News Feeds

"I value criticism and my collaborations are based on the ability to openly criticize other's ideas as a means of finding the 'right' answer."

The post An Open Letter to Dr. Stefan Baral: Let’s Revisit Your Article “Covid Vaccines for Children Should Not Get Emergency Use Authorization.” first appeared on Science-Based Medicine.

One proposal offers a unique method to directly image ExoEarths, or rocky worlds around nearby stars.

It’s the holy grail of modern exoplanet astronomy. As of writing this, the count of known worlds beyond the solar system stands at 6,520. Most of these are ‘hot Jupiters,’ large worlds in tight orbits around their host star. But what we’d really like to get a look at are ‘ExoEarths,’ rocky worlds (hopefully) like our own.

Now, a recent study out of the University of Paris, the European Southern Observatory (ESO) and the University of Cambridge entitled Exoplanets in Reflected Starlight with Dual-Field Interferometry: A Case For Shorter Wavelengths and a Fifth Unit Telescope at VLTI/Paranal suggests a method to do just that in the coming decade. This would involve one the most massive telescope complexes ever built: the Very Large Telescope. Based at Paranal Observatory in Chile, this array consists of four 8.2-metre telescopes working in concert via a method known as interferometry. The study advocates adding a fifth telescope, giving the VLT the capacity to see Jupiter-sized worlds shining directly in the host star’s light… and with a few key upgrades, the new and improved VLT could perhaps image ‘ExoEarths’ directly.

Pioneering Dual-Field Interferometry

Interferometry is the method of using superimposed waves collected from two telescopes to merge a signal into one image. This method allows for a resolution equivalent to the baseline between the two collecting instruments, bypassing the need for one enormous telescope. Long baseline radio interferometry can span continents, and there are plans to move the technique into space. Interferometry at visual wavelengths is a tougher proposition, one that’s just reaching its true potential.

Dual Field Interferometry uses the technique to simultaneously focus on two narrow fields in context within a larger field. One field is centered on the host star, and one on the target exoplanet. This can then minimize (subtract) photon shot noise from the primary, allowing for a clear view of the target world.

“With this technique, at the VLTI, we have a resolution equivalent to having a telescope of 130 meters,” lead author on the study Sylvestre Lacour (University of Paris) told Universe Today. “This allows us to distinguish the exoplanet’s light from the contamination by the stellar light, allowing to detect exoplanets very close to the star.”

ESO’s Very Large Telescope (VLT) timelapse of Beta Pictoris b around its parent star. This young massive exoplanet was initially discovered in 2008 using the NACO instrument at the VLT.  The sequence tracked the exoplanet from late 2014 until late 2016, using the Spectro-Polarimetric High-contrast Exoplanet REsearch instrument (SPHERE) — another instrument on the VLT.

“The term ‘dual’ in dual interferometry comes from the fact the we are observing at the same time the exoplanet and the star with the optical interferometer,” says Lacour. “This is necessary to be able to probe at the same time the phase of the stellar light and the phase of the exoplanet light, to be able to distinguish the two. By ‘phase’ I mean the phase of the electric field entering the interferometer.”

The GRAVITY instrument at the VLTI in Paranal. Credit: ESO The Hunt for ExoEarths

The method is already being applied to reveal nearby worlds. “We typically observe exoplanets at a few tens of parsecs,” says Lacour. “They are massive exoplanets, more massive than Jupiter (between 4 and 10 Jupiter masses), and they are young, less than 50 million years (old). You can look for the results for the GRAVITY collaboration, operating the GRAVITY instrument at Paranal.”

One key technique used to overcome the effects of ‘shot noise’ is what’s termed as ‘apodization’. “Apodization is a way to decrease the contamination of the stellar light entering into our interferometer,” says Lacour. “It is similar to adding a coronagraph.”

Apodization makes ground-based systems such as the VLTI viable in terms of exoplanet science and direct detection. Other efforts such as the European Space Agency’s Proba-3 space telescope launching later in 2024 will use a free flying coronagraph to directly image exoplanets.

A pro to this method is it can characterize orbits within a few Astronomical Units from their host star. Other techniques observe planets very close in, or very far out. The downside of the method is that it’s a very difficult technique, right on the grim edge of what’s currently possible with existing telescopes.

An artist’s conception of the E-ELT telescope. Credit: Swinburne Astronomy Productions/ESO The Future of Exoplanet Astronomy

There’s already a good case for plans to extend the VLTI baseline to a fifth instrument. This includes direct imaging for worlds known orbiting around nearby stars to include Proxima Centauri B and Tau Ceti e. Lessons learned from the VLTI could also work for the Extremely Large Telescope, which may see first light in 2028.

