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Quantum computers could be powerful enough to decrypt Bitcoin sometime after 2030, CEO of Nvidia’s quantum partner says

“You should have a few good years ahead of you but I wouldn’t hold my Bitcoin,” Peronnin said, laughing. “They need to fork [move to a stronger blockchain] by 2030, basically. Quantum computers will be ready to be a threat a bit later than that,” he said.

Quantum doesn’t just threaten Bitcoin, of course, but all banking encryption. And it is likely that in all these cases companies are developing quantum resistant tools to upgrade their existing security systems.

Defensive security algorithms are improving, Peronnin said, so it’s not certain when the blockchain will become vulnerable to a quantum attack. But “the threshold for such an event is coming closer to us year by year,” he said.

First full simulation of 50 qubit universal quantum computer achieved

A research team at the Jülich Supercomputing Center, together with experts from NVIDIA, has set a new record in quantum simulation: for the first time, a universal quantum computer with 50 qubits has been fully simulated—a feat achieved on Europe’s first exascale supercomputer, JUPITER, inaugurated at Forschungszentrum Jülich in September.

The result surpasses the previous world record of 48 qubits, established by Jülich researchers in 2022 on Japan’s K computer. It showcases the immense computational power of JUPITER and opens new horizons for developing and testing quantum algorithms. The research is published on the arXiv preprint server.

Quantum computer simulations are vital for developing future quantum systems. They allow researchers to verify experimental results and test new algorithms long before powerful quantum machines become reality. Among these are the Variational Quantum Eigensolver (VQE), which can model molecules and materials, and the Quantum Approximate Optimization Algorithm (QAOA), used for optimization problems in logistics, finance, and artificial intelligence.

Sharper MRI scans may be on horizon thanks to new physics-based model

Researchers at Rice University and Oak Ridge National Laboratory have unveiled a physics-based model of magnetic resonance relaxation that bridges molecular-scale dynamics with macroscopic magnetic resonance imaging (MRI) signals, promising new insight into how contrast agents interact with water molecules. This advancement paves the way for sharper medical imaging and safer diagnostics using MRI.

The study is published in The Journal of Chemical Physics.

This new approach, known as the NMR eigenmodes framework, solves the full physical equations that can be used to interpret how water molecules relax around metal-based imaging agents, a task that previous models approximated. These findings could alter the development and application of new contrast agents in both medicine and materials science.

New Quantum Algorithm Could Explain Why Matter Exists at All

Researchers used IBM’s quantum computers to create scalable quantum circuits that simulate matter under extreme conditions, offering new insight into fundamental forces and the origins of the universe. Simulating how matter behaves under extreme conditions is essential for exploring some of the d

From Data to Physics: An Agentic Large Language Model Solves a Competitive Adsorption Puzzle

We show that an agentic large language model (LLM) (OpenAI o3 with deep research) can autonomously reason, write code, and iteratively refine hypotheses to derive a physically interpretable equation for competitive adsorption on metal-organic layers (MOLs)—an open problem our lab had struggled with for months. In a single 29-min session, o3 formulated the governing equations, generated fitting scripts, diagnosed shortcomings, and produced a compact three-parameter model that quantitatively matches experiments across a dozen carboxylic acids.

Cracking the code of complexity in computer science’s P vs. NP problem

New research from the University of Waterloo is making inroads on one of the biggest problems in theoretical computer science. But the way to do it, according to Cameron Seth, a Ph.D. researcher working in the field of algorithmic approximation, is by breaking the problem down into smaller pieces.

“Everyone working in computer science and mathematics knows about the ‘P vs. NP’ problem,” Seth says. “It’s one of the notorious Millennium Prize Problems: so famous and so difficult that solving one will earn you a million dollars.”

To understand the crux of the “P vs. NP” problem, imagine an enormous jigsaw puzzle or a Sudoku puzzle. It would be a “P” problem if it could be solved relatively quickly by a computer, whereas they would be an “NP” problem if they were extremely difficult to solve, but a provided solution could be quickly verified.

Black hole mergers could give rise to observable gravitational-wave tails

Black holes, regions of spacetime in which gravity is so strong that nothing can escape, are intriguing and extensively studied cosmological phenomena. Einstein’s general theory of relativity predicts that when two black holes merge, they emit ripples in spacetime known as gravitational waves.

Once the gravitational waves originating from black hole mergers fade, subtle hints of these waves could remain, known as late-time gravitational-wave tails. While the existence of these tails has been widely theorized about in the past, it was not yet conclusively confirmed.

Researchers at Niels Bohr Institute, University of Lisbon and other institutes worldwide recently performed black hole merger simulations based on Einstein’s equations, to further probe the existence of late-time gravitational-wave tails. Their simulations, outlined in a paper in Physical Review Letters, suggest that these tails not only exist, but could also have a larger amplitude than originally predicted and could thus be observed in future experiments.

Algorithms reveal how propane becomes propylene for everyday products

Countless everyday products, from plastic squeeze bottles to outdoor furniture, are derived by first turning propane into propylene.

A 2021 study in Science demonstrated that chemists could use tandem nanoscale catalysts to integrate multiple steps of the process into a single reaction—a way for companies to increase yield and save money. But it was unclear what was happening at the , making it difficult to apply the technique to other key industrial processes.

Researchers at the University of Rochester have developed algorithms that show the key atomic features driving the complex chemistry when the nanoscale catalysts turn propane into propylene.

Humans have ability to detect objects without touching them

In terms of objects, human touch has typically been understood to be limited to physical touch, where we detect objects through contact with our skin.

However, recent findings in animal have challenged this view. It is known that certain wading birds such as sandpipers and plovers, for example, use a form of ‘remote touch’ to detect prey hidden beneath the sand using their beaks.

Remote touch allows the detection of objects buried under granular materials, such as sand or soil, through subtle mechanical signals transmitted through the material when pressure is applied nearby.

The new study, published in IEEE International Conference on Development and Learning (ICDL), investigated whether humans share a similar capability to touch objects remotely.

The researchers asked 12 participants to move their fingers gently through sand to locate a hidden cube before physically touching it.

Remarkably, the results revealed a comparable ability to that seen in wading birds, despite humans lacking the specialised beak structures that enable this sense in birds.

By modelling the physical aspects of the remote touch phenomenon, the study found that human hands are remarkably sensitive, detecting the presence of buried objects by perceiving small displacements in the sand surrounding them with 70% precision within the expected detectable range.

Continue reading “Humans have ability to detect objects without touching them” | >

First full simulation of 50-qubit universal quantum computer achieved

A research team at the Jülich Supercomputing Center, together with experts from NVIDIA, has set a new record in quantum simulation: for the first time, a universal quantum computer with 50 qubits has been fully simulated—a feat achieved on Europe’s first exascale supercomputer, JUPITER, inaugurated at Forschungszentrum Jülich in September.

The result surpasses the previous world record of 48 qubits, established by Jülich researchers in 2022 on Japan’s K computer. It showcases the immense computational power of JUPITER and opens new horizons for developing and testing . The research is published on the arXiv preprint server.

Quantum computer simulations are vital for developing future quantum systems. They allow researchers to verify experimental results and test new algorithms long before powerful quantum machines become reality. Among these are the Variational Quantum Eigensolver (VQE), which can model molecules and materials, and the Quantum Approximate Optimization Algorithm (QAOA), used for optimization problems in logistics, finance, and artificial intelligence.

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