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Category: supercomputing

Elon Just Made Tesla Unstoppable

Questions to inspire discussion.

🚀 Q: How might Elon Musk’s diverse projects contribute to Tesla’s value? A: Musk’s involvement in AI, energy, transportation, and communication through projects like Tesla, SpaceX, and Neuralink demonstrates his capacity to make progress on multiple fronts, potentially creating significant value for Tesla.

Political Involvement and Economic Strategy.

đŸ›ïž Q: Why is Elon Musk getting involved in politics? A: Musk’s political involvement aims to create a better political system on Earth, addressing the unsustainability of US government spending and debt to avoid a fiscal doom loop.

📊 Q: What is Musk’s strategy to improve the US economy? A: Musk plans to accelerate GDP growth through AI-driven growth, humanoid bots, and reducing government spending and waste, potentially breaking free from the constant 7% growth line of the US stock market.

💰 Q: How could reducing government spending benefit the economy? A: By cutting wasteful spending and implementing a balanced budget requirement, the US could potentially grow its economy faster than its spending, reducing interest costs and freeing up money for other investments.

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Dark matter could create dark dwarfs at the center of the Milky Way

Dark matter is one of nature’s most confounding mysteries. It keeps particle physicists up at night and cosmologists glued to their supercomputer simulations. We know it’s real because its mass prevents galaxies from falling apart. But we don’t know what it is.

Dark matter doesn’t like other matter and may prefer its own company. While it doesn’t seem to interact with regular baryonic matter, it could possibly react with itself and self-annihilate. It needs a tightly-packed environment to do that, and that may lead to a way astrophysicists can finally detect it.

New theoretical research outlines how this could happen and states that sub-stellar objects, basically , could host the process. The research is titled “Dark dwarfs: -powered sub-stellar objects awaiting discovery at the ,” and it’s published in the Journal of Cosmology and Astroparticle Physics. The lead author is Djuna Croon, a and assistant professor in the Institute for Particle Physics Phenomenology in the Department of Physics at Durham University.

Cancer drug candidate developed using supercomputing & AI blocks tumor growth without toxic side effect

A new cancer drug candidate developed by Lawrence Livermore National Laboratory (LLNL), BBOT (BridgeBio Oncology Therapeutics) and the Frederick National Laboratory for Cancer Research (FNLCR) has demonstrated the ability to block tumor growth without triggering a common and debilitating side effect. In early clinical trials, the compound, known as BBO-10203, has shown promise in disrupting a key interaction between two cancer-driving proteins — RAS and PI3Kα — without causing hyperglycemia (high blood-sugar levels), which has historically hindered similar treatments. Published in Science

Machine learning outpaces supercomputers for simulating galaxy evolution coupled with supernova explosion

Researchers have used machine learning to dramatically speed up the processing time when simulating galaxy evolution coupled with supernova explosion. This approach could help us understand the origins of our own galaxy, particularly the elements essential for life in the Milky Way.

The findings are published in The Astrophysical Journal.

The team was led by Keiya Hirashima at the RIKEN Center for Interdisciplinary Theoretical and Mathematical Sciences (iTHEMS) in Japan, along with colleagues from the Max Planck Institute for Astrophysics (MPA) and the Flatiron Institute.

Unique method enables simulation of error-correctable quantum computers

Quantum computers still face a major hurdle on their pathway to practical use cases: their limited ability to correct the arising computational errors. To develop truly reliable quantum computers, researchers must be able to simulate quantum computations using conventional computers to verify their correctness—a vital yet extraordinarily difficult task.

Now, in a world-first, researchers from Chalmers University of Technology in Sweden, the University of Milan, the University of Granada, and the University of Tokyo have unveiled a method for simulating specific types of error-corrected quantum computations—a significant leap forward in the quest for robust quantum technologies.

Quantum computers have the potential to solve complex problems that no supercomputer today can handle. In the foreseeable future, ’s computing power is expected to revolutionize fundamental ways of solving problems in medicine, energy, encryption, AI, and logistics.

Quantum Entanglement: The “Spooky” Glue Uniting Qubits and Beyond

From enabling quantum supercomputers to securing communications and teleporting quantum states, entanglement is the thread weaving through all of quantum technology. What once struck Einstein as a paradox is today routinely observed and harnessed in labs – the “spooky action” has become a practical tool. We have learned that entanglement is not some esoteric fringe effect; it’s a concrete physical resource, much like energy or information, that can be exploited to do tasks that are otherwise impossible. Its special correlations allow quantum computers to perform massively parallel computations in a single wavefunction, allow cryptographers to detect eavesdroppers with absolute certainty, and allow quantum states to be transmitted without moving a physical carrier.

