It’s possible that I shall make an ass of myself. But in that case one can always get out of it with a little dialectic. I have, of course, so worded my proposition as to be right either way (K.Marx, Letter to F.Engels on the Indian Mutiny)
How can Marvel movie character Ant-Man produce such strong energy out of his small body? The secret lies in the “transistors” on his suit that amplify weak signals for processing. Transistors that amplify electrical signals in the conventional way lose heat energy and limit the speed of signal transfer, which degrades performance. What if it were possible to overcome such limitation and make a high-performance suit that is light and small but without loss of heat energy?
A POSTECH team of Professor Kyoung-Duck Park and Yeonjeong Koo from the Department of Physics and a team from ITMO University in Russia led by Professor Vasily Kravtsov jointly developed a “nano-excitonic transistor” using intralayer and interlayer excitons in heterostructure-based semiconductors, which addresses the limitationsof existing transistors.
“Excitons” are responsible for light emission of semiconductor materials and are key to developing a next-generation light-emitting element with less heat generation and a light source for quantum information technology due to the free conversion between light and material in their electrically neutral states. There are two types of excitons in a semiconductor heterobilayer, which is a stack of two different semiconductor monolayers: the intralayer excitons with horizontal direction and the interlayer excitons with vertical direction.
Optical signals emitted by the two excitons have different lights, durations, and coherence times. This means that selective control of the two optical signals could enable the development of a two-bit exciton transistor. However, it was challenging to control intra- and interlayer excitons in nano-scale spaces due to the non-homogeneity of semiconductor heterostructures and low luminous efficiency of interlayer excitons in addition to the diffraction limit of light.
The team in its previous research had proposed technology for controlling excitons in nano-level spaces by pressing semiconductor materials with a nano-scale tip. This time, for the first time ever, the researchers were able to remotely control the density and luminance efficiency of excitons based on polarized light on the tip without directly touching the excitons. The most significant advantage of this method, which combines a photonic nanocavity and a spatial light modulator, is that it can reversibly control excitons, minimizing physical damage to the semiconductor material. Also, the nano-excitonic transistor that utilizes “light” can help process massive amounts of data at the speed of light while minimizing heat energy loss.
Artificial intelligence (AI) has made inroads into our lives more quickly than we ever expected, and it requires huge volumes of data for learning in order to provide good answers that are actually helpful for users. The ever-increasing volume of information should be collected and processed as more and more fields utilize AI. This research is expected to propose a new data processing strategy befitting an era of data explosion. Yeonjeong Koo, one of the co-first authors of the research paper, said, “The nano-excitonic transistor is expected to play an integral role in realizing an optical computer, which will help process the huge amounts of data driven by AI technology.
The research, recently published in international journal ACS Nano, was supported by the Samsung Science and Technology Foundation and National Research Foundation of Korea.
Methamphetamine, nicotine, caffeine and tetrahydrocannabinol (THC) were detected in downtown Auckland air in the first study of its type in New Zealand and Australia.
Traces caught by filters at a pollution monitoring site on Customs St near the bottom of Queen St were analysed by scientists from Waipapa Taumata Rau, University of Auckland.
The largest concentration of meth detected was 104 picograms (a picogram is one-trillionth of a gram) per cubic metre of air, according to Master of Science student Olivia Johnson and Dr Joel Rindelaub, a research fellow in the School of Chemical Sciences.
The average for 10 samples over five weeks was 24.8 picograms per cubic metre.
“Assuming an active dose of 5 milligrams and 16 cubic metres of air inhaled per person each day, it would take an individual over 8,000 years to inhale an active dose,” the scientists wrote in a paper published in the journal Atmospheric Pollution Research.
Methamphetamine concentrations were higher than in overseas cities such as Barcelona. Airborne drug concentrations spiked in the week leading up to the Christmas holidays and also over New Year’s Eve.
Unsurprisingly, nicotine had the highest average concentration of the four drugs at 4.91 nanograms (a nanogram is one billionth of a gram) per cubic metre, a level lower than in many cities overseas.
