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Category: computing – Page 135

Loop-shaped structures called vortex rings are remarkably stable and are seen throughout nature, appearing as bubble rings blown by dolphins and smoke rings emitted by erupting volcanoes. Recently, scientists observed vortex rings made from electron spins in magnetic materials. These structures have properties that make them attractive for use in energy-efficient data storage and processing. Now Yizhou Liu and Naoto Nagaosa at the RIKEN Center for Emergent Matter Science in Japan have proposed a way to create such magnetic vortex rings on demand [1].

Liu and Nagaosa considered a nanometer-scale cylinder made of a “chiral” magnetic material, one whose magnetic structure differs from that of its mirror image. The magnetic vortex rings that form in such a system have more diverse topologies and greater stability than those that form in other systems. In numerical simulations, the researchers injected a pulse of electric current into their chiral magnetic cylinder through a circular trench etched into the cylinder’s top surface. They then studied how the current pulse affected the material’s spin configurations.

Liu and Nagaosa observed a chain of interconnected magnetic vortex rings form along the length of the cylinder. Varying the duration and amplitude of the injected current pulse, they were able to control the topology of the vortex rings and their connections. The researchers say that the next step is for experimentalists to replicate these findings in the lab. They also suggest that their technique could be adapted to produce magnetic vortex rings in other physical systems, such as liquid crystals and Bose-Einstein condensates.

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To operate reliably a quantum computer needs to correct the errors introduced into the system by noise in its hardware. Error-correction approaches typically use “logical” qubits, which are qubits made up of as many as a few thousand “physical” qubits. Logical qubits are much less error prone than physical qubits, but the hardware overhead complicates the realization of fault-tolerant quantum computers based on this approach. Now a team led by Harry Levine and Oskar Painter of the Amazon Web Services Center for Quantum Computing in California has demonstrated a new qubit design with built-in error-detection ability [1]. Painter says this qubit could serve as an alternative building block for error-correcting schemes, substantially reducing complexity.

The demonstrated qubit is an “erasure” qubit, one in which the most likely error type involves the loss, or erasure, of the qubit’s state [2]. This error is easier to spot and correct for than other qubit errors, such as those that flip the qubit’s state. Researchers have previously demonstrated erasure qubits made from single atoms. The new study makes the leap to transmons, the superconducting qubit used in the quantum processors developed by Google and IBM.

The erasure qubit of Levine, Painter, and colleagues contains three transmons. Two of the transmons are coupled together and store a qubit’s worth of information in a single, shared microwave photon. The third transmon reveals the loss of the photon—the erasure—through a shift in its operating frequency. The researchers show that in this qubit erasure errors are the dominant error type and can be detected in real time. The researchers now plan to use their new qubit to build logic gates and error-correcting circuits.

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“The Most Powerful Type Of Computing Machine That Is Possible In This Universe”

Aka Hyper Computers they are based on Quantum Computing & Gravity. They are agnostic to Causality i.e. they have Indefinite Causality (Cause & Effect Relationships)

Automatski is 5,000 years ahead of everyone else. It built the worlds first Quantum Gravity Computer in ~2006.

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I am, I’m slightly embarrassed to admit, quoted pretty extensively in the cover story of this week’s New Scientist magazine (alas, only available to subscribers or those willing to shell out $4.95). The story, by Michael Brooks, is about an interesting recent paper by Lucien Hardy of Perimeter Institute, on the power of “quantum gravity computers.” Lucien’s paper considers the following question: by exploiting quantum fluctuations in the causal structure of spacetime, can one efficiently solve problems that are not efficiently solvable with a garden-variety quantum computer?

As I told Brooks, I really do think this is a hell of a question, one that’s intimately related to the challenge of understanding quantum gravity itself. The trouble is that, until an actual quantum theory of gravity chooses to make itself known to us, almost everything we can say about the question is pure speculation.

But of course, pure speculation is what New Scientist gobbles up with french fries and coleslaw. And so, knowing what kind of story they were going to run, I did my best to advocate giving reality at least a few column inches. Fortunately, the end result isn’t quite as bad as I’d feared.

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Demonstrating a long-coherence dual-rail erasure qubit using tunable transmons.

AWS today reported demonstrating an improved approach to quantum error correction that accounts for flip and phase errors in qubits with less overhead (redundant qubits) and on time scales that allow for effective error correction. The work, published today in APS Physical Review X, uses what’s called dual-rail erasure qubits.

Broadly, qubits undergo three types, report AWS researchers Harry Levine and Arbel Haim, in a blog (A new building block for error-corrected quantum computers) today, “[The] vast majority of errors (96%) in our dual-rail qubit are erasure errors (leakage to |00 ⟩), with only a small fraction (4%) of residual (silent) bit-flip and phase-flip errors. This is a strong indicator that if we can accurately flag the erasures, then we can efficiently correct most errors that occur in this system.”

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Our H+ friend Rob Wilkes alerted me to this today!

March 20 (Reuters) — Elon Musk’s brain-chip startup Neuralink livestreamed on Wednesday its first patient implanted with a chip using his mind to play online chess.

Noland Arbaugh, the 29-year-old patient who was paralyzed below the shoulder after a diving accident, played chess on his laptop and moved the cursor using the Neuralink device. The implant seeks to enable people to control a computer cursor or keyboard using only their thoughts.

Arbaugh had received an implant from the company in January and could control a computer mouse using his thoughts, Musk said last month.

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Neuralink, Elon Musk ’s brain chip startup, released a video on Wednesday showing the company’s first patient using a laptop with just his mind.

The video, which was livestreamed on Neuralink’s account on X, showed 29-year-old Noland Arbaugh playing a game of chess on his laptop using Neuralink’s brain computer interface (BCI) technology. Arbaugh is paralyzed from the shoulders down due to what he describes as a “freak diving accident.”

“It’s all brain power there,” Arbaugh said, referring to his ability to use a mouse and keyboard unassisted. He later added, “Basically, it was like using the Force on the cursor and I could get it to move wherever I wanted.”

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Significant advancements have been made in quantum computing, with major international companies like Google and IBM now providing quantum computing services via the cloud. Nevertheless, quantum computers are not yet capable of addressing issues that arise when conventional computers hit their performance ceilings. This limitation is primarily the availability of qubits or quantum bits, i.e., the basic units of quantum information, is still insufficient.

One of the reasons for this is that bare qubits are not of immediate use for running a quantum algorithm. While the binary bits of customary computers store information in the form of fixed values of either 0 or 1, qubits can represent 0 and 1 at one and the same time, bringing probability as to their value into play. This is known as quantum superposition.

This makes them very susceptible to external influences, which means that the information they store can readily be lost. In order to ensure that quantum computers supply reliable results, it is necessary to generate a genuine entanglement to join together several physical qubits to form a logical qubit. Should one of these physical qubits fail, the other qubits will retain the information. However, one of the main difficulties preventing the development of functional quantum computers is the large number of physical qubits required.

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