Aurelia Butler

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    in Physics

    Physicists have coaxed ultracold atoms into an elusive form of quantum matter

    An elusive form of matter called a quantum spin liquid isn’t a liquid, and it doesn’t spin — but it sure is quantum.

    Predicted nearly 50 years ago, quantum spin liquids have long evaded definitive detection in the laboratory. But now, a lattice of ultracold atoms held in place with lasers has shown hallmarks of the long-sought form of matter, researchers report in the Dec. 3 Science.

    Quantum entanglement goes into overdrive in the newly fashioned material. Even atoms on opposite sides of the lattice share entanglement, or quantum links, meaning that the properties of distant atoms are correlated with one another. “It’s very, very entangled,” says physicist Giulia Semeghini of Harvard University, a coauthor of the new study. “If you pick any two points of your system, they are connected to each other through this huge entanglement.” This strong, long-range entanglement could prove useful for building quantum computers, the researchers say.

    The new material matches predictions for a quantum spin liquid, although its makeup strays a bit from conventional expectations. While the traditional idea of a quantum spin liquid relies on the quantum property of spin, which gives atoms magnetic fields, the new material is based on different atomic quirks.

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    A standard quantum spin liquid should arise among atoms whose spins are in conflict. Spin causes atoms to act as tiny magnets. Normally, at low temperatures, those atoms would align their magnetic poles in a regular pattern. For example, if one atom points up, its neighbors point down. But if atoms are arranged in a triangle, for example, each atom has two neighbors that themselves point in opposite directions. That arrangement leaves the third one with nowhere to turn — it can’t oppose both of its neighbors at once.

    So atoms in quantum spin liquids refuse to choose (SN: 9/21/21). Instead, the atoms wind up in a superposition, a quantum combination of spin up and down, and each atom’s state is linked with those of its compatriots. The atoms are constantly fluctuating and never settle down into an orderly arrangement of spins, similarly to how atoms in a normal liquid are scattered about rather than arranged in a regularly repeating pattern, hence the name.

    Conclusive evidence of quantum spin liquids has been hard to come by in solid materials. In the new study, the researchers took a different tack: They created an artificial material composed of 219 trapped rubidium atoms cooled to a temperature of around 10 microkelvins (about –273.15° Celsius). The array of atoms, known as a programmable quantum simulator, allows scientists to fine-tune how atoms interact to investigate exotic forms of quantum matter.

    In the new experiment, rather than the atoms’ spins being in opposition, a different property created disagreement. The researchers used lasers to put the atoms into Rydberg states, meaning one of an atom’s electrons is bumped to a very high energy level (SN: 8/29/16). If one atom is in a Rydberg state, its neighbors prefer not to be. That setup begets a Rydberg-or-not discord, analogous to the spin-up and -down battle in a traditional quantum spin liquid.

    The scientists confirmed the quantum spin liquid effect by studying the properties of atoms that fell along loops traced through the material. According to quantum math, those atoms should have exhibited certain properties unique to quantum spin liquids. The results matched expectations for a quantum spin liquid and revealed that long-range entanglement was present.

    Notably, the material’s entanglement is topological. That means it is described by a branch of mathematics called topology, in which an object is defined by certain geometrical properties, for example, its number of holes (SN: 10/4/16). Topology can protect information from being destroyed: A bagel that falls off the counter will still have exactly one hole, for example. This information-preserving feature could be a boon to quantum computers, which must grapple with fragile, easily destroyed quantum information that makes calculations subject to mistakes (SN: 6/22/20).

    Whether the material truly qualifies as a quantum spin liquid, despite not being based on spin, depends on your choice of language, says theoretical physicist Christopher Laumann of Boston University, who was not involved with the study. Some physicists use the term “spin” to describe other systems with two possible options, because it has the same mathematics as atomic spins that can point either up or down. “Words have meaning, until they don’t,” he quips. It all depends how you spin them. More

