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Category: quantum physics – Page 563

Among all the curious states of matter that can coexist in a quantum material, jostling for preeminence as temperature, electron density and other factors change, some scientists think a particularly weird juxtaposition exists at a single intersection of factors, called the quantum critical point or QCP.

“Quantum critical points are a very hot issue and interesting for many problems,” says Wei-Sheng Lee, a staff scientist at the Department of Energy’s SLAC National Accelerator Laboratory and investigator with the Stanford Institute for Materials and Energy Sciences (SIMES). “Some suggest that they’re even analogous to black holes in the sense that they are singularities—point-like intersections between different states of matter in a quantum material—where you can get all sorts of very strange electron behavior as you approach them.”

Lee and his collaborators reported in Nature Physics today that they have found strong evidence that QCPs and their associated fluctuations exist. They used a technique called resonant inelastic X-ray scattering (RIXS) to probe the electronic behavior of a copper oxide material, or cuprate, that conducts electricity with perfect efficiency at relatively high temperatures.

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If a tree falls in a forest and no one is there to hear it, does it make a sound? Perhaps not, some say.

And if someone is there to hear it? If you think that means it obviously did make a sound, you might need to revise that opinion.

We have found a new paradox in quantum mechanics – one of our two most fundamental scientific theories, together with Einstein’s theory of relativity – that throws doubt on some common-sense ideas about physical reality.

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The White House on Wednesday will announce that federal agencies and their private sector partners are committing more than $1 billion over the next five years to establish 12 new research institutes focused on artificial intelligence and quantum information sciences.

The effort is designed to ensure the U.S. remains globally competitive in AI and quantum technologies, administration officials said.

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Physicists’ latest achievement with neutral atoms paves the way for new quantum computer designs.

In the quest to develop quantum computers, physicists have taken several different paths. For instance, Google recently reported that their prototype quantum computer might have made a specific calculation faster than a classical computer. Those efforts relied on a strategy that involves superconducting materials, which are materials that, when chilled to ultracold temperatures, conduct electricity with zero resistance. Other quantum computing strategies involve arrays of charged or neutral atoms.

Now, a team of quantum physicists at Caltech has made strides in work that uses a more complex class of neutral atoms called the alkaline-earth atoms, which reside in the second column of the periodic table. These atoms, which include magnesium, calcium, and strontium, have two electrons in their outer regions, or shells. Previously, researchers who experimented with neutral atoms had focused on elements located in the first column of the periodic table, which have just one electron in their outer shells.

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The quantum properties underlying crystal formation can be replicated and investigated with the help of ultracold atoms. A team led by Dr. Axel U. J. Lode from the University of Freiburg’s Institute of Physics has now described in the journal Physical Review Letters how the use of dipolar atoms enables even the realization and precise measurement of structures that have not yet been observed in any material. The theoretical study was a collaboration involving scientists from the University of Freiburg, the University of Vienna and the Technical University of Vienna in Austria, and the Indian Institute of Technology in Kanpur, India.

Crystals are ubiquitous in nature. They are formed by many different materials—from mineral salts to heavy metals like bismuth. Their structures emerge because a particular regular ordering of atoms or molecules is favorable, because it requires the smallest amount of energy. A cube with one constituent on each of its eight corners, for instance, is a that is very common in nature. A crystal’s determines many of its , such as how well it conducts a current or heat or how it cracks and behaves when it is illuminated by light. But what determines these crystal structures? They emerge as a consequence of the of and the interactions between their constituents, which, however, are often scientifically hard to understand and also hard measure.

To nevertheless get to the bottom of the quantum properties of the formation of crystal structures, scientists can simulate the process using Bose-Einstein condensates—trapped ultracold atoms cooled down to temperatures close to absolute zero or minus 273.15 degrees Celsius. The atoms in these highly artificial and highly fragile systems are extremely well under control.

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DARPA announces a new type of cryptography to protect the Big Tech firm profits from the dawn of quantum computers and allow backdoor access into 3 trillion internet-connected devices.

by Raul Diego

The U.S. Military-Industrial complex is sprinting on a chariot to shore up the encryption space before the next era of computation upends the entire digital edifice built on semiconductors and transistors. But, the core of the effort is protecting markets for Big Tech and all of its tentacles, which stand to lose years or even decades of profits should the new tech be rolled out too quickly.