An artist’s conception of Tau Ceti e, a possible ‘ExoEarth’ in the habitable zone. Ph03nix1986/Wikimedia Commons/CCA 4.0

It’ll be exciting to see more nearby worlds revealed by this technique in the coming decade.

The post Existing Telescopes Could Directly Observe ‘ExoEarths…’ with a Few Tweaks appeared first on Universe Today.

A survey of women who have had vaginal sex with men found that 4 in 5 said they had experienced pain during intercourse

Note from editors: In response to the growing concerns about artificial intelligence development, on November 1–2, 2023, the British Government held the first ever summit on AI Safety, attended by representatives of 28 countries as well as business leaders working in the field of AI. The summit aptly took place at Bletchley Park, the very location where Alan Turing cracked the German Enigma code, which played a significant part in the Allied victory in WWII.

The result of the summit was the signing of The Bletchley Declaration, which recognizes the urgent need to understand and collectively manage potential risks of AI through a joint global effort to ensure AI is developed and deployed in a safe, responsible way for the benefit of the global community. The signatories of the declaration include Canada, China, the European Union, Japan, the United Kingdom, and the United States.

The world leaders in attendance officially recognized the need to collaborate on testing the next generation of AI models against a range of critical national security, safety, and societal risks.

At the conclusion of the event, the British Prime Minister Rishi Sunak and tech entrepreneur Elon Musk sat down at the prime minister’s residence for a private conversation, and then held a public discussion. Their public dialogue is transcribed below, with only minor edits for clarity.

Rishi Sunak has served as the Prime Minister of the United Kingdom since 2022 and has been Member of Parliament since 2015. He studied philosophy, politics and economics at Oxford and earned his MBA from Stanford as a Fulbright Scholar. Prior to his political career, he was a hedge fund manager.

Elon Musk was a founding board member of OpenAI, the research organization behind ChatGPT. He is the owner of Tesla, a pioneer in autonomous electric vehicles, and the founder of Neuralink, a company working on developing implantable brain-computer interfaces. He is also the CEO of the rocket company SpaceX and owner of the social media platform X.com (formerly Twitter).

Rishi Sunak: Bill Gates said there is no one in our time who has done more to push the bounds of science innovation than you. That’s a nice thing to have anyone say about you. But oddly enough, when it comes to AI, you’ve been doing almost the opposite. For around a decade, you’ve been saying, “Hang on, we need to think about what we’re doing and what we’re pushing here. And what do we do to make this safe?” What was it that caused you to think about it that way? Why do we need to be worried?

Elon Musk: I’ve been somewhat concerned for quite a while. I would tell people, “We should really be concerned about AI.” They’re like, “What are you talking about?” They’ve never really had any experience with AI. But since I have been immersed in technology for a long time, I could see it coming.

I think this year there have been a number of breakthroughs. We’re at the point at which someone can see a dynamically created video of themselves, like video of you saying anything in real time. These sorts of deep fake videos are really incredibly good, sometimes more convincing than real ones. And then obviously things like ChatGPT were quite remarkable. I saw GPT-1, GPT-2, GPT-3, GPT-4—the whole sort of lead up to that. It was easy for me to see where it’s going. If you just extrapolate the points on a curve and assume that trend will continue, then we will have profound artificial intelligence. And obviously at a level that far exceeds human intelligence.

But I’m glad to see that, at this point, people are taking safety seriously, and I’d like to say thank you for holding this AI Safety conference. I think it will go down in history as being very important. It’s really quite profound.

I do think, overall, that the potential is there for artificial intelligence to most likely have a positive effect and to create a future of abundance where there is no scarcity of goods and services. But it is somewhat of the Magic Genie problem: if you have a magic genie that can grant all the wishes…usually those stories don’t end well. Be careful what you wish for, including wishes.

RS: So, you talked a little bit about the summit and thank you for being engaged in it, which has been great. One of the things that we achieved today in the meetings between the companies and the leaders was an agreement that, ideally, governments should be doing safety testing of models before they’re released.

In government, my job is to say, “Hang on, there is a potential risk here.” Not a definite risk, but a potential risk of something that could be bad. My job is to protect the country, and we can only do that if we develop the capability we need in our safety institute, and then make sure we can test the models before they are released. You’ve talked about the potential risk. What are the types of things governments like ours should be doing to manage and mitigate those risks?

EM: Well, I generally think that it is good for government to play a role when public safety is at risk. For the vast majority of software, public safety is not at risk. If the app crashes on your phone or your laptop, it’s not a massive catastrophe. But talking about digital super intelligence, does it pose a risk to the public? Then there is a role for government to play, to safeguard the interests of the public.

