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Archive for the ‘computing’ category: Page 69

Apr 14, 2024

TSMC: One Trillion Transistor GPUs Will Be Possible in a Decade

Posted by in category: computing

3D-stacking chiplets will be the standard to increase compute power going forward.

Apr 14, 2024

Researchers Prove Electrons Move Along “Quantum Paths” in New Study

Posted by in categories: computing, quantum physics

The Quantum Insider (TQI) is the leading online resource dedicated exclusively to Quantum Computing.

Apr 14, 2024

Photonic Quantum Computing: A Promising Future With Mature Technologies And Room-Temperature Operations

Posted by in categories: computing, particle physics, quantum physics

Photonic quantum computation, a type of quantum computation that uses light particles or photons, is divided into two main categories: discrete-variable (DV) and continuous-variable (CV) photonic quantum computation. Both have been realized experimentally and can be combined to overcome individual limitations. Photonic quantum computation is important as it can perform specific computational tasks more efficiently. It has several advantages, including the ability to observe and engineer quantum phenomena at room temperature, maintain coherence, and be engineered using mature technologies. The future of photonic quantum computing looks promising due to the significant progress in photonic technology.

Photonic quantum computation is a type of quantum computation that uses photons, particles of light, as the physical system for performing the computation. Photons are ideal for quantum systems because they operate at room temperature and photonic technologies are relatively mature. The field of photonic quantum computation is divided into two main categories: discrete-variable (DV) and continuous-variable (CV) photonic quantum computation.

In DV photonic quantum computation, quantum information is represented by one or more modal properties, such as polarization, that take on distinct values from a finite set. Quantum information is processed via operations on these modal properties and eventually measured using single photon detectors. On the other hand, in CV photonic quantum computation, quantum information is represented by properties of the electromagnetic field that take on any value in an interval, such as position. The electromagnetic field is transformed via Gaussian and non-Gaussian operations and then detected via homodyne detection.

Apr 14, 2024

4TB SD cards are arriving in 2025 for your cameras and laptops

Posted by in categories: computing, electronics

This new SD card will support 8K video recording.

Apr 13, 2024

Private Quantum Cloud: Oxford University Physicists Make Advance in ‘Blind Quantum Computing’

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

PRESS RELEASE — The full power of next-generation quantum computing could soon be harnessed by millions of individuals and companies, thanks to a breakthrough by scientists at Oxford University Physics guaranteeing security and privacy. This advance promises to unlock the transformative potential of cloud-based quantum computing and is detailed in a new study published in the influential U.S. scientific journal Physical Review Letters.

Quantum computing is developing rapidly, paving the way for new applications which could transform services in many areas like healthcare and financial services. It works in a fundamentally different way to conventional computing and is potentially far more powerful. However, it currently requires controlled conditions to remain stable and there are concerns around data authenticity and the effectiveness of current security and encryption systems.

Several leading providers of cloud-based services, like Google, Amazon, and IBM, already separately offer some elements of quantum computing. Safeguarding the privacy and security of customer data is a vital precursor to scaling up and expending its use, and for the development of new applications as the technology advances. The new study by researchers at Oxford University Physics addresses these challenges.

Apr 13, 2024

Rice team demonstrates miniature brain stimulator in humans

Posted by in categories: bioengineering, biotech/medical, computing, neuroscience

Rice University engineers have developed the smallest implantable brain stimulator demonstrated in a human patient. Thanks to pioneering magnetoelectric power transfer technology, the pea-sized device developed in the Rice lab of Jacob Robinson in collaboration with Motif Neurotech and clinicians Dr. Sameer Sheth and Dr. Sunil Sheth can be powered wirelessly via an external transmitter and used to stimulate the brain through the dura ⎯ the protective membrane attached to the bottom of the skull.

The device, known as the Digitally programmable Over-brain Therapeutic (DOT), could revolutionize treatment for drug-resistant depression and other psychiatric or neurological disorders by providing a therapeutic alternative that offers greater patient autonomy and accessibility than current neurostimulation-based therapies and is less invasive than other brain-computer interfaces (BCIs).

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Apr 13, 2024

Oxford breakthrough allows secure quantum computing from homes

Posted by in categories: computing, quantum physics

Researchers have developed a “blind quantum computing” method enabling secure, scalable quantum cloud computing connecting quantum entities over networks.

Apr 12, 2024

Breaking the Limits: Overcoming Heisenberg’s Uncertainty in Quantum Measurements

Posted by in categories: computing, engineering, quantum physics

Aalto University researchers are the first in the world to measure qubits with ultrasensitive thermal detectors—thus evading the Heisenberg uncertainty principle.

Chasing ever-higher qubit counts in near-term quantum computers constantly demands new feats of engineering.

Among the troublesome hurdles of this scaling-up race is refining how qubits are measured. Devices called parametric amplifiers are traditionally used to do these measurements. But as the name suggests, the device amplifies weak signals picked up from the qubits to conduct the readout, which causes unwanted noise and can lead to decoherence of the qubits if not protected by additional large components. More importantly, the bulky size of the amplification chain becomes technically challenging to work around as qubit counts increase in size-limited refrigerators.

Apr 11, 2024

How to Speed up a Quantum Network

Posted by in categories: computing, particle physics, quantum physics

A future quantum network of optical fibers will likely maintain communication between distant quantum computers. Sending quantum information rapidly across long distances has proved difficult, in part because most photons don’t survive the trip. Now Viktor Krutyanskiy of the University of Innsbruck, Austria, and his colleagues have more than doubled the success rate for sending photons that are quantum mechanically entangled with atoms to a distant site [1]. Instead of the previous approach of sending photons one at a time and waiting to see if each one arrives successfully, the researchers sent photons in groups of three. They believe that sending photons in larger numbers should be feasible in the future, allowing much faster transmission of quantum information.

Quantum networks require entanglement distribution, which involves sending a photon entangled with a local qubit to a distant location. The distribution system must check for the arrival and for the entanglement of each photon at the remote site before another attempt can be made, which can be time consuming. For a 100-km-long fiber, the light travel time combined with losses in the fiber and other inefficiencies limit the rate for this process to about one successful photon transfer per second using state-of-the-art equipment.

For faster distribution, Krutyanskiy and his colleagues trapped three calcium ions (qubits) in an optical cavity and performed repeated rounds of their protocol: in rapid sequence, each ion was triggered to emit an entangled photon that was sent down a 101-km-long, spooled optical fiber. In one experiment, the team performed nearly 900,000 of these “attempts,” detecting entangled photons at the far end 1906 times. The effective success rate came out to 2.9 per second. The team’s single-ion success rate was 1.2 per second.

Apr 10, 2024

Evaluating the Bayesian causal inference model of intentional binding through computational modeling

Posted by in category: computing

Tanaka, T. Evaluating the Bayesian causal inference model of intentional binding through computational modeling. Sci Rep 14, 2,979 (2024). https://doi.org/10.1038/s41598-024-53071-7

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