View insights.
Not only do quantum computers have the edge over classical computers on some tasks, but they are also exponentially faster, according to a new mathematical proof.
Machine learning can get a boost from quantum physics.
On certain types of machine learning tasks, quantum computers have an exponential advantage over standard computation, scientists report in the June 10 Science. The researchers proved that, according to quantum math, the advantage applies when using machine learning to understand quantum systems. And the team showed that the advantage holds up in real-world tests.
“People are very excited about the potential of using quantum technology to improve our learning ability,” says theoretical physicist and computer scientist Hsin-Yuan Huang of Caltech. But it wasn’t entirely clear if machine learning could benefit from quantum physics in practice.
A team of researchers from the University of Shanghai for Science and Technology and the University of Dayton has developed a way to bend light into a vortex ring using mirrors, lasers and lenses. In their study, published in the journal Nature Photonics, the group built on work done by other teams in which vortex rings were observed incidentally, and then mathematically designed a system that could generate them on demand.
In 2016, another team of researchers discovered that under the right circumstances, strong pulses of light swirling around a central pipe-shaped pulse, could sometimes form into a donut-shaped vortex. Intrigued by the finding, the researchers with this new effort began to wonder if it might be possible to create such vortex rings on demand.
They started by studying the properties and conditions that had led to the formations observed by the team in 2016 and applied mathematics to the problem. They found solutions that appeared to show how such rings could be made—solutions to Maxwell’s equations, in particular, they found, could be used to generate the kind of conformal mapping required.
AI For Defense Nuclear Nonproliferation — Angela Sheffield, Senior Program Manager, National Nuclear Security Administration, U.S. Department of Energy.
Angela Sheffield is a graduate student and Space Industry fellow at the National Defense University’s Eisenhower School. She is on detail from the National Nuclear Security Administration (NNSA), where she serves as the Senior Program Manager for AI for Defense Nuclear Nonproliferation Research and Development.
As physicists delve deeper into the quantum realm, they are discovering an infinitesimally small world composed of a strange and surprising array of links, knots and winding. Some quantum materials exhibit magnetic whirls called skyrmions—unique configurations described as “subatomic hurricanes.” Others host a form of superconductivity that twists into vortices.
Now, in an article published in Nature a Princeton-led team of physicists has discovered that electrons in quantum matter can link to one another in strange new ways. The work brings together ideas in three areas of science—condensed matter physics, topology, and knot theory —in a new way, raising unexpected questions about the quantum properties of electronic systems.
Topology is the branch of theoretical mathematics that studies geometric properties that can be deformed but not intrinsically changed. Topological quantum states first came to the public’s attention in 2016 when three scientists, including Duncan Haldane, who is Princeton’s Thomas D. Jones Professor of Mathematical Physics and Sherman Fairchild University Professor of Physics, were awarded the Nobel Prize for their theoretical prediction of topology in electronic materials.
Andrew Lincoln, your boss?
Vanessa YelenaYour boss is deathist cringe. Let’s see if it stays that way when he’s getting old…
Continue reading “How I make beautiful GRAPHS and PLOTS using LaTeX” »
As physicists dig deeper into the quantum realm, they are discovering an infinitesimally small world composed of a strange and surprising array of links, knots, and winding. Some quantum materials exhibit magnetic whirls called skyrmions — unique configurations sometimes described as “subatomic hurricanes.” Others host a form of superconductivity that twists into vortices.
Now, in an article published in the journal Nature, a Princeton-led team of scientists has discovered that electrons in quantum matter can link one another in strange new ways. The work brings together ideas in three areas of science – condensed matter physics, topology, and knot theory – in a new way, raising unexpected questions about the quantum properties of electronic systems.
Topology is the branch of theoretical mathematics that studies geometric properties that can be deformed but not intrinsically changed. Topological quantum states first came to the public’s attention in 2016 when three scientists, including Duncan Haldane, who is Princeton’s Thomas D. Jones Professor of Mathematical Physics and Sherman Fairchild University Professor of Physics, were awarded the Nobel Prize for their theoretical prediction of topology in electronic materials.
This March, we, a group of educators, scientists, and psychologists started an educational non-profit (501 c3) Earthlings Hub, helping kids in refugee camps and evacuated orphanages. We are getting lots of requests for help, and are in urgent need to raise funds. If you happen to have any connections to educational and humanitarian charities, or if your universities or companies may be interested in providing some financial support to our program, we would really appreciate that! Please share with everyone who might be able to offer help or advice.
Our advisory board includes NASA astronaut Greg Chamitoff, Professor Uri Wilensky, early math educator Maria Droujkova, AI visionary Joscha Bach, and others.
Support Us The Earthlings Hub works with a fiscal sponsor Blue Marble Space. CREDIT CARD & PAYPAL Please contact us if you would like to via other means, such as checks, stocks, cryptocurrency, or using your Donor Advised Fund: [email protected]
If you are interested in artificial general intelligence (AGI), then I have a panel discussion to recommend. My friend, David Wood, has done a masterful job of selecting three panelists with deep insight into possible regulation of AGI. One of the panelists was my friend, Dan Faggella, who was eloquent and informative as usual. For this session of the London Futurists, David Wood selected two other panelists with significantly different opinions on how to properly restrain AGI.
An artificial general intelligence (AGI), by one definition, is an agent that requires less information than any other to make an accurate prediction. It is arguable that the general reinforcement learning agent AIXI not only met this definition, but was the only mathematical formalism to do so. Though a significant result, AIXI was incomputable and its performance subjective. This paper proposes an alternative formalism of AGI which overcomes both problems. Formal proof of its performance is given, along with a simple implementation and experimental results that support these claims.