Caffeine, likely from sources including steaming takeaway coffees, and THC, from people smoking cannabis, were both detected at lower average concentrations than in studies elsewhere.
“The results aren’t as concerning as a headline might make them sound,” says Rindelaub. “However, they highlight that we really don’t know as much as we should about what’s in the air that we breathe.”
For context, concentrations of PM2.5 and PM10 particulates in the air are typically measured in micrograms (one millionth of a gram).
Airborne monitoring of drugs could be complementary to wastewater analyses, which are carried out for the likes of cocaine, fentanyl, heroin, methamphetamine and MDMA to track drug consumption in communities around the country.
Assessing the effectiveness of policies such as restrictions on tobacco products could be easier with the technique. Caffeine concentrations, meanwhile, seem to correlate with urban pedestrian counts, suggesting a potential proxy for urban activity.
Hamish Patel, a PhD candidate and air quality scientist at Mote Ltd., and Associate Professor Gordon Miskelly also worked on the study, which used liquid chromatography with tandem mass spectrometry to analyse samples collected from 7 December 2020 to 11 January 2021.
The study, the first of its type in Oceania, was only looking for methamphetamine, nicotine, caffeine, and THC, leaving unknown what other drugs may be floating around.
Microplastics swirling in Auckland’s air are equivalent to more than 3 million plastic bottles falling from the sky every year, Rindelaub and colleagues showed in a separate study published in December.
The problem is indoors, too: testing the air in a university lecture theatre where he was delivering a TEDx talk on pollution, Rindelaub found indications of polyester, nylon and PVC.
Over 3,300 premature deaths per year are related to air pollution in Aotearoa, Rindelaub says.
IMAGE: A PHOTO OF THE HUGE ELLIPTICAL GALAXY M87 [LEFT] IS COMPARED TO ITS THREE-DIMENSIONAL SHAPE AS GLEANED FROM METICULOUS OBSERVATIONS MADE WITH THE HUBBLE AND KECK TELESCOPES [RIGHT]. BECAUSE THE GALAXY IS TOO FAR AWAY FOR ASTRONOMERS TO EMPLOY STEREOSCOPIC VISION, THEY INSTEAD FOLLOWED THE MOTION OF STARS AROUND THE CENTER OF M87, LIKE BEES AROUND A HIVE. THIS CREATED A THREE-DIMENSIONAL VIEW OF HOW STARS ARE DISTRIBUTED WITHIN THE GALAXY.view more
CREDIT: ILLUSTRATION: NASA, ESA, JOSEPH OLMSTED (STSCI), FRANK SUMMERS (STSCI) SCIENCE: CHUNG-PEI MA (UC BERKELEY)
Though we live in a vast three-dimensional universe, celestial objects seen through a telescope look flat because everything is so far away. Now for the first time, astronomers have measured the three-dimensional shape of one of the biggest and closest elliptical galaxies to us, M87. This galaxy turns out to be "triaxial," or potato-shaped. This stereo vision was made possible by combining the power of NASA's Hubble Space Telescope and the ground-based W. M. Keck Observatory on Maunakea, Hawaii.
In most cases, astronomers must use their intuition to figure out the true shapes of deep-space objects. For example, the whole class of huge galaxies called "ellipticals" look like blobs in pictures. Determining the true shape of giant elliptical galaxies will help astronomers understand better how large galaxies and their central large black holes form.
Scientists made the 3D plot by measuring the motions of stars that swarm around the galaxy's supermassive central black hole. The stellar motion was used to provide new insights into the shape of the galaxy and its rotation, and it also yielded a new measurement of the black hole's mass. Tracking the stellar speeds and position allowed researchers to build a three-dimensional view of the galaxy.
Astronomers at the University of California, Berkeley, were able to determine the mass of the black hole at the galaxy's core to a high precision, estimating it at 5.4 billion times the mass of the Sun. Hubble observations in 1995 first measured the M87 black hole as being 2.4 billion solar masses, which astronomers deduced by clocking the speed of the gas swirling around the black hole. When the Event Horizon Telescope, an international collaboration of ground-based telescopes, released the first-ever image of the same black hole in 2019, the size of its pitch-black event horizon allowed researchers to calculate a mass of 6.5 billion solar masses using Einstein's theory of general relativity.
