binary system that were the target of the study are common making an excellent case study. 

DF Tau is a binary quasi-twin star system with component separation of 14 astronomical units with elongated orbits. ALMA detected two circumstellar cool dust disks with one locked magnetically to the star and accreting material onto it. The inner disk seems to have largely eroded and decoupled from the rapidly rotating star. This suggests a link between the rotation of the star, magnetic disk locking and the resultant early disk dissipation. Misalignment of the orbits and disks could impact the evolution of the disk. FO Tau is slightly different where the disks are aligned with the binary orbit, the stars have modest rotation speeds and seem to be magnetically locked to their disks.

ALMA has afforded high resolution images revealing fine levels of disk sub-structures which include spiral patterns, gaps and ring formations around single stars and wide binary companions. It cannot yet resolve detail in the disks of DF Tau and FO Tau systems, to be able to determine disk properties in close binary systems marks a step forward in our understanding of planetary formation.

Source : ALMA Observations Reveal New Insights into Planet Formation in Binary Star Systems

The post Astronomers See Planets Forming Around Binary Stars appeared first on Universe Today.

There are secrets aplenty in a pot of honey – from information about bees' "micro-bee-ota" to DNA from the environment – that can help us fight food fraud and even monitor shifts in climate

A robot mimics the clever fin-folding mechanism used by tuna fish, which increased the bot's turning velocity by almost 33 per cent