Archive for the ‘encryption’ category: Page 2

Jan 27, 2024

Nanoscale Power Plants: Turning Heat Into Power With Graphene Ribbons

Posted by in categories: computing, encryption, nanotechnology, quantum physics

Quantum physicist Mickael Perrin uses graphene ribbons to build nanoscale power plants that turn waste heat from electrical equipment into electricity.

When Mickael Perrin started out on his scientific career 12 years ago, he had no way of knowing he was conducting research in an area that would be attracting wide public interest only a few years later: quantum electronics.

Continue reading “Nanoscale Power Plants: Turning Heat Into Power With Graphene Ribbons” »

Jan 27, 2024

Google Bard AI’s addition to Messages could change the way we text forever

Posted by in categories: encryption, mobile phones, robotics/AI

If you use Android, this might come in handy except for the lab of encryption. Hopefully iPhone copies this and it says a standard that’s regulated.

AI could change Google’s Messages app in a big way.

Jan 23, 2024

Performing complex-valued linear transformations using spatially incoherent diffractive optical networks

Posted by in categories: encryption, robotics/AI

The bulk of the computing in state-of-the-art neural networks comprises linear operations, e.g., matrix-vector multiplications and convolutions. Linear operations can also play an important role in cryptography. While dedicated processors such as GPUs and TPUs are available for performing highly parallel linear operations, these devices are power-hungry, and the low bandwidth of electronics still limits their operation speed. Optics is better suited for such operations because of its inherent parallelism and large bandwidth and computation speed.

Built from a set of spatially engineered thin surfaces, diffractive deep (D2NN), also known as diffractive networks, form a recently emerging optical computing architecture capable of performing passively at the speed of light propagation through an ultra-thin volume.

These task-specific all-optical computers are designed digitally through learning of the spatial features of their constituent diffractive surfaces. Following this one-time design process, the optimized surfaces are fabricated and assembled to form the physical hardware of the diffractive optical .

Jan 22, 2024

Mass-Producible Miniature Quantum Memory

Posted by in categories: computing, encryption, mobile phones, quantum physics

PRESS RELEASE — It is hard to imagine our lives without networks such as the internet or mobile phone networks. In the future, similar networks are planned for quantum technologies that will enable the tap-proof transmission of messages using quantum cryptography and make it possible to connect quantum computers to each other.

Like their conventional counterparts, such quantum networks require memory elements in which information can be temporarily stored and routed as needed. A team of researchers at the University of Basel led by Professor Philipp Treutlein has now developed such a memory element, which can be micro-fabricated and is, therefore, suitable for mass production. Their results were recently published in the scientific journal Physical Review Letters.

Jan 21, 2024

Quantum physicist uses graphene ribbons to build nanoscale power plants

Posted by in categories: computing, encryption, nanotechnology, quantum physics

When Mickael Perrin started out on his scientific career 12 years ago, he had no way of knowing he was conducting research in an area that would be attracting wide public interest only a few years later: Quantum electronics. “At the time, physicists were just starting to talk about the potential of quantum technologies and quantum computers,” he recalls.

“Today there are dozens of start-ups in this area, and governments and companies are investing billions in developing the technology further. We are now seeing the first applications in computer science, cryptography, communications and sensors.” Perrin’s research is opening up another field of application: Electricity production using with almost zero energy loss. To achieve this, the 36-year-old scientist combines two usually separate disciplines of physics: thermodynamics and quantum mechanics.

In the past year, the quality of Perrin’s research and its potential for future applications has brought him two awards. He received not only one of the ERC Starting Grants that are so highly sought-after by young researchers, but also an Eccellenza Professorial Fellowship of the Swiss National Science Foundation (SNS)F. He now leads a research group of nine at Empa as well as being an Assistant Professor of Quantum Electronics at ETH Zurich.

Jan 17, 2024

Scientists build mass-producible miniature quantum memory element

Posted by in categories: computing, encryption, mobile phones, quantum physics

Light pulses can be stored and retrieved in the glass cell, which is filled with rubidium atoms and is only a few millimeters in size.

Light particles are particularly suited to transmitting quantum information.

Researchers at the University of Basel have built a quantum memory element based on atoms in a tiny glass cell. In the future, such quantum memories could be mass-produced on a wafer.

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Jan 11, 2024

Quantum Leap: The New Frontier of Polymer Simulations

Posted by in categories: biological, chemistry, computing, encryption, mathematics, quantum physics

A new study shows how quantum computing can be harnessed to discover new properties of polymer systems central to biology and material science.