This is true in many fields. I deal with regulators throughout the world because of Starlink (communications), SpaceX (aerospace), and Tesla (cars). So I’m very familiar with dealing with regulators and I actually agree with the vast majority of regulations. There are a few that I disagree with from time to time, probably less than one percent.

There is some concern from people in Silicon Valley who have never dealt with regulators before, and they think that this is going to just crush innovation, slow them down, and be annoying. And it will be annoying—it’s true, they’re not wrong about that. But I think we’ve learned over the years that having a referee is a good thing. And if you look at any sports game, there’s always a referee and nobody’s suggesting to have a sports game without one. I think that’s the right way to think about this: for government to be a referee to make sure the public safety is addressed.

I think there might be, at times, too much optimism about technology. I say that as a technologist, so I ought to know. But like I said, on balance, I think that the AI will be a force for good. But the probability of it going bad is not zero percent. We just need to mitigate the downside potential.

UK Prime Minister Rishi Sunak speaks at a plenary session on day two of the AI Summit at Bletchley Park on November 2, 2023. (Photo by Kirsty O’Connor / No 10 Downing Street [CC BY-NC-ND 2.0 DEED])

RS: Do you think governments can develop the expertise? Governments need to quickly tool up capability personnel-wise, which is what we’re doing. Is it possible for governments to do that fast enough given how quickly the technology is developing?

EM: It’s a great point you’re making. The pace of AI is faster than any technology I’ve seen in history, by far. And it seems to be growing in capability by at least five-fold, perhaps ten-fold per year. It will certainly grow by an order of magnitude in 2024. And government isn’t used to moving at that speed. But I think even if there are no firm regulations and even if there isn’t an enforcement capability, simply having insight and being able to highlight concerns to the public will be very powerful.

RS: Well, hopefully we can do better than that. What was interesting over the last couple of days talking to everyone who’s doing the development of this—and I think you can go with this—is just the pace of advancement here is unlike anything all of you have seen in your careers in technology, because you’ve got these kind of compounding effects from the hardware, and the data, and the personnel.

EM: Currently, the two leading centers for AI development are the San Francisco Bay Area and the London area, and there are many other places where it’s being done, but those are the two leading areas. So, I think if the U.S. and the UK, and China are aligned on safety, that’s all going to be a good thing because that’s really where the leadership is generally.

RS: Good. Thanks. You mentioned China. I took a decision to invite China to the summit over the last days, and it was not an easy decision. A lot of people criticize me for it. My view is, if you’re going to try to have a serious conversation, you need to. What are your thoughts?

EM: It’s essential.

RS: Should we be engaging with China? Can we trust them?

EM: If we don’t, if China is not on board with AI safety, it’s somewhat of a moot situation. The single biggest objection that I get to any kind of AI regulation or sort of safety controls is, “Well, China is not going to do it and therefore they will just jump into the lead and exceed us all.” But actually, China is willing to participate in AI safety. And thank you for inviting them. And I think we should thank China for attending. When I was in China earlier this year, my main subject of discussion with the leadership in China was AI safety. They took it seriously, which is great, and having them here I think was essential. Really, if they are not participants, it’s pointless.

RS: We were pleased they were engaged in the discussions yesterday and actually ended up signing the same communiqué that everyone else did. Which is a good start. And as I said, we need everyone to approach this in a similar way if we’re going to have a realistic chance of resolving it.

We had a good debate today about open source. And I think you’ve been a proponent of algorithmic transparency, making some of the X.com algorithms public. Some are very concerned about open source models being used by bad actors. And then you’ve got people who say they are critical to innovation. What are your thoughts on how we should approach this?

EM: Well, the open source algorithms and data tend to lag the closed source by 6 to 12 months. Given the rate of improvement this is quite a big difference; if things are improving by a factor of let’s say five or more, then being a year behind you are five times worse. It’s a pretty big difference. And that might be an OK situation.

But certainly it will get to the point where you’ve got open source AI that will start to approach human level intelligence, perhaps exceed it. I don’t quite know what to do about it. I think it’s somewhat inevitable. There will be some amount of open source and I guess I would have a slight bias towards open source because at least you can see what’s going on, whereas with closed source, you don’t know what’s happening. Now it should be said that even if AI is open source, do you actually know what’s going on? If you’ve got a gigantic data file and billions of data points, weights, and parameters…you can’t just read it and see what it’s going to do. It’s a gigantic file of inscrutable numbers. You can test it when you run it. But it’s probabilistic as opposed to deterministic. It’s not like traditional programming where you’ve got very discrete logic, and the outcome is very predictable and you can read each line and see what each line is going to do. A neural net is just a whole bunch of probabilities.

