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Creating brain-like computers with minimal energy requirements would revolutionize nearly every aspect of modern life. Funded by the Department of Energy, Quantum Materials for Energy Efficient Neuromorphic Computing ( Q-MEEN-C) — a nationwide consortium led by the University of California San Diego — has been at the forefront of this research. UC San Diego Assistant Professor of Physics Alex Frañó is co-director of Q-MEEN-C and thinks of the center’s work in phases. In the first phase, he worked closely with President Emeritus of University of California and Professor of Physics Robert Dynes, as well as Rutgers Professor of Engineering Shriram Ramanathan. Together, their teams were successful in finding ways to create or mimic the properties of a single brain element (such as a neuron or synapse) in a quantum material. Now, in phase two, new research from Q-MEEN-C, published in Nano Letters, shows that electrical stimuli passed between neighboring electrodes can also affect non-neighboring electrodes. Known as non-locality, this discovery is a crucial milestone in the journey toward new types of devices that mimic brain functions known as neuromorphic computing. Like many research projects now bearing fruit, the idea to test whether non-locality in quantum materials was possible came about during the pandemic. Physical lab spaces were shuttered, so the team ran calculations on arrays that contained multiple devices to mimic the multiple neurons and synapses in the brain. In running these tests, they found that non-locality was theoretically possible. "In the brain it’s understood that these non-local interactions are nominal — they happen frequently and with minimal exertion,” stated Frañó, one of the paper’s co-authors. “It’s a crucial part of how the brain operates, but similar behaviors replicated in synthetic materials are scarce. When labs reopened, they refined this idea further and enlisted UC San Diego Jacobs School of Engineering Associate Professor Duygu Kuzum, whose work in electrical and computer engineering helped them turn a simulation into an actual device. This involved taking a thin film of nickelate — a “quantum material” ceramic that displays rich electronic properties — inserting hydrogen ions, and then placing a metal conductor on top. A wire is attached to the metal so that an electrical signal can be sent to the nickelate. The signal causes the gel-like hydrogen atoms to move into a certain configuration and when the signal is removed, the new configuration remains.
Richard Feynman’s path integral is a powerful prediction machine and a philosophy. Physicists still struggle to figure out how to use it, and what it means. The most powerful formula in physics starts with a slender S, the symbol for a sort of sum known as an integral. Further along comes a second S, representing a quantity known as action. Together, these twin S’s form the essence of an equation that is arguably the most effective diviner of the future yet devised. The oracular formula is known as the Feynman path integral. As far as physicists can tell, it precisely predicts the behavior of any quantum system—an electron, a light ray, or even a black hole. The path integral has racked up so many successes that many physicists believe it to be a direct window into the heart of reality. “It’s how the world really is,” said Renate Loll, a theoretical physicist at Radboud University in the Netherlands. But the equation, although it graces the pages of thousands of physics publications, is more of a philosophy than a rigorous recipe. It suggests that our reality is a sort of blending—a sum—of all imaginable possibilities. But it does not tell researchers exactly how to carry out the sum. So physicists have spent decades developing an arsenal of approximation schemes for constructing and computing the integral for different quantum systems. The approximations work well enough that intrepid physicists like Loll are now pursuing the ultimate path integral: one that blends all conceivable shapes of space and time and produces a universe shaped like ours as the net result. But in this quest to show that reality is indeed the sum of all possible realities, they face deep confusion about which possibilities should enter the sum. All Roads Lead to One Quantum mechanics really got off the ground in 1926 when Erwin Schrödinger devised an equation describing how the wavelike states of particles evolve from moment to moment. The next decade, Paul Dirac advanced an alternative vision of the quantum world. His was based on the venerable notion that things take the path of “least action” to get from A to B—the route that, loosely speaking, takes the least time and energy. Richard Feynman later stumbled upon Dirac’s work and fleshed out the idea, unveiling the path integral in 1948. The heart of the philosophy is on full display in the quintessential quantum mechanics demonstration: the double-slit experiment. Physicists fire particles at a barrier with two slits in it and observe where the particles land on a wall behind the barrier. If particles were bullets, they’d form a cluster behind each slit. Instead, particles land along the back wall in repeating stripes. The experiment suggests that what moves through the slits is actually a wave representing the particle’s possible locations. The two emerging wavefronts interfere with each other, producing a series of peaks where the particle might end up being detected. Original story reprinted with permission from Quanta Magazine, an editorially independent publication of the Simons Foundation whose mission is to enhance public understanding of science by covering research developments and trends in mathematics and the physical and life sciences.
