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  • richardmitnick 12:28 pm on February 24, 2021 Permalink | Reply
    Tags: "Lack of symmetry in qubits can’t fix errors in quantum computing but might explain matter/antimatter imbalance", A new way to separate isotopes, , Hobbled by decoherence, Kibble-Zurek theory, Phase transition, Quantum annealing computers, , The adiabatic theorem   

    From DOE’s Los Alamos National Laboratory(US): “Lack of symmetry in qubits can’t fix errors in quantum computing but might explain matter/antimatter imbalance” 

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    From DOE’s Los Alamos National Laboratory(US)

    February 22, 2021

    A new paper seeking to cure a time restriction in quantum annealing computers instead opened up a class of new physics problems that can now be studied with quantum annealers without requiring they be too slow.

    A team of quantum theorists seeking to cure a basic problem with quantum annealing computers—they have to run at a relatively slow pace to operate properly—found something intriguing instead. While probing how quantum annealers perform when operated faster than desired, the team unexpectedly discovered a new effect that may account for the imbalanced distribution of matter and antimatter in the universe and a novel approach to separating isotopes.

    “Although our discovery did not cure the annealing time restriction, it brought a class of new physics problems that can now be studied with quantum annealers without requiring they be too slow,” said Nikolai Sinitsyn, a theoretical physicist at Los Alamos National Laboratory. Sinitsyn is author of the paper published Feb. 19 in Physical Review Letters, with coauthors Bin Yan and Wojciech Zurek, both also of Los Alamos, and Vladimir Chernyak of Wayne State University(US).

    Significantly, this finding hints at how at least two famous scientific problems may be resolved in the future. The first one is the apparent asymmetry between matter and antimatter in the universe.

    “We believe that small modifications to recent experiments with quantum annealing of interacting qubits made of ultracold atoms across phase transitions will be sufficient to demonstrate our effect,” Sinitsyn said.

    Explaining the matter/antimatter discrepancy

    Both matter and antimatter resulted from the energy excitations that were produced at the birth of the universe. The symmetry between how matter and antimatter interact was broken but very weakly. It is still not completely clear how this subtle difference could lead to the large observed domination of matter compared to antimatter at the cosmological scale.

    The newly discovered effect demonstrates that such an asymmetry is physically possible. It happens when a large quantum system passes through a phase transition, that is, a very sharp rearrangement of quantum state. In such circumstances, strong but symmetric interactions roughly compensate each other. Then subtle, lingering differences can play the decisive role.

    Making quantum annealers slow enough

    Quantum annealing computers are built to solve complex optimization problems by associating variables with quantum states or qubits. Unlike a classical computer’s binary bits, which can only be in a state, or value, of 0 or 1, qubits can be in a quantum superposition of in-between values. That’s where all quantum computers derive their awesome, if still largely unexploited, powers.

    In a quantum annealing computer, the qubits are initially prepared in a simple lowest energy state by applying a strong external magnetic field. This field is then slowly switched off, while the interactions between the qubits are slowly switched on.

    “Ideally an annealer runs slow enough to run with minimal errors, but because of decoherence, one has to run the annealer faster,” Yan explained. The team studied the emerging effect when the annealers are operated at a faster speed, which limits them to a finite operation time.)

    “According to the adiabatic theorem in quantum mechanics, if all changes are very slow, so-called adiabatically slow, then the qubits must always remain in their lowest energy state,” Sinitsyn said. “Hence, when we finally measure them, we find the desired configuration of 0s and 1s that minimizes the function of interest, which would be impossible to get with a modern classical computer.”

    Hobbled by decoherence

    However, currently available quantum annealers, like all quantum computers so far, are hobbled by their qubits’ interactions with the surrounding environment, which causes decoherence. Those interactions restrict the purely quantum behavior of qubits to about one millionth of a second. In that timeframe, computations have to be fast—nonadiabatic—and unwanted energy excitations alter the quantum state, introducing inevitable computational mistakes.

