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Quantum circuits still can’t outperform classical ones when simulating molecules.

Quantum computers promise to directly simulate systems governed by quantum principles, such as molecules or materials, since the quantum bits themselves are quantum objects. Recent experiments have demonstrated the power of these devices when performing carefully chosen tasks. But a new study shows that for problems of real-world interest, such as calculating the energy states of a cluster of atoms, quantum simulations are no more accurate than those of classical computers [1]. The results offer a benchmark for judging how close quantum computers are to becoming useful tools for chemists and materials scientists.

Richard Feynman proposed the idea of quantum computers in 1982, suggesting they might be used to calculate the properties of quantum matter. Today, quantum processors are available with several hundred quantum bits (qubits), and some can, in principle, represent quantum states that are impossible to encode in any classical device. The 53-qubit Sycamore processor developed by Google has demonstrated the potential to perform calculations in a few days that would take many millennia on current classical computers [2]. But this “quantum advantage” is achieved only for selected computational tasks that play to these devices’ strengths. How well do such quantum computers fare for the sorts of everyday challenges that researchers studying molecules and materials actually wish to solve?

Researchers at Purdue University have discovered new waves with picometer-scale spatial variations of electromagnetic fields that can propagate in semiconductors like silicon. The research team, led by Dr. Zubin Jacob, Elmore Associate Professor of Electrical and Computer Engineering and Department of Physics and Astronomy, published their findings in Physical Review Applied in a paper titled “Picophotonics: Anomalous Atomistic Waves in Silicon.”

“The word microscopic has its origins in the length scale of a micron, which is a million times smaller than a meter. Our work is for matter interaction within the picoscopic regime which is far smaller, where the discrete arrangement of atomic lattices changes light’s properties in surprising ways,” says Jacob.

These intriguing findings demonstrate that natural media host a variety of rich light-matter interaction phenomena at the atomistic level. The use of picophotonic waves in semiconducting materials may lead researchers to design new, functional optical devices, allowing for applications in .

Femtosecond pulsed lasers—which emit light in ultrafast bursts lasting a millionth of a billionth of a second—are powerful tools used in a range of applications from medicine and manufacturing, to sensing and precision measurements of space and time. Today, these lasers are typically expensive table-top systems, which limits their use in applications that have size and power consumption restrictions.

An on-chip femtosecond pulse source would unlock new applications in quantum and optical computing, astronomy, optical communications and beyond. However, it’s been a challenge to integrate tunable and highly efficient pulsed lasers onto chips.

Now, researchers from the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have developed a high-performance, on-chip femtosecond pulse source using a tool that seems straight out of science fiction: a time lens.

It’s diversifying from its initial reliance on Taiwan-made chips.

Apple is diversifying its supply chain away from Taiwan as it has plans to buy some of its chips from a factory in Arizona, company CEO Tim Cook said last month at an internal meeting in Germany, according to a report by Bloomberg News.


Manufacturing A-series and M-series processors

All of the firm’s current processors are sourced from factories in Taiwan. Although Apple currently designs its own chips, the Taiwan Semiconductor Manufacturing Company (TSMC) is responsible for manufacturing the A-series and M-series processors that power the ever popular iPhones and Mac computers.

Researchers solved a differential equation behind the interaction of two neurons through synapses, creating a faster AI algorithm.

Artificial intelligence uses a technique called artificial neural networks (ANN) to mimic the way a human brain works. A neural network uses input from datasets to “learn” and output its prediction based on the given information.

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Commercial deployment could be achieved as early as 2024.

Energy Dome, the Italian company that uses carbon dioxide for long-duration energy storage, has now entered the U.S. energy market, Electrek.

Countries around the world are looking to switch to sources of renewable energy in a bid to reduce their carbon emissions. Recently, the world’s largest floating offshore wind farm went online in Norway and will use the harnessed energy to reduce emissions from its oil and gas production facilities.

As far as we know, our home planet is the only one that harbors life. But, as many scientists believe, there are likely countless other planets out there with conditions “just right” to allow life to develop and thrive.

If this is true, these planets could, conceivably, provide additional potential homes ripe for colonization by our species. Of course, we’d need to develop long-range spaceships to get there — and make sure they were not already inhabited.

Their experiment could help to create a unified theory of quantum gravity.

A team of physicists from the University of Amsterdam in the Netherlands simulated the event horizon of a black hole in a lab and observed the equivalent of an elusive form of radiation first theorized by Stephen Hawking, a report from Science Alert.

The new discovery could help the scientific community develop a whole new theory that marries the general theory of relativity with the principles of quantum mechanics. John/iStock.

Are we soon going to be traveling enormous distances via wormholes?

A team of scientists from the University of Sofia in Bulgaria believes they have discovered a new method for detecting wormholes — though they still only exist in theory.

Wormholes are theorized shortcuts through space and time. Sci-fi depictions traditionally show a spacecraft traveling through a wormhole, or creating one, to traverse immense distances to far-off regions of the universe in a short amount of time.

The issue is that black holes and wormholes look very similar, and we have barely developed the technology required to directly observe the former. Now, a team of scientists believes its mathematical model can help to tell the two apart, a report from New Scientist reveals.

“Everyone at school thinks I am very smart.”

Yusuf Shah, a Year 6 student at Wigton Moor Primary School, took the Mensa IQ test as he wanted to know if he figured in the top two percent of the people who take the test.


Bruno Vincent/Getty Images.

You know, just casually.