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  • richardmitnick 9:08 am on July 29, 2020 Permalink | Reply
    Tags: "A method to predict the properties of complex quantum systems", , , Machines are currently unable to support quantum systems with over tens of qubits., , Quantum Physics, Quantum state tomography, Unitary t-design   

    From Caltech via phys.org: “A method to predict the properties of complex quantum systems” 

    Caltech Logo

    From Caltech

    via


    phys.org

    July 29, 2020
    Ingrid Fadelli

    1
    Credit: Huang, Kueng & Preskill.

    Predicting the properties of complex quantum systems is a crucial step in the development of advanced quantum technologies. While research teams worldwide have already devised a number of techniques to study the characteristics of quantum systems, most of these have only proved to be effective in some cases.

    Three researchers at California Institute of Technology recently introduced a new method that can be used to predict multiple properties of complex quantum systems from a limited number of measurements. Their method, outlined in a paper published in Nature Physics, has been found to be highly efficient and could open up new possibilities for studying the ways in which machines process quantum information.

    “During my undergraduate, my research centered on statistical machine learning and deep learning,” Hsin-Yuan Huang, one of the researchers who carried out the study, told Phys.org. “A central basis for the current machine-learning era is the ability to use highly parallelized hardware, such as graphical processing units (GPU) or tensor processing units (TPU). It is natural to wonder how an even more powerful learning machine capable of harnessing quantum-mechanical processes could emerge in the far future. This was my aspiration when I started my Ph.D. at Caltech.”

    The first step toward the development of more advanced machines based on quantum-mechanical processes is to gain a better understanding of how current technologies process and manipulate quantum systems and quantum information. The standard method for doing this, known as quantum state tomography, works by learning the entire description of a quantum system. However, this requires an exponential number of measurements, as well as considerable computational memory and time.

    As a result, when using quantum state tomography, machines are currently unable to support quantum systems with over tens of qubits. In recent years, researchers have proposed a number of techniques based on artificial neural networks that could significantly enhance the quantum information processing of machines. Unfortunately, however, these techniques do not generalize well across all cases, and the specific requirements that allow them to work are still unclear.

    “To build a rigorous foundation for how machines can perceive quantum systems, we combined my previous knowledge about statistical learning theory with Richard Kueng and John Preskill’s expertise on a beautiful mathematical theory known as unitary t-design,” Huang said. “Statistical learning theory is the theory that underlies how the machine could learn an approximate model about how the world behaves, while unitary t-design is a mathematical theory that underlies how quantum information scrambles, which is central to understand quantum many-body chaos, in particular, quantum black holes.”

    By combining statistical learning and unitary t-design theory, the researchers were able to devise a rigorous and efficient procedure that allows classical machines to produce approximate classical descriptions of quantum many-body systems. These descriptions can be used to predict several properties of the quantum systems that are being studied by performing a minimal number of quantum measurements.

    “To construct an approximate classical description of the quantum state, we perform a randomized measurement procedure given as follows,” Huang said. “We sample a few random quantum evolutions that would be applied to the unknown quantum many-body system. These random quantum evolutions are typically chaotic and would scramble the quantum information stored in the quantum system.”

    The random quantum evolutions sampled by the researchers ultimately enable the use of the mathematical theory of unitary t-design to study such chaotic quantum systems as quantum black holes. In addition, Huang and his colleagues examined a number of randomly scrambled quantum systems using a measurement tool that elicits a wave function collapse, a process that turns a quantum system into a classical system. Finally, they combined the random quantum evolutions with the classical system representations derived from their measurements, producing an approximate classical description of the quantum system of interest.

    “Intuitively, one could think of this procedure as follows,” Huang explained. “We have an exponentially high-dimensional object, the quantum many-body system, that is very hard to grasp by a classical machine. We perform several random projections of this extremely high-dimension object to a much lower dimensional space through the use of random/chaotic quantum evolution. The set of random projections provides a rough picture of how this exponentially high dimensional object looks, and the classical representation allows us to predict various properties of the quantum many-body system.”

    Huang and his colleagues proved that by combining statistical learning constructs and the theory of quantum information scrambling, they could accurately predict M properties of a quantum system based solely on log(M) measurements. In other words, their method can predict an exponential number of properties simply by repeatedly measuring specific aspects of a quantum system for a specific number of times.

    “The traditional understanding is that when we want to measure M properties, we have to measure the quantum system M times,” Huang said. “This is because after we measure one property of the quantum system, the quantum system would collapse and become classical. After the quantum system has turned classical, we cannot measure other properties with the resulting classical system. Our approach avoids this by performing randomly generated measurements and infer the desired property by combining these measurement data.”

    The study partly explains the excellent performance achieved by recently developed machine learning (ML) techniques in predicting properties of quantum systems. In addition, its unique design makes the method they developed significantly faster than existing ML techniques, while also allowing it to predict properties of quantum many-body systems with a greater accuracy.

    “Our study rigorously shows that there is much more information hidden in the data obtained from quantum measurements than we originally expected,” Huang said. “By suitably combining these data, we can infer this hidden information and gain significantly more knowledge about the quantum system. This implies the importance of data science techniques for the development of quantum technology.”

    The results of tests the team conducted suggest that to leverage the power of machine learning, it is first necessary to attain a good understanding of intrinsic quantum physics mechanisms. Huang and his colleagues showed that although directly applying standard machine-learning techniques can lead to satisfactory results, organically combining the mathematics behind machine learning and quantum physics results in far better quantum information processing performance.

    “Given a rigorous ground for perceiving quantum systems with classical machines, my personal plan is to now take the next step toward creating a learning machine capable of manipulating and harnessing quantum-mechanical processes,” Huang said. “In particular, we want to provide a solid understanding of how machines could learn to solve quantum many-body problems, such as classifying quantum phases of matter or finding quantum many-body ground states.”

    This new method for constructing classical representations of quantum systems could open up new possibilities for the use of machine learning to solve challenging problems involving quantum many-body systems. To tackle these problems more efficiently, however, machines would also need to be able to simulate a number of complex computations, which would require a further synthesis between the mathematics underlying machine learning and quantum physics. In their next studies, Huang and his colleagues plan to explore new techniques that could enable this synthesis.

    “At the same time, we are also working on refining and developing new tools for inferring hidden information from the data collected by quantum experimentalists,” Huang said. “The physical limitation in the actual systems provides interesting challenges for developing more advanced techniques. This would further allow experimentalists to see what they originally could not and help advance the current state of quantum technology.”

    See the full article here .


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    The California Institute of Technology (commonly referred to as Caltech) is a private research university located in Pasadena, California, United States. Caltech has six academic divisions with strong emphases on science and engineering. Its 124-acre (50 ha) primary campus is located approximately 11 mi (18 km) northeast of downtown Los Angeles. “The mission of the California Institute of Technology is to expand human knowledge and benefit society through research integrated with education. We investigate the most challenging, fundamental problems in science and technology in a singularly collegial, interdisciplinary atmosphere, while educating outstanding students to become creative members of society.”

    Caltech campus

     
  • richardmitnick 1:05 pm on July 23, 2020 Permalink | Reply
    Tags: , Computational Quantum Physics, , , Flatiron Institute, In the quantum mechanical world electrical resistance is a byproduct of electrons bumping into things., Links to astrophysics, , , Quantum Monte Carlo algorithm, Quantum Physics, , Strange metals are related to high-temperature superconductors and have surprising connections to the properties of black holes.,   

    From Simons Foundation: “Quantum physicists crack mystery of ‘strange metals,’ a new state of matter” 

    From Simons Foundation

    July 23, 2020
    Thomas Sumner

    Strange metals have surprising connections to high-temperature superconductors and black holes.

    1
    A diagram showing different states of matter as a function of temperature, T, and interaction strength, U (normalized to the amplitude, t, of electrons hopping between sites). Strange metals emerge in a regime separating a metallic spin glass and a Fermi liquid. P. Cha et al./Proceedings of the National Academy of Sciences 2020.

    Even by the standards of quantum physicists, strange metals are just plain odd. The materials are related to high-temperature superconductors and have surprising connections to the properties of black holes. Electrons in strange metals dissipate energy as fast as they’re allowed to under the laws of quantum mechanics, and the electrical resistivity of a strange metal, unlike that of ordinary metals, is proportional to the temperature.

    Generating a theoretical understanding of strange metals is one of the biggest challenges in condensed matter physics. Now, using cutting-edge computational techniques, researchers from the Flatiron Institute in New York City and Cornell University have solved the first robust theoretical model of strange metals. The work reveals that strange metals are a new state of matter, the researchers report July 22 in the Proceedings of the National Academy of Sciences.

    “The fact that we call them strange metals should tell you how well we understand them,” says study co-author Olivier Parcollet, a senior research scientist at the Flatiron Institute’s Center for Computational Quantum Physics (CCQ). “Strange metals share remarkable properties with black holes, opening exciting new directions for theoretical physics.”

    In addition to Parcollet, the research team consisted of Cornell doctoral student Peter Cha, CCQ associate data scientist Nils Wentzell, CCQ director Antoine Georges, and Cornell physics professor Eun-Ah Kim.

    In the quantum mechanical world, electrical resistance is a byproduct of electrons bumping into things. As electrons flow through a metal, they bounce off other electrons or impurities in the metal. The more time there is between these collisions, the lower the material’s electrical resistance.