    The Kibble-Zurek theory, co-developed by Wojciech Zurek, predicts that the most errors occur when the qubits encounter a phase transition, that is, a very sharp rearrangement of their collective quantum state.

    For this paper, the team studied a known solvable model where identical qubits interact only with their neighbors along a chain; the model verifies the Kibble-Zurek theory analytically. In the theorists’ quest to cure limited operation time in quantum annealing computers, they increased the complexity of that model by assuming that the qubits could be partitioned into two groups with identical interactions within each group but slightly different interactions for qubits from the different groups.

    In such a mixture, they discovered an unusual effect: One group still produced a large amount of energy excitations during the passage through a phase transition, but the other group remained in the energy minimum as if the system did not experience a phase transition at all.

    “The model we used is highly symmetric in order to be solvable, and we found a way to extend the model, breaking this symmetry and still solving it,” Sinitsyn explained. “Then we found that the Kibble-Zurek theory survived but with a twist—half of the qubits did not dissipate energy and behaved ‘nicely.’ In other words, they maintained their ground states.”

    Unfortunately, the other half of the qubits did produce many computational errors—thus, no cure so far for a passage through a phase transition in quantum annealing computers.

    A new way to separate isotopes

    Another long-standing problem that can benefit from this effect is isotope separation. For instance, natural uranium often must be separated into the enriched and depleted isotopes, so the enriched uranium can be used for nuclear power or national security purposes. The current separation process is costly and energy intensive. The discovered effect means that by making a mixture of interacting ultra-cold atoms pass dynamically through a quantum phase transition, different isotopes can be selectively excited or not and then separated using available magnetic deflection technique.

    The funding: This work was carried out under the support of the U.S. Department of Energy, Office of Science, Basic Energy Sciences, Materials Sciences and Engineering Division, Condensed Matter Theory Program. Bin Yan also acknowledges support from the Center for Nonlinear Studies at LANL.

    See the full article here .


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    DOE’s Los Alamos National Laboratory(US) mission is to solve national security challenges through scientific excellence.

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    DOE’sLos Alamos National Laboratory(US), a multidisciplinary research institution engaged in strategic science on behalf of national security, is operated by Los Alamos National Security, LLC, a team composed of Bechtel National, the University of California, The Babcock & Wilcox Company, and URS for the Department of Energy’s National Nuclear Security Administration.
    Los Alamos enhances national security by ensuring the safety and reliability of the U.S. nuclear stockpile, developing technologies to reduce threats from weapons of mass destruction, and solving problems related to energy, environment, infrastructure, health, and global security concerns.

    Operated by Los Alamos National Security, LLC for the U.S. Dept. of Energy’s NNSA

  • richardmitnick 11:57 am on November 8, 2017 Permalink | Reply
    Tags: At higher temperature snapshots at different times show the moments pointing in different random directions, , Magnetic moments, , , , Phase transition, , Rules of attraction   

    From ORNL OLCF via D.O.E.: “Rules of attraction” 


    Oak Ridge National Laboratory


    November 8, 2017
    No writer credit

    A depiction of magnetic moments obtained using the hybrid WL-LSMS modeling technique inside nickel (Ni) as the temperature is increased from left to right. At low temperature (left), Ni atoms in their magnetic moments all point in one direction and align. At higher temperature (right) snapshots at different times show the moments pointing in different, random directions, and the individual atoms no longer perfectly align. Image courtesy of Oak Ridge National Laboratory.

    The atoms inside materials are not always perfectly ordered, as usually depicted in models. In magnetic, ferroelectric (or showing electric polarity) and alloy materials, there is competition between random arrangement of the atoms and their desire to align in a perfect pattern. The change between these two states, called a phase transition, happens at a specific temperature.

    Markus Eisenbach, a computational scientist at the Department of Energy’s Oak Ridge National Laboratory, heads a group of researchers who’ve set out to model the behavior of these materials using first principles – from fundamental physics without preset conditions that fit external data.

    “We’re just scratching the surface of comprehending the underlying physics of these three classes of materials, but we have an excellent start,” Eisenbach says. “The three are actually overlapping in that their modes of operation involve disorder, thermal excitations and resulting phase transitions – from disorder to order – to express their behavior.”