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    in Computers Math

    Liquid crystals for fast switching devices

    Liquid crystals are not solid, but some of their physical properties are directional — like in a crystal. This is because their molecules can arrange themselves into certain patterns. The best-known applications include flat screens and digital displays. They are based on pixels of liquid crystals whose optical properties can be switched by electric fields.
    Some liquid crystals form the so-called cholesteric phases: the molecules self-assemble into helical structures, which are characterised by pitch and rotate either to the right or to the left. “The pitch of the cholesteric spirals determines how quickly they react to an applied electric field,” explains Dr. Alevtina Smekhova, physicist at HZB and first author of the study, which has now been published in Soft Matter.
    Simple molecular chain
    In this work, she and partners from the Academies of Sciences in Prague, Moscow and Chernogolovka investigated a liquid crystalline cholesteric compound called EZL10/10, developed in Prague. “Such cholesteric phases are usually formed by molecules with several chiral centres, but here the molecule has only one chiral centre,” explains Dr. Smekhova. It is a simple molecular chain with one lactate unit.
    Ultrashort pitch
    At BESSY II, the team has now examined this compound with soft X-ray light and determined the pitch and space ordering of the spirals. This was the shortest up-to-date reported value of the pitch: only 104 nanometres! This is twice as short as the previously known pitch of spiral structures in liquid crystals. Further analysis showed that in this material the cholesteric spirals form domains with characteristic lengths of about five pitches.
    Outlook
    “This very short pitch makes the material unique and promising for optoelectronic devices with very fast switching times,” Dr. Smekhova points out. In addition, the EZ110/10 compound is thermally and chemically stable and can easily be further varied to obtain structures with customised pitch lengths.
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    in Heart

    Invasive grasses are taking over the American West’s sea of sagebrush

    No one likes a cheater, especially one that prospers as easily as the grass Bromus tectorum does in the American West. This invasive species is called cheatgrass because it dries out earlier than native plants, shortchanging wildlife and livestock in search of nutritious food.

    Unfortunately for those animals and the crowded-out native plants, cheatgrass and several other invasive annual grasses now dominate one-fifth of the Great Basin, a wide swath of land that includes portions of Oregon, Nevada, Idaho, Utah and California. In 2020, these invasive grasses covered more than 77,000 square kilometers of Great Basin ecosystems, including higher elevation habitats that are now accessible to nonnative plants due to climate change, researchers report November 17 in Diversity and Distributions.

    This invasion of exotic annual grasses is degrading one of North America’s most imperiled biomes: a vast sea of sagebrush shrubs, wildflowers and bunchgrasses where pronghorn and mule deer roam and where ranchers rely on healthy rangelands to raise cattle.

    What’s more, these invasive grasses, which are highly flammable when dry, are also linked to more frequent and larger wildfires. In parts of Idaho’s Snake River Plain that are dominated by cheatgrass, for example, fires now occur every three to five years as opposed to the historical average of 60 to 110 years. From 2000 to 2009, 39 out of 50 of the largest fires in the Great Basin were associated with cheatgrass.

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    To add insult to injury, cheatgrass is more efficient at recolonizing burned areas after a fire than native plants, creating a vicious loop: More cheatgrass causes more fires, and more fires foster more of the weeds. This means that land managers are often behind the curve, trying to keep cheatgrass from spreading to prevent wildfires, while also attempting to restore native plant communities after fires so that the sagebrush ecosystems don’t transition into a monoculture of invasive grasses.

    “We need to get strategic spatially to pinpoint where to protect intact native plant communities rather than constantly chasing the problem,” says Joseph Smith, a rangeland ecology researcher at the University of Montana in Missoula.

    To do that, Smith and his colleagues quantified how much of the Great Basin has transitioned to invasive annual grasses over the last three decades. The researchers used the Rangeland Analysis Platform, or RAP, a remote sensing product powered by Google Earth Engine that estimates the type and percentage of vegetation at a baseball diamond–sized scale.

    While the satellite imagery that RAP relies on can show where annual grasses turn brown in late spring in the West or where perennial plants stay green longer into the summer, the technology can’t delineate between native and nonnative plants. So researchers cross-checked RAP data with on-the-ground vegetation surveys collected through the U.S. Bureau of Land Management’s assessment, inventory and monitoring strategy.

    Invasive annual grasses have increased eightfold in area in the Great Basin region since 1990, the team found. Smith and colleagues estimate that areas dominated by the grasses have grown more than 2,300 square kilometers annually, a rate of take-over proportionally greater than recent deforestation of the Amazon rainforest.

    Perhaps most alarmingly, the team found that annual grasses, most of which are invasive, are steadily moving into higher elevations previously thought to be at minimal risk of invasion (SN: 10/3/14). Invasive annual grasses don’t tolerate cold, snowy winters as well as native perennial plants. But as a result of climate change, winters are trending more mild in the Great Basin and summers more arid. While perennial plants are struggling to survive the hot, dry months, invasive grass seeds simply lie dormant and wait for fall rains.

    “In a lot of ways, invasive grasses just do an end run around perennials. They don’t have to deal with the harshest effects of climate change because of their different life cycle,” Smith explains.