    For typical metals, electrical resistance increases with temperature, following a complex equation. But in unusual cases, such as when a high-temperature superconductor is heated just above the point where it stops superconducting, the equation becomes much more straightforward. In a strange metal, electrical conductivity is linked directly to temperature and to two fundamental constants of the universe: Planck’s constant and Boltzmann’s constant. Consequently, strange metals are also known as Planckian metals.

    Models of strange metals have existed for decades, but accurately solving such models proved out of reach with existing methods. Quantum entanglements between electrons mean that physicists can’t treat the electrons individually, and the sheer number of particles in a material makes the calculations even more daunting.

    Cha and his colleagues employed two different methods to crack the problem. First, they used a quantum embedding method based on ideas developed by Georges in the early ’90s. With this method, instead of performing detailed computations across the whole quantum system, physicists perform detailed calculations on only a few atoms and treat the rest of the system more simply. They then used a quantum Monte Carlo algorithm (named for the Mediterranean casino), which uses random sampling to compute the answer to a problem. The researchers solved the model of strange metals down to absolute zero (minus 273.15 degrees Celsius), the unreachable lower limit for temperatures in the universe.

    The resulting theoretical model reveals the existence of strange metals as a new state of matter bordering two previously known phases of matter: Mott insulating spin glasses and Fermi liquids. “We found there is a whole region in the phase space that is exhibiting a Planckian behavior that belongs to neither of the two phases that we’re transitioning between,” Kim says. “This quantum spin liquid state is not so locked down, but it’s also not completely free. It is a sluggish, soupy, slushy state. It is metallic but reluctantly metallic, and it’s pushing the degree of chaos to the limit of quantum mechanics.”

    The new work could help physicists better understand the physics of higher-temperature superconductors. Perhaps surprisingly, the work has links to astrophysics. Like strange metals, black holes exhibit properties that depend only on temperature and the Planck and Boltzmann constants, such as the amount of time a black hole ‘rings’ after merging with another black hole. “The fact that you find this same scaling across all these different systems, from Planckian metals to black holes, is fascinating,” Parcollet says.

    For more information, please contact Stacey Greenebaum at press@simonsfoundation.org.

    See the full article here.

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    Mission and Model

    The Simons Foundation’s mission is to advance the frontiers of research in mathematics and the basic sciences.

    Co-founded in New York City by Jim and Marilyn Simons, the foundation exists to support basic — or discovery-driven — scientific research undertaken in the pursuit of understanding the phenomena of our world.

    The Simons Foundation’s support of science takes two forms: We support research by making grants to individual investigators and their projects through academic institutions, and, with the launch of the Flatiron Institute in 2016, we now conduct scientific research in-house, supporting teams of top computational scientists.

     
  • richardmitnick 11:15 am on April 16, 2020 Permalink | Reply
    Tags: "New quantum computers can operate at higher temperatures", Current quantum computers top out at around 50 quantum bits but scientists expect quantum computers will need millions of these qubits to perform some tasks. So scientists are working to scale them up, Quantum Physics, , Silicon chips raise hopes for scaling up devices to millions of quantum bits., Warmer quantum computers are made with silicon.   

    From Science News: “New quantum computers can operate at higher temperatures” 

    From Science News

    April 15, 2020
    Emily Conover

    Silicon chips raise hopes for scaling up devices to millions of quantum bits.

    1
    Quantum computers are warming up. Researchers from QuTech work on a silicon-based quantum computer that operates at higher temperatures than most other types. Credit: Wouterslitsfotografie for QuTech.

    Computers that harness quantum physics could trump standard computers on certain types of calculations. But the machines typically work only at temperatures tiny fractions of a degree above absolute zero. Now, two teams of physicists report that they’ve created silicon-based quantum computers that work under warmer conditions.

    The devices operate more than a degree above absolute zero, the scientists report in two papers published in the April 16 Nature: [ https://www.nature.com/articles/s41586-020-2171-6 ] and [ https://www.nature.com/articles/s41586-020-2170-7 ]. Although still chilly, that temperature is much easier to achieve than the approximately 10 millikelvin (0.01 degrees above absolute zero) temperatures typical of a popular type of quantum computer based on superconductors, materials which transmit electricity without resistance.

    Current quantum computers top out at around 50 quantum bits, but scientists expect quantum computers will need millions of these qubits to perform some tasks. So scientists are working to scale them up.

    Simplifying the cooling process could help the computers grow. That’s because extremely cold quantum computers have an additional complication. The electronic components required to control the qubits don’t work under such chilly conditions, and need to be kept in a warmer location and connected to the quantum chip with wiring. That wiring would become unreasonably complex as quantum computers scale up. But with quantum computers that operate at these warmer temperatures, the qubits and electronics could be joined together, akin to the integrated circuits that helped make conventional computers increasingly powerful and ubiquitous.

    Created by teams including researchers from the University of New South Wales in Australia and QuTech in Delft, the Netherlands, the warmer quantum computers are made with silicon. That material is used in standard computer chips, so manufacturers are already skilled with it (SN: 2/14/18). That could also speed quantum computers’ scale-up.

    See the full article here .


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  • richardmitnick 9:57 am on March 8, 2020 Permalink | Reply
    Tags: "A Computer Science Proof Holds Answers for Math and Physics", , , , Game Show Physics, Quantum Physics, The commuting operator model of entanglement, The computer researchers: Henry Yuen the University of Toronto a; Zhengfeng Ji the University of Technology Sydney; Anand Natarajan and Thomas Vidick Caltech; John Wright the University of Texas, The Connes embedding conjecture, The correspondence between entanglement and computing came as a jolt to many researchers., The problems that can be verified through interactions with entangled quantum provers called MIP* equals the class of problems no harder than the halting problem a class called RE. “MIP*=RE.”, The tensor product model,   

    From WIRED: “A Computer Science Proof Holds Answers for Math and Physics” 


    From WIRED

    03.08.2020
    Kevin Hartnett

    An advance in our understanding of quantum computing offers stunning solutions to problems that have long puzzled mathematicians and physicists.

    In 1935, Albert Einstein, working with Boris Podolsky and Nathan Rosen, grappled with a possibility revealed by the new laws of quantum physics: that two particles could be entangled, or correlated, even across vast distances.

    The very next year, Alan Turing formulated the first general theory of computing and proved that there exists a problem that computers will never be able to solve.

    These two ideas revolutionized their respective disciplines. They also seemed to have nothing to do with each other. But now a landmark proof has combined them while solving a raft of open problems in computer science, physics, and mathematics.

    The new proof establishes that quantum computers that calculate with entangled quantum bits or qubits, rather than classical 1s and 0s, can theoretically be used to verify answers to an incredibly vast set of problems. The correspondence between entanglement and computing came as a jolt to many researchers.

    “It was a complete surprise,” said Miguel Navascués, who studies quantum physics at the Institute for Quantum Optics and Quantum Information in Vienna.

    The proof’s co-authors set out to determine the limits of an approach to verifying answers to computational problems. That approach involves entanglement. By finding that limit the researchers ended up settling two other questions almost as a byproduct: Tsirelson’s problem in physics, about how to mathematically model entanglement, and a related problem in pure mathematics called the Connes embedding conjecture.

    In the end, the results cascaded like dominoes.

    “The ideas all came from the same time. It’s neat that they come back together again in this dramatic way,” said Henry Yuen of the University of Toronto and an author of the proof, along with Zhengfeng Ji of the University of Technology Sydney, Anand Natarajan and Thomas Vidick of the California Institute of Technology, and John Wright of the University of Texas, Austin. The five researchers are all computer scientists.

    Undecidable Problems

    Turing defined a basic framework for thinking about computation before computers really existed. In nearly the same breath, he showed that there was a certain problem computers were provably incapable of addressing. It has to do with whether a program ever stops.

    Typically, computer programs receive inputs and produce outputs. But sometimes they get stuck in infinite loops and spin their wheels forever. When that happens at home, there’s only one thing left to do.

    “You have to manually kill the program. Just cut it off,” Yuen said.

    Turing proved that there’s no all-purpose algorithm that can determine whether a computer program will halt or run forever. You have to run the program to find out.

    1
    The computer scientists Henry Yuen, Thomas Vidick, Zhengfeng Ji, Anand Natarajan and John Wright co-authored a proof about verifying answers to computational problems and ended up solving major problems in math and quantum physics.Courtesy of (Yuen) Andrea Lao; (Vidick) Courtesy of Caltech; (Ji) Anna Zhu; (Natarajan) David Sella; (Wright) Soya Park.

    “You’ve waited a million years and a program hasn’t halted. Do you just need to wait 2 million years? There’s no way of telling,” said William Slofstra, a mathematician at the University of Waterloo.

    In technical terms, Turing proved that this halting problem is undecidable — even the most powerful computer imaginable couldn’t solve it.

    After Turing, computer scientists began to classify other problems by their difficulty. Harder problems require more computational resources to solve — more running time, more memory. This is the study of computational complexity.

    Ultimately, every problem presents two big questions: “How hard is it to solve?” and “How hard is it to verify that an answer is correct?”

    Interrogate to Verify

    When problems are relatively simple, you can check the answer yourself. But when they get more complicated, even checking an answer can be an overwhelming task. However, in 1985 computer scientists realized it’s possible to develop confidence that an answer is correct even when you can’t confirm it yourself.