RS: The point you’ve just made is one that we have been talking about a lot. AI is not like normal software, where there’s predictability about inputs improving leading to a particular output improving. And as the models iterate and improve, we don’t quite know what’s going to come out the other end. Which is why there is this bias for that we need to get in there while the training runs are being done, before the models are released…to understand what has this new iteration brought about in terms of capability,

When I talk to people about AI, the thing that comes up the most is probably not so much the stuff we’ve been talking about, but jobs. It’s, “What does AI mean for my job? Is it going to mean that I don’t have a job, or my kids are not going to have a job?”

My answer as a policymaker and as a leader is that AI is already creating jobs and you can see that in the companies that are starting, and also in the way it’s being used more as a co-pilot versus replacing the person. There’s still human agency, but AI is helping you do your job better, which is a good thing. And as we’ve seen with technological revolutions in the past, clearly there’s change in the labor market. I was quoting an MIT study today that they did a couple of years ago; something like 60 percent of the jobs at that moment didn’t exist 40 years ago. So—it’s hard to predict.

And my job is to create an incredible education system, whether it’s at school, whether it’s retraining people at any point in their career. Ultimately, if we’ve got a skilled population, then we ought to keep up with the pace of change and have a good life. But it’s still a concern. What are your observations on AI and the impact on labor markets and people’s jobs, and how people should feel as they think about this?

EM: Well, I think we are seeing the most disruptive force in history here. For the first time, we will have something that is smarter than the smartest human. It’s hard to say exactly what that moment is, but there will come a point where no job is needed. You can have a job if you want to have a job for personal satisfaction, but the AI will be able to do everything. I don’t know if that makes people comfortable or uncomfortable. That’s why I say, if you wish for a magic genie that gives you any wishes you want and there’s no limit—you don’t have this three wish limit—you just have as many wishes as you want… It’s both good and bad.

One of the challenges in the future will be, how do we find meaning in life, if you have a magic genie that can do everything you want? When there’s new technology, it tends to usually follow an S-curve. In this case, we’re going to be on the exponential portion of the S-curve for a long time. You’ll be able to ask for anything. We won’t have universal basic income. We’ll have universal high income. In some sense, it’ll be somewhat of a leveler or an equalizer. Really, I think everyone will have access to this magic genie. You’ll be able to ask any question. It’ll certainly be good for education. It’ll be the best, most patient tutor. There will be no shortage of goods and services. It will be an age of abundance.

I’d recommend people read Iain Banks. The Banks culture books are definitely, by far, the best envisioning of an AI future. There’s nothing even close that’ll give you a sense of what is a fairly utopian or protopian future with AI.

RS: Universal high income is a nice phrase. I think part of our job is to make sure that we can navigate to that largely positive place that you’re describing and help people through it between now and then.

EM: It is largely positive, yes. You know, a lot of jobs are uncomfortable or dangerous or sort of tedious, and the computer will have no problem doing that. It will be happy to do it all. And we still have sports where humans compete, like the Olympics. Obviously, a machine can go faster than any human, but humans still race against each other. Even though the machines are better, people do find fulfillment in that.

RS: Yes, we still find a way. It’s a good analogy. We’ve been talking a lot about managing the risks… Let’s talk a little bit about the opportunities.

Having that personalized tutor is incredible compared to classroom learning. If you can have every child have a personal tutor specifically for them that evolves with them over time, that could be extraordinary. And so that you know, for me, I look at that, I think, gosh, that is within reach at this point! That’s one of the benefits I’m most excited about.

I was just going over a couple of things with the team, like how are we doing AI right now that it’s making a difference to people’s lives. We have this thing called gov.uk, all the government information brought together on one website. If you need to get a driving license, passport, pay your taxes, any interaction with government, it is centralized in a very easy to use way. So, a large chunk of the population is interacting with gov.uk every single day to do all these day-to-day tasks, right?

We are about to deploy AI across the platform to make that whole process even easier. Like, “Look, I’m currently here and I’ve lost my passport and my flight is in five hours.” At the moment, that would require how many steps to figure out what you do. When we deploy the AI, it should be that you could just literally say that, and boom, we’re going to walk you through. And that’s going to benefit millions and millions of people every single day.

That’s a very practical way that, in my seat, I can start using this technology to help people in their day-to-day lives—not just healthcare discoveries and everything else that we’re also doing. That’s quite a powerful demonstration.

This article appeared in Skeptic magazine 29.1
Buy print edition
Buy digital edition
Subscribe to print edition
Subscribe to digital edition
Download our app

When you look at the landscape of things that you see as possible, what are you particularly excited about?