MIT physicsts identified new multilayered configurations of graphene that can be twisted and stacked to elicit robust superconductivity at low temperatures. The study establishes these configurations as the first known “family” of multilayer magic-angle superconductors. When it comes to graphene, it appears that superconductivity runs in the family. Graphene is a single-atom-thin material that can be exfoliated from the same graphite that is found in pencil lead. The ultrathin material is made entirely from carbon atoms that are arranged in a simple hexagonal pattern, similar to that of chicken wire. Since its isolation in 2004, graphene has been found to embody numerous remarkable properties in its single-layer form. In 2018, MIT researchers found that if two graphene layers are stacked at a very specific “magic” angle, the twisted bilayer structure could exhibit robust superconductivity, a widely sought material state in which an electrical current can flow through with zero energy loss. Recently, the same group found a similar superconductive state exists in twisted trilayer graphene — a structure made from three graphene layers stacked at a precise, new magic angle. Now the team reports that — you guessed it — four and five graphene layers can be twisted and stacked at new magic angles to elicit robust superconductivity at low temperatures. This latest discovery, published this week in Nature Materials, establishes the various twisted and stacked configurations of graphene as the first known “family” of multilayer magic-angle superconductors. The team also identified similarities and differences between graphene family members. The findings could serve as a blueprint for designing practical, room-temperature superconductors. If the properties among family members could be replicated in other, naturally conductive materials, they could be harnessed, for instance, to deliver electricity without dissipation or build magnetically levitating trains that run without friction. “The magic-angle graphene system is now a legitimate ‘family,’ beyond a couple of systems,” says lead author Jeong Min (Jane) Park, a graduate student in MIT’s Department of Physics. “Having this family is particularly meaningful because it provides a way to design robust superconductors.”
In recent years, artificial intelligence has become ubiquitous, with applications such as speech interpretation, image recognition, medical diagnosis, and many more. At the same time, quantum technology has been proven capable of computational power well beyond the reach of even the world’s largest supercomputer. Quantum physicists at the University of Vienna have now demonstrated a new device, called quantum memristor, which may allow to combine these two worlds, thus unlocking unprecedented capabilities. The experiment, carried out in collaboration with the National Research Council (CNR) and the Politecnico di Milano in Italy, has been realized on an integrated quantum processor operating on single photons. The work is published in the current issue of the journal "Nature Photonics". At the heart of all artificial intelligence applications are mathematical models called neural networks. These models are inspired by the biological structure of the human brain, made of interconnected nodes. Just like our brain learns by constantly rearranging the connections between neurons, neural networks can be mathematically trained by tuning their internal structure until they become capable of human-level tasks: recognizing our face, interpreting medical images for diagnosis, even driving our cars. Having integrated devices capable of performing the computations involved in neural networks quickly and efficiently has thus become a major research focus, both academic and industrial. One of the major game changers in the field was the discovery of the memristor, made in 2008. This device changes its resistance depending on a memory of the past current, hence the name memory-resistor, or memristor. Immediately after its discovery, scientists realized that (among many other applications) the peculiar behavior of memristors was surprisingly similar to that of neural synapses. The memristor has thus become a fundamental building block of neuromorphic architectures. By using single photons, i.e. single quantum particles of lights, and exploiting their unique ability to propagate simultaneously in a superposition of two or more paths, the physicists have overcome the challenge. In their experiment, single photons propagate along waveguides laser-written on a glass substrate and are guided on a superposition of several paths. One of these paths is used to measure the flux of photons going through the device and this quantity, through a complex electronic feedback scheme, modulates the transmission on the other output, thus achieving the desired memristive behavior. Besides demonstrating the quantum memristor, the researchers have provided simulations showing that optical networks with quantum memristor can be used to learn on both classical and quantum tasks, hinting at the fact that the quantum memristor may be the missing link between artificial intelligence and quantum computing.