    Though the scale of the problem can seem overwhelming, free remote sensing technology like RAP may help land managers better target efforts to slow the spread of these invasive grasses and explore their connection to wildfires. Smith, for instance, is now researching how mapping annual grasses in the spring might help forecast summer wildfires.

    “If we don’t know where the problem is, then we don’t know where to focus solutions,” says Bethany Bradley, an invasion ecologist and biogeographer at the University of Massachusetts Amherst who wasn’t involved in the research. “Mapping invasive grasses can certainly help people stop the grass-fire cycle by knowing where to treat them with herbicides.” More

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    in Computers Math

    How statistics can aid in the fight against misinformation

    An American University math professor and his team created a statistical model that can be used to detect misinformation in social posts. The model also avoids the problem of black boxes that occur in machine learning.
    With the use of algorithms and computer models, machine learning is increasingly playing a role in helping to stop the spread of misinformation, but a main challenge for scientists is the black box of unknowability, where researchers don’t understand how the machine arrives at the same decision as human trainers.
    Using a Twitter dataset with misinformation tweets about COVID-19, Zois Boukouvalas, assistant professor in AU’s Department of Mathematics and Statistics, College of Arts and Sciences, shows how statistical models can detect misinformation in social media during events like a pandemic or a natural disaster. In newly published research, Boukouvalas and his colleagues, including AU student Caitlin Moroney and Computer Science Prof. Nathalie Japkowicz, also show how the model’s decisions align with those made by humans.
    “We would like to know what a machine is thinking when it makes decisions, and how and why it agrees with the humans that trained it,” Boukouvalas said. “We don’t want to block someone’s social media account because the model makes a biased decision.”
    Boukouvalas’ method is a type of machine learning using statistics. It’s not as popular a field of study as deep learning, the complex, multi-layered type of machine learning and artificial intelligence. Statistical models are effective and provide another, somewhat untapped, way to fight misinformation, Boukouvalas said.
    For a testing set of 112 real and misinformation tweets, the model achieved a high prediction performance and classified them correctly, with an accuracy of nearly 90 percent. (Using such a compact dataset was an efficient way for verifying how the method detected the misinformation tweets.)
    “What’s significant about this finding is that our model achieved accuracy while offering transparency about how it detected the tweets that were misinformation,” Boukouvalas added. “Deep learning methods cannot achieve this kind of accuracy with transparency.” More

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    in Computers Math

    Twisting elusive quantum particles with a quantum computer

    While the number of qubits and the stability of quantum states are still limiting current quantum computing devices, there are questions where these processors are already able to leverage their enormous computing power. In collaboration with the Google Quantum AI team scientists from the Technical University of Munich (TUM) and the University of Nottingham used a quantum processor to simulate the ground state of a so-called toric code Hamiltonian — an archetypical model system in modern condensed matter physics, which was originally proposed in the context of quantum error correction.
    What would it be like if we lived in a flat two-dimensional world? Physicists predict that quantum mechanics would be even stranger in that case resulting in exotic particles — so-called “anyons” — that cannot exist in the three-dimensional world we live in. This unfamiliar world is not just a curiosity but may be key to unlocking quantum materials and technologies of the future.
    In collaboration with the Google Quantum AI team scientists from the Technical University of Munich and the University of Nottingham used a highly controllable quantum processor to simulate such states of quantum matter. Their results appear in the current issue of the scientific journal Science.
    Emergent quantum particles in two-dimensional systems
    All particles in our universe come in two flavors, bosons or fermions. In the three-dimensional world we live in, this observation stands firm. However, it was theoretically predicted almost 50 years ago that other types of particles, dubbed anyons, could exist when matter is confined to two dimensions.
    While these anyons do not appear as elementary particles in our universe, it turns out that anyonic particles can emerge as collective excitations in so-called topological phases of matter, for which the Nobel prize was awarded in 2016.
    “Twisting pairs of these anyons by moving them around one another in the simulation unveils their exotic properties — physicists call it braiding statistics,” says Dr. Adam Smith from the University of Nottingham.
    A simple picture for these collective excitations is “the wave” in a stadium crowd — it has a well-defined position, but it cannot exist without the thousands of people that make up the crowd. However, realizing and simulating such topologically ordered states experimentally has proven to be extremely challenging.
    Quantum processors as a platform for controlled quantum simulations
    In landmark experiments, the teams from TUM, Google Quantum AI, and the University of Nottingham programmed Google’s quantum processor to simulate these two-dimensional states of quantum matter. “Google’s quantum processor named ‘Sycamore’ can be precisely controlled and is a well-isolated quantum system, which are key requirements for performing quantum computations,” says Kevin Satzinger, a scientist from the Google team.
    The researchers came up with a quantum algorithm to realize a state with topological order, which was confirmed by simulating the creation of anyon excitations and twisting them around one another. Fingerprints from long-range quantum entanglement could be confirmed in their study. As a possible application, such topologically ordered states can be used to improve quantum computers by realizing new ways of error correction. First steps toward this goal have already been achieved in their work.
    “Near term quantum processors will represent an ideal platform to explore the physics of exotic quantum phases matter,” says Prof. Frank Pollmann from TUM. “In the near future, quantum processors promise to solve problems that are beyond the reach of current classical supercomputers.”
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    in Computers Math