Yet, there is still much to master. Entangling a handful of qubits is easy; doing so with thousands or millions – while keeping them error-corrected – remains a grand challenge. As we push the number of entangled particles higher, we are essentially scaling up new forms of matter (entangled states) that have no counterpart in classical physics. In 2022, a 12-qubit entangled state might be a small quantum circuit; by 2035, we could be operating machines where 1,000 qubits are all entangled in complex ways, delivering computational feats far beyond today’s reach. On the communications front, nascent quantum networks are entangling nodes over city-scale distances, working toward a future quantum internet that could interconnect quantum computers or enable clock synchronization and sensing with unprecedented precision. Each improvement in generating high-quality entanglement over distance inches us closer to unhackable global communication links.

Entanglement also raises philosophical questions about the nature of reality – it blurs the boundary between “separate” objects and challenges our intuitions of locality. But from an engineer’s perspective, entanglement is also just another phenomenon to be tamed and utilized. The narrative of quantum technology is one of turning quantum quirks into quantum capabilities. Where classical engineers use wires and signals, quantum engineers use entanglement and superposition. It’s telling that entanglement is often called the “essence” or “cornerstone” of quantum mechanics – crack it, and you unlock a whole new paradigm of information processing.

‘A first in applied physics’: Breakthrough quantum computer could consume 2,000 times less power than a supercomputer and solve problems 200 times faster

Scientists have built a compact physical qubit with built-in error correction, and now say it could be scaled into a 1,000-qubit machine that is small enough to fit inside a data center. They plan to release this machine in 2031.

New hybrid quantum–classical computing approach used to study chemical systems

Caltech professor of chemistry Sandeep Sharma and colleagues from IBM and the RIKEN Center for Computational Science in Japan are giving us a glimpse of the future of computing. The team has used quantum computing in combination with classical distributed computing to attack a notably challenging problem in quantum chemistry: determining the electronic energy levels of a relatively complex molecule.

The work demonstrates the promise of such a quantum–classical hybrid approach for advancing not only , but also fields such as , nanotechnology, and drug discovery, where insight into the electronic fingerprint of materials can reveal how they will behave.

“We have shown that you can take classical algorithms that run on high-performance classical computers and combine them with quantum algorithms that run on quantum computers to get useful chemical results,” says Sharma, a new member of the Caltech faculty whose work focuses on developing algorithms to study quantum . “We call this quantum-centric supercomputing.”

It’s elementary: Problem-solving AI approach tackles inverse problems used in nuclear physics and beyond

Solving life’s great mysteries often requires detective work, using observed outcomes to determine their cause. For instance, nuclear physicists at the U.S. Department of Energy’s Thomas Jefferson National Accelerator Facility analyze the aftermath of particle interactions to understand the structure of the atomic nucleus.

This type of subatomic sleuthing is known as the inverse problem. It is the opposite of a forward problem, where causes are used to calculate the effects. Inverse problems arise in many descriptions of physical phenomena, and often their solution is limited by the experimental data available.

That’s why scientists at Jefferson Lab and DOE’s Argonne National Laboratory, as part of the QuantOm Collaboration, have led the development of an artificial intelligence (AI) technique that can reliably solve these types of puzzles on supercomputers at large scales.

Post-Alcubierre Warp-Drives

Researchers are actively exploring and revising the concept of Alcubierre warp drive, as well as alternative approaches, to potentially make superluminal travel feasible with reduced energy requirements and advanced technologies ## ## Questions to inspire discussion.

Practical Warp Drive Concepts.

🚀 Q: What is the Alcubierre warp drive? A: The Alcubierre warp drive (1994) is a superluminal travel concept within general relativity, using a warp bubble that contracts space in front and expands behind the spacecraft.

🌌 Q: How does Jose Natario’s warp drive differ from Alcubierre’s? A: Natario’s warp drive (2001) describes the warp bubble as a soliton and vector field, making it harder to visualize but potentially more mathematically robust.

🔬 Q: What is unique about Chris Van Den Broeck’s warp drive? A: Van Den Broeck’s warp drive (1999) uses a nested warp field, creating a larger interior than exterior, similar to a TARDIS, while remaining a physical solution within general relativity. Energy Requirements and Solutions.

💡 Q: How do Eric Lent’s hyperfast positive energy warp drives work? A: Lent’s warp drives (2020) are solitons capable of superluminal travel using purely positive energy densities, reopening discussions on conventional physics-based superluminal mechanisms.

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