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Physicists at the University of Innsbruck are proposing a new model that could demonstrate the supremacy of quantum computers over classical supercomputers in solving optimization problems. In a recent paper, they demonstrate that just a few quantum particles would be sufficient to solve the mathematically difficult N-queens problem in chess even for large chess boards.

Even in the strange world of open quantum systems, the arrow of time points steadily forward—most of the time. New experiments conducted at Washington University in St. Louis compare the forward and reverse trajectories of superconducting circuits called qubits, and find that they follow the second law of thermodynamics. The research is published July 9 in the journal Physical Review Letters.

“When you look at a quantum system, the act of measuring usually changes the way it behaves,” said Kater Murch, associate professor of physics in Arts & Sciences. “Imagine shining light on a small particle. The photons end up pushing it around and there is a dynamic associated with the measurement process alone.

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The quantum computing revolution is upon us.

Establish a foundation of knowledge for understanding quantum computing with this two-course online program. Starts October 7th, 2019.

If scientists could find a way to control the process for making semiconductor components on a nanometric scale, they could give those components unique electronic and optical properties—opening the door to a host of useful applications.

Researchers at the Laboratory of Microsystems, in EPFL’s School of Engineering, have taken an important step towards that goal with their discovery of semiconducting nanotubes that assemble automatically in solutions of metallic nanocrystals and certain ligands. The tubes have between three and six walls that are perfectly uniform and just a few atoms thick—making them the first such nanostructures of their kind.

What’s more, the nanotubes possess photoluminescent properties: they can absorb light of a specific wavelength and then send out intense light waves of a different color, much like quantum dots and quantum wells. That means they can be used as fluorescent markers in medical research, for example, or as catalysts in photoreduction reactions, as evidenced by the removal of the colors of some organic dyes, based on the results of initial experiments. The researchers’ findings have made the cover of ACS Central Science.

Honeywell Quantum Solutions has demonstrated record-breaking high fidelity quantum operations on their trapped-ion qubits. It is a major step towards producing the world’s most powerful quantum computer. Honeywell targets an operational trapped ion quantum computer by the end of 2019.

Currently the leading trapped ion quantum computer is by the startup IonQ. There are commercial quantum annealing systems from D-Wave Systems with 2000 qubits. There are superconducting quantum computers with 16–72 qubits from Google, IBM, Intel and Rigetti Systems.

https://youtube.com/watch?v=hyx6tBTk1p0

We know that the rule “nothing lasts forever” holds true for everything. But the world of quantum particles doesn’t always seem to follow the rules.

In the latest findings, scientists have observed that quasiparticles in quantum systems could be virtually immortal. These particles can regenerate themselves after they have decayed — and this can have a significant impact on the future of quantum computing and humanity itself.

Continue reading “Quantum Particles Found Exhibiting Immortality Through ‘Infinite Decay And Rebirth’” »

In the summer of 1935, the physicists Albert Einstein and Erwin Schrödinger engaged in a rich, multifaceted and sometimes fretful correspondence about the implications of the new theory of quantum mechanics.

The focus of their worry was what Schrödinger later dubbed entanglement: the inability to describe two quantum systems or particles independently, after they have interacted.

Until his death, Einstein remained convinced that entanglement showed how quantum mechanics was incomplete. Schrödinger thought that entanglement was the defining feature of the new physics, but this didn’t mean that he accepted it lightly.

It’s difficult to simulate quantum physics, as the computing demand grows exponentially the more complex the quantum system gets — even a supercomputer might not be enough. AI might come to the rescue, though. Researchers have developed a computational method that uses neural networks to simulate quantum systems of “considerable” size, no matter what the geometry. To put it relatively simply, the team combines familiar methods of studying quantum systems (such as Monte Carlo random sampling) with a neural network that can simultaneously represent many quantum states.

The Born rule, which connects the math of quantum theory to the outcomes of experiments, has been derived from simpler physical principles. The new work promises to give researchers a better grip on the core mystery of quantum mechanics.