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Recent advancements in quantum computing have driven the scientific community’s quest to solve a certain class of complex problems for which quantum computers would be better suited than traditional supercomputers. To improve the efficiency with which quantum computers can solve these problems, scientists are investigating the use of artificial intelligence approaches.

In a new study, scientists at the U.S. Department of Energy’s (DOE) Argonne National Laboratory have developed a based on reinforcement learning to find the optimal parameters for the Quantum Approximate Optimization Algorithm (QAOA), which allows a quantum computer to solve certain combinatorial problems such as those that arise in materials design, chemistry and wireless communications.

“Combinatorial optimization problems are those for which the solution space gets exponentially larger as you expand the number of decision variables,” said Argonne scientist Prasanna Balaprakash. “In one traditional example, you can find the shortest route for a salesman who needs to visit a few cities once by enumerating all possible routes, but given a couple thousand cities, the number of possible routes far exceeds the number of stars in the universe; even the fastest supercomputers cannot find the shortest route in a reasonable time.”

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A team of researchers with Google’s AI Quantum team (working with unspecified collaborators) has conducted the largest chemical simulation on a quantum computer to date. In their paper published in the journal Science, the group describes their work and why they believe it was a step forward in quantum computing. Xiao Yuan of Stanford University has written a Perspective piece outlining the potential benefits of quantum computer use to conduct chemical simulations and the work by the team at AI Quantum, published in the same journal issue.

Developing an ability to predict by simulating them on computers would be of great benefit to chemists—currently, they do most of it through trial and error. Prediction would open up the door to the development of a wide range of new materials with still unknown properties. Sadly, current computers lack the exponential scaling that would be required for such work. Because of that, chemists have been hoping quantum computers will one day step in to take on the role.

Current quantum computer technology is not yet ready to take on such a challenge, of course, but computer scientists are hoping to get them there sometime in the near future. In the meantime, big companies like Google are investing in research geared toward using quantum computers once they mature. In this new effort, the team at AI Quantum focused their efforts on simulating a simple chemical process—the Hartree-Fock approximation of a real system—in this particular case, a diazene molecule undergoing a reaction with hydrogen atoms, resulting in an altered configuration.

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Accurate computational prediction of chemical processes from the quantum mechanical laws that govern them is a tool that can unlock new frontiers in chemistry, improving a wide variety of industries. Unfortunately, the exact solution of quantum chemical equations for all but the smallest systems remains out of reach for modern classical computers, due to the exponential scaling in the number and statistics of quantum variables. However, by using a quantum computer, which by its very nature takes advantage of unique quantum mechanical properties to handle calculations intractable to its classical counterpart, simulations of complex chemical processes can be achieved. While today’s quantum computers are powerful enough for a clear computational advantage at some tasks, it is an open question whether such devices can be used to accelerate our current quantum chemistry simulation techniques.

In “Hartree-Fock on a Superconducting Qubit Quantum Computer”, appearing today in Science, the Google AI Quantum team explores this complex question by performing the largest chemical simulation performed on a quantum computer to date. In our experiment, we used a noise-robust variational quantum eigensolver (VQE) to directly simulate a chemical mechanism via a quantum algorithm. Though the calculation focused on the Hartree-Fock approximation of a real chemical system, it was twice as large as previous chemistry calculations on a quantum computer, and contained ten times as many quantum gate operations. Importantly, we validate that algorithms being developed for currently available quantum computers can achieve the precision required for experimental predictions, revealing pathways towards realistic simulations of quantum chemical systems.

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Berkeley Lab-led center to catalyze U.S. leadership in quantum information science, and strengthen the nation’s research community to accelerate commercialization.

The Department of Energy (DOE) has awarded $115 million over five years to the Quantum Systems Accelerator (QSA), a new research center led by Lawrence Berkeley National Laboratory (Berkeley Lab) that will forge the technological solutions needed to harness quantum information science for discoveries that benefit the world. It will also energize the nation’s research community to ensure U.S. leadership in quantum R&D and accelerate the transfer of quantum technologies from the lab to the marketplace. Sandia National Laboratories is the lead partner of the center.

Total planned funding for the center is $115 million over five years, with $15 million in Fiscal Year 2020 dollars and outyear funding contingent on congressional appropriations. The center is one of five new Department of Energy Quantum Information Science (QIS) Research Centers announced today (August 26, 2020).

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