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When you turn on a lamp to brighten a room, you are experiencing light energy transmitted as photons, which are small, discrete quantum packets of energy.

These photons must obey the sometimes strange laws of quantum mechanics, which, for instance, dictate that photons are indivisible, but at the same time, allow a photon to be in two places at once.

Similar to the photons that make up beams of light, indivisible quantum particles called phonons make up a beam of sound. These particles emerge from the collective motion of quadrillions of atoms, much as a “stadium wave” in a sports arena is due to the motion of thousands of individual fans. When you listen to a song, you’re hearing a stream of these very small quantum particles.

Using nanostructured glass, scientists from the University of Southampton’s Optoelectronics Research Centre (ORC) have developed the recording and retrieval processes of five dimensional (5D) digital data by femtosecond laser writing.

The storage allows unprecedented properties including 360 TB/disc data capacity, thermal stability up to 1,000°C and virtually unlimited lifetime at room temperature (13.8 billion years at 190°C) opening a new era of eternal data archiving. [source].

New research by the University of Liverpool could signal a step change in the quest to design the new materials that are needed to meet the challenge of net zero and a sustainable future.

Published in the journal Nature, Liverpool researchers have shown that a mathematical algorithm can guarantee to predict the structure of any material just based on knowledge of the atoms that make it up.

Developed by an interdisciplinary team of researchers from the University of Liverpool’s Departments of Chemistry and Computer Science, the algorithm systematically evaluates entire sets of possible structures at once, rather than considering them one at a time, to accelerate identification of the correct solution.

Camera sensitive enough to spot a single photon finally achieved by researchers in colorado.


A team of researchers from the National Institute of Standards and Technology in Boulder, Colorado, has successfully developed a super-sensitive camera capable of detecting a single photon.

This remarkable achievement opens up new avenues for scientific exploration and holds significant potential for applications in quantum computing, communications, space exploration, and medical research.

Sponges might not look like particularly complex animals, but they’ve had billions of years to evolve their own special systems. And one of those systems might involve sending messages through their body in the form of light.

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The term ‘quantum computer’ gets usually tossed around in the context of hyper-advanced, state-of-the-art computing devices, but much as how a 19th century mechanical computer, a discrete computer created from individual transistors, and a human being are all computers, the important quantifier is how fast and accurate the system is at the task, whether classical or quantum computing. This is demonstrated succinctly by [Davide ‘dakk’ Gessa] with 200 lines of BASIC code on a Commodore 64 (GitHub), implementing a range of quantum gates.

Much like a transistor in classical computing, the qubit forms the core of quantum computing, and we have known for a long time that a qubit can be simulated, even on something as mundane as an 8-bit MPU. Ergo [Davide]’s simulations of various quantum gates on a C64, ranging from Pauli-X, Pauli-Y, Pauli-Z, Hadamard, CNOT and SWAP, all using a two-qubit system running on a system that first saw the light of day in the early 1980s.

Naturally, the practical use of simulating a two-qubit system on a general-purpose MPU running at a blistering ~1 MHz is quite limited, but as a teaching tool it’s incredibly accessible and a fun way to introduce people to the world of quantum computing.

Quantum computing has long been heralded as the next frontier in computing. However, despite their immense potential, quantum computers today still make too many errors to be useful.

While it may become possible to correct these errors in the future, there is still a long way to go to reach fault tolerance. For now, the best strategy is to minimize errors and mitigate their impact on quantum computations by devising methods that can work with the existing quantum hardware.

QEDMA Quantum Computing was founded in 2020 by Asif Sinay, Netanel Lindner, and Dorit Aharonov to develop the quantum operating system of the future. QEDMA’s vision encompasses not only methods to characterize quantum hardware but also robust error mitigation strategies to get optimal results from the current generation of quantum computers.

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Our universe has been developing for about 14 billion years, but human-level intelligence, at least on Earth, has emerged in a remarkably short period of time, measured in tens or hundreds of thousands of years. What then is the future of intelligence? With the exponential growth of computing, will non-biological intelligence dominate?

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Sasselov has been a professor at Harvard since 1998. He arrived to CfA in 1990 as a Harvard-Smithsonian Center post-doctoral fellow. Between 1999 and 2003 he was the Head Tutor of the Astronomy Department.

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Presenting its findings as “Unlocking the future of computing” Microsoft is edging ever closer to photon computing technology with the Analog Iterative Machine (AIM). Right now, the light-based machine is being licensed for use in financial institutions, to help navigate the endlessly complex data flowing through them.

According to the Microsoft Research Blog, “Microsoft researchers have been developing a new kind of analog optical computer that uses photons and electrons to process continuous value data, unlike today’s digital computers that use transistors to crunch through binary data” (via Hardware Info).

The product itself is an interesting one, and seems built to hit a sweet price/performance ratio for anyone that plans on using a discrete GPU solution. Of course, the absence of an integrated GPU does limit the users’ flexibility — I can’t count the number of times I used an integrated GPU to try and pinpoint issues with my systems (and graphics cards). But the fact remains that more consumer choice is best: users can make their own decision on whether that’s worth the extra $10 or not.

Most of this information comes courtesy of Harukaze (via Twitter), as well as a benchmark on PugetBench, where the Ryzen 5 7500F was paired with an X670E motherboard and 32 GB of DDR5-4800 memory.