    Eisenbach says he’s fascinated by “how magnetism appears and then disappears at varying temperatures. Controlling magnetism from one direction to another has implications for magnetic recording, for instance, and all sorts of electric machines – for example, motors in automobiles or generators in wind turbines.”

    The researchers’ models also could help find strong, versatile magnets that don’t use rare earth elements as an ingredient. Located at the bottom of the periodic table, these 17 materials come almost exclusively from China and, because of their limited source, are considered critical. They are a mainstay in the composition of many strong magnets.

    Eisenbach and his collaborators, which includes his ORNL team and Yang Wang with the Pittsburgh Supercomputing Center, are in the second year of a DOE INCITE (Innovative and Novel Computational Impact on Theory and Experiment) award to model all three materials at the atomic level. They’ve been awarded 100 million processor hours on ORNL’s Titan supercomputer and already have impressive results in magnetics and alloys. Titan is housed at the Oak Ridge Leadership Computing Facility (OLCF), a DOE Office of Science user facility.

    The researchers tease out atomic-scale behavior using, at times, a hybrid code that combines Wang-Landau (WL) Monte Carlo and locally self-consistent multiple scattering (LSMS) methods. WL is a statistical approach that samples the atomic energy landscape in terms of finite temperature effects; LSMS determines energy value. With LSMS alone, they’ve calculated the ground state magnetic properties of an iron-platinum particle. And without making any assumption beyond the chemical composition, they’ve determined the temperature at which copper-zinc alloy goes from a disordered state to an ordered one.

    Moreover, Eisenbach has co-authored two materials science papers in the past year, one in Leadership Computing, the other a letter in Nature, in which he and colleagues reported using the three-dimensional coordinates of a real iron-platinum nanoparticle with 6,560 iron and 16,627 platinum atoms to find its magnetic properties.

    “We’re combining the efficiency of WL sampling, the speed of the LSMS and the computing power of Titan to provide a solid first-principles thermodynamics description of magnetism,” Eisenbach says. “The combination also is giving us a realistic treatment of alloys and functional materials.”

    Alloys are comprised of at least two metals. Brass, for instance, is an alloy of copper and zinc. Magnets, of course, are used in everything from credit cards to MRI machines and in electric motors. Ferroelectric materials, such as barium titanate and zirconium titanate, form what’s known as an electric moment, in a transition phase, when temperatures drop beneath the ferroelectric Curie temperature – the point where atoms align, triggering spontaneous magnetism. The term – named after the French physicist Pierre Curie, who in the late 19th century described how magnetic materials respond to temperature changes – applies to both ferroelectric and ferromagnetic transitions. Eisenbach and his collaborators are interested in both phenomena.

    Eisenbach is particularly intrigued by high-entropy alloys, a relatively new sub-class discovered a decade ago that may hold useful mechanical properties. Conventional alloys have a dominant element – for instance, iron in stainless steel. High-entropy alloys, on the other hand, evenly spread out their elements on a crystal lattice. They don’t get brittle when chilled, remaining pliable at extremely low temperatures.

    To understand the configuration of high-entropy alloys, Eisenbach uses the analogy of a chess board sprinkled with black and white beads. In an ordered material, black beads occupy black squares and white beads, white squares. In high-entropy alloys, however, the beads are scattered randomly across the lattice regardless of color until the material reaches a low temperature, much lower than normal alloys, when it almost grudgingly orders itself.

    Eisenbach and his colleagues have modelled a material as large as 100,000 atoms using the Wang-Landau/LSMS method. “If I want to represent disorder, I want a simulation that calculates for hundreds if not thousands of atoms, rather than just two or three,” he says.

    To model an alloy, the researchers first deploy the Schrodinger equation to determine the state of electrons in the atoms. “Solving the equation lets you understand the electrons and their interactions, which is the glue that holds the material together and determines their physical properties.”