The stereo model of M87 and the more precise mass of the central black hole could help astrophysicists learn the black hole's spin rate. "Now that we know the direction of the net rotation of stars in M87 and have an updated mass of the black hole, we can combine this information with data from the Event Horizon Telescope to constrain the spin," said Chung-Pei Ma, a UC Berkeley lead investigator on the research.
Over ten times the mass of the Milky Way, M87 probably grew from the merger of many other galaxies. That's likely the reason M87's central black hole is so large – it assimilated the central black holes of one or more galaxies it swallowed.
Ma, together with UC Berkeley graduate student Emily Liepold (lead author on the paper published in theAstrophysical Journal Letters) and Jonelle Walsh at Texas A&M University were able to determine the 3D shape of M87 thanks to a new precision instrument mounted on the Keck II Telescope. They pointed Keck at 62 adjacent locations of the galaxy, mapping out the spectra of stars over a region about 70,000 light-years across. This region spans the central 3,000 light-years where gravity is largely dominated by the supermassive black hole. Though the telescope cannot resolve individual stars because of M87's great distance, the spectra can reveal the range of velocities to calculate mass of the object they're orbiting.
"It's sort of like looking at a swarm of 100 billion bees," said Ma. "Though we are looking at them from a distance and can't discern individual bees, we are getting very detailed information about their collective velocities."
The researchers took the data between 2020 and 2022, as well as earlier star brightness measurements of M87 from Hubble, and compared them to computer model predictions of how stars move around the center of the triaxial-shaped galaxy. The best fit to this data allowed them to calculate the black hole's mass. "Knowing the 3D shape of the 'swarming bees' enabled us to obtain a more robust dynamical measurement of the mass of the central black hole that is governing the bees' orbiting velocities," said Ma.
In the 1920s, astronomer Edwin Hubble first classified galaxies according to their shapes. Flat disk spiral galaxies could be viewed from various projection angles of the sky: face-on, oblique, or edge-on. But the "blobby-looking" galaxies were more problematic to characterize. Hubble came up with the term elliptical. They could only be sorted out by how great the ellipticity was. They didn't have any apparent dust or gas inside of them for better distinguishing between them. Now, a century later astronomers have a stereoscopic look at a prototypical elliptical galaxy.
The Hubble Space Telescope is a project of international cooperation between NASA and ESA. NASA's Goddard Space Flight Center in Greenbelt, Maryland, manages the telescope. The Space Telescope Science Institute (STScI) in Baltimore, Maryland, conducts Hubble and Webb science operations. STScI is operated for NASA by the Association of Universities for Research in Astronomy, in Washington, D.C.
IMAGE: THE HERA RADIO TELESCOPE, LOCATED IN KAROO IN SOUTH AFRICA, CONSISTS OF 350 DISHES POINTED UPWARD TO DETECT RADIO WAVES FROM THE EARLY UNIVERSE.view more
CREDIT: DARA STORER
An array of 350 radio telescopes in the Karoo desert of South Africa is getting closer to detecting the “cosmic dawn” — the era after the Big Bang when stars first ignited and galaxies began to bloom.
A team of scientists from across North America, Europe, and South Africa has doubled the sensitivity of a radio telescope called the Hydrogen Epoch of Reionization Array (HERA). With this breakthrough, they hope to peer into the secrets of the early universe.
“Over the last couple of decades, teams from around the world have worked towards a first detection of radio waves from the cosmic dawn. While such a detection remains elusive, HERA’s results represent the most precise pursuit to date,” says Adrian Liu, an Assistant Professor at the Department of Physics and the Trottier Space Institute at McGill University.
The array was already the most sensitive radio telescope in the world dedicated to exploring the cosmic dawn. Now the HERA team has improved its sensitivity by a factor of 2.1 for radio waves emitted about 650 million years after the Big Bang and 2.6 for radio waves emitted about 450 million years after the Big Bang. Their work is described in a paper published in The Astrophysical Journal.
