Reported plan to potentially subject new large electricity users to curtailment periods during supply shortfalls was rejected.
Category: computing – Page 4
Samsung invests nearly $23M in Central Texas ahead of second Taylor chip plant
The investment will go into the Taylor community and across Central Texas, benefiting education and nonprofits.
God’s Number is 20
The Rubik’s Cube is one of the most iconic mathematical puzzles ever invented, created by Hungarian architect Ernő Rubik in 1974.
A standard 3×3×3 cube has-1 possible configurations — roughly 43 quintillion!
And here’s the remarkable mathematical result: every reachable configuration can be solved in 20 moves or fewer, provided a 180° face turn counts as one move.
Proven in 2010, this result is known as God’s Number.
A simple-looking puzzle. More than 43 quintillion configurations. And a mathematically proven upper limit on the number of moves needed to solve any of them.
Reference: [God’s Number Is 20 —]//www.cube20.org/)
Single 2D crystal transforms into transistor with built-in insulation and electrical contacts
A transistor normally requires several fundamentally different materials—a semiconductor to carry current, an insulating dielectric to control it and metallic contacts through which current enters and leaves. Integrating all of these components becomes increasingly difficult as semiconductor devices approach the atomic scale.
A research team led by Director Jo Moon-Ho of the Center for Van der Waals Quantum Solids within the Institute for Basic Science (IBS) has now demonstrated a fundamentally different approach. Instead of fabricating the semiconductor, dielectric and contact materials separately and then assembling them into a device, the researchers started from a single layered crystal and chemically converted selected atomic layers and regions into the different materials needed for a working transistor. The work is published in the journal Science.
Quantum calculations reveal how spin defects lose energy
When light hits a tiny defect embedded in a solid material like diamond or silicon carbide, it can kick the defect’s electrons into an excited state. These spin defects have the potential to be used as stable, readable qubits for quantum technologies, for example, quantum sensing. But modeling the full physics of their energetics over time—a key step in developing spin defects into new technologies—is a challenging task.
Now, researchers at the University of Chicago Pritzker School of Molecular Engineering (UChicago PME) have built a computational framework that captures the full optical cycle of such spin defects, including the prediction of internal conversion, a process particularly hard to model.
Their results, published in Physical Review Letters, shed light on how to use the defects in the design of quantum materials and could also be applied to a different class of systems used in renewable energy conversion and storage.
Critical PwnEscape Linux Kernel Vulnerability Lets Guest VMs Read Host Memory
A critical Linux kernel flaw let a guest VM read host memory in Vercel’s live sandboxes; host code execution was shown only in lab tests.
Human Neurons Grew Inside a Living Mouse Brain With Bizarre Results
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Hello and welcome! My name is Anton and in this video, we will talk about xenocortication — putting hybrid neurons inside animals.
Links:
https://www.nature.com/articles/s4158…
Previous video: • Lab-Grown Human Brain Cells Can Sense Time…
#xenocortication #neuroscience #neurobiology.
0:00 Xenocortication — what’s that Anton?
1:50 Genetically modified mice and the experiment.
3:10 Older experiment and the challenge.
4:40 New experiment transplanting neurons.
6:00 Human specific neuron formation (VEN)
7:20 Surprise from some of the mice.
8:30 Longterm effects.
10:10 Implications for the medical fields.
11:00 Ethical implications and guidelines.
13:00 Why it’s permitted in mice but not primates.
14:30 Conclusions.
Enjoy and please subscribe.
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Silicon qubits surpass 99.99% gate fidelity while operating three at once
Silicon spin qubits are a promising platform for building scalable quantum computers as they are compatible with the semiconductor manufacturing technologies used to produce today’s computer chips. However, they have an important weakness: silicon spin qubits typically lose accuracy when several qubits are under parallel control. To be useful, quantum computers will need to operate many qubits simultaneously without compromising the accuracy of their operations.
Now, in a study published in Nature Physics, researchers from the RIKEN Center for Emergent Matter Science and collaborators have addressed this challenge by achieving high-fidelity control of multiple silicon spin qubits operating in parallel. Using a five-qubit silicon array controlled through a single shared microwave line, they identified a key source of errors during the simultaneous operation of qubits and developed a way to mitigate its effects.
According to Leon Camenzind, a research scientist at RIKEN and co-first author who supervised the experiments, “This shows that high-fidelity control can be maintained even when several qubits are operated at the same time and represents an important step toward scaling up silicon-based quantum processors.”
Jamming the flow to enable memory in quantum materials
Understanding and controlling phase transitions are fundamental to physics and central to many technological revolutions. There is currently strong interest in materials with coupled structural and electronic phase transitions, where controlling the transition plasticity naturally yields built-in memory—a key step in emulating neurons and synapses for “neuromorphic” or brain-like computing technologies.
A team of UC San Diego researchers led by physics professor Oleg Shpyrko developed a new approach to coherent X-ray diffraction—a microscopy technique that is highly sensitive to specific nanoscale domain configurations —that allowed them to observe dynamics within a neuristor (a man-made device that mimics the brain’s neurons) made of vanadium dioxide while electricity was applied.
By taking measurements while operating the neuristor, they discovered a strategy to make the material learn and forget a specific state, opening an avenue toward developing energy-efficient brain-inspired hardware.
New chip-scale gyroscope measures rotation with unprecedented sensitivity
Researchers have developed a chip-scale optical ring-laser gyroscope that can measure rotation as slow as 37 degrees per hour. This record sensitivity, approaching Earth’s rotation rate of 15 degrees per hour, could eventually be useful for precision navigation and orientation systems, particularly where GPS is unavailable.
Gyroscopes measure how an object rotates, helping determine its orientation and movement. The chip-based gyroscopes found in smartphones and other everyday devices tend to have limited sensitivity, making them unsuitable for some demanding applications. This has driven scientists to develop chip-based versions of optical gyroscopes, which are sensitive enough for applications such as aircraft navigation.
“Our new gyroscope combines several advanced technologies to achieve a high level of sensitivity in a format that can be made with standard CMOS chip-processing methods and uses just milliwatts of optical power,” said Daniel J. Blumenthal, who led the research team from the University of California, Santa Barbara. “A fully integrated optical gyroscope would not only be smaller than today’s systems but also have no moving parts and thus be very resilient to vibrations and shocks.”