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Category: computing – Page 29

Computer Has One Instruction, Many Transistors

There’s always some debate around what style of architecture is best for certain computing applications, with some on the RISC side citing performance per watt and some on the CISC side citing performance per line of code. But when looking at instruction sets it’s actually possible to eliminate every instruction except one and still have a working, Turing-complete computer. This instruction is called subleq or “subtract and branch if less-than or equal to zero ”. [Michael] has built a computer that does this out of discrete components from scratch.

We’ll save a lot of the details of the computer science for [Michael] or others to explain, but at its core this is a computer running with a 1 kHz clock with around 700 transistors total. Since the goal of a single-instruction computer like this is simplicity, the tradeoff is that many more instructions need to be executed for equivalent operations. For this computer it takes six clock cycles to execute one instruction, for a total of about 170 instructions per second. [Michael] also created an assembler for this computer, so with an LCD screen connected and mapped to memory he can write and execute a simple hello world program just like any other computer.

[Michael] does note that since he was building this from Logisim directly he doesn’t have a circuit schematic, but due to some intermittent wiring issues might have something in the future if he decides to make PCBs for this instead of using wire on a cardboard substrate. There’s plenty of other information on his GitHub page though. It’s a unique project that gets to the core of what’s truly needed for a working computer. There are a few programming languages out there that are built on a similar idea.

MIT engineers develop a magnetic transistor for more energy-efficient electronics

Transistors, the building blocks of modern electronics, are typically made of silicon. Because it’s a semiconductor, this material can control the flow of electricity in a circuit. But silicon has fundamental physical limits that restrict how compact and energy-efficient a transistor can be.

MIT researchers have now replaced silicon with a magnetic semiconductor, creating a magnetic transistor that could enable smaller, faster, and more energy-efficient circuits. The material’s magnetism strongly influences its electronic behavior, leading to more efficient control of the flow of electricity.

The team used a novel magnetic material and an optimization process that reduces the material’s defects, which boosts the transistor’s performance.

Breakthrough: Quantum Entanglement Achieved Between The Hearts of Two Atoms

Quantum entanglement – once dismissed by Albert Einstein as “spooky action at a distance” – has long captured the public imagination and puzzled even seasoned scientists.

But for today’s quantum practitioners, the reality is rather more mundane: entanglement is a kind of connection between particles that is the quintessential feature of quantum computers.

Though these devices are still in their infancy, entanglement is what will allow them to do things classical computers cannot, such as better simulating natural quantum systems like molecules, pharmaceuticals, or catalysts.

Innovative transistor design offering advantages for controlling and reading quantum chips

The smaller electronic components become, the more complex their manufacture becomes. This has been a major problem for the chip industry for years. At TU Wien, researchers have now succeeded for the first time in manufacturing a silicon-germanium (SiGe) transistor using an alternative approach that will not only enable smaller dimensions in the future, but will also be faster, require less energy and function at extremely low temperatures, which is important for quantum chips.

The key trick lies in the oxide layer that insulates the semiconductor: it is doped and produces a long-range effect that extends into the semiconductor. The technology was developed by TU Wien (Vienna), JKU Linz and Bergakademie Freiberg. The results have now been published in the journal IEEE Electron Device Letters and selected as Editor’s Pick on the cover of the August issue.

Analog computing platform uses synthetic frequency domain to boost scalability

Analog computers, computing systems that represent data as continuous physical quantities, such as voltage, frequency or vibrations, can be significantly more energy-efficient than digital computers, which represent data as binary states (i.e., 0s and 1s). However, upscaling analog computing platforms is often difficult, as their underlying components can behave differently in larger systems.

Researchers at Virginia Tech, Oak Ridge National Laboratory and the University of Texas at Dallas have developed a new synthetic domain approach, a technique to encode information at different frequencies in a single device that could enable upscaling analog computers without the need to add more physical components.

Their proposed approach, outlined in a paper published in Nature Electronics, was used to develop a compact and highly efficient analog computing platform based on lithium niobate integrated nonlinear phononics.

New, improved 3,000-qubit neutral atom array system reloads atoms continuously for more than two hours

The neutral atom array architecture for quantum computing has been rapidly advancing over the last several years, and a recent study published in Nature has just revealed another step forward for this technology. The team of Harvard researchers involved in this study have engineered a 3,000-qubit neutral atom array system capable of operating continuously for more than two hours, which goes far beyond typical trap lifetimes of only about 60 seconds.

Typically, neutral atom array systems arrange , like rubidium, in an array using highly focused , called optical tweezers. The are arranged and held under vacuum conditions and then used as qubits to perform and other operations. However, the procedure results in the loss of some atoms.

“An outstanding challenge associated with these systems involves atom loss, originating from errors in entangling operations, state-readout, and finite trap lifetime. Atom losses necessitate pulsed operation which limits the performance of these quantum systems, including the circuit depth of quantum computation, accuracy of , and the rate of entanglement generation in quantum networking protocols,” the study authors explain.

New design tackles integer factorization problems through digital probabilistic computing

Probabilistic Ising machines (PIMs) are advanced and specialized computing systems that could tackle computationally hard problems, such as optimization or integer factorization tasks, more efficiently than classical systems. To solve problems, PIMs rely on interacting probabilistic bits (p-bits), networks of interacting units of digital information with values that randomly fluctuate between 0 and 1, but that can be biased to converge to yield desired solutions.

Microendovascular Neural Recording from Cortical and Deep Vessels with High Precision and Minimal Invasiveness

Interesting paper where microintravascular electrodes were inserted into cortical veins of pigs to record somatosensory and visual neuronal activity as well as selectively stimulate motor areas. Compared to electrocorticography, this is a less invasive approach with similar capabilities. #neurotech [ https://doi.org/10.1002/aisy.202500487](https://doi.org/10.1002/aisy.202500487)

Intravascular electroencephalography (ivEEG) with microintravascular electrodes enhances neural monitoring, functional mapping, and brain–computer interfaces (BCIs), offering a minimally invasive approach to assess cortical activities; however, this approach remains unrealized. Current ivEEG methods using electrode-attached stents are limited to recording from large vessels, such as the superior sagittal sinus (SSS), restricting access to cortical regions essential for precise BCI control, such as those for hand and mouth movements. Here, ivEEG signals from small and soft cortical veins (CV-ivEEGs) in eight pigs using microintravascular electrodes are recorded, achieving higher resting-state signal power and greater spatial resolution of somatosensory evoked potentials (SEPs) compared to SSS-based ivEEG. Additionally, ivEEG recorded from deep veins clearly captures visual evoked potentials. Furthermore, comparisons between CV-ivEEG and electrocorticography (ECoG) using epidural and subdural electrodes in two pigs demonstrate that CV-ivEEG captures cortical SEPs comparable to ECoG. Targeted electrical stimulation via cortical vein electrodes induces specific contralateral muscle contractions in five anesthetized pigs, confirming selective motor-region stimulation with minimal invasiveness. The findings suggest that ivEEG with microintravascular electrodes is capable of accessing diverse cortical areas and capturing localized neural activity with high signal fidelity for minimally invasive cortical mapping and BCI.

Lasers just made atoms dance, unlocking the future of electronics

Scientists at Michigan State University have discovered how to use ultrafast lasers to wiggle atoms in exotic materials, temporarily altering their electronic behavior. By combining cutting-edge microscopes with quantum simulations, they created a nanoscale switch that could revolutionize smartphones, laptops, and even future quantum computers.

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