    The method follows the logic of a police interrogation.

    If a suspect tells an elaborate story, maybe you can’t go out into the world to confirm every detail. But by asking the right questions, you can catch your suspect in a lie or develop confidence that the story checks out.

    In computer science terms, the two parties in an interrogation are a powerful computer that proposes a solution to a problem—known as the prover—and a less powerful computer that wants to ask the prover questions to determine whether the answer is correct. This second computer is called the verifier.

    To take a simple example, imagine you’re colorblind and someone else—the prover—claims two marbles are different colors. You can’t check this claim by yourself, but through clever interrogation you can still determine whether it’s true.

    Put the two marbles behind your back and mix them up. Then ask the prover to tell you which is which. If they really are different colors, the prover should answer the question correctly every time. If the marbles are actually the same color—meaning they look identical—the prover will guess wrong half the time.

    “If I see you succeed a lot more than half the time, I’m pretty sure they’re not” the same color, Vidick said.

    By asking a prover questions, you can verify solutions to a wider class of problems than you can on your own.

    In 1988, computer scientists considered what happens when two provers propose solutions to the same problem. After all, if you have two suspects to interrogate, it’s even easier to solve a crime, or verify a solution, since you can play them against each other.

    “It gives more leverage to the verifier. You interrogate, ask related questions, cross-check the answers,” Vidick said. If the suspects are telling the truth, their responses should align most of the time. If they’re lying, the answers will conflict more often.

    Similarly, researchers showed that by interrogating two provers separately about their answers, you can quickly verify solutions to an even larger class of problems than you can when you only have one prover to interrogate.

    Computational complexity may seem entirely theoretical, but it’s also closely connected to the real world. The resources that computers need to solve and verify problems—time and memory—are fundamentally physical. For this reason, new discoveries in physics can change computational complexity.

    “If you choose a different set of physics, like quantum rather than classical, you get a different complexity theory out of it,” Natarajan said.

    The new proof is the end result of 21st-century computer scientists confronting one of the strangest ideas of 20th-century physics: entanglement.

    The Connes Embedding Conjecture

    When two particles are entangled, they don’t actually affect each other—they have no causal relationship. Einstein and his co-authors elaborated on this idea in their 1935 paper. Afterward, physicists and mathematicians tried to come up with a mathematical way of describing what entanglement really meant.

    Yet the effort came out a little muddled. Scientists came up with two different mathematical models for entanglement—and it wasn’t clear that they were equivalent to each other.

    In a roundabout way, this potential dissonance ended up producing an important problem in pure mathematics called the Connes embedding conjecture. Eventually, it also served as a fissure that the five computer scientists took advantage of in their new proof.

    The first way of modeling entanglement was to think of the particles as spatially isolated from each other. One is on Earth, say, and the other is on Mars; the distance between them is what prevents causality. This is called the tensor product model.

    But in some situations, it’s not entirely obvious when two things are causally separate from each other. So mathematicians came up with a second, more general way of describing causal independence.

    When the order in which you perform two operations doesn’t affect the outcome, the operations “commute”: 3 x 2 is the same as 2 x 3. In this second model, particles are entangled when their properties are correlated but the order in which you perform your measurements doesn’t matter: Measure particle A to predict the momentum of particle B or vice versa. Either way, you get the same answer. This is called the commuting operator model of entanglement.

    Both descriptions of entanglement use arrays of numbers organized into rows and columns called matrices. The tensor product model uses matrices with a finite number of rows and columns. The commuting operator model uses a more general object that functions like a matrix with an infinite number of rows and columns.

    Over time, mathematicians began to study these matrices as objects of interest in their own right, completely apart from any connection to the physical world. As part of this work, a mathematician named Alain Connes conjectured in 1976 that it should be possible to approximate many infinite-dimensional matrices with finite-dimensional ones. This is one implication of the Connes embedding conjecture.

    The following decade a physicist named Boris Tsirelson posed a version of the problem that grounded it in physics once more. Tsirelson conjectured that the tensor product and commuting operator models of entanglement were roughly equivalent. This makes sense, since they’re theoretically two different ways of describing the same physical phenomenon. Subsequent work showed that because of the connection between matrices and the physical models that use them, the Connes embedding conjecture and Tsirelson’s problem imply each other: Solve one, and you solve the other.

    Yet the solution to both problems ended up coming from a third place altogether.

    Game Show Physics

    In the 1960s, a physicist named John Bell came up with a test for determining whether entanglement was a real physical phenomenon, rather than just a theoretical notion. The test involved a kind of game whose outcome reveals whether something more than ordinary, non-quantum physics is at work.

    Computer scientists would later realize that this test about entanglement could also be used as a tool for verifying answers to very complicated problems.

    But first, to see how the games work, let’s imagine two players, Alice and Bob, and a 3-by-3 grid. A referee assigns Alice a row and tells her to enter a 0 or a 1 in each box so that the digits sum to an odd number. Bob gets a column and has to fill it out so that it sums to an even number. They win if they put the same number in the one place her row and his column overlap. They’re not allowed to communicate.

    Under normal circumstances, the best they can do is win 89% of the time. But under quantum circumstances, they can do better.

    Imagine Alice and Bob split a pair of entangled particles. They perform measurements on their respective particles and use the results to dictate whether to write 1 or 0 in each box. Because the particles are entangled, the results of their measurements are going to be correlated, which means their answers will correlate as well — meaning they can win the game 100% of the time.

    2
    Illustration: Lucy Reading-Ikkanda/Quanta Magazine

    So if you see two players winning the game at unexpectedly high rates, you can conclude that they are using something other than classical physics to their advantage. Such Bell-type experiments are now called “nonlocal” games, in reference to the separation between the players. Physicists actually perform them in laboratories.

    “People have run experiments over the years that really show this spooky thing is real,” said Yuen.

    As when analyzing any game, you might want to know how often players can win a nonlocal game, provided they play the best they can. For example, with solitaire, you can calculate how often someone playing perfectly is likely to win.

    But in 2016, William Slofstra proved that there’s no general algorithm for calculating the exact maximum winning probability for all nonlocal games. So researchers wondered: Could you at least approximate the maximum-winning percentage?

    Computer scientists have homed in on an answer using the two models describing entanglement. An algorithm that uses the tensor product model establishes a floor, or minimum value, on the approximate maximum-winning probability for all nonlocal games. Another algorithm, which uses the commuting operator model, establishes a ceiling.

    These algorithms produce more precise answers the longer they run. If Tsirelson’s prediction is true, and the two models really are equivalent, the floor and the ceiling should keep pinching closer together, narrowing in on a single value for the approximate maximum-winning percentage.

    But if Tsirelson’s prediction is false, and the two models are not equivalent, “the ceiling and the floor will forever stay separated,” Yuen said. There will be no way to calculate even an approximate winning percentage for nonlocal games.

    In their new work, the five researchers used this question — about whether the ceiling and floor converge and Tsirelson’s problem is true or false — to solve a separate question about when it’s possible to verify the answer to a computational problem.

    Entangled Assistance

    In the early 2000s, computer scientists began to wonder: How does it change the range of problems you can verify if you interrogate two provers that share entangled particles?

    Most assumed that entanglement worked against verification. After all, two suspects would have an easier time telling a consistent lie if they had some means of coordinating their answers.

    But over the last few years, computer scientists have realized that the opposite is true: By interrogating provers that share entangled particles, you can verify a much larger class of problems than you can without entanglement.

    “Entanglement is a way to generate correlations that you think might help them lie or cheat,” Vidick said. “But in fact you can use that to your advantage.”

    To understand how, you first need to grasp the almost otherworldly scale of the problems whose solutions you could verify through this interactive procedure.

    Imagine a graph—a collection of dots (vertices) connected by lines (edges). You might want to know whether it’s possible to color the vertices using three colors, so that no vertices connected by an edge have the same color. If you can, the graph is “three-colorable.”

    If you hand a pair of entangled provers a very large graph, and they report back that it can be three-colored, you’ll wonder: Is there a way to verify their answer?

    For very big graphs, it would be impossible to check the work directly. So instead, you could ask each prover to tell you the color of one of two connected vertices. If they each report a different color, and they keep doing so every time you ask, you’ll gain confidence that the three-coloring really works.

    But even this interrogation strategy fails as graphs get really big—with more edges and vertices than there are atoms in the universe. Even the task of stating a specific question (“Tell me the color of XYZ vertex”) is more than you, the verifier, can manage: The amount of data required to name a specific vertex is more than you can hold in your working memory.

    But entanglement makes it possible for the provers to come up with the questions themselves.

    “The verifier doesn’t have to compute the questions. The verifier forces the provers to compute the questions for them,” Wright said.

    The verifier wants the provers to report the colors of connected vertices. If the vertices aren’t connected, then the answers to the questions won’t say anything about whether the graph is three-colored. In other words, the verifier wants the provers to ask correlated questions: One prover asks about vertex ABC and the other asks about vertex XYZ. The hope is that the two vertices are connected to each other, even though neither prover knows which vertex the other is thinking about. (Just as Alice and Bob hope to fill in the same number in the same square even though neither knows which row or column the other has been asked about.)

    If two provers were coming up with these questions completely on their own, there’d be no way to force them to select connected, or correlated, vertices in a way that would allow the verifier to validate their answers. But such correlation is exactly what entanglement enables.

