Fast radio bursts (FRBs) are millisecond-long cosmic explosions that each produce the energy equivalent to the sun’s annual output. More than 15 years after the deep-space pulses of electromagnetic radio waves were first discovered, their perplexing nature continues to surprise scientists – and newly published research only deepens the mystery surrounding them.
Harvard Medical School scientists and colleagues at Stanford University have developed an artificial intelligence diagnostic tool that can detect diseases on chest X-rays directly from natural-language descriptions contained in accompanying clinical reports.
The step is deemed a major advance in clinical AI design because most current AI models require laborious human annotation of vast reams of data before the labeled data are fed into the model to train it.
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China Launches World’s Fastest Quantum Computers | China’s Advancement In Quantum Computers #technology.
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Nine Inch Nails “Me I’m Not” remixed with US military, math, science, and computer footage from the Prelinger Archives.
Companies and research labs across the globe are working towards getting their nascent quantum technologies out of the lab and into the real world, with the US technology giant IBM being a key player. In May this year, IBM Quantum unveiled its latest roadmap for the future of quantum computing in the coming decade, and the firm has set some ambitious targets. Having announced its Eagle processor with 127 quantum bits (qubits) last year, the company is now developing the 433-qubit Osprey processor for a debut later this year, to be followed in 2023 by the 1121-qubit Condor.
But beyond that, the company says, the game will switch to assembling such processors into modular circuits, in which the chips are wired together via sparser quantum or classical interconnections. That effort will culminate in what they refer to as their 4158-qubit Kookaburra device in 2025. Beyond then, IBM forecasts modular processors with 100,000 or more qubits, capable of computing without the errors that currently make quantum computing a matter of finding workarounds for the noisiness of the qubits. With this approach, the company’s quantum computing team is confident that it can achieve a general “quantum advantage”, where quantum computers will consistently outperform classical computers and conduct complex computations beyond the means of classical devices.
While he was in London on his way to the 28 th Solvay conference in Brussels, which tackled quantum information, Physics World caught up with physicist Jay Gambetta, vice-president of IBM Quantum. Having spearheaded much of the company’s advances over the past two decades, Gambetta explained how these goals might be reached and what they will entail for the future of quantum computing.
A new photodetector design borrows its light-gathering architecture from plants, offering a potential path to more efficient solar cells.
An information engine uses information to convert heat into useful energy. Such an engine can be made, for example, from a heavy bead in an optical trap. A bead engine operates using thermal noise. When noise fluctuations raise the bead vertically, the trap is also lifted. This change increases the average height of the bead, and the engine produces energy. No work is done to cause this change; rather, the potential energy is extracted from information. However, measurement noise—whose origin is intrinsic to the system probing the bead’s position—can degrade the engine’s efficiency, as it can add uncertainty to the measurement, which can lead to incorrect feedback decisions by the algorithm that operates the engine. Now Tushar Saha and colleagues at Simon Fraser University in Canada have developed an algorithm that doesn’t suffer from these errors, allowing for efficient operation of an information engine even when there is high measurement noise [1].
To date, most information engines have operated using feedback algorithms that consider only the most recent bead-position observation. In such a system, when the engine’s signal-to-noise ratio falls below a certain value, the engine stops working.
To overcome this problem, Saha and colleagues instead use a “filtering” algorithm that replaces the most recent bead measurement with a so-called Bayesian estimate. This estimate accounts for both measurement noise and delay in the device’s feedback.
In a first-of-its-kind test for planetary defense, NASA’s DART spacecraft is scheduled next week to crash into an asteroid and alter the celestial body’s course.
If all goes according to plan, on September 26th at 7:14 pm Eastern Daylight Time, NASA’s DART spacecraft will meet a fiery end. DART, whose name stands for Double Asteroid Redirection Test, is poised to intentionally crash into an asteroid that, at the time of impact, will be 11 million km from Earth. The goal of the mission is to alter the speed and trajectory of the impacted space boulder. The technology developed for the mission could one day aid in shifting the orbit of an asteroid that—unlike this one—is on a collision course with Earth.
“Our DART spacecraft is going to impact an asteroid in humanity’s first attempt to change the motion of a natural celestial body,” said Tom Statler, a scientist in NASA’s planetary defense team, in a recent press conference about the mission. “It will be a truly historic moment for the entire world.”