Atomic clocks are the best sensors mankind has ever built. Today, they can be found in national standards institutes or satellites of navigation systems. Scientists all over the world are working to further optimize the precision of these clocks. Now, a research group led by Peter Zoller, a theorist from Innsbruck, Austria, has developed a new concept that can be used to operate sensors with even greater precision irrespective of which technical platform is used to make the sensor. "We answer the question of how precise a sensor can be with existing control capabilities, and give a recipe for how this can be achieved," explain Denis Vasilyev and Raphael Kaubrügger from Peter Zoller's group at the Institute of Quantum Optics and Quantum Information at the Austrian Academy of Sciences in Innsbruck. For this purpose, the physicists use a method from quantum information processing: Variational quantum algorithms describe a circuit of quantum gates that depends on free parameters. Through optimization routines, the sensor autonomously finds the best settings for an optimal result. "We applied this technique to a problem from metrology—the science of measurement," Vasilyev and Kaubrügger explain. "This is exciting because historically advances in atomic physics were motivated by metrology, and in turn quantum information processing emerged from that. So, we've come full circle here," Peter Zoller says. With the new approach, scientists can optimize quantum sensors to the point where they achieve the best possible precision technically permissible. Better measurements with little extra effort For some time, it has been understood that atomic clocks could run even more accurately by exploiting quantum mechanical entanglement. However, there has been a lack of methods to realize robust entanglement for such applications. The Innsbruck physicists are now using tailor-made entanglement that is precisely tuned to real-world requirements. With their method, they generate exactly the combination consisting of quantum state and measurements that is optimal for each individual quantum sensor. This allows the precision of the sensor to be brought close to the optimum possible according to the laws of nature, with only a slight increase in overhead. "In the development of quantum computers, we have learned to create tailored entangled states," says Christian Marciniak from the Department of Experimental Physics at the University of Innsbruck. "We are now using this knowledge to build better sensors." Demonstrating quantum advantage with sensors This theoretical concept was now implemented in practice for the first time at the University of Innsbruck, as the research group led by Thomas Monz and Rainer Blatt now reported in Nature. The physicists performed frequency measurements based on variational quantum calculations on their ion trap quantum computer. Because the interactions used in linear ion traps are still relatively easy to simulate on classical computers, the theory colleagues were able to check the necessary parameters on a supercomputer at the University of Innsbruck. Although the experimental setup is by no means perfect, the results agree surprisingly well with the theoretically predicted values. Since such simulations are not feasible for all sensors, the scientists demonstrated a second approach: They used methods to automatically optimize the parameters without prior knowledge. "Similar to machine learning, the programmable quantum computer finds its optimal mode autonomously as a high-precision sensor," says experimental physicist Thomas Feldker, describing the underlying mechanism.
Researchers show how intelligent aliens might draw nearly-limitless power from a black hole using a Dyson sphere. The search for extraterrestrial intelligence (SETI) has been conducted for nearly 60 yr. A Dyson sphere, a spherical structure that surrounds a star and transports its radiative energy outwards as an energy source for an advanced civilization, is one of the main targets of SETI to identify intelligent aliens around galactic energy sources. Recently, astronomers analyzed whether building a Dyson sphere around a black hole is effective. They considered six energy sources: (i) the cosmic microwave background, (ii) the Hawking radiation, (iii) an accretion disc, (iv) Bondi accretion, (v) a corona, and (vi) relativistic jets. To develop future civilizations (for example, a Type II civilization), 4×1026W(1L⊙)4×1026W(1L⊙) is expected to be needed. Among (iii) to (vi), the largest luminosity can be collected from an accretion disc, reaching 105L⊙105L⊙, enough to maintain a Type II civilization. Moreover, if a Dyson sphere collects not only the electromagnetic radiation but also other types of energy (e.g. kinetic energy) from the jets, the total collected energy would be approximately 5 times larger. Considering the emission from a Dyson sphere, their analysis shows that the Dyson sphere around a stellar-mass black hole in the Milky Way (10kpc away from us) should be detectable in the ultraviolet (10−400nm)(10−400nm), optical (400−760nm)(400−760nm), near-infrared (760nm−5μm760nm−5μm), and mid-infrared (5−40μm5−40μm) wavelengths via the waste heat radiation using current telescopes such as Galaxy Evolution Explorer Ultraviolet Sky Surveys. Performing model fitting to observed spectral energy distributions and measuring the variability of radial velocity may help astronomers to identify these possible artificial structures.