    “We’re going to use entanglement to offload almost everything onto the provers. We make them select questions by themselves,” Vidick said.

    At the end of this procedure, the provers each report a color. The verifier checks whether they’re the same or not. If the graph really is three-colorable, the provers should never report the same color.

    “If there is a three-coloring, the provers will be able to convince you there is one,” Yuen said.

    As it turns out, this verification procedure is another example of a nonlocal game. The provers “win” if they convince you their solution is correct.

    In 2012, Vidick and Tsuyoshi Ito proved that it’s possible to play a wide variety of nonlocal games with entangled provers to verify answers to at least the same number of problems you can verify by interrogating two classical computers. That is, using entangled provers doesn’t work against verification. And last year, Natarajan and Wright proved that interacting with entangled provers actually expands the class of problems that can be verified.

    But computer scientists didn’t know the full range of problems that can be verified in this way. Until now.

    A Cascade of Consequences

    In their new paper, the five computer scientists prove that interrogating entangled provers makes it possible to verify answers to unsolvable problems, including the halting problem.

    “The verification capability of this type of model is really mind-boggling,” Yuen said.

    But the halting problem can’t be solved. And that fact is the spark that sets the final proof in motion.

    Imagine you hand a program to a pair of entangled provers. You ask them to tell you whether it will halt. You’re prepared to verify their answer through a kind of nonlocal game: The provers generate questions and “win” based on the coordination between their answers.

    If the program does in fact halt, the provers should be able to win this game 100 percent of the time—similar to how if a graph is actually three-colorable, entangled provers should never report the same color for two connected vertices. If it doesn’t halt, the provers should only win by chance—50 percent of the time.

    That means if someone asks you to determine the approximate maximum-winning probability for a specific instance of this nonlocal game, you will first need to solve the halting problem. And solving the halting problem is impossible. Which means that calculating the approximate maximum-winning probability for nonlocal games is undecidable, just like the halting problem.

    This in turn means that the answer to Tsirelson’s problem is no—the two models of entanglement are not equivalent. Because if they were, you could pinch the floor and the ceiling together to calculate an approximate maximum-winning probability.

    “There cannot be such an algorithm, so the two [models] must be different,” said David Pérez-García of the Complutense University of Madrid.

    The new paper proves that the class of problems that can be verified through interactions with entangled quantum provers, a class called MIP*, is exactly equal to the class of problems that are no harder than the halting problem, a class called RE. The title of the paper states it succinctly: “MIP* = RE.”

    In the course of proving that the two complexity classes are equal, the computer scientists proved that Tsirelson’s problem is false, which, due to previous work, meant that the Connes embedding conjecture is also false.

    For researchers in these fields, it was stunning that answers to such big problems would fall out from a seemingly unrelated proof in computer science.

    “If I see a paper that says MIP* = RE, I don’t think it has anything to do with my work,” said Navascués, who co-authored previous work tying Tsirelson’s problem and the Connes embedding conjecture together. “For me it was a complete surprise.”

    Quantum physicists and mathematicians are just beginning to digest the proof. Prior to the new work, mathematicians had wondered whether they could get away with approximating infinite-dimensional matrices by using large finite-dimensional ones instead. Now, because the Connes embedding conjecture is false, they know they can’t.

    “Their result implies that’s impossible,” said Slofstra.

    The computer scientists themselves did not aim to answer the Connes embedding conjecture, and as a result, they’re not in the best position to explain the implications of one of the problems they ended up solving.

    “Personally, I’m not a mathematician. I don’t understand the original formulation of the Connes embedding conjecture well,” said Natarajan.

    He and his co-authors anticipate that mathematicians will translate this new result into the language of their own field. In a blog post announcing the proof, Vidick wrote, “I don’t doubt that eventually complexity theory will not be needed to obtain the purely mathematical consequences.”

    Yet as other researchers run with the proof, the line of inquiry that prompted it is coming to a halt. For more than three decades, computer scientists have been trying to figure out just how far interactive verification will take them. They are now confronted with the answer, in the form of a long paper with a simple title and echoes of Turing.

    “There’s this long sequence of works just wondering how powerful” a verification procedure with two entangled quantum provers can be, Natarajan said. “Now we know how powerful it is. That story is at an end.”

    See the full article here .

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  • richardmitnick 5:06 pm on February 13, 2020 Permalink | Reply
    Tags: "Study uncovers new electronic state of matter", , , Quantum Physics, , We have moved into the era of research in quantum computing; quantum teleportation; quantum communications; and quantum sensing.   

    From University of Pittsburgh via phys.org: “Study uncovers new electronic state of matter” 

    U Pitt bloc

    From University of Pittsburgh

    via


    From phys.org

    2.13.20

    1
    Clumps of electrons speeding down the superconductor highway represent the the motion of the Pascal conductance series. Credit: Jeremy Levy

    A research team led by professors from the University of Pittsburgh Department of Physics and Astronomy has announced the discovery of a new electronic state of matter.

    Jeremy Levy, a distinguished professor of condensed matter physics, and Patrick Irvin, a research associate professor are coauthors of the paper Pascal conductance series in ballistic one-dimensional LaAIO3/SrTiO3 channels. The research focuses on measurements in one-dimensional conducting systems where electrons are found to travel without scattering in groups of two or more at a time, rather than individually.

    The study was published in Science on Feb. 14.

    “Normally, electrons in semiconductors or metals move and scatter, and eventually drift in one direction if you apply a voltage. But in ballistic conductors the electrons move more like cars on a highway. The advantage of that is they don’t give off heat and may be used in ways that are quite different from ordinary electronics. Researchers before us have succeeded in creating this kind of ballistic conductor,” explained Levy.

    “The discovery we made shows that when electrons can be made to attract one another, they can form bunches of two, three, four and five electrons that literally behave like new types of particles, new forms of electronic matter.”


    34:15
    11Levels: Pascal conductance series in ballistic one-dimensional LaAlO3/SrTiO3 channels

    Levy compared the finding to the way in which quarks bind together to form neutrons and protons. An important clue to uncovering the new matter was recognizing that these ballistic conductors matched a sequence within Pascal’s Triangle.

    “If you look along different directions of Pascal’s Triangle you can see different number patterns and one of the patterns was one, three, six, 10, 15, 21. This is a sequence we noticed in our data, so it became a challenging clue as to what was actually going on. The discovery took us some time to understand but it was because we initially did not realize we were looking at particles made up of one electron, two electrons, three electrons and so forth. If you combine all this together you get the sequence of 1,3,6,10.”

    Levy, who is also director of the Pittsburgh Quantum Institute, noted that the new particles feature properties related to quantum entanglement, which can potentially be used for quantum computing and quantum redistribution. He said the discovery is an exciting advancement toward the next stage of quantum physics.

    “This research falls within a larger effort here in Pittsburgh to develop new science and technologies related to the second quantum revolution,” he said.

    “In the first quantum revolution people discovered the world around them was governed fundamentally by laws of quantum physics. That discovery led to an understanding of the periodic table, how materials behave and helped in the development of transistors, computers, MRI scanners and information technology.

    “Now in the 21st century, we’re looking at all the strange predictions of quantum physics and turning them around and using them. When you talk about applications, we’re thinking about quantum computing, quantum teleportation, quantum communications, quantum sensing—ideas that use properties of the quantum nature of matter that were ignored before.”

    See the full article here .

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    About Science X in 100 words

    Science X™ is a leading web-based science, research and technology news service which covers a full range of topics. These include physics, earth science, medicine, nanotechnology, electronics, space, biology, chemistry, computer sciences, engineering, mathematics and other sciences and technologies. Launched in 2004 (Physorg.com), Science X’s readership has grown steadily to include 5 million scientists, researchers, and engineers every month. Science X publishes approximately 200 quality articles every day, offering some of the most comprehensive coverage of sci-tech developments world-wide. Science X community members enjoy access to many personalized features such as social networking, a personal home page set-up, article comments and ranking, the ability to save favorite articles, a daily newsletter, and other options.
    Mission 12 reasons for reading daily news on Science X Organization Key editors and writersinclude 1.75 million scientists, researchers, and engineers every month. Phys.org publishes approximately 100 quality articles every day, offering some of the most comprehensive coverage of sci-tech developments world-wide. Quancast 2009 includes Phys.org in its list of the Global Top 2,000 Websites. Phys.org community members enjoy access to many personalized features such as social networking, a personal home page set-up, RSS/XML feeds, article comments and ranking, the ability to save favorite articles, a daily newsletter, and other options.

    U Pitt campus

    The University of Pittsburgh is a state-related research university, founded as the Pittsburgh Academy in 1787. Pitt is a member of the Association of American Universities (AAU), which comprises 62 preeminent doctorate-granting research institutions in North America.

    From research achievements to the quality of its academic programs, the University of Pittsburgh ranks among the best in higher education.

    Faculty members have expanded knowledge in the humanities and sciences, earning such prestigious honors as the National Medal of Science, the MacArthur Foundation’s “genius” grant, the Lasker-DeBakey Clinical Medical Research Award, and election to the National Academy of Sciences and the Institute of Medicine.

    Pitt students have earned Rhodes, Goldwater, Marshall, and Truman Scholarships, among other highly competitive national and international scholarships.

    Alumni have pioneered MRI and TV, won Nobels and Pulitzers, led corporations and universities, served in government and the military, conquered Hollywood and The New York Times bestsellers list, and won Super Bowls and NBA championships.

