Deep Follow-up of GW151226 — an ordinary binary or a low-mass ratio merger?
Now that we’ve been detecting gravitational waves.
Continue reading “Gravitational Wave Events With Split Personalities” »
The violent death throes of a nearby star so thoroughly disrupted its planetary system that the dead star left behind—known as a white dwarf—is sucking in debris from both the system’s inner and outer reaches, UCLA astronomers and colleagues report today.
This is the first case of cosmic cannibalism in which astronomers have observed a white dwarf consuming both rocky-metallic material, likely from a nearby asteroid, and icy material, presumed to be from a body similar to those found in the Kuiper belt at the fringe of our own solar system.
After some serious number crunching, a UBC researcher has come up with a mathematical model for a viable time machine.
Ben Tippett, a mathematics and physics instructor at UBC’s Okanagan campus, recently published a study about the feasibility of time travel. Tippett, whose field of expertise is Einstein’s theory of general relativity, studies black holes and science fiction when he’s not teaching. Using math and physics, he has created a formula that describes a method for time travel.
“People think of time travel as something as fiction,” says Tippett. “And we tend to think it’s not possible because we don’t actually do it. But, mathematically, it is possible.”
https://youtube.com/watch?v=V9Id-Ayy12g
Time travel into the past is a tricky thing. We know of no single law of physics that absolutely forbids it, and yet we can’t find a way to do it, and if we could do it, the possibility opens up all sorts of uncomfortable paradoxes (like what would happen if you killed your own grandfather).
But there could be a way to do it. We just need to find a wormhole first.
For years, physicists have been making major advances and breakthroughs in the field using their minds as their primary tools. But what if artificial intelligence could help with these discoveries?
Last month, researchers at Duke University demonstrated that incorporating known physics into machine learning algorithms could result in new levels of discoveries into material properties, according to a press release by the institution. They undertook a first-of-its-kind project where they constructed a machine-learning algorithm to deduce the properties of a class of engineered materials known as metamaterials and to determine how they interact with electromagnetic fields.
This sci-fi megastructure has captivated big thinkers for decades. A leading expert in astrobiology tells us how to construct one.
The paper focused more on theory than engineering, and Dyson provided scant details on what such a megastructure might look like or how we might build one. He described his sphere only as a “habitable shell” encircling a star. But that was enough to captivate and inspire astrophysicists, scientists, and sci-fi writers. In some depictions, the Dyson Sphere, as it became known, appears as a massive ring encircling a star and reaching nearly to Earth. In others, the Sphere completely encases the sun, a hulking megastructure capturing every bit of that star’s energy. In addition to scientific works, Dyson Spheres have appeared in novels, movies, and TV shows—including Star Trek —as a home for advanced civilizations.
Dyson himself understood the challenges of constructing such a massive structure, and he was skeptical that it might ever happen. Nonetheless, his Sphere has stirred ambitious ideas about the future of our civilization, and it continues to be offered as a solution to some of humanity’s most dire dilemmas. Harnessing the total energy of our sun—or any star—would solve our immediate and long-term energy crisis, but when civilization gains access to the complete energy output of a star, meeting our terrestrial energy needs is just the beginning.
Continue reading “Swarms of Satellites Around the Sun Could Supply Us With Unlimited Power” »
Incorporating established physics into neural network algorithms helps them to uncover new insights into material properties
According to researchers at Duke University, incorporating known physics into machine learning algorithms can help the enigmatic black boxes attain new levels of transparency and insight into the characteristics of materials.
Researchers used a sophisticated machine learning algorithm in one of the first efforts of its type to identify the characteristics of a class of engineered materials known as metamaterials and to predict how they interact with electromagnetic fields.
Time travel makes regular appearances in popular culture, with innumerable time travel storylines in movies, television and literature. But it is a surprisingly old idea: one can argue that the Greek tragedy Oedipus Rex, written by Sophocles over 2,500 years ago, is the first time travel story.
But is time travel in fact possible? Given the popularity of the concept, this is a legitimate question. As a theoretical physicist, I find that there are several possible answers to this question, not all of which are contradictory.
The simplest answer is that time travel cannot be possible because if it was, we would already be doing it. One can argue that it is forbidden by the laws of physics, like the second law of thermodynamics or relativity. There are also technical challenges: it might be possible but would involve vast amounts of energy.
Lemoine, an engineer for Google’s responsible AI organization, described the system he has been working on since last fall as sentient, with a perception of, and ability to express thoughts and feelings that was equivalent to a human child.
“If I didn’t know exactly what it was, which is this computer program we built recently, I’d think it was a seven-year-old, eight-year-old kid that happens to know physics,” Lemoine, 41, told the Washington Post.
Continue reading “Google engineer put on leave after saying AI chatbot has become sentient” »
