Anchored by next-generation IBM Quantum System Two in Illinois Quantum and Microelectronics Park, new initiative will advance useful quantum applications as industries move towards quantum-centric supercomputing.
Google’s latest quantum computer chip, which the team dubbed Willow, has ignited a heated debate in the scientific community over the existence of parallel universes.
Following an eye-opening achievement in computational problem-solving, claims have surfaced that the chip’s success aligns with the theory of a multiverse, a concept that suggests our universe is one of many coexisting in parallel dimensions. In this piece, we’ll examine both sides of this argument that seems to have opened up a parallel universe of its own — with one universe of scientists suggesting the Willow experiments offer evidence of a multiverse and the other suggesting it has nothing to do with the theory at all.
According to Google, Willow solved a computational problem in under five minutes — a task that would have taken the world’s fastest supercomputers approximately 10 septillion years. This staggering feat, announced in a blog post and accompanied by a study in the journal Nature, demonstrates the extraordinary potential of quantum computing to tackle problems once thought unsolvable within a human timeframe.
A NASA study using a series of supercomputer simulations reveals a potential new solution to a longstanding Martian mystery: How did Mars get its moons? The first step, the findings say, may have involved the destruction of an asteroid.
The research team, led by Jacob Kegerreis, a postdoctoral research scientist at NASA’s Ames Research Center in California’s Silicon Valley, found that an asteroid passing near Mars could have been disrupted—a nice way of saying “ripped apart”—by the red planet’s strong gravitational pull.
The paper is published in the journal Icarus.
Fusion energy research is being pursued around the world as a means of solving energy problems. Magnetic confinement fusion reactors aim to extract fusion energy by confining extremely hot plasma in strong magnetic fields.
Its development is a comprehensive engineering project involving many advanced technologies, such as superconducting magnets, reduced-activation materials, and beam and wave heating devices. In addition, predicting and controlling the confined plasma, in which numerous charged particles and electromagnetic fields interact in complex ways, is an interesting research subject from a physics perspective.
To understand the transport of energy and particles in confined plasmas, theoretical studies, numerical simulations using supercomputers, and experimental measurements of plasma turbulence are being conducted.
Quantum calculations of molecular systems often require extraordinary amounts of computing power; these calculations are typically performed on the world’s largest supercomputers to better understand real-world products such as batteries and semiconductors.
Now, UC Berkeley and Lawrence Berkeley National Laboratory (Berkeley Lab) researchers have developed a new machine learning method that significantly speeds up atomistic simulations by improving model scalability. This approach reduces the computing memory required for simulations by more than fivefold compared to existing models and delivers results over ten times faster.
Their research has been accepted at Neural Information Processing Systems (NeurIPS) 2024, a conference and publication venue in artificial intelligence and machine learning. They will present their work at the conference on December 13, and a version of their paper is available on the arXiv preprint server.
Google’s new 105-qubit quantum processor has surpassed a key milestone first proposed in 1995.
Quantum computers hope to excel at solving problems that are too large, complex, or cumbersome for even the most powerful supercomputers, but many hurdles remain before they can be reliably put to commercial use. Here, we share an update on PsiQuantum’s approach, and recent progress towards useful, large-scale machines.
PsiQuantum co-founder \& Chief Scientific Officer Pete Shadbolt presents at the 2024 MIT EmTech conference in Cambridge, MA.
Google’s new quantum computing chip, Willow, has set a groundbreaking standard by achieving unparalleled speed and precision, outperforming supercomputers in specific tasks by millions of times. This revolutionary chip enhances quantum error correction, making scalable quantum systems a reality and unlocking new possibilities for artificial intelligence, scientific research, and real-world problem-solving. Willow’s success marks a major milestone in the integration of quantum computing and AI, driving innovation across industries.
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Humanity’s quest for answers has a new ally: Google’s Willow chip — a quantum chip that outpaces the fastest supercomputers by septillions of years! Imagine solving problems regular computers take years for—like creating life-saving medicines, predicting weather, or designing tech we haven’t dreamed of yet. But with great power comes challenges: high costs, logistics, and even risks to cybersecurity. The quantum revolution has begun, but the big question is—how will we use this power? Palki Sharma tells you.
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Google has unveiled a quantum computing chip, “Willow,” capable of performing tasks in minutes that would take supercomputers 10 septillion years. This breakthrough in error correction marks a significant step towards practical quantum computing, with potential applications in drug discovery, fusion energy, and climate change solutions.
Google on Monday showed off a new quantum computing chip that it said was a major breakthrough that could bring practical quantum computing closer to reality.
A custom chip called “Willow” does in minutes what it would take leading supercomputers 10 septillion years to complete, according to Google Quantum AI founder Hartmut Neven.
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