     
  • richardmitnick 12:14 am on February 8, 2020 Permalink | Reply
    Tags: "A Quantum of Solid", , , Cooling a levitated nanoparticle to its motional quantum groundstate., , , New macroscopic quantum states involving large masses should become possible., Physicists do something very cool, , Quantum Physics, Universität Wien   

    From Universität Wien: “A Quantum of Solid” 

    From Universität Wien

    30. January 2020
    Scientific contact
    Univ.-Prof. Dr. Markus Aspelmeyer
    Quantenoptik, Quantennanophysik und Quanteninformation
    Universität Wien
    1090 – Wien, Boltzmanngasse 5
    +43-1-4277-725 31
    markus.aspelmeyer@univie.ac.at

    Dr. Uros Delic, BSc MSc
    Fakultät für Physik
    Universität Wien
    1090 – Wien, Boltzmanngasse 5
    +43-1-4277-72532
    uros.delic@univie.ac.at

    Further inquiry note
    Mag. Alexandra Frey
    Pressebüro und stv. Pressesprecherin
    Universität Wien
    1010 – Wien, Universitätsring 1
    +43-1-4277-175 33
    +43-664-60277-175 33
    alexandra.frey@univie.ac.at

    1
    Scientists from Vienna, Kahan Dare (left) and Manuel Reisenbauer (right) working on the experiment that cooled a levitated nanoparticle to its motional quantum groundstate. (© Lorenzo Magrini, Yuriy Coroli/Universität Wien)

    2
    Scientist from Vienna working on the experiment that cooled a levitated nanoparticle to its motional quantum groundstate. (© Lorenzo Magrini, Yuriy Coroli/Universität Wien)

    3
    Researchers cooled a levitated nanoparticle to the quantum groundstate for the first time. This work was made possible by the recent breakthrough application of coherent scattering in the field of cavity optomechanics. (© Lorenzo Magrini, Yuriy Coroli/Universität Wien)

    Researchers in Austria use lasers to levitate and cool a glass nanoparticle into the quantum regime. Although it is trapped in a room temperature environment, the particle’s motion is solely governed by the laws of quantum physics. The team of scientists from the Universität Wien, the Austrian Academy of Sciences and the Massachusetts Institute of Technology (MIT) published their new study in the journal Science.

    It is well known that quantum properties of individual atoms can be controlled and manipulated by laser light. Even large clouds of hundreds of millions of atoms can be pushed into the quantum regime, giving rise to macroscopic quantum states of matter such as quantum gases or Bose-Einstein condensates, which nowadays are also widely used in quantum technologies. An exciting next step is to extend this level of quantum control to solid state objects. In contrast to atomic clouds, the density of a solid is a billion times higher and all atoms are bound to move together along the object’s center of mass. In that way, new macroscopic quantum states involving large masses should become possible.

    However, entering this new regime is not at all a straightforward endeavour. A first step for achieving such quantum control is to isolate the object under investigation from influences of the environment and to remove all thermal energy – by cooling it down to temperatures very close to absolute zero (-273.15 °C) such that quantum mechanics dominates the particle’s motion. To show this the researchers chose to experiment with a glass bead approximately a thousand times smaller than a typical grain of sand and containing a few hundred million atoms. Isolation from the environment is achieved by optically trapping the particle in a tightly focused laser beam in high vacuum, a trick that was originally introduced by Nobel laureate Arthur Ashkin many decades ago and that is also used for isolating atoms. “The real challenge is for us to cool the particle motion into its quantum ground state. Laser cooling via atomic transitions is well established and a natural choice for atoms, but it does not work for solids”, says lead-author Uros Delic from the Universität Wien.

    For this reason, the team has been working on implementing a laser-cooling method that was proposed by Austrian physicist Helmut Ritsch at the University of Innsbruck and, independently, by study co-author Vladan Vuletic and Nobel laureate Steven Chu. They had recently announced a first demonstration of the working principle, “cavity cooling by coherent scattering”, however they were still limited to operating far away from the quantum regime. “We have upgraded our experiment and are now able not only to remove more background gas but also to send in more photons for cooling”, says Delic. In that way, the motion of the glass bead can be cooled straight into the quantum regime. “It is funny to think about this: the surface of our glass bead is extremely hot, around 300°C, because the laser heats up the electrons in the material. But the motion of the center of mass of the particle is ultra-cold, around 0.00001°C away from absolute zero, and we can show that the hot particle moves in a quantum way.”

    The researchers are excited about the prospects of their work. The quantum motion of solids has also been investigated by other groups all around the world, along with the Vienna team. Thus far, experimental systems were comprised of nano- and micromechanical resonators, in essence drums or diving boards that are clamped to a rigid support structure. “Optical levitation brings in much more freedom: by changing the optical trap – or even switching it off – we can manipulate the nanoparticle motion in completely new ways”, says Nikolai Kiesel, co-author and Assistant Professor at the Universität Wien. Several schemes along these lines have been proposed, amongst others by Austrian-based physicists Oriol Romero-Isart and Peter Zoller at Innsbruck, and may now become possible. For example, in combination with the newly achieved motional ground state the authors expect that this opens new opportunities for unprecedented sensing performance, the study of fundamental processes of heat engines in the quantum regime, as well as the study of quantum phenomena involving large masses. “A decade ago we started this experiment motivated by the prospect of a new category of quantum experiments. We finally have opened the door to this regime.”

    See the full article here .

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    Universität Wien Campus

    Universität Wien is a public university located in Vienna, Austria. It was founded by Duke Rudolph IV in 1365 and is the oldest university in the German-speaking world. With its long and rich history, the University of Vienna has developed into one of the largest universities in Europe, and also one of the most renowned, especially in the Humanities. It is associated with 20 Nobel prize winners and has been the academic home to many scholars of historical as well as of academic importance.

     
  • richardmitnick 1:10 pm on December 6, 2019 Permalink | Reply
    Tags: "A platform for stable quantum computing, a playground for exotic physics", , , , , Quantum Physics, Topological insulators are materials that can conduct electricity on their surface or edge but not in the middle.   

    From Harvard Gazette: “A platform for stable quantum computing, a playground for exotic physics” 

    Harvard University


    From Harvard Gazette

    December 5, 2019
    Leah Burrows

    1
    A close-up view of a quantum computer. Courtesy of Harvard SEAS

    Recent research settles a long-standing debate.

    Move over Godzilla vs. King Kong. This is the crossover event you’ve been waiting for — at least if you’re a condensed-matter physicist. Harvard University researchers have demonstrated the first material that can have both strongly correlated electron interactions and topological properties.

    Not sure what that means? Don’t worry, we’ll walk you through it. But the important thing to know is that this discovery not only paves the way for more stable quantum computing, but also creates an entirely new platform to explore the wild world of exotic physics.

    The research was published in Nature Physics.

    Let’s start with the basics. Topological insulators are materials that can conduct electricity on their surface or edge, but not in the middle. The strange thing about these materials is that no matter how you cut them, the surface will always be conducting and the middle always insulating. These materials offer a playground for fundamental physics, and are also promising for a number of applications in special types of electronics and quantum computing.

    Since the discovery of topological insulators, researchers around the world have been working to identify materials with these powerful properties.

    “A recent boom in condensed-matter physics has come from discovering materials with topologically protected properties,” said Harris Pirie, a graduate student in the Department of Physics and first author of the paper.

    One potential material, samarium hexaboride, has been at the center of a fierce debate among condensed-matter physicists for more than a decade. At issue: Is it or isn’t it a topological insulator?

    “Over the last 10 years, a bunch of papers have come out saying yes and a bunch of papers have come out saying no,” said Pirie. “The crux of the issue is that most topological materials don’t have strongly interacting electrons, meaning the electrons move too quickly to feel each other. But samarium hexaboride does, meaning that electrons inside this material slow down enough to interact strongly. In this realm, the theory gets fairly speculative and it’s been unclear whether or not it’s possible for materials with strongly interacting properties to also be topological. As experimentalists, we’ve been largely operating blind with materials like this.”

    In order to settle the debate and figure out, once and for all, whether it’s possible to have both strongly interacting and topological properties, the researchers first needed to find a well-ordered patch of samarium hexaboride surface on which to perform the experiment.

    2
    A simulation of electrons scattering off atomic defects in samarium hexaboride. By observing the waves, the researchers could figure out the momentum of the electrons in relation to their energy. Video courtesy of Harris Pirie/Harvard University

    It was no easy task, considering the majority of the material surface is a craggy, disordered mess. The researchers used ultrahigh precision measurement tools developed in the lab of Jenny Hoffman, the Clowes Professor of Science and senior author of the paper, to find a suitable, atomic-scale patch of samarium hexaboride.

    Next, the team set out to determine if the material was topologically insulating by sending waves of electrons through the material and scattering them off of atomic defects — like dropping a pebble into a pond. By observing the waves, the researchers could figure out the momentum of the electrons in relation to their energy.

    “We found that the momentum of the electrons is directly proportional to their energy, which is the smoking gun of a topological insulator,” said Pirie. “It’s really exciting to be finally moving into this intersection of interacting physics and topological physics. We don’t know what we’ll find here.”

    As it relates to quantum computing, strongly interacting topological materials may be able to protect qubits from forgetting their quantum state, a process called decoherence.