EM: I think certainly an AI tutor is going to be amazing. I think there’s also, perhaps, companionship, which may seem odd. How can a computer really be your friend? But if you have an AI that has memory and remembers all of your interactions, and, say, you gave it permission to read everything you’ve ever done…and you can talk to it every day, and those conversations build upon each other… It will really know you better than anyone, perhaps even yourself. You will actually have a great friend. I think that will be a real thing. One of my sons has some learning disabilities and has trouble making friends. An AI friend would be great for him.

RS: OK… You know, that was a surprising answer that’s worth reflecting on. That’s really interesting.

© Crown Copyright 2023. Reproduced under the Open Government Licence v 3.0. Transcribed by Skeptic.

One of the most fundamental questions astronomers ask about an object is “What’s its distance?” For very faraway objects, they use classical Cepheid variable stars as “distance rulers”. Astronomers call these pulsating stars “standard candles”. Now there’s a whole team of them precisely clocking their speeds along our line of sight.

What makes a classical Cepheid a “standard candle” in the darkness of the Universe? It’s that pulsation. Not only does a Cepheid grow larger in a regular rhythm, but its brightness changes over predictable periods of time. In the early 1900s, astronomer Henrietta Leavitt studied thousands of these stars. She found something pretty interesting: there’s a strong relationship between a Cepheid’s luminosity and its pulsation period. And that’s a useful relationship.

When you compare a Cepheid’s luminosity to its pulsation period, you can derive the star’s distance. This relationship appears to be true for all known Cepheids. That’s why they’re considered an important part of the cosmic distance ladder. They’re the main benchmark for scaling the huge distances between galaxies and galaxy clusters.

Types of Cepheids

There are different “flavors” of Cepheids. The “classical” ones have pulsation periods ranging from a few days to a few months. They’re all more massive than the Sun and can be up to a hundred thousand times more luminous. Their radii can change pretty drastically during a cycle—some grow by millions of kilometers and then shrink. Type II Cepheids have pulsation periods between 1 and 50 days and are usually very old, low-mass stars. There are other types, including anomalous Cepheids with very short periods. Scientists also know about double-mode Cepheids with “heartbeats” that pulsate in two or more modes.

Some pretty well-known stars are Cepheid variables. For example, Polaris—the well-known “North Star” is one, as is RR Puppis, Delta Cephei, and Eta Aquilae—all visible from Earth. Why these stars pulsate is still being studied but here’s a very basic look at their process. The core of the star produces heat which heats the outer layers. They expand, and then cool. Radiation is escaping, which makes the star appear brighter. The cooler gas contracts under gravity and makes the star look smaller and cooler. Of course, the devil is in the details, which is why astronomers want to know more about the processes these stars undergo.

Polaris A (Pole Star) with its two stellar companions, Polaris Ab and Polaris B. Polaris itself is a Cepheid type variable star. Artists impression. Credit: NASA

However, it turns out Cepheids are not exactly easy to study. For one thing, it’s tough to measure their pulsations and radial velocities accurately. In addition, some have companion stars and the presence of a nearby star complicates any measurements. For another thing, different instruments and measuring methods give slightly different results, which doesn’t help astronomers understand those stars any better.

Precision Measurements of Cepheid Variables

Measuring the intricacies of Cepheid pulsations requires spectroscopic techniques that can measure light from stars and break it down into its component wavelengths. That reveals a lot of data about a star, including its chemical makeup, temperature, and motions in space.

Calibrated Period-luminosity Relationship for Cepheid variables. Courtesy Spitzer Space Telescope/IPAC.

A worldwide consortium of astronomers led by Richard I. Anderson at Switzerland’s École Polytechnique Fédérale de Lausanne (EPFL) is measuring specific properties of classical and other Cepheids using two high-resolution spectrographs. One is called HERMES on La Palma in the northern hemisphere and the other is CORALIE in Chile. They both detected tiny shifts in the light of target Cepheids. Those shifts gave valuable information about the motions of the stars.

“Tracing Cepheid pulsations with high-definition velocimetry gives us insights into the structure of these stars and how they evolve,” he said. “In particular, measurements of the speed at which the stars expand and contract along the line of sight—so-called radial velocities—provide a crucial counterpart to precise brightness measurements from space. However, there has been an urgent need for high-quality radial velocities because they are expensive to collect and because few instruments are capable of collecting them.”

VELOCE is on the Job

The team’s measurement project is called the VELOCE Project—short for VELOcities of CEpheids. It’s 12-year-long collaboration among astronomers and astrophysicists. Anderson began the VELOCE project during his Ph.D work at the University of Geneva, continued it as a postdoc in the US and Germany, and has now completed it at EPFL.