    Researchers develop an algorithm to increase the efficiency of quantum computers

    Quantum computing is taking a new leap forward due to research done in collaboration between University of Helsinki, Aalto University, University of Turku, and IBM Research Europe-Zurich. The team of researchers have proposed a scheme to reduce the number of calculations needed to read out data stored in the state of a quantum processor. This, in turn, will make quantum computers more efficient, faster, and ultimately more sustainable.
    Quantum computers have the potential to solve important problems that are beyond reach even for the most powerful supercomputers, but they require an entirely new way of programming and creating algorithms.
    Universities and major tech companies are spearheading research on how to develop these new algorithms. In a recent collaboration between University of Helsinki, Aalto University, University of Turku, and IBM Research Europe-Zurich, a team of researchers have developed a new method to speed up calculations on quantum computers. The results are published in the journal PRX Quantum of the American Physical Society.
    – Unlike classical computers, which use bits to store ones and zeros, information is stored in the qubits of a quantum processor in the form of a quantum state, or a wavefunction, says postdoctoral researcher Guillermo García-Pérez from the Department of Physics at the University of Helsinki, first author of the paper.
    Special procedures are thus required to read out data from quantum computers. Quantum algorithms also require a set of inputs, provided for example as real numbers, and a list of operations to be performed on some reference initial state.
    – The quantum state used is, in fact, generally impossible to reconstruct on conventional computers, so useful insights must be extracted by performing specific observations (which quantum physicists refer to as measurements) says García-Pérez.
    The problem with this is the large number of measurements required for many popular applications of quantum computers (like the so-called Variational Quantum Eigensolver, which can be used to overcome important limitations in the study of chemistry, for instance in drug discovery). The number of calculations required is known to grow very quickly with the size of the system one wants to simulate, even if only partial information is needed. This makes the process hard to scale up, slowing down the computation and consuming a lot of computational resources.
    The method proposed by García-Pérez and co-authors uses a generalized class of quantum measurements that are adapted throughout the calculation in order to extract the information stored in the quantum state efficiently. This drastically reduces the number of iterations, and therefore the time and computational cost, needed to obtain high-precision simulations.
    The method can reuse previous measurement outcomes and adjust its own settings. Subsequent runs are increasingly accurate, and the collected data can be reused again and again to calculate other properties of the system without additional costs.
    – We make the most out of every sample by combining all data produced. At the same time, we fine-tune the measurement to produce highly accurate estimates of the quantity under study, such as the energy of a molecule of interest. Putting these ingredients together, we can decrease the expected runtime by several orders of magnitude, says García-Pérez.
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    Materials provided by University of Helsinki. Original written by Paavo Ihalainen. Note: Content may be edited for style and length. More

