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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.

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.

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 crystal structure that is very common in nature. A crystal’s structure determines many of its physical properties, 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 quantum properties 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.

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

Continue reading “DARPA Launches Project CHARIOT in Bid to Shield Big Tech Profits” »

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 new algorithm 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 computer 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.”

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 chemical processes 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 chemical system—in this particular case, a diazene molecule undergoing a reaction with hydrogen atoms, resulting in an altered configuration.

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.

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).

🤔 “The White House today detailed the establishment of 12 new research institutes focused on AI and quantum information science. Agencies including the National Science Foundation (NSF), U.S. Department of Homeland Security, and U.S. Department of Energy (DOE) have committed to investing tens of millions of dollars in centers intended to serve as nodes for AI and quantum computing study.

Laments over the AI talent shortage in the U.S. have become a familiar refrain. While higher education enrollment in AI-relevant fields like computer science has risen rapidly in recent years, few colleges have been able to meet student demand due to a lack of staffing. In June, the Trump administration imposed a ban on U.S. entry for workers on certain visas — including for high-skilled H-1B visa holders, an estimated 35% of whom have an AI-related degree — through the end of the year. And Trump has toyed with the idea of suspending the Optional Practical Training program, which allows international students to work for up to three years in the U.S.”

The White House announced the creation of AI and quantum research institutes funded by billions in venture and taxpayer dollars.

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