    All of a material’s properties and energies are calculated by many hundreds of thousands of calculations over many possible configurations and over varying temperatures to give a rendering so that modelers can determine at what temperature a material loses or gains its magnetism, or at what temperature an alloy goes from a disordered state to a perfectly ordered one.

    Eisenbach eagerly awaits the arrival of the Summit supercomputer – five to six times more powerful than Titan – to OLCF in late 2018.

    Two views of Summit-

    ORNL IBM Summit Supercomputer

    ORNL IBM Summit supercomputer depiction

    “Ultimately, we can do larger simulations and possibly look at even more complex disordered materials with more components and widely varying compositions, where the chemical disorder might lead to qualitatively new physical behaviors.”

    See the full article here .

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    ORNL is managed by UT-Battelle for the Department of Energy’s Office of Science. DOE’s Office of Science is the single largest supporter of basic research in the physical sciences in the United States, and is working to address some of the most pressing challenges of our time.


    The Oak Ridge Leadership Computing Facility (OLCF) was established at Oak Ridge National Laboratory in 2004 with the mission of accelerating scientific discovery and engineering progress by providing outstanding computing and data management resources to high-priority research and development projects.

    ORNL’s supercomputing program has grown from humble beginnings to deliver some of the most powerful systems in the world. On the way, it has helped researchers deliver practical breakthroughs and new scientific knowledge in climate, materials, nuclear science, and a wide range of other disciplines.

    The OLCF delivered on that original promise in 2008, when its Cray XT “Jaguar” system ran the first scientific applications to exceed 1,000 trillion calculations a second (1 petaflop). Since then, the OLCF has continued to expand the limits of computing power, unveiling Titan in 2013, which is capable of 27 petaflops.

    ORNL Cray XK7 Titan Supercomputer

    Titan is one of the first hybrid architecture systems—a combination of graphics processing units (GPUs), and the more conventional central processing units (CPUs) that have served as number crunchers in computers for decades. The parallel structure of GPUs makes them uniquely suited to process an enormous number of simple computations quickly, while CPUs are capable of tackling more sophisticated computational algorithms. The complimentary combination of CPUs and GPUs allow Titan to reach its peak performance.

    The OLCF gives the world’s most advanced computational researchers an opportunity to tackle problems that would be unthinkable on other systems. The facility welcomes investigators from universities, government agencies, and industry who are prepared to perform breakthrough research in climate, materials, alternative energy sources and energy storage, chemistry, nuclear physics, astrophysics, quantum mechanics, and the gamut of scientific inquiry. Because it is a unique resource, the OLCF focuses on the most ambitious research projects—projects that provide important new knowledge or enable important new technologies.

  • richardmitnick 2:56 pm on July 15, 2017 Permalink | Reply
    Tags: , Gorsky effect, Gorsky-Bragg-Williams approximation, He (Gorsky) was promptly executed, Landau wrote to the military prosecutor “Gorsky was one of the brightest theoreticians in x-ray crystallography and 20 years later we still have no equivalent to him.", Lev Landau, Phase transition, , , Vadim Gorsky   

    From Physics Today: “Vadim Gorsky, a forgotten physics pioneer” 

    Physics Today bloc

    Physics Today

    13 Jul 2017
    Olivier Hardouin Duparc, École Polytechnique in Palaiseau, France
    Alexander Krajnikov, Mational Academy of Sciences of Ukraine in Kiev

    The brilliant Soviet physicist was executed by Stalin’s secret police after resigning in protest over the dismissal of a prominent colleague.

    Vadim Gorsky is at right in this photograph of staff at the Leningrad Physics and Technology Institute. Ivan Obreimov, who ran the lab at which Gorsky worked, is at center; George Gamow is seated next to him. Credit: Peter Kapitza Memorial Museum

    Joseph Stalin’s “Great Terror” cost the lives of many innocent people, including physicists. One often overlooked victim is Vadim Sergeevich Gorsky, who in 1937 was arrested and subsequently executed by Stalin’s People’s Commissariat for Internal Affairs, or the NKVD. Gorsky was a pioneer in the field of phase transition who laid the foundation for the Gorsky-Bragg-Williams approximation. He also proposed what’s now known as the Gorsky effect to describe diffusion under stress.