    “If we could encode the quantum information in a topologically protected state, it is less susceptible to external noise that can accidentally switch the qubit,” said Hoffman. “Microsoft already has a large team pursuing topological quantum computation in composite materials and nanostructures. Our work demonstrates a first in a single topological material that harnesses strong electron interactions that might eventually be used for topological quantum computing.”

    “The next step will be to use the combination of topologically protected quantum states and strong interactions to engineer novel quantum states of matter, such as topological superconductors,” said Dirk Morr, professor of physics at the University of Illinois, Chicago, and the senior theorist on the paper. “Their extraordinary properties could open unprecedented possibilities for the implementation of topological quantum bits.”

    This research was co-authored by Yu Liu, Anjan Soumyanarayanan, Pengcheng Chen, Yang He, M.M. Yee, P.F.S. Rosa, J.D. Thompson, Dae-Jeong Kim, Z. Fisk, Xiangfeng Wang, Johnpierre Paglione, and M.H. Hamidian.

    See the full article here .

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    Harvard University campus
    Harvard University is the oldest institution of higher education in the United States, established in 1636 by vote of the Great and General Court of the Massachusetts Bay Colony. It was named after the College’s first benefactor, the young minister John Harvard of Charlestown, who upon his death in 1638 left his library and half his estate to the institution. A statue of John Harvard stands today in front of University Hall in Harvard Yard, and is perhaps the University’s best known landmark.

    Harvard University has 12 degree-granting Schools in addition to the Radcliffe Institute for Advanced Study. The University has grown from nine students with a single master to an enrollment of more than 20,000 degree candidates including undergraduate, graduate, and professional students. There are more than 360,000 living alumni in the U.S. and over 190 other countries.

     
  • richardmitnick 9:58 am on September 25, 2019 Permalink | Reply
    Tags: , Quantum Physics, The many-worlds interpretation   

    From Curiosity: “The Many-Worlds Interpretation Says There Are Infinite Timelines and Infinite Yous” 

    Curiosity Makes You Smarter

    From From Curiosity

    April 26, 2017 [Just now in social media]
    Ashley Hamer

    1
    Curiosity

    Quantum physics is mind-bending, counterintuitive, and close to impossible to understand. It’s so complicated that a theory saying our reality is just one of an infinite web of infinite timelines is one that’s actually simpler than what most quantum physicists believe. That neat-and-tidy explanation is known as the many-worlds interpretation, and it has caused plenty of controversy in physics circles.

    Split the Difference

    In the 1950s, a student at Princeton University named Hugh Everett III was studying quantum mechanics. He learned about the Copenhagen interpretation, which says that at the very, very smallest level — what we mean when we say quantum — matter exists not just as a particle and not just as a wave, but in all possible states at once (all of those states together is called its wave function; the phenomenon of existing in all of those states at once is called superposition). It also says that when you observe a quantum object, you break that superposition and it essentially “chooses” one state to be in. He also learned about the Heisenberg Uncertainty Principle, which says that because we affect a quantum object’s behavior through observation, we can never be completely certain where it is or what it’s doing at any given time.

    Everett understood these principles, but he took issue with one part: What if, instead of a quantum object “choosing” a state when you observe it — say, it becomes a particle instead of a wave — there was an actual split in the universe that created separate timelines? According to Everett’s theory, in this timeline, the object is a particle, but there’s another timeline where it’s a wave. Even more baffling, this implies that quantum phenomena aren’t the only things that split the universe into separate timelines. For everything that happens, every action you take or decide not to take, there are infinite other timelines — worlds, if we may — where something else took place. That’s the many-worlds interpretation of quantum physics. It may not seem like it, but it’s actually simpler than the Copenhagen interpretation — it doesn’t strike an arbitrary line between the quantum world and everything else, because everything behaves in the same way. It also removes randomness from the picture, which helps the math work out nicely.

    2
    Curiosity

    Many Worlds Means Big Implications

    Not all physicists subscribe to this theory — a recent poll found that the majority are Copenhagen all the way — but a growing minority do. Sean Carroll, for one. He explains that many objections to the theory arise because people come at it from a classical physics point of view. “In classical mechanics … it’s quite a bit of work to accommodate extra universes, and you better have a good reason to justify putting in that work,” he writes. “That is not what happens in quantum mechanics. The capacity for describing multiple universes is automatically there. We don’t have to add anything.”

    If the many-worlds interpretation is true, what does this say about the nature of reality? It says there are infinite versions of you living in infinite alternate timelines. There’s a version of you that got out of bed on a different side this morning, one that ate a different breakfast, one that has differently colored hair, one that’s a different gender, one that’s a foot taller, one that’s a psychopath, one that — we can hardly stomach it! — didn’t decide to read this article. That might make you feel less than unique. On the contrary, the you that you are right now is the only you there will ever be. The moment you do anything, the universe splits and you’re a you that’s living in a different timeline than the you that didn’t take that action. Wild, isn’t it?

    See the full article here .

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    Curiosity Makes You Smarter

    Curiosity is on a mission to make learning easier and more fun than it has ever been. Our goal is to ignite curiosity and inspire people to learn. Each day, we create and curate engaging topics for millions of lifelong learners worldwide.

    Experience Curiosity on our website, through our apps and across social media. We designed Curiosity with your busy life in mind. Our editors find interesting and important topics that you’ll want to know more about, and introduce you to the best ways to keep learning.

    We hope you make Curiosity part of your daily digital diet. Never stop learning!

     
  • richardmitnick 2:41 pm on August 27, 2019 Permalink | Reply
    Tags: "Department of Energy awards Fermilab $3.5 million for quantum science", Cryogenic engineering, , , QuantISED-Quantum Information Science-Enabled Discovery program, , , Quantum Physics,   

    From Fermi National Accelerator Lab: “Department of Energy awards Fermilab $3.5 million for quantum science” 

    FNAL Art Image
    FNAL Art Image by Angela Gonzales

    From Fermi National Accelerator Lab , an enduring source of strength for the US contribution to scientific research world wide.

    August 27, 2019
    Edited by Leah Hesla

    The U.S. Department of Energy has awarded researchers at its Fermi National Accelerator Laboratory more than $3.5 million to boost research in the fast-emerging field of Quantum Information Science.

    “Few pursuits have the revolutionary potential that quantum science presents,” said Fermilab Chief Research Officer Joe Lykken. “Fermilab’s expertise in quantum physics and cryogenic engineering is world-class, and combined with our experience in conventional computing and networks, we can advance quantum science in directions that not many other places can.”

    As part of a number of grants to national laboratories and universities offered through its Quantum Information Science-Enabled Discovery (QuantISED) program, DOE’s recent round of funding to Fermilab covers three initiatives related to quantum science. It also funds Fermilab’s participation in a fourth initiative led by Argonne National Laboratory.

    1
    The DOE QuantISED grants will fund initiatives related to quantum computing. These include the simulation of advanced quantum devices that will improve quantum computing simulations and the development of novel electronics to work with large arrays of ultracold qubits.

    For a half-century, Fermilab researchers have closely studied the quantum realm and provided the computational and engineering capabilties needed to zoom in on nature at its most fundamental level. The projects announced by the Department of Energy will build on those capabilities, pushing quantum science and technology forward and leading to new discoveries that will enhance our picture of the universe at its smallest scale.

    “Fermilab is well-versed in engineering, algorithmic development and recruiting massive computational resources to explore quantum-scale phenomena,” said Fermilab Head of Quantum Science Panagiotis Spentzouris. “Now we’re wrangling those competencies and capabilities to advance quantum science in many areas, and in a way that only a leading physics laboratory could.”

    _________________________________________________
    The Fermilab-led initiatives funded through these DOE QuantISED grants are:

    Large Scale Simulations of Quantum Systems on High-Performance Computing with Analytics for High-Energy Physics Algorithms
    Lead principal investigator: Adam Lyon, Fermilab

    The large-scale simulation of quantum computers has plenty in common with simulations in high-energy physics: Both must sweep over a large number of variables. Both organize their inputs and outputs similarly. And in both cases, the simulation has to be analyzed and consolidated into results. Fermilab scientists, in collaboration with scientists at Argonne National Laboratory, will use tools from high-energy physics to produce and analyze simulations using high-performance computers at the Argonne Leadership Computing Facility. Specifically, they will simulate the operation of a qubit device that uses superconducting cavities (which are also used as components in particle accelerators) to maintain quantum information over a relatively long time. Their results will determine the device’s impact on high-energy physics algorithms using an Argonne-developed quantum simulator.

    Partner institution: Argonne National Laboratory

    Research Technology for Quantum Information Systems
    Lead principal investigator: Gustavo Cancelo, Fermilab

    One of the main challenges in quantum information science is designing an architecture that solves problems of massive interconnection, massive data processing and heat load. The electronics must be able to operate and interface with other electronics operating both at 4 kelvins and at near absolute zero. Fermilab scientists and engineers are designing novel electronic circuits as well as massive control and readout electronics to be compatible with quantum devices, such as sensors and quantum qubits. These circuits will enable many applications in the quantum information science field.