According to Ph.D student Giordano Viviani, the data from the project are already enabling new discoveries about Cepheids. “The wonderful precision and long-term stability of the measurements have enabled interesting new insights into how Cepheids pulsate,” Viviani said. “The pulsations lead to changes in the line-of-sight velocity of up to 70 km/s, or about 250,000 km/h. We have measured these variations with a typical precision of 130 km/h (37 m/s), and in some cases as good as 7 km/h (2 m/s), which is roughly the speed of a fast walking human.”

Uncovering New Details about these Pulsating Stars

The VELOCE project’s precision measurements also revealed some strange facts about these stars. For example, there’s an interesting phenomenon called the Hertzsprung Progression. It describes double-peaked bumps in a Cepheid’s pulsations. Astronomers aren’t quite sure yet why these bumps occur. But, they could give some insight into the structure of Cepheid variables, particularly the so-called “classical” ones.

Other Cepheids show very complex variability, and changes in their radial velocities are not always consistent with predicted periods, according to postdoctoral researcher Henryka Netzel. “This suggests that there are more intricate processes occurring within these stars, such as interactions between different layers of the star, or additional (non-radial) pulsation signals that may present an opportunity to determine the structure of Cepheid stars by asteroseismology,” Netzel said.

As part of their study, the team also measured 77 Cepheids that are part of binary systems. One in three Cepheids “lives” in a binary system, and often those unseen companions are detectable by velocity measurements. Characterizing the different “flavors” of Cepheids and the intricacies of their pulsations has larger implications than determining their radial velocities and bumps in their periods, according to Anderson. “Understanding the nature and physics of Cepheids is important because they tell us about how stars evolve in general, and because we rely on them for determining distances and the expansion rate of the Universe,” Anderson said, noting that VELOCE is also providing a valuable “cross-check” with Gaia measurements. It’s on track to conduct a large-scale survey of Cepheid radial velocity measurements.

Cross-checking with Gaia

Additionally, VELOCE provides the best available cross-checks for similar, but less precise, measurements from the ESA mission Gaia. That spacecraft is on track to conduct the largest survey of Cepheid radial velocity measurements. Data from that mission provides a growing three-dimensional map of millions of stars in the Milky Way and beyond. It not only charts their positions but also their motions (including radial velocity), as well as temperatures and compositions. Combined with high-precision data from VELOCE about Cepheids, astronomers should soon be able to get a handle on stellar and galactic evolutionary history.

For More Information

High-precision Measurements Challenge the Understanding of Cepheids
VELOcities of CEpheids (VELOCE)

The post Cepheid Variables are the Bedrock of the Cosmic Distance Ladder. Astronomers are Trying to Understand them Better appeared first on Universe Today.

To form qubit states in semiconductor materials, it requires tuning for numerous parameters. But as the number of qubits increases, the amount of parameters also increases, thereby complicating this process. Now, researchers have automated this process, overcoming a significant barrier to realizing quantum computers.

To form qubit states in semiconductor materials, it requires tuning for numerous parameters. But as the number of qubits increases, the amount of parameters also increases, thereby complicating this process. Now, researchers have automated this process, overcoming a significant barrier to realizing quantum computers.

A research team has developed an optimal artificial intelligence model to predict the yield strength of various metals, effectively addressing traditional cost and time limitations.

Universe Today has had some incredible discussions with a wide array of scientists regarding impact craters, planetary surfaces, exoplanets, astrobiology, solar physics, comets, planetary atmospheres, planetary geophysics, cosmochemistry, meteorites, radio astronomy, extremophiles, organic chemistry, black holes, cryovolcanism, and planetary protection, and how these intriguing fields contribute to our understanding regarding our place in the cosmos.

Here, Universe Today discusses the mysterious field of dark matter with Dr. Shawn Westerdale, who is an assistant professor in the Department of Physics & Astronomy and head of the Dark Matter and Neutrino Lab at the University of California, Riverside, regarding the importance of studying dark matter, the benefits and challenges, how dark matter can teach us about finding life beyond Earth, the most exciting aspects about dark matter he’s studied throughout his career, and advice for upcoming students who wish to pursue studying dark matter. So, what is the importance of studying dark matter?

“About 80% of the mass of all matter in the universe is dark matter, despite the fact that our (otherwise extremely successful) model of fundamental particle physics cannot explain what it is,” Dr. Westerdale tells Universe Today. “We can see the gravitational influence of dark matter in our own galaxy and throughout the entire structure of the observable universe. It leaves a clear imprint on all of our cosmological and astrophysical observations through these gravitational interactions, so we know it is there and it does a remarkable job of explaining what we see. But we have no idea what it actually is made of, and this is an essential part of understanding nature.”