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    in Computers Math

    Artificial material protects light states on smallest length scales

    Light not only plays a key role as an information carrier for optical computer chips, but also in particular for the next generation of quantum computers. Its lossless guidance around sharp corners on tiny chips and the precise control of its interaction with other light are the focus of research worldwide. Scientists at Paderborn University have now demonstrated, for the very first time, the spatial confinement of a light wave to a point smaller than the wavelength in a ‘topological photonic crystal’. These are artificial electromagnetic materials that facilitate robust manipulation of light. The state is protected by special properties and is important for use in quantum chips, for example. The findings have now been published in renowned journal “Science Advances.”
    Topological crystals function on the basis of specific structures, the properties of which remain largely unaffected by disturbances and deviations. While in normal photonic crystals the effects needed for light manipulation are fragile and can be affected by defects in the material structure, for example, in topological photonic crystals, they are protected from this. The topological structures allow properties such as unidirectional light propagation and increased robustness for guiding photons, small particles of light — features that are crucial for future light-based technologies.
    Photonic crystals influence the propagation of electromagnetic waves with the help of an optical band gap for photons, which blocks the movement of light in certain directions. Scattering usually occurs — some photons are reflected back, while others are reflected away. “With topological light states that span an extended range of photonic crystals, you can prevent this. In normal optical waveguides and fibers, back reflection poses a major problem because it leads to unwanted feedback. Loss during propagation hinders large-scale integration in optical chips, in which photons are responsible for transmitting information. With the help of topological photonic crystals, novel unidirectional waveguides can be achieved that transmit light without any back reflection, even in the presence of arbitrarily large disorder,” explains Professor Thomas Zentgraf, head of the Ultrafast Nanophotonics research group at Paderborn University. The concept, which has its origins in solid-state physics, has already led to numerous applications, including robust light transmission, topological delay lines, topological lasers and quantum interference.
    “It was also recently proven that topological photonic crystals based on a weak topology with a crystal dislocation in the periodic structure also exhibit these special properties and also support what are known as topologically-protected strongly spatially localised light states. When something is topologically protected, any changes in the parameters do not affect the protected properties. Localised light states are extremely useful for non-linear amplification, miniaturisation of photonic components and integration of photonic quantum chips,” adds Zentgraf. In this context, weak topological states are special states for the light that result not only from the topological band structure, but also from the formation of the crystal structure.
    In a joint experiment, researchers from Paderborn University and RWTH Aachen University used a special near-field optical microscope to demonstrate the existence of such strongly localised light states in topological structures. “We showed that the versatility of weak topology can produce a strongly spatially localised optical field in an intentionally induced structural dislocation,” explains Jinlong Lu, a PhD student in Zentgraf’s group and lead author of the paper. “Our study demonstrates a viable strategy for achieving a topologically-protected, localised zero-dimensional state for light,” adds Zentgraf. With their work, the researchers have proven that near-field microscopy is a valuable tool for characterising topological structures with nanoscale resolution at optical frequencies.
    The findings provide a basis for the use of strongly localised optical light states based on weak topology. Phase-change materials with a tunable refractive index could therefore also be used for the nanostructures used in the experiment to produce robust and active topological photonic elements. “We’re now working on concepts to equip the dislocation centres in the crystal structure with special quantum emitters for single photon generation,” says Zentgraf, adding: “These could then be used in future optical quantum computers, for which single photon generation plays an important role.”
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    in Computers Math

    Physicists exploit space and time symmetries to control quantum materials

    Physicists from Exeter and Trondheim have developed a theory describing how space reflection and time reversal symmetries can be exploited, allowing for greater control of transport and correlations within quantum materials.
    Two theoretical physicists, from the University of Exeter (United Kingdom) and the Norwegian University of Science and Technology (in Trondheim, Norway), have built a quantum theory describing a chain of quantum resonators satisfying space reflection and time reversal symmetries. They have shown how the different quantum phases of such chains are associated with remarkable phenomena, which may be useful in the design of future quantum devices relying on strong correlations.
    A common distinction in physics is between open and closed systems. Closed systems are isolated from any external environment, such that energy is conserved because there is nowhere for it to escape to. Open systems are connected to the outer world, and via exchanges with the environment they are subject to energy gains and energy losses. There is an important third case. When the energy flowing in and flowing out of the system is finely balanced, an intermediate situation between being open and closed arises. This equilibrium can occur when the system obeys a combined symmetry of space and time, that is when (1) switching left and right and (2) flipping the arrow of time leave the system essentially unchanged.
    In their latest research, Downing and Saroka discuss the phases of a quantum chain of resonators satisfying space reflection and time reversal symmetries. There are principally two phases of interest, a trivial phase (accompanied by intuitive physics) and a nontrivial phase (marked with surprising physics). The border between these two phases is marked by an exceptional point. The researchers have found the locations of these exceptional points for a chain with an arbitrary number of resonators, providing insight into the scaling up of quantum systems obeying these symmetries. Importantly, the nontrivial phase allows for unconventional transport effects and strong quantum correlations, which may be used to control the behaviour and propagation of light at nanoscopic length scales.
    This theoretical study may be useful for the generation, manipulation and control of light in low-dimensional quantum materials, with a view to building light-based devices exploiting photons, the particles of light, as workhorses down at sizes around one billionth of a meter.
    Charles Downing, from the University of Exeter, commented: “Our work on parity-time symmetry in open quantum systems further emphasises how symmetry underpins our understanding of the physical world, and how we may benefit from it.”
    Vasil Saroka, from the Norwegian University of Science and Technology, added: “We hope that our theoretical work on parity-time symmetry can inspire further experimental research in this exciting area of physics.”
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