    Partner institutions: Argonne National Laboratory, Massachusetts Institute of Technology, University of Chicago

    MAGIS-100 – co-led by Stanford University and Fermilab
    Lead Fermilab principal investigator: Rob Plunkett

    Fermilab will host a new experiment to test quantum mechanics on macroscopic scales of space and time. Scientists on the MAGIS-100 experiment will drop clouds of ultracold atoms down a 100-meter-long vacuum pipe on the Fermilab site, and use a stable laser to create an atom interferometer which will look for dark matter made of ultralightweight particles. They will also advance a technique for gravitational-wave detection at relatively low frequencies.

    This is a joint venture under the collaboration leadership of Stanford University Professor Jason Hogan, who is funded by grant GBMF7945 from the Gordon and Betty Moore Foundation. Rob Plunkett of Fermilab serves as the project manager.

    Other participating institutions: Northern Illinois University, Northwestern University, Stanford University, Johns Hopkins University, University of Liverpool

    _________________________________________________

    Fermilab was also funded to participate in another initiative led by Argonne National Laboratory:

    Quantum Sensors for Wide Band Axion Dark Matter Detection
    Lead principal investigator: Peter Barry, Argonne

    Researchers are searching high and low for dark matter, the mysterious substance that makes up a quarter of our universe. One theory proposes that it could be made of particles called axions, which would signal their presence by converting into particles of light, called photons. Fermilab researchers are part of a team developing specialized detectors that look for photons in the terahertz range — at frequencies just below the infrared. The development of these detectors will widen the range of frequencies where axions may be discovered. To bring the faint signals to the fore, the team is using supersensitive quantum amplifiers.

    Other participating institutions: National Institute of Standards and Technology, University of Colorado

    See the full here.


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    FNAL Icon

    Fermi National Accelerator Laboratory (Fermilab), located just outside Batavia, Illinois, near Chicago, is a US Department of Energy national laboratory specializing in high-energy particle physics. Fermilab is America’s premier laboratory for particle physics and accelerator research, funded by the U.S. Department of Energy. Thousands of scientists from universities and laboratories around the world
    collaborate at Fermilab on experiments at the frontiers of discovery.

     
  • richardmitnick 11:59 am on July 28, 2019 Permalink | Reply
    Tags: A quantum particle can have a range of possible states known as a “superposition.”, “Quantum-classical transition.”, But why can’t we see a quantum superposition?, , Darwin-Survival of the Fittest, Many independent observers can make measurements of a quantum system and agree on the outcome—a hallmark of classical behavior., Quantum Darwinism, , Quantum Physics, The definite properties of objects that we associate with classical physics—position and speed say—are selected from a menu of quantum possibilities., The process is loosely analogous to natural selection in evolution., The vexing question then becomes: How do quantum probabilities coalesce into the sharp focus of the classical world?, This doesn’t really mean it is in several states at once; rather it means that if we make a measurement we will see one of those outcomes., This process by which “quantumness” disappears into the environment is called decoherence.,   

    From WIRED: “Quantum Darwinism Could Explain What Makes Reality Real” 

    Wired logo

    From WIRED

    07.28.19
    Philip Ball

    1
    Contrary to popular belief, says physicist Adán Cabello, “quantum theory perfectly describes the emergence of the classical world.” Olena Shmahalo/Quanta Magazine

    It’s not surprising that quantum physics has a reputation for being weird and counterintuitive. The world we’re living in sure doesn’t feel quantum mechanical. And until the 20th century, everyone assumed that the classical laws of physics devised by Isaac Newton and others—according to which objects have well-defined positions and properties at all times—would work at every scale. But Max Planck, Albert Einstein, Niels Bohr and their contemporaries discovered that down among atoms and subatomic particles, this concreteness dissolves into a soup of possibilities. An atom typically can’t be assigned a definite position, for example—we can merely calculate the probability of finding it in various places. The vexing question then becomes: How do quantum probabilities coalesce into the sharp focus of the classical world?

    Physicists sometimes talk about this changeover as the “quantum-classical transition.” But in fact there’s no reason to think that the large and the small have fundamentally different rules, or that there’s a sudden switch between them. Over the past several decades, researchers have achieved a greater understanding of how quantum mechanics inevitably becomes classical mechanics through an interaction between a particle or other microscopic system and its surrounding environment.

    One of the most remarkable ideas in this theoretical framework is that the definite properties of objects that we associate with classical physics—position and speed, say—are selected from a menu of quantum possibilities in a process loosely analogous to natural selection in evolution: The properties that survive are in some sense the “fittest.” As in natural selection, the survivors are those that make the most copies of themselves. This means that many independent observers can make measurements of a quantum system and agree on the outcome—a hallmark of classical behavior.

    This idea, called quantum Darwinism (QD), explains a lot about why we experience the world the way we do rather than in the peculiar way it manifests at the scale of atoms and fundamental particles. Although aspects of the puzzle remain unresolved, QD helps heal the apparent rift between quantum and classical physics.

    3
    Chaoyang Lu (left) and Jian-Wei Pan of the University of Science and Technology of China in Hefei led a recent experiment that tested quantum Darwinism in an artificial environment made of interacting photons. Chaoyang Lu

    Only recently, however, has quantum Darwinism been put to the experimental test. Three research groups, working independently in Italy, China and Germany, have looked for the telltale signature of the natural selection process by which information about a quantum system gets repeatedly imprinted on various controlled environments. These tests are rudimentary, and experts say there’s still much more to be done before we can feel sure that QD provides the right picture of how our concrete reality condenses from the multiple options that quantum mechanics offers. Yet so far, the theory checks out.

    Survival of the Fittest

    At the heart of quantum Darwinism is the slippery notion of measurement—the process of making an observation. In classical physics, what you see is simply how things are. You observe a tennis ball traveling at 200 kilometers per hour because that’s its speed. What more is there to say?

    In quantum physics that’s no longer true. It’s not at all obvious what the formal mathematical procedures of quantum mechanics say about “how things are” in a quantum object; they’re just a prescription telling us what we might see if we make a measurement. Take, for example, the way a quantum particle can have a range of possible states, known as a “superposition.” This doesn’t really mean it is in several states at once; rather, it means that if we make a measurement we will see one of those outcomes. Before the measurement, the various superposed states interfere with one another in a wavelike manner, producing outcomes with higher or lower probabilities.

    But why can’t we see a quantum superposition? Why can’t all possibilities for the state of a particle survive right up to the human scale?

    The answer often given is that superpositions are fragile, easily disrupted when a delicate quantum system is buffeted by its noisy environment. But that’s not quite right. When any two quantum objects interact, they get “entangled” with each other, entering a shared quantum state in which the possibilities for their properties are interdependent. So say an atom is put into a superposition of two possible states for the quantum property called spin: “up” and “down.” Now the atom is released into the air, where it collides with an air molecule and becomes entangled with it. The two are now in a joint superposition. If the atom is spin-up, then the air molecule might be pushed one way, while, if the atom is spin-down, the air molecule goes another way—and these two possibilities coexist. As the particles experience yet more collisions with other air molecules, the entanglement spreads, and the superposition initially specific to the atom becomes ever more diffuse. The atom’s superposed states no longer interfere coherently with one another because they are now entangled with other states in the surrounding environment—including, perhaps, some large measuring instrument. To that measuring device, it looks as though the atom’s superposition has vanished and been replaced by a menu of possible classical-like outcomes that no longer interfere with one another.

    This process by which “quantumness” disappears into the environment is called decoherence. It’s a crucial part of the quantum-classical transition, explaining why quantum behavior becomes hard to see in large systems with many interacting particles. The process happens extremely fast. If a typical dust grain floating in the air were put into a quantum superposition of two different physical locations separated by about the width of the grain itself, collisions with air molecules would cause decoherence—making the superposition undetectable—in about 10−31 seconds. Even in a vacuum, light photons would trigger such decoherence very quickly: You couldn’t look at the grain without destroying its superposition.

    Surprisingly, although decoherence is a straightforward consequence of quantum mechanics, it was only identified in the 1970s, by the late German physicist Heinz-Dieter Zeh. The Polish-American physicist Wojciech Zurek further developed the idea in the early 1980s and made it better known, and there is now good experimental support for it.

    5
    Wojciech Zurek, a theoretical physicist at Los Alamos National Laboratory in New Mexico, developed the quantum Darwinism theory in the 2000s to account for the emergence of objective, classical reality. Los Alamos National Laboratory

    But to explain the emergence of objective, classical reality, it’s not enough to say that decoherence washes away quantum behavior and thereby makes it appear classical to an observer. Somehow, it’s possible for multiple observers to agree about the properties of quantum systems. Zurek, who works at Los Alamos National Laboratory in New Mexico, argues that two things must therefore be true.

    First, quantum systems must have states that are especially robust in the face of disruptive decoherence by the environment. Zurek calls these “pointer states,” because they can be encoded in the possible states of a pointer on the dial of a measuring instrument. A particular location of a particle, for instance, or its speed, the value of its quantum spin, or its polarization direction can be registered as the position of a pointer on a measuring device. Zurek argues that classical behavior—the existence of well-defined, stable, objective properties—is possible only because pointer states of quantum objects exist.

    What’s special mathematically about pointer states is that the decoherence-inducing interactions with the environment don’t scramble them: Either the pointer state is preserved, or it is simply transformed into a state that looks nearly identical. This implies that the environment doesn’t squash quantumness indiscriminately but selects some states while trashing others. A particle’s position is resilient to decoherence, for example. Superpositions of different locations, however, are not pointer states: Interactions with the environment decohere them into localized pointer states, so that only one can be observed. Zurek described this “environment-induced superselection” of pointer states in the 1980s [Physical Review D].