Although the scientists have yet to detect radio emissions from the end of the cosmic dark ages, their results provide clues about the composition of stars and galaxies in the early universe. So far, their data suggest that early galaxies contained very few elements besides hydrogen and helium, unlike our galaxies today. Today’s stars, have a variety of elements, ranging from lithium to uranium, that are heavier than helium.
Ruling out some theories
When the radio dishes are fully online and calibrated, the team hopes to construct a 3D map of the bubbles of ionized and neutral hydrogen – markers for early galaxies – as they evolved from about 200 million years to around 1 billion years after the Big Bang. The map could tell us how early stars and galaxies differed from those we see around us today, and how the universe looked in its adolescence, say the researchers.
According to the researchers, the fact that the HERA team has not yet detected these signals rules out some theories of how stars evolved in the early universe. “Our data suggest that early galaxies were about 100 times more luminous in X-rays than today’s galaxies. The lore was that this would be the case, but now we have actual data that bolsters this hypothesis,” says Liu.
Waiting for a signal
The HERA team continues to improve the telescope’s calibration and data analysis in hopes of seeing those bubbles in the early universe. However, filtering out the local radio noise to see the signals from the early universe has not been easy. “If it’s Swiss cheese, the galaxies make the holes, and we’re looking for the cheese,” says David DeBoer, a research astronomer in University of California Berkeley’s Radio Astronomy Laboratory.
“HERA is continuing to improve and set better and better limits,” says Aaron Parsons, principal investigator for HERA and a University of California Berkeley Associate Professor of astronomy. “The fact that we’re able to keep pushing through, and we have new techniques that are continuing to bear fruit for our telescope, is great.”
IMAGE: A UNIVERSITY OF MINNESOTA TWIN CITIES-LED TEAM LOOKED MORE THAN 13 BILLION YEARS INTO THE PAST TO DISCOVER A UNIQUE, MINUSCULE GALAXY THAT COULD HELP ASTRONOMERS LEARN MORE ABOUT GALAXIES THAT WERE PRESENT SHORTLY AFTER THE BIG BANG.view more
CREDIT: ESA/WEBB, NASA & CSA, P. KELLY
Using first-of-their-kind observations from the James Webb Space Telescope, a University of Minnesota Twin Cities-led team looked more than 13 billion years into the past to discover a unique, minuscule galaxy that generated new stars at an extremely high rate for its size. The galaxy is one of the smallest ever discovered at this distance—around 500 million years after the Big Bang—and could help astronomers learn more about galaxies that were present shortly after the Universe came into existence.
The paper is published in Science, one of the world's top peer-reviewed academic journals.
The University of Minnesota researchers were one of the first teams to study a distant galaxy using the James Webb Space Telescope, and their findings will be among the first ever published.
“This galaxy is far beyond the reach of all telescopes except the James Webb, and these first-of-their-kind observations of the distant galaxy are spectacular,” said Patrick Kelly, senior author of the paper and an assistant professor in the University of Minnesota School of Physics and Astronomy. “Here, we’re able to see most of the way back to the Big Bang, and we've never looked at galaxies when the universe was this young in this level of detail. The galaxy’s volume is roughly a millionth of the Milky Way’s, but we can see that it’s still forming the same numbers of stars each year.”
The James Webb telescope can observe a wide enough field to image an entire galaxy cluster at once. The researchers were able to find and study this new, tiny galaxy because of a phenomenon called gravitational lensing—where mass, such as that in a galaxy or galaxy cluster, bends and magnifies light. A galaxy cluster lens caused this small background galaxy to appear 20 times brighter than it would if the cluster were not magnifying its light.
The researchers then used spectroscopy to measure how far away the galaxy was, in addition to some of its physical and chemical properties. Studying galaxies that were present when the Universe was this much younger can help scientists get closer to answering a huge question in astronomy regarding how the Universe became reionized.