Physicists have performed an improved measurement of the free neutron lifetime using the UCNτ apparatus at the Los Alamos Neutron Science Center. Their results, published in the journal Physical Review Letters, represent a more than two-fold improvement over previous measurements. Gonzalez et al. report an improved measurement of the free neutron lifetime. “This work sets a new gold-standard for a measurement that has fundamental importance to such questions as the relative abundances of the elements created in the early Universe,” said Dr. David Baxter, chair of the Department of Physics at Indiana University Bloomington.
“The process by which a neutron decays into a proton — with an emission of a light electron and an almost massless neutrino — is one of the most fascinating processes known to physicists,” added Dr. Daniel Salvat, also from the Department of Physics at Indiana University Bloomington.
“The effort to measure this value very precisely is significant because understanding the precise lifetime of the neutron can shed light on how the Universe developed — as well as allow physicists to discover flaws in our model of the subatomic Universe that we know exist but nobody has yet been able to find.”
The UCNτ experiment captures neutrons, whose temperatures are lowered to nearly absolute zero, inside a ‘bathtub’ lined with about 4,000 magnets. After waiting 30 to 90 min, the physicists count the surviving neutrons in the tub as they’re levitated against gravity by the force of the magnets.
The unique design of the UCNτ trap allows neutrons to remain stored for more than 11 days, a significantly longer time than earlier designs, minimizing the need for systematic corrections that could skew the results of the lifetime measurements. Over two years, the authors counted 38 million neutrons captured using this method. Their experiment gave a value for the free neutron lifetime of 877.75 seconds.
The thorny thought experiment has been turned into a real experiment — one that physicists use to probe the physics of information. In the thought experiment, Maxwell imagined splitting a room full of gas into two compartments by erecting a wall with a small door. Like all gases, this one is made of individual particles. The average speed of the particles corresponds to the temperature of the gas — faster is hotter. But at any given time, some particles will be moving more slowly than others. What if, suggested Maxwell, a tiny imaginary creature — a demon, as it was later called — sat at the door. Every time it saw a fast-moving particle approaching from the left-hand side, it opened the door and let it into the right-hand compartment. And every time a slow-moving particle approached from the right, the demon let it into the left-hand compartment. After a while, the left-hand compartment would be full of slow, cold particles, and the right-hand compartment would grow hot. This isolated system would seem to grow more orderly, not less, because two distinguishable compartments have more order than two identical compartments. Maxwell had created a system that appeared to defy the rise of entropy, and thus the laws of the universe. “He tried to prove a system where the entropy would decrease,” said Laia Delgado Callico, a physicist at King’s College London. “It’s a paradox.”
Via Complexity Digest
A team of physicists from the Harvard-MIT Center for Ultracold Atoms and other universities has developed a special type of quantum computer known as a programmable quantum simulator capable of operating with 256 quantum bits, or "qubits." The system marks a major step toward building large-scale quantum machines that could be used to shed light on a host of complex quantum processes and eventually help bring about real-world breakthroughs in material science, communication technologies, finance, and many other fields, overcoming research hurdles that are beyond the capabilities of even the fastest supercomputers today. Qubits are the fundamental building blocks on which quantum computers run and the source of their massive processing power. "This moves the field into a new domain where no one has ever been to thus far," said Mikhail Lukin, the George Vasmer Leverett Professor of Physics, co-director of the Harvard Quantum Initiative, and one of the senior authors of the study published today in the journal Nature. "We are entering a completely new part of the quantum world." According to Sepehr Ebadi, a physics student in the Graduate School of Arts and Sciences and the study's lead author, it is the combination of system's unprecedented size and programmability that puts it at the cutting edge of the race for a quantum computer, which harnesses the mysterious properties of matter at extremely small scales to greatly advance processing power. Under the right circumstances, the increase in qubits means the system can store and process exponentially more information than the classical bits on which standard computers run. "The number of quantum states that are possible with only 256 qubits exceeds the number of atoms in the solar system," Ebadi said, explaining the system's vast size. Already, the simulator has allowed researchers to observe several exotic quantum states of matter that had never before been realized experimentally, and to perform a quantum phase transition study so precise that it serves as the textbook example of how magnetism works at the quantum level. These experiments provide powerful insights on the quantum physics underlying material properties and can help show scientists how to design new materials with exotic properties. The project uses a significantly upgraded version of a platform the researchers developed in 2017, which was capable of reaching a size of 51 qubits. That older system allowed the researchers to capture ultra-cold rubidium atoms and arrange them in a specific order using a one-dimensional array of individually focused laser beams called optical tweezers. This new system allows the atoms to be assembled in two-dimensional arrays of optical tweezers. This increases the achievable system size from 51 to 256 qubits. Using the tweezers, researchers can arrange the atoms in defect-free patterns and create programmable shapes like square, honeycomb, or triangular lattices to engineer different interactions between the qubits.