    Gorsky (or Gorskiĭ, according to the rather arbitrary transliteration of Вадим Горский) was born on 1 May 1905 in Gatchina, 45 km south of St Petersburg, which was renamed Petrograd in 1914 and Leningrad in 1924. In 1922 Gorsky began working in a lab run by Ivan Obreimov at Petrograd’s Polytechnic Institute (later renamed the Leningrad Physics and Technology Institute). Six years later Gorsky published a paper in German on an x-ray investigation of transformations in a copper–gold alloy. It is there that the atomic mean-field analysis of order–disorder transformation in metallic alloys appeared for the first time. In the approximation, the potential energy of an individual atom is assumed to depend only on the average degree of chemical order throughout the entire system, rather than on the actual chemical configuration of its neighboring atoms. Statistical thermal analysis is then applied to estimate the evolution of the average degree of chemical order as a function of temperature. Gorsky only considered the CuAu stoichiometry with equal atomic concentration; Lawrence Bragg and Evan James Williams broadened the scope in 1934–35, and the Gorsky-Bragg-Williams approximation was born. Bragg and Williams recognized Gorsky’s 1928 paper in 1935 but claimed that “the formula he obtains is incorrect.” That statement was rebutted in 1939 by Ralph Fowler and Edward Guggenheim, who in their book Statistical Thermodynamics wrote of the “approximation of Gorsky, and of Bragg and Williams.”

    In 1930 Gorsky was appointed to lead x-ray structure analysis at a new physics and technology institute that was established in Kharkov, Ukraine, under the lead of Obreimov. Lev Shubnikov (profiled in Physics Today, December 1997, page 95) became head of the cryogenics department. Gorsky produced three more papers on the structure of ordered and partially ordered CuAu solid solutions. In 1935 he published a theory regarding disordered solid solutions that’s now known as the Gorsky effect. The phenomenon is best illustrated using Gorsky’s own words: “Let us consider a substitutional solid solution of two kinds of atoms with different atomic radii. If we bend such a crystal, it is very natural that the large atoms will diffuse into the stretched layers, and the small atoms into the compressed layers until an equilibrium implying a concentration gradient is reached.”

    The Kharkov institute’s theoretical-physics department was led by Lev Landau, who along with many of his colleagues also taught at Kharkov State University. A first-rank theoretician, Landau was also a very good professor—his colleagues called him “The Teacher” (see the article by I. M. Khalatnikov, Physics Today, May 1989, page 34). But he was uncompromising with his students when it came to grading them. Some of them complained, and in late 1936, the chancellor of the university asked Landau to lower his grading standards. When Landau refused, he was “invited” to resign his professorship. Within the next two days, some of Landau’s colleagues, Gorsky among them, wrote applications for termination of their own contracts in solidarity.

    The Soviet government, which had put a lot of money into the creation of the institute in Kharkov, immediately triggered repressions against those requesting termination. Several people from the institute were arrested, including Obreimov, Shubnikov, and Gorsky. Two of the arrested scientists agreed to present evidence that Landau was an unnecessarily tough professor, but Gorsky did not. He was promptly executed. He might have been shot on 8 November 1937, according to official documents released decades later, but there are rumors that he was killed later while being tortured in prison. He was 32 years old. No burial site is known. Shubnikov was shot very soon after Gorsky, as were Lev Rosenkevich and others. Obreimov was imprisoned but released in 1941.

    Landau ended up moving to Moscow, where he was invited by Peter Kapitza to be head of the theoretical-physics department at the Institute for Physical Problems. The case of the NKVD against Gorsky, Shubnikov, and Rosenkevich was dismissed in 1956, during Nikita Khrushchev’s de-Stalinization of the Soviet Union. Landau wrote to the military prosecutor, “Gorsky was one of the brightest theoreticians in x-ray crystallography, and 20 years later we still have no equivalent to him.”

    See the full article here .

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