The term “dark matter” was first coined in 1906 by French mathematician and theoretical physicist, Dr. Henri Poincaré, to describe work from 1884 by the British mathematical physicist, Dr. William Thomson (Lord Kelvin), regarding velocities of stars and some potentially being dark bodies. Throughout the rest of the 20th century, dark matter became a focal point in hypothesizing the behavior of galaxies and galaxy clusters with countless studies being published from academia, including the California Institute of Technology, along with research organizations like the SETI Institute. Despite decades of research, including the hypothesis of “cold”, “warm”, and “hot” dark matter, this mysterious substance has yet to be observed. Therefore, what are some of the benefits and challenges of studying dark matter?

Dr. Westerdale tells Universe Today, “We haven’t found it yet, but we have ruled out many models, and in doing so we have helped refine our understanding of nature by ruling out possible modifications to the Standard Model of particle physics. On a sociological level, the study of dark matter has led to many new technologies for detecting radiation. Some of these may lead to new quantum technologies, and others are being developed into new medical imaging devices, just to name a few examples.”

The three methods for attempting to observe dark matter include direct detection, indirect detection, and laboratory experiments using a myriad of laboratories from several countries around the world, including the Large Hadron Collider, which is the world’s largest particle collider. Additionally, several ground- and space-based telescopes have conducted surveys to try and create dark matter maps, including NASA’s Hubble Space Telescope, the Canada-France-Hawaii Telescope, the VLT Survey Telescope, and the Subaru Telescope. But what are the most exciting aspects about dark matter that Dr. Westerdale has studied during his career?

Dr. Westerdale tells Universe Today, “To me the most exciting aspect of dark matter research has been the magnitude of the question. We have such successful models of cosmology and particle physics, and yet for all the success of these models, we still don’t know what most of the universe is even made of or how it got here!”

The study of dark matter comprises some of the most fundamental questions pertaining to cosmology, the nature of the universe, and our place in it. What is the universe made of? How did it form? How did galaxies form? How do galaxies behave the way they do? How has all of this led to us being here and writing articles about dark matter like this one? The answers to these questions continue to elude astrophysicists, cosmologists, and countless other scientists despite decades of research, experiments, models, and hypotheses.

Dr. Westerdale tells Universe Today, “One of the fun challenges of dark matter detection is that we are looking for extremely rare interactions and so we have to go to extraordinary lengths to make our experiments as quiet as possible. We put our detectors in deep underground labs, up to a mile underground, to avoid noise from cosmic rays, and levels of radioactivity that are normally so low they cannot be measured can swamp the signals we’re looking for. It is an exciting challenge to confront these things in our research and figure out how to design detectors that can meet all of our goals.”

Despite the lack of observing dark matter and confirming its existence, this nonetheless signals that the next generation of dark matter enthusiasts, whether they become astrophysicists, cosmologists, or come from other scientific backgrounds, will have their work cut out for them, with some possibly being the ones to confirm dark matter’s existence. Like nearly all scientific research trajectories, the study of dark matter involves constant collaboration between scientists from a myriad of backgrounds and expertise’s. Therefore, what advice can Dr. Westerdale offer to upcoming students who wish to pursue studying dark matter?

Dr. Westerdale tells Universe Today, “Experimental dark matter physics requires a very large breadth of knowledge, and so don’t silo your studies — any physics, math, and engineering skills you learn will at some point be useful. Programming skills are especially important, as are learning statistics, chemistry, and other engineering skills. And when you encounter something new, take the time to learn how it works on a fundamental level — it will be worth it later on once you can see how it fits into the big picture.”

Will we ever observe dark matter and how will it help us better understand our place in the universe in the coming years and decades? Only time will tell, and this is why we science!

As always, keep doing science & keep looking up!

The post Dark Matter: Why study it? What makes it so fascinating? appeared first on Universe Today.

One of the easiest ways to find exoplanets is using the transit method. It relies upon monitoring the brightness of a star which will then dim as a planet passes in front of it. It is of course possible that other objects could pass between us and a star; perhaps binary planets, tidally distorted planets, exocomets and, ready for it…. alien megastructures! A transit simulator has been created by a team of researchers and it can predict the brightness change from different transiting objects, even Dyson Swarms in construction. 

51 Pegasi-b was the first exoplanet discovered in 1995 and it sparked the development of numerous ground-based and space-based instruments. The launch of the Kepler Space Telescope and the Transiting Exoplanet Survey Satellite (TESS) in 2018 popularised the transit method, leading to the discovery of over 4,000 exoplanets. As instruments have become increasingly sensitive and precise, research has progressed from simply detecting exoplanets to studying their detailed characteristics.