“The galaxies that existed when the Universe was in its infancy are very different from what we see in the nearby Universe now,” explained Hayley Williams, first author on the paper and a Ph.D. student at the Minnesota Institute for Astrophysics. “This discovery can help us learn more about the characteristics of those first galaxies, how they differ from nearby galaxies, and how the earlier galaxies formed.”
The James Webb telescope can collect about 10 times as much light as the Hubble Space Telescope and is much more sensitive at redder, longer wavelengths in the infrared spectrum. This allows scientists to access an entirely new window of data, the researchers said.
“The James Webb Space Telescope has this amazing capability to see extremely far into the universe,” Williams said. “This is one of the most exciting things about this paper. We're seeing things that previous telescopes would have ever been able to capture. It’s basically getting a snapshot of our universe in the first 500 million years of its life.”
The research was supported by the National Science Foundation and NASA through the Space Telescope Science Institute, with additional funding from the United States-Israel Binational Science Foundation and the Spanish State Research Agency.
In addition to Williams and Kelly, the research team included University of Minnesota School of Physics and Astronomy postdoctoral researcher Wenlei Chen, Professor Claudia Scarlata, Ph.D. student Yu-Heng Lin, and graduate student Noah Rogers; University of Copenhagen researchers Gabriel Brammer, Jens Hjorth, and Danial Langeroodi; Ben-Gurion University of the Negev Associate Professor Adi Zitrin; University of California Los Angeles faculty member Tomasso Treu; Space Telescope Science Institute researchers Anton Koekemoer, Lou Strolger, and Justin Pierel; Chiba University faculty member Masamune Oguri; University of Cantebria researcher Jose Diego; Astronomical Observatory of Trieste researcher Mario Nonino; University of the Basque Country Professor Tom Broadhurst; University of La Laguna researchers Ismael Perez-Fournon and Frederick Poidevin; University of California Santa Cruz Assistant Professor Ryan Foley; Rutgers University Professor Saurabh Jha; University of California Berkeley Professor Alexei Filippenko; and University of Tokyo postdoctoral researcher Lilan Yang.
JOURNAL
Science
METHOD OF RESEARCH
Observational study
ARTICLE TITLE
A magnified compact galaxy at redshift 9.51 with strong nebular emission lines
CREDIT: ESA/STFC RAL SPACE/UCL/UK SPACE AGENCY/ ATG MEDIALAB
Artificial Intelligence (AI) experts have been challenged to help a new space mission to investigate Earth’s place in the universe.
The Ariel Data Challenge 2023, which launches on 14 April, is inviting AI and machine learning experts from industry and academia to help astronomers understand planets outside our solar system, known as exoplanets.
Dr Ingo Waldmann, Associate Professor in Astrophysics, UCL (University College London) and Ariel Data Challenge lead said:
“AI has revolutionised many fields of science and industry in the past years. The field of exoplanets has fully arrived in the era of big-data and cutting edge AI is needed to break some of our biggest bottlenecks holding us back.”
Understanding our place in the universe
For centuries, astronomers could only glimpse the planets in our solar system but in recent years, thanks to telescopes in space, they have discovered more than 5000 planets orbiting other stars in our galaxy.
The European Space Agency’s Ariel telescope will complete one of the largest-ever surveys of these planets by observing the atmospheres of around one-fifth of the known exoplanets.
Due to the large number of planets in this survey, and the expected complexity of the captured observations, Ariel mission scientists are calling for the help of the AI and machine learning community to help interpret the data.
Ariel Data Challenge
Ariel will study the light from each exoplanet’s host star after it has travelled through the planet’s atmosphere in what is known as a spectrum. The information from these spectra can help scientists investigate the chemical makeup of the planet’s atmosphere and discover more about these planets and how they formed.
Scientists involved in the Ariel mission need a new method to interpret these data. Advanced machine learning techniques could help them to understand the impact of different atmospheric phenomena on the observed spectrum.
The Ariel Data Challenge calls on the AI community to investigate solutions. The competition is open from 14 April to 18t June 2023.
