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Category: quantum physics – Page 247

A shadowy form of light within a universe of hypothetical particles is getting some serious consideration as a means of discovering the identity of dark matter.

According to a comprehensive new analysis under quantum chromodynamics, the dark photon is a much better fit for the observed results of particle collider experiments than the standard model of particle physics, by quite a wide margin.

In fact, a team of researchers led by physicist Nicholas Hunt-Smith of the ARC Centre of Excellence for Dark Matter Particle Physics and the University of Adelaide in Australia calculated a confidence level of 6.5 sigma, suggesting the odds that dark photons don’t explain the observations are in the ballpark of one in a billion.

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Quantum behavior is a strange, fragile thing that hovers on the edge of reality, between a world of possibility and a Universe of absolutes. In that mathematical haze lies the potential of quantum computing; the promise of devices that could quickly solve algorithms that would take classic computers too long to process.

For now, quantum computers are confined to cool rooms close to absolute zero (−273 degrees Celsius) where particles are less likely to tumble out of their critical quantum states.

Breaking through this temperature barrier to develop materials that still exhibit quantum properties at room temperatures has long been the goal of quantum computing. Though the low temperatures help keep the particle’s properties from collapsing out of their useful fog of possibility, the bulk and expense of the equipment limits their potential and ability to be scaled up for general use.

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Quantum computing has provided new insights into a fundamental aspect of photochemical reactions that has previously proven difficult to study. The findings could improve scientists’ understanding of light-driven processes such as photosynthesis, smog formation and ozone destruction.

Photochemical processes occur when atomic nuclei and their electrons take on different configurations after absorbing a photon. Some of these reactions are guided by a quantum phenomenon called a conical intersection, where the potential energy surfaces that describe a molecule in its ground state and in its excited state converge. In these situations, quantum mechanical interference can prevent certain molecular transformations from taking place – a constraint known as a geometric phase. This limits the path that the reaction can take and affects the reaction outcome. The geometric phase has been known about since the 1950s, but due to the femtosecond timescales involved, it has never been directly observed in a molecular system.

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Kevin Slagle, Quantum 7, 1113 (2023). Although tensor networks are powerful tools for simulating low-dimensional quantum physics, tensor network algorithms are very computationally costly in higher spatial dimensions. We introduce $\textit{quantum gauge networks}$: a different kind of tensor network ansatz for which the computation cost of simulations does not explicitly increase for larger spatial dimensions. We take inspiration from the gauge picture of quantum dynamics, which consists of a local wavefunction for each patch of space, with neighboring patches related by unitary connections. A quantum gauge network (QGN) has a similar structure, except the Hilbert space dimensions of the local wavefunctions and connections are truncated. We describe how a QGN can be obtained from a generic wavefunction or matrix product state (MPS). All $2k$-point correlation functions of any wavefunction for $M$ many operators can be encoded exactly by a QGN with bond dimension $O(M^k)$. In comparison, for just $k=1$, an exponentially larger bond dimension of $2^{M/6}$ is generically required for an MPS of qubits. We provide a simple QGN algorithm for approximate simulations of quantum dynamics in any spatial dimension. The approximate dynamics can achieve exact energy conservation for time-independent Hamiltonians, and spatial symmetries can also be maintained exactly. We benchmark the algorithm by simulating the quantum quench of fermionic Hamiltonians in up to three spatial dimensions.

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A new record time for quantum coherence is reported, with a single-photon qubit encoded for 34 milliseconds. This is 55% longer than the previous record set in 2020.

In classical computing – such as the PC, smartphone, or other device you are currently using – information is processed with bits, which exist in a binary state of either a 0 or a 1. Quantum computing, by contrast, involves the processing of information with quantum bits, or qubits, which can exist in a “superposition” of both 0 and 1 simultaneously. This allows quantum computers to do certain types of calculations much faster than classical computers.

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Magnets, those everyday objects we stick to our fridges, all share a unique characteristic: they always have both a north and a south pole. Even if you tried breaking a magnet in half, the poles would not separate—you would only get two smaller dipole magnets. But what if a particle could have a single pole with a magnetic charge?

For over a century, physicists have been searching for such . A new study on the preprint server arXiv from the ATLAS collaboration at the Large Hadron Collider (LHC) places new limits on these hypothetical particles, adding new clues for the continuing search.

In 1931, physicist Paul Dirac proved that the existence of magnetic monopoles would be consistent with quantum mechanics and require—as has been observed—the quantization of the electric charge. In the 1970s, magnetic monopoles were also predicted by new theories attempting to unify all the fundamental forces of nature, inspiring physicist Joseph Polchinski to claim that their existence was “one of the safest bets that one can make about physics not yet seen.” Magnetic monopoles might have been present in the but diluted to an unnoticeably tiny density during the early exponential expansion phase known as cosmic inflation.

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The Association for Computing Machinery has just put out the finalists for the Gordon Bell Prize award that will be given out at the SC23 supercomputing conference in Denver, and as you might expect, some of the biggest iron assembled in the world are driving the advanced applications that have their eyes on the prize.

The ACM warns that the final system sizes and final results of the simulations and models run are not yet completed, but we have a look at one of them because the researchers in China’s National Supercomputing Center in Wuxi actually published a paper they will formally released in November ahead of the SC23 conference. That paper, Towards Exascale Computation for Turbomachinery Flows, was run on the “Oceanlite” supercomputing system, which we first wrote about way back in February 2021, that won a Gorden Bell prize in November 2021 for a quantum simulation across 41.9 million cores, and that we speculated the configuration of back in March 2022 when Alibaba Group, Tsinghua University, DAMO Academy, Zhejiang Lab, and Beijing Academy of Artificial Intelligence ran a pretrained machine learning model called BaGuaLu, across more than 37 million cores and 14.5 trillion parameters in the Oceanlite machine.

NASA tossed down a grand challenge nearly a decade ago to do a time-dependent simulation of a complete jet engine, with aerodynamic and heat transfer simulated, and the Wuxi team, with the help of engineering researchers at a number of universities in China, the United States, m and the United Kingdom have picked up the gauntlet. What we found interesting about the paper is that it confirmed many of our speculations about the Oceanlite machine.

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Any physical object, alive or inanimate, is composed of atoms and subatomic particles that interact in different ways governed by the principles of quantum mechanics. Some particles are in a pure state—they remain fixed and unchanged. Others are in a quantum state—a concept that can be difficult to understand because it involves having a particle occupy multiple states simultaneously. For instance, an electron in a pure state spins up or down; in a quantum state, also referred to as superposition, it spins up and down simultaneously. Another quantum principle states that particles can be in a state of entanglement in which changes in one directly affect the other. The principles of superposition and entanglement are fundamental to quantum computing.

Quantum bits, or qubits, are the smallest units of data that a quantum computer can process and store. In a pure state, qubits have a value of 1 or 0, similar to the bits used in computing today. In superposition, they can be both of these values simultaneously, and that enables parallel computations on a massive scale. While classical computers must conduct a new calculation any time a variable changes, quantum computers can explore a problem with many possible variables simultaneously.

Existing computers, although sufficient for many applications, can’t fully support all of the changes required to create a connected and intelligent-mobility ecosystem. Quantum computing (QC) could potentially provide faster and better solutions by leveraging the principles of quantum mechanics—the rules that govern how atoms and subatomic particles act and interact. (See sidebar, “Principles of quantum computing,” for more information). Over the short term, QC may be most applicable to solving complex problems involving small data sets; as its performance improves, QC will be applied to extremely large datasets.

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