MIT researchers develop compact on-chip device for detecting electric-field waveforms with attosecond time resolution. Understanding how light waves oscillate in time as they interact with materials is essential to understanding light-driven energy transfer in materials, such as solar cells or plants. Due to the fantastically high speeds at which light waves oscillate, however, scientists have yet to develop a compact device with enough time resolution to directly capture them. Now, a team led by MIT researchers has demonstrated chip-scale devices that can directly trace the weak electric field of light waves as they change in time. Their device, which incorporates a microchip that uses short laser pulses and nanoscale antennas, is easy to use, requiring no special environment for operation, minimal laser parameters, and conventional laboratory electronics. The team’s work, published earlier this month in Nature Photonics, may enable the development of new tools for optical measurements with applications in areas such as biology, medicine, food safety, gas sensing, and drug discovery. “The potential applications of this technology are many,” says co-author Phillip Donnie Keathley, group leader and Research Laboratory of Electronics (RLE) research scientist. “For instance, using these optical sampling devices, researchers will be able to better understand optical absorption pathways in plants and photovoltaics, or to better identify molecular signatures in complex biological systems.”
Via Tony Shan
Scientists have created a new class of laser beam that appears to violate long-held laws of light physics. These new beams, which the team calls “spacetime wave packets,” follow different rules of refraction, which could lead to new communication technologies Light travels at different speeds through different media, slowing down in denser materials. It’s a phenomenon that’s best summed up in a basic, middle-school science experiment: if you place a spoon in a glass of water, the spoon will appear to be broken at the water’s surface. That’s because the light is traveling slower through the water than the air, and the light rays bend as they enter the water – a phenomenon known as Snell’s Law. But the new laser beams don’t follow this basic law of light. And it’s not just Snell’s Law either – the team says they also ignore Fermat’s Principle, which says that light always takes the shortest possible path. “This new class of laser beams has unique properties that are not shared by common laser beams,” says Ayman Abouraddy, principal investigator of the study. “Spacetime wave packets can be arranged to behave in the usual manner, to not change speed at all, or even to anomalously speed up in denser materials. As such, these pulses of light can arrive at different points in space at the same time.” This has some major implications for optical communications technologies. The team uses the example of a plane sending messages encoded in light to two submarines, at the same depth but different distances away. Normally, the message would arrive at the closer sub first, but with spacetime wave packets the pulses could be propagated to reach both at the exact same time.