Illustration of NASA’s Transiting Exoplanet Survey Satellite. Credit: NASA’s Goddard Space Flight Center

Transit photometry has uncovered signatures of many interesting phenomena beyond the detection of exoplanets and eclipsing binaries. This technique has been instrumental in identifying features such as star-spots, and signatures of tidal interactions between host stars and exoplanets leading to significant growth in the sub-field of Asteroseismology

The study of transiting exoplanets and their timing variations has led to many discoveries. Non-transiting planets in distant solar systems have been found, orbital decay, disintegrating planets, exocomets and exomoon candidates has all been identified. Additionally, and perhaps of particular interest is that transit photometry has detected signals that have sparked interest in the search for technosignatures for the evidence of advanced civilizations.

It is important to note that no technosignatures have been confirmed yet but such signatures would not arise form natural processes and would demonstrate the presence of intelligent life. The signatures would come from a wide range of astroengineering projects like Dyson Spheres (a theoretical shell surrounding a star to capture its energy output) or the newly conceptualised Dyson Swarms (habitable satellites and energy collectors that orbit the star in formation. 

The research team led by Ushasi Bhowmick from the Indian based Space Application Centre has reported that they have developed a transit simulator that can not only generate light curves for exoplanets but also for any object of any size or shape! The simulation uses the Monte-Carlo technique that predicts all possible outcomes of an uncertain event. In this instance it can predict the light curve when an object of any shape or size transits across the disk of star. 

Artist’s impressions of two exoplanets in the TRAPPIST-1 system (TRAPPIST-1d and TRAPPIST-1f). Credit: NASA/JPL-Caltech

When the simulation was tested against actual exoplanet systems such as Trappist-1 it nicely predicted the light curve. It can also be used to model tidal distortions in binary star systems and even predict the light curve of non-natural objects such as the alien megastructures. The simulator has shown itself to be an invaluable method for understanding a wide range of transit phenomena. 

Source : A General-Purpose Transit Simulator for Arbitrary Shaped Objects Orbiting Stars

The post That’s No Planet. Detecting Transiting Megastructures appeared first on Universe Today.

Scientists develop the next generation of highly efficient memory materials with atom-level control.

Why do just one experiment at a time when you can do ten? Researchers have developed an automated system, which allows them to research catalysts, electrodes, and reaction conditions for CO2 electrolysis up to ten times faster. The system is complemented by an open-source software for data analysis.

Why do just one experiment at a time when you can do ten? Researchers have developed an automated system, which allows them to research catalysts, electrodes, and reaction conditions for CO2 electrolysis up to ten times faster. The system is complemented by an open-source software for data analysis.

Researchers have developed a tiny robot replicating the aerial dance of falling maple seeds. In the future, this robot could be used for real-time environmental monitoring or delivery of small samples even in inaccessible terrain such as deserts, mountains or cliffs, or the open sea. This technology could be a game changer for fields such as search-and-rescue, endangered species studies, or infrastructure monitoring.

Researchers have developed a tiny robot replicating the aerial dance of falling maple seeds. In the future, this robot could be used for real-time environmental monitoring or delivery of small samples even in inaccessible terrain such as deserts, mountains or cliffs, or the open sea. This technology could be a game changer for fields such as search-and-rescue, endangered species studies, or infrastructure monitoring.

The majority of stars in our galaxy are home to planets. The most abundant are the sub-Neptunes, planets between the size of Earth and Neptune. Calculating their density poses a problem for scientists: depending on the method used to measure their mass, two populations are highlighted, the dense and the less dense. Is this due to an observational bias or the physical existence of two distinct populations of sub-Neptunes? Recent work argues for the latter.

Structural formulas are a source of dread for many students, but they're an essential tool in biology lessons. A study has now shown that the stress levels of students working with chemical formulas are significantly reduced if they are given simple tips on how to deal with these formulas.

Chemists have successfully synthesized Ruddlesden-Popper nitrides for the first time, opening the door to new materials with unique properties.

A more accurate way to scan for tuberculosis (TB) has been developed, using positron emission tomography (PET). The team has developed a new radiotracer, which is taken up by live TB bacteria in the body. Radiotracers are radioactive compounds which give off radiation that can be detected by scanners and turned into a 3D image. The new radiotracer, called FDT, enables PET scans to be used for the first time to accurately pinpoint when and where the disease is still active in a patient's lungs.

Just four per cent of talented teen academy prospects make it to the top tier of professional football, a new study has shown. A sample of nearly 200 players, aged between 13-18, also revealed only six per cent of the budding ballers even go on to play in lower leagues.