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Category: quantum physics – Page 718

Theorists attribute the unexpectedly slow thermalization of cold atoms seen in recent experiments to an effect called quantum many-body scarring.

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Researchers still have some way to go before they can assemble enough quantum bits (qubits) to make a practical, large-scale quantum computer. But already the best prototypes, made up of several tens of qubits, are opening our eyes to new behavior in the quantum realm. Last year, a team from Harvard University and the Massachusetts Institute of Technology (MIT) unveiled a quantum “simulator” made up of a row of 51 interacting atoms [1]. Exciting the individual atoms in various patterns (Fig. 1), they discovered something unexpected: atoms in certain patterns took at least 10 times longer to relax towards thermal equilibrium than atoms in other patterns. Four groups of theorists have tried to make sense of this observation [2–6], in all cases attributing the slow thermalization to a never-before-seen effect called quantum many-body scarring.

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Over the past few years, thermoelectric generators have become the focus of a growing number of studies, due to their ability to convert waste heat into electrical energy. Quantum dots, semiconductor crystals with distinctive conductive properties, could be good candidates for thermoelectric generation, as their discrete resonant levels provide excellent energy filters.

In a recent study, researchers at the University of Cambridge, in collaboration with colleagues in Madrid, Rochester, Duisburg and Sheffield, have experimentally demonstrated the potential of an autonomous nanoscale harvester based on resonant tunneling quantum dots. This harvester is based on previous research carried out by part of their team, who had proposed a three-terminal energy harvester based on two resonant-tunneling quantum dots with different energy levels.

The energy harvester device was realized at Cavendish Laboratory in Cambridge by a researcher called Gulzat Jaliel. The original theoretical proposal for the device, however, was introduced by Andrew Jordan in 2013, and the theoretical work behind the harvester was carried out by him in collaboration with renowned semiconductor physicist Markus Büttiker and a team of post-doctoral students in Geneva.

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Quantum mechanics and the general theory of relativity form the bedrock of the current understanding of physics—yet the two theories don’t seem to work together. Physical phenomena rely on relationship of motion between the observed and the observer. Certain rules hold true across types of observed objects and those observing, but those rules tend to break down at the quantum level, where subatomic particles behave in strange ways.

An international team of researchers developed a unified framework that would account for this apparent break down between classical and , and they put it to the test using a quantum satellite called Micius. They published their results ruling out one version of their theory on Sept 19th in Science.

Micius is part of a Chinese research project called Quantum Experiments at Space Scale (QUESS), in which researchers can examine the relationship with quantum and classical physics using light experiments. In this study, the researchers used the satellite to produce and measure two entangled particles.

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Wave function represents the quantum state of an atom, including the position and movement states of the nucleus and electrons. For decades researchers have struggled to determine the exact wave function when analyzing a normal chemical molecule system, which has its nuclear position fixed and electrons spinning. Fixing wave function has proven problematic even with help from the Schrödinger equation.

Previous research in this field used a Slater-Jastrow Ansatz application of quantum Monte Carlo (QMC) methods, which takes a linear combination of Slater determinants and adds the Jastrow multiplicative term to capture the close-range correlations.

Now, a group of DeepMind researchers have brought QMC to a higher level with the Fermionic Neural Network — or Fermi Net — a neural network with more flexibility and higher accuracy. Fermi Net takes the electron information of the molecules or chemical systems as inputs and outputs their estimated wave functions, which can then be used to determine the energy states of the input chemical systems.

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This could make zero point energy teleportation for spaceships for near I instant object transfer.

Scientific American is the essential guide to the most awe-inspiring advances in science and technology, explaining how they change our understanding of the world and shape our lives.

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The previously “impossible to solve” problems for some of the biggest financial, technological and academic institutions will soon be solved in Poughkeepsie.

That’s according to IBM, which announced the opening of its first Quantum Computing Center on Wednesday, based on its Poughkeepsie campus.

Quantum computing is “nothing short of a revolution for how we are going to process information,” Director of IBM Research Dario Gil said. While computers have traditionally processed binary code — a collection of ones and zeroes — quantum computers, he said, process information in qubits, or quantum bits.

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IBM continues to push its quantum computing efforts forward and today announced that it will soon make a 53-qubit quantum computer available to clients of its IBM Q Network. The new system, which is scheduled to go online in the middle of next month, will be the largest universal quantum computer available for external use yet.

The new machine will be part of IBM’s new Quantum Computation Center in New York State, which the company also announced today. The new center, which is essentially a data center for IBM’s quantum machines, will also feature five 20-qubit machines, but that number will grow to 14 within the next month. IBM promises a 95 percent service availability for its quantum machines.

IBM notes that the new 53-qubit system introduces a number of new techniques that enable the company to launch larger, more reliable systems for cloud deployments. It features more compact custom electronics for improves scaling and lower error rates, as well as a new processor design.

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(Phys.org)—Light behaves both as a particle and as a wave. Since the days of Einstein, scientists have been trying to directly observe both of these aspects of light at the same time. Now, scientists at EPFL have succeeded in capturing the first-ever snapshot of this dual behavior.

Quantum mechanics tells us that can behave simultaneously as a particle or a wave. However, there has never been an experiment able to capture both natures of light at the same time; the closest we have come is seeing either wave or particle, but always at different times. Taking a radically different experimental approach, EPFL scientists have now been able to take the first ever snapshot of light behaving both as a wave and as a particle. The breakthrough work is published in Nature Communications.

When UV light hits a metal surface, it causes an emission of . Albert Einstein explained this “photoelectric” effect by proposing that light – thought to only be a wave – is also a stream of particles. Even though a variety of experiments have successfully observed both the particle- and wave-like behaviors of light, they have never been able to observe both at the same time.

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A model based on Brownian motion describes the tsunami-like propagation of chaotic behavior in a system of quantum particles.

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In daily life, “chaos” describes anything messy. In physics, the term has a more specific meaning: It refers to systems that, while subject to deterministic laws, are totally unpredictable because of an exponential sensitivity to initial conditions—think of the butterfly flapping its wings and causing a distant tornado. But how does the chaos observed in the classical, macroscopic world emerge from the quantum-mechanical laws that govern the microscopic world? A recently proposed explanation invokes quantum “information scrambling” [1, 3], in which information gets rapidly dispersed into quantum correlations among the particles of a system. This scrambling is a memory-loss mechanism that can cause the unpredictability of chaos. Developing a theory that fully describes information scrambling remains, however, a daunting task.

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