Participants are free to use any model, algorithm, data pre-processing technique or other tools to provide a solution. They may submit as many solutions as they like and collaborations between teams are welcomed.
This year, the competition also offers participants access to High Powered Computing resources through DiRAC, part of the UK’s Science and Technology Facilities Council’s computing facilities.
Kai Hou (Gordon) Yip, Postdoctoral Research Fellow at UCL and Ariel Data Challenge Lead said:
“With the arrival of next-generation instrumentation, astronomers are struggling to keep up with the complexity and volume of incoming exo-planetary data. The ECML-PKDD data challenge 2023 provides an excellent platform to facilitate cross-disciplinary solutions with AI experts.”
The competition
Winners will be invited to present their solutions at the prestigious ECML conference. The top three winning teams will be receive sponsored tickets to ECML-PKDD in Turing or the cash equivalent.
Winners will also be invited to present their solutions to the Ariel consortium.
The UK Space Agency, Centre National d’Etudes Spatiales (CNES), European Research Council, UKRI Science and Technology Funding Council (STFC), European Space Agency and Europlanet Society support the competition.
For the first time, DiRAC is providing free access to GPU computing resources to selected participants. The application is open for all.
Previous competition
This is the fourth Ariel Machine Learning Data challenge following successful competitions in 2019, 2021 and 2022. The 2022 challenge welcomed 230 participating teams from across the world, including entrants from leading academic institutes and AI companies.
This challenge and its predecessor have taken a bite-sized aspect of a larger problem to help make exoplanet research more accessible to the machine-learning community. These challenges are not designed to solve the data analysis issues faced by the mission outright but provide a forum for new ideas, discussions and to encourage future collaborations.
More details about the competition and how to take part can be found on the Ariel Data Challenge website. Follow @ArielTelescope for more updates.
Ariel will be placed in orbit around the Lagrange Point 2 (L2), a gravitational balance point 1.5 million kilometres beyond the Earth’s orbit around the Sun
IMAGE: INFRARED IMAGE OF HIP 99770 TAKEN BY THE SUBARU TELESCOPE. THE BRIGHT MAIN STAR AT THE POSITION MARKED WITH * IS HIDDEN. THE DASHED ELLIPSE SHOWS THE SIZE OF JUPITER’S ORBIT AROUND THE SUN FOR SCALE. THE ARROW POINTS TO THE DISCOVERED EXOPLANET HIP 99770 B.view more
CREDIT: T. CURRIE/SUBARU TELESCOPE, UTSA
An international team of astronomers announced the first exoplanet discovered through a combined approach of direct imaging and precision measurements of a star’s motion on the sky. This new method promises to improve the efficiency of exoplanet searches, paving the way for the discovery of an Earth twin.
To discover exoplanets, planets which orbit stars other than the Sun, by imaging astronomers have up until now used “blind surveys”: stars are selected for imaging consider factors such as age and distance but are otherwise unbiased. However, blind surveys find planets very infrequently. Knowing where to look would help increase detection rates.
An international research team led by Subaru Telescope, the University of Tokyo, the University of Texas-San Antonio, and the Astrobiology Center of Japan, searched for hints of unknown planets in the data from the European Space Agency’s Gaia mission and its predecessor, Hipparcos. The team identified a star, HIP 99770 located 133 light-years away in the constellation Cygnus, whose motion suggests that an unseen planet is gravitationally pulling on it. Direct imaging observations with the Subaru Telescope detected the planet, HIP 99770 b.
The newly discovered planet is 14-16 times more massive than Jupiter. Its orbit is just over 3 times further from its star than Jupiter is from the Sun. The planet is 10 times hotter than Jupiter, with signs of water and carbon monoxide in its atmosphere.
A decade from now, astronomers hope to image a potentially-habitable planet with a size and temperature like the Earth using observatories like the Thirty Meter Telescope (TMT). Compared with HIP 99770 b, this Earth twin will be smaller and closer to its star, traits that will make it harder to detect. But with precise motion measurements, researchers will know where to look in this game of planetary hide and seek.