The advent of quantum computing is opening previously unimaginable perspectives for solving problems deemed beyond the reach of conventional computers, from cryptography and pharmacology to the physical and chemical properties of molecules and materials. However, the computational capabilities of present-day quantum computers are still relatively limited. A newly published study in Science Advances fosters an unexpected alliance between the methods used in quantum and traditional computing.

The research team, formed by Cristian Micheletti and Francesco Slongo of SISSA in Trieste, Philipp Hauke of the University of Trento, and Pietro Faccioli of the University of Milano-Bicocca, used a mathematical approach called QUBO (from “Quadratic Unconstraint Binary Optimization”) that is ideally suited for specific quantum computers, called “quantum annealers.”

Jan 10, 2024

Single-Photon Source Marks Quantum Cryptography Gain

Posted by in categories: computing, encryption, engineering, internet, nanotechnology, quantum physics

Producing photons one at a time on demand at room temperature is a key requirement for the rollout of a quantum internet—and the practical quantum computers that would undergird that network. The photons can be used as quantum bits (qubits), the quantum equivalent of classical computing’s 0s and 1s. Labs around the world have devised various ways to generate single photons, but they can involve complex engineering techniques such as doped carbon nanotubes or costly cryogenically-cooled conditions. On the other hand, less complicated techniques such as using traditional light sources do not provide the necessary level of control over single-photon emissions required for quantum networks and computers.

Now, researchers from Tokyo University of Science (TUS) and the Okinawa Institute of Science and Technology have collaborated to develop a prototype room temperature single-photon light source using standard materials and methods. The team described the fabrication of the prototype and its results in a recent issue of the journal Physical Review Applied.

“Our single-photon light source … increases the potential to create quantum networks—a quantum internet—that are cost-effective and accessible.” —Kaoru Sanaka, Tokyo University of Science.

Jan 8, 2024

Overcoming ‘Noise’ Challenges: A Leap Forward in Quantum Computing

Posted by in categories: computing, encryption, finance, quantum physics

Over the past twenty years, many companies, including Google, Microsoft, and IBM, have invested in quantum computing development. Investors have contributed over $5 billion to this cause. The aim is to use quantum physics properties to process information in ways that traditional computers cannot. Quantum computing could impact various fields, including drug discovery, cryptography, finance, and supply-chain logistics. However, the excitement around this technology has led to a mix of claims, making it hard to gauge the actual progress.

The main challenge in developing quantum computers is managing the ‘noise’ that can interfere with these sensitive systems. Quantum systems can be disrupted by disturbances like stray photons from heat, random signals from nearby electronics, or physical vibrations. This noise can cause errors or stop a quantum computation. Regardless of the processor size or the technology’s potential uses, a quantum computer will not surpass a classical computer unless the noise is controlled.

For a while, researchers thought they might have to tolerate some noise in their quantum systems, at least temporarily. They looked for applications that could still work effectively with this constraint. However, recent theoretical and experimental advances suggest that the noise issue might soon be resolved. A mix of hardware and software strategies is showing potential for reducing and correcting quantum errors. Earl Campbell, vice president of quantum science at Riverlane, a UK-based quantum computing company, believes there is growing evidence to be hopeful about quantum computing’s future.

Jan 6, 2024

Fear is not an argument for rejecting artificial intelligence

Posted by in categories: biotech/medical, economics, encryption, genetics, quantum physics, robotics/AI

Scientific knowledge can progress rapidly, yet its social, economic, and political impacts often unfold at a painstakingly slow pace. The medicine of the 21st century draws upon genetic and embryological breakthroughs of the 19th century. Our current technology is firmly grounded in quantum physics, which was formulated a century ago. And the topic of the day, artificial intelligence (AI), traces its origins to the secret weapons research during World War II.

‌In 1935, the brilliant British mathematician, Alan Turing, envisioned a conceptual computer. His genius would later lead him to crack the Enigma code used by German submarines for secret communications during the war. Turing’s contributions extended beyond cryptography, as he introduced fundamental concepts of AI, including the training of artificial neural networks. Benedict Cumberbatch portrayed Turing in the 2014 film The Imitation Game, which earned a screenplay Oscar that year. All this historical context brings us to the heart of the current AI revolution.

‌AI uses neural networks, also known as artificial neural networks, which are comprised of multiple layers of artificial neurons. Each neuron receives numerous inputs from the lower layer and produces a single output to the upper layer, similar to the dendrites and axon of natural neurons. As information progresses through each layer, it gradually becomes more abstract, resembling the process that occurs in the visual cortex of our brains.

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