Using natural quantum interactions allows faster, more robust computation for Grover’s algorithm and many others.
Los Alamos National Laboratory scientists have developed a groundbreaking quantum computing.
Performing computation using quantum-mechanical phenomena such as superposition and entanglement.
By Charlie Wood
Quantum computing is still really, really hard. But the rise of a powerful class of error-correcting codes suggests that the task might be slightly more feasible than many feared.
How looks life with na implant in brain.
Brain-computer interface technology is a fast-growing field but how does it feel to live with an implant inside of you?
In 2014, Ian Burkhart looked down at his hand and imagined closing it. To his astonishment, his hand did just that.
This was the first time a paraplegic person had regained the ability to move his arm by the sheer force of his thought, assisted by an implant in his brain.
In their 1982 paper, Fredkin and Toffoli had begun developing their work on reversible computation in a rather different direction. It started with a seemingly frivolous analogy: a billiard table. They showed how mathematical computations could be represented by fully reversible billiard-ball interactions, assuming a frictionless table and balls interacting without friction.
This physical manifestation of the reversible concept grew from Toffoli’s idea that computational concepts could be a better way to encapsulate physics than the differential equations conventionally used to describe motion and change. Fredkin took things even further, concluding that the whole Universe could actually be seen as a kind of computer. In his view, it was a ‘cellular automaton’: a collection of computational bits, or cells, that can flip states according to a defined set of rules determined by the states of the cells around them. Over time, these simple rules can give rise to all the complexities of the cosmos — even life.
He wasn’t the first to play with such ideas. Konrad Zuse — a German civil engineer who, before the Second World War, had developed one of the first programmable computers — suggested in his 1969 book Calculating Space that the Universe could be viewed as a classical digital cellular automaton. Fredkin and his associates developed the concept with intense focus, spending years searching for examples of how simple computational rules could generate all the phenomena associated with subatomic particles and forces3.
That early experience drove his professional interest in helping people communicate.
Now, Henderson’s an author on one of two papers published Wednesday showing substantial advances toward enabling speech in people injured by stroke, accident or disease.
Although still very early in development, these so-called brain-computer interfaces are five times better than previous generations of the technology at “reading” brainwaves and translating them into synthesized speech. The successes suggest it will someday be possible to restore nearly normal communication ability to people like Henderson’s late father.
Tech executives, researchers and government officials are gathering in Seattle this week to figure out ways to add a new dimension to America’s chip industry — figuratively and literally.
“We’re going to talk about a once-in-a-lifetime opportunity to reinvent domestic microelectronics manufacturing,” Mark Rosker, director of the Defense Advanced Research Projects Agency’s Microsystems Technology Office, said today at the opening session of the ERI 2.0 Summit at the Hyatt Regency Seattle.
More than 1,300 attendees signed up for the DARPA event, which follows up on a series of Electronics Resurgence Initiative Summits that were conducted before the COVID-19 pandemic.
Fermionic atoms adhere to the Pauli exclusion principle, preventing more than one from simultaneously being in the same quantum state. As a result, they are perfect for modeling systems like molecules, superconductors, and quark-gluon plasmas where fermionic statistics are critical.
Using fermionic atoms, scientists from Austria and the USA have designed a new quantum computer to simulate complex physical systems. The processor uses programmable neutral atom arrays and has hardware-efficient fermionic gates for modeling fermionic models.
The group, under the direction of Peter Zoller, showed how the new quantum processor can simulate fermionic models from quantum chemistry and particle physics with great accuracy.
Researchers from the University of Cambridge have unveiled a surprising discovery that holds the potential to reshape the landscape of electrochemical devices. This new insight opens the door for the creation of cutting-edge materials and paves the way for enhancements in sectors like energy storage, neuromorphic computing, and bioelectronics.
Electrochemical devices rely on the movement of charged particles, both ions, and electrons, to function properly. However, understanding how these charged particles move together has presented a significant challenge, hindering progress in creating new materials for these devices.
In the rapidly evolving field of bioelectronics, soft conductive materials known as conjugated polymers are used for developing medical devices that can be used outside of traditional clinical settings. For example, this type of material can be used to make wearable sensors that monitor patients’ health remotely or implantable devices that actively treat disease.