Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog

Category: information science – Page 2

Exactly 100 years ago, famed Austrian physicist Erwin Schrödinger (yes, the cat guy) postulated his eponymous equation that explains how particles in quantum physics behave. A key component of quantum mechanics, Schrödinger’s Equation provides a way to calculate the wave function of a system and how it changes dynamically in time.

“Quantum mechanics, along with Albert Einstein’s theory of general relativity are the two pillars of modern physics,” says Utah State University physicist Abhay Katyal. “The challenge is, for more than half a century, scientists have struggled to reconcile these two theories.”

Quantum mechanics, says Katyal, a doctoral student and Howard L. Blood Graduate Fellow in the Department of Physics, describes the behavior of matter and forces at the subatomic level, while explains gravity on a large scale.

Read more | >

Ever since general relativity pointed to the existence of black holes, the scientific community has been wary of one peculiar feature: the singularity at the center—a point, hidden behind the event horizon, where the laws of physics that govern the rest of the universe appear to break down completely. For some time now, researchers have been working on alternative models that are free of singularities.

A new paper published in the Journal of Cosmology and Astroparticle Physics, the outcome of work carried out at the Institute for Fundamental Physics of the Universe (IFPU) in Trieste, reviews the state of the art in this area. It describes two alternative models, proposes observational tests, and explores how this line of research could also contribute to the development of a theory of quantum gravity.

“Hic sunt leones,” remarks Stefano Liberati, one of the authors of the paper and director of IFPU. The phrase refers to the hypothetical singularity predicted at the center of standard —those described by solutions to Einstein’s field equations. To understand what this means, a brief historical recap is helpful.

Read more | >

Solving one of the oldest algebra problems isn’t a bad claim to fame, and it’s a claim Norman Wildberger can now make: The mathematician has solved what are known as higher-degree polynomial equations, which have been puzzling experts for nearly 200 years.

Wildberger, from the University of New South Wales (UNSW) in Australia, worked with computer scientist Dean Rubine on a paper that details how these incredibly complex calculations could be worked out.

“This is a dramatic revision of a basic chapter in algebra,” says Wildberger. “Our solution reopens a previously closed book in mathematics history.”

Read more | >

RIKEN and Fujitsu Limited have developed a 256-qubit superconducting quantum computer that will significantly expand their joint quantum computing capabilities. The system, located at the RIKEN RQC-FUJITSU Collaboration Center, located on the RIKEN Wako campus, builds upon the advanced technology of the 64-qubit iteration, which was launched with the support of the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT) in October 2023, and incorporates newly-developed high-density implementation techniques. The new system overcomes some key technical challenges, including appropriate cooling within the dilution refrigerator, which is achieved through the incorporation of high-density implementation and cutting-edge thermal design.

This announcement marks a new step toward the practical application of superconducting quantum computers and unlocking their potential to grapple with some of the world’s most complex issues, such as the analysis of larger molecules and the implementation and demonstration of sophisticated error correction algorithms.

The organizations plan to integrate the 256-qubit superconducting quantum computer into their platform for hybrid quantum computing lineup and offer it to companies and research institutions globally starting in the first quarter of fiscal 2025. Looking further into the future, Fujitsu and RIKEN will continue R&D efforts toward the launch of a 1,000-qubit computer, scheduled to be launched in 2026. For more information, see a longer press release on Fujitsu’s websiteThe webpage will open in a new tab..

Read more | >

Discovering new, powerful electrolytes is one of the major bottlenecks in designing next-generation batteries for electric vehicles, phones, laptops and grid-scale energy storage.

The most stable electrolytes are not always the most conductive. The most efficient batteries are not always the most stable. And so on.

“The electrodes have to satisfy very different properties at the same time. They always conflict with each other,” said Ritesh Kumar, an Eric and Wendy Schimdt AI in Science Postdoctoral Fellow working in the Amanchukwu Lab at the University of Chicago Pritzker School of Molecular Engineering (UChicago PME).

Read more | >

A mathematician has solved a 200-year-old maths problem after figuring out a way to crack higher-degree polynomial equations without using radicals or irrational numbers.

The method developed by Norman Wildberger, PhD, an honorary professor at the School of Mathematics and Statistics at UNSW Sydney, solves one of algebra’s oldest challenges by finding a general solution to equations where the variable is raised to the fifth power or higher.

Read more | >

IN A NUTSHELL 🔬 Scientists at the University of South China have developed innovative algorithms to optimize radiation shielding for next-generation nuclear reactors. 💡 The newly created algorithms, RP-NSGA and RP-MOABC, significantly improve performance by integrating a reference-point-selection strategy with established optimization techniques. 📈 Experiments demonstrated that these algorithms achieve substantial reductions in volume and.

Read more | >

Pulsatile tinnitus (PT) is a challenging diagnostic condition arising from various vascular, neoplastic, and systemic disorders. Non-invasive imaging is essential for identifying underlying causes while minimizing risks of invasive diagnostic angiography. Although no consensus exists on the primary imaging modality for PT and currently CT, ultrasound, and MRI are used in the diagnostic pathway, MRI is increasingly preferred as the first-line screening test for its diagnostic efficacy and safety. MRI protocols such as time-of-flight, magnetic resonance angiography, diffusion-weighted imaging, and arterial spin labeling can identify serious causes, including vascular shunting lesions, venous sinus stenosis, and tumors.

Read more | >

A machine-learning algorithm rapidly generates designs that can be simpler than those developed by humans.

Researchers in optics and photonics rely on devices that interact with light in order to transport it, amplify it, or change its frequency, and designing these devices can be painstaking work requiring human ingenuity. Now a research team has demonstrated that the discovery of the core design concepts can be automated using machine learning, which can rapidly provide efficient designs for a wide range of uses [1]. The team hopes the approach will streamline research and development for scientists and engineers who work with optical, mechanical, or electrical waves, or with combinations of these wave types.

When a researcher needs a transducer, an amplifier, or a similar element in their experimental setup, they draw on design concepts tested and proven in earlier experiments. “There are literally hundreds of articles that describe ideas for the design of devices,” says Florian Marquardt of the University of Erlangen-Nuremberg in Germany. Researchers often adapt an existing design to their specific needs. But there is no standard procedure to find the best design, and researchers could miss out on simpler designs that would be easier to implement.

Read more | >

Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a novel artificial intelligence (AI) model inspired by neural oscillations in the brain, with the goal of significantly advancing how machine learning algorithms handle long sequences of data.

AI often struggles with analyzing complex information that unfolds over long periods of time, such as climate trends, biological signals, or financial data. One new type of AI model called “state-space models” has been designed specifically to understand these sequential patterns more effectively. However, existing state-space models often face challenges—they can become unstable or require a significant amount of computational resources when processing long data sequences.

To address these issues, CSAIL researchers T. Konstantin Rusch and Daniela Rus have developed what they call “linear oscillatory state-space models” (LinOSS), which leverage principles of forced harmonic oscillators—a concept deeply rooted in physics and observed in .

Read more | >