    But there’s a second condition that a quantum property must meet to be observed. Although immunity to interaction with the environment assures the stability of a pointer state, we still have to get at the information about it somehow. We can do that only if it gets imprinted in the object’s environment. When you see an object, for example, that information is delivered to your retina by the photons scattering off it. They carry information to you in the form of a partial replica of certain aspects of the object, saying something about its position, shape and color. Lots of replicas are needed if many observers are to agree on a measured value—a hallmark of classicality. Thus, as Zurek argued in the 2000s, our ability to observe some property depends not only on whether it is selected as a pointer state, but also on how substantial a footprint it makes in the environment. The states that are best at creating replicas in the environment—the “fittest,” you might say—are the only ones accessible to measurement. That’s why Zurek calls the idea quantum Darwinism [Nature Physics].

    It turns out that the same stability property that promotes environment-induced superselection of pointer states also promotes quantum Darwinian fitness, or the capacity to generate replicas. “The environment, through its monitoring efforts, decoheres systems,” Zurek said, “and the very same process that is responsible for decoherence should inscribe multiple copies of the information in the environment.”

    Information Overload

    It doesn’t matter, of course, whether information about a quantum system that gets imprinted in the environment is actually read out by a human observer; all that matters for classical behavior to emerge is that the information get there so that it could be read out in principle. “A system doesn’t have to be under study in any formal sense” to become classical, said Jess Riedel, a physicist at the Perimeter Institute for Theoretical Physics in Waterloo, Canada, and a proponent of quantum Darwinism.


    “QD putatively explains, or helps to explain, all of classicality, including everyday macroscopic objects that aren’t in a laboratory, or that existed before there were any humans.”

    About a decade ago, while Riedel was working as a graduate student with Zurek, the two showed theoretically that information from some simple, idealized quantum systems is “copied prolifically into the environment,” Riedel said, “so that it’s necessary to access only a small amount of the environment to infer the value of the variables.” They calculated [Physical Review Letters] that a grain of dust one micrometer across, after being illuminated by the sun for just one microsecond, will have its location imprinted about 100 million times in the scattered photons.

    It’s because of this redundancy that objective, classical-like properties exist at all. Ten observers can each measure the position of a dust grain and find that it’s in the same location, because each can access a distinct replica of the information. In this view, we can assign an objective “position” to the speck not because it “has” such a position (whatever that means) but because its position state can imprint many identical replicas in the environment, so that different observers can reach a consensus.

    What’s more, you don’t have to monitor much of the environment to gather most of the available information—and you don’t gain significantly more by monitoring more than a fraction of the environment. “The information one can gather about the system quickly saturates,” Riedel said.

    This redundancy is the distinguishing feature of QD, explained Mauro Paternostro, a physicist at Queen’s University Belfast who was involved in one of the three new experiments. “It’s the property that characterizes the transition towards classicality,” he said.

    Quantum Darwinism challenges a common myth about quantum mechanics, according to the theoretical physicist Adán Cabello of the University of Seville in Spain: namely, that the transition between the quantum and classical worlds is not understood and that measurement outcomes cannot be described by quantum theory. On the contrary, he said, “quantum theory perfectly describes the emergence of the classical world.”

    Just how perfectly remains contentious, however. Some researchers think decoherence and QD provide a complete account of the quantum-classical transition. But although these ideas attempt to explain why superpositions vanish at large scales and why only concrete “classical” properties remain, there’s still the question of why measurements give unique outcomes. When a particular location of a particle is selected, what happens to the other possibilities inherent in its quantum description? Were they ever in any sense real? Researchers are compelled to adopt philosophical interpretations of quantum mechanics precisely because no one can figure out a way to answer that question experimentally.

    Into the Lab

    Quantum Darwinism looks fairly persuasive on paper. But until recently that was as far as it got. In the past year, three teams of researchers have independently put the theory to the experimental test by looking for its key feature: how a quantum system imprints replicas of itself on its environment.

    The experiments depended on the ability to closely monitor what information about a quantum system gets imparted to its environment. That’s not feasible for, say, a dust grain floating among countless billions of air molecules. So two of the teams created a quantum object in a kind of “artificial environment” with only a few particles in it. Both experiments—one by Paternostro [Physical Review A] and collaborators at Sapienza University of Rome, and the other by the quantum-information expert Jian-Wei Pan [https://arxiv.org/abs/1808.07388] and co-authors at the University of Science and Technology of China—used a single photon as the quantum system, with a handful of other photons serving as the “environment” that interacts with it and broadcasts information about it.

    Both teams passed laser photons through optical devices that could combine them into multiply entangled groups. They then interrogated the environment photons to see what information they encoded about the system photon’s pointer state—in this case its polarization (the orientation of its oscillating electromagnetic fields), one of the quantum properties able to pass through the filter of quantum Darwinian selection.

    A key prediction of QD is the saturation effect: Pretty much all the information you can gather about the quantum system should be available if you monitor just a handful of surrounding particles. “Any small fraction of the interacting environment is enough to provide the maximal classical information about the observed system,” Pan said.

    The two teams found precisely this. Measurements of just one of the environment photons revealed a lot of the available information about the system photon’s polarization, and measuring an increasing fraction of the environment photons provided diminishing returns. Even a single photon can act as an environment that introduces decoherence and selection, Pan explained, if it interacts strongly enough with the lone system photon. When interactions are weaker, a larger environment must be monitored.

    6
    Fedor Jelezko, director of the Institute for Quantum Optics at Ulm University in Germany. Ulm University

    7
    A team led by Jelezko probed the state of a nitrogen “defect” inside a synthetic diamond (shown mounted on the right) by monitoring surrounding carbon atoms. Their findings confirmed predictions of a theory known as quantum Darwinism.
    Ulm University

    The third experimental test of QD, led by the quantum-optical physicist Fedor Jelezko at Ulm University in Germany in collaboration with Zurek and others, used a very different system and environment, consisting of a lone nitrogen atom substituting for a carbon atom in the crystal lattice of a diamond—a so-called nitrogen-vacancy defect. Because the nitrogen atom has one more electron than carbon, this excess electron cannot pair up with those on neighboring carbon atoms to form a chemical bond. As a result, the nitrogen atom’s unpaired electron acts as a lone “spin,” which is like an arrow pointing up or down or, in general, in a superposition of both possible directions.

    This spin can interact magnetically with those of the roughly 0.3 percent of carbon nuclei present in the diamond as the isotope carbon-13, which, unlike the more abundant carbon-12, also has spin. On average, each nitrogen-vacancy spin is strongly coupled to four carbon-13 spins within a distance of about 1 nanometer.

    By controlling and monitoring the spins using lasers and radio-frequency pulses, the researchers could measure how a change in the nitrogen spin is registered by changes in the nuclear spins of the environment. As they reported in a preprint last September, they too observed the characteristic redundancy predicted by QD: The state of the nitrogen spin is “recorded” as multiple copies in the surroundings, and the information about the spin saturates quickly as more of the environment is considered.

    Zurek says that because the photon experiments create copies in an artificial way that simulates an actual environment, they don’t incorporate a selection process that picks out “natural” pointer states resilient to decoherence. Rather, the researchers themselves impose the pointer states. In contrast, the diamond environment does elicit pointer states. “The diamond scheme also has problems, because of the size of the environment,” Zurek added, “but at least it is, well, natural.”

    Generalizing Quantum Darwinism

    So far, so good for quantum Darwinism. “All these studies see what is expected, at least approximately,” Zurek said.

    Riedel says we could hardly expect otherwise, though: In his view, QD is really just the careful and systematic application of standard quantum mechanics to the interaction of a quantum system with its environment. Although this is virtually impossible to do in practice for most quantum measurements, if you can sufficiently simplify a measurement, the predictions are clear, he said: “QD is most like an internal self-consistency check on quantum theory itself.”

    But although these studies seem consistent with QD, they can’t be taken as proof that it is the sole description for the emergence of classicality, or even that it’s wholly correct. For one thing, says Cabello, the three experiments offer only schematic versions of what a real environment consists of. What’s more, the experiments don’t cleanly rule out other ways to view the emergence of classicality. A theory called “spectrum broadcasting,” for example, developed by Pawel Horodecki at the Gdańsk University of Technology in Poland and collaborators, attempts to generalize QD. Spectrum broadcast theory (which has only been worked through for a few idealized cases) identifies those states of an entangled quantum system and environment that provide objective information that many observers can obtain without perturbing it. In other words, it aims to ensure not just that different observers can access replicas of the system in the environment, but that by doing so they don’t affect the other replicas. That too is a feature of genuinely “classical” measurements.

    Horodecki and other theorists have also sought to embed QD in a theoretical framework that doesn’t demand any arbitrary division of the world into a system and its environment, but just considers how classical reality can emerge from interactions between various quantum systems. Paternostro says it might be challenging to find experimental methods capable of identifying the rather subtle distinctions between the predictions of these theories.

    Still, researchers are trying, and the very attempt should refine our ability to probe the workings of the quantum realm. “The best argument for performing these experiments probably is that they are good exercise,” Riedel said. “Directly illustrating QD can require some very difficult measurements that will push the boundaries of existing laboratory techniques.” The only way we can find out what measurement really means, it seems, is by making better measurements.

    See the full article here .

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