Via Sepp Hasslberger
The Kavli Institute for the Physics and Mathematics of the Universe (Kavli IPMU) is home to many interdisciplinary projects which benefit from the synergy of a wide range of expertise available at the institute. One such project is the study of black holes that could have formed in the early universe, before stars and galaxies were born. Such primordial black holes (PBHs) could account for all or part of dark matter, be responsible for some of the observed gravitational waves signals, and seed supermassive black holes found in the center of our Galaxy and other galaxies. They could also play a role in the synthesis of heavy elements when they collide with neutron stars and destroy them, releasing neutron-rich material. In particular, there is an exciting possibility that the mysterious dark matter, which accounts for most of the matter in the universe, is composed of primordial black holes. The 2020 Nobel Prize in physics was awarded to a theorist, Roger Penrose, and two astronomers, Reinhard Genzel and Andrea Ghez, for their discoveries that confirmed the existence of black holes. Since black holes are known to exist in nature, they make a very appealing candidate for dark matter. The recent progress in fundamental theory, astrophysics, and astronomical observations in search of PBHs has been made by an international team of particle physicists, cosmologists and astronomers, including Kavli IPMU members Alexander Kusenko, Misao Sasaki, Sunao Sugiyama, Masahiro Takada and Volodymyr Takhistov. To learn more about primordial black holes, the research team looked at the early universe for clues. The early universe was so dense that any positive density fluctuation of more than 50 percent would create a black hole. However, cosmological perturbations that seeded galaxies are known to be much smaller. Nevertheless, a number of processes in the early universe could have created the right conditions for the black holes to form. One exciting possibility is that primordial black holes could form from the “baby universes” created during inflation, a period of rapid expansion that is believed to be responsible for seeding the structures we observe today, such as galaxies and clusters of galaxies. During inflation, baby universes can branch off of our universe. A small baby (or “daughter”) universe would eventually collapse, but the large amount of energy released in the small volume causes a black hole to form. An even more peculiar fate awaits a bigger baby universe. If it is bigger than some critical size, Einstein's theory of gravity allows the baby universe to exist in a state that appears different to an observer on the inside and the outside. An internal observer sees it as an expanding universe, while an outside observer (such as us) sees it as a black hole. In either case, the big and the small baby universes are seen by us as primordial black holes, which conceal the underlying structure of multiple universes behind their “event horizons.” The event horizon is a boundary below which everything, even light, is trapped and cannot escape the black hole.
A team of scientists at the Freie Universität in Berlin has developed an artificial intelligence (AI) method for calculating the ground state of the Schrödinger equation. The goal was to predict chemical and physical properties of molecules based solely on the arrangement of their atoms in space, avoiding the need for resource-intensive and time-consuming laboratory experiments. In principle, this can be achieved by solving the Schrödinger equation, but in practice this is extremely difficult. Up until now, it has been impossible to find an exact solution for arbitrary molecules that can be efficiently computed. But the team at the Freie Universität Berlin has developed an AI deep learning method that can achieve an unprecedented combination of accuracy and computational efficiency. AI has transformed many technological and scientific areas, from computer vision to materials science. “We believe that our approach may significantly impact the future of quantum chemistry,” says Professor Frank Noé, who led the team effort. The results were published in the reputed journal Nature Chemistry. Central to both quantum chemistry and the Schrödinger equation is the wave function – a mathematical object that completely specifies the behavior of the electrons in a molecule. The wave function is a high-dimensional entity, and it is therefore extremely difficult to capture all the nuances that encode how the individual electrons affect each other. Many methods of quantum chemistry in fact give up on expressing the wave function altogether, instead attempting only to determine the energy of a given molecule. This however requires approximations to be made, limiting the prediction quality of such methods. Other methods represent the wave function with the use of an immense number of simple mathematical building blocks, but such methods are so complex that they are impossible to put into practice for more than a mere handful of atoms. “Escaping the usual trade-off between accuracy and computational cost is the highest achievement in quantum chemistry,” explains Dr. Jan Hermann of Freie Universität Berlin, who designed the key features of the method in the study. “As yet, the most popular such outlier is the extremely cost-effective density functional theory. We believe that deep “Quantum Monte Carlo,” the approach we are proposing, could be equally, if not more successful. It offers unprecedented accuracy at a still acceptable computational cost.”
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Recently, researchers have published an important white paper identifying activities in particle physics where burgeoning quantum-computing technologies could be applied. The paper, authored by experts from CERN, DESY, IBM Quantum and over 30 other organisations, is now available on ArXiv. With quantum-computing technologies rapidly improving, the paper sets out where these could be applied within particle physics, in order to help tackle computing challenges related not only to the Large Hadron Collider’s ambitious upgrade program, but also to other colliders and low energy experiments world-wide. The paper was produced by a working group set up at the first-of-its-kind “QT4HEP” conference, held at CERN last November. Over the last eight months, the 46 people in this working group have worked hard to identify areas where quantum-computing technologies could provide a significant boon. The areas identified relate to both theoretical and experimental particle physics. The paper then maps these areas to “problem formulations” in quantum computing. This is an important step in ensuring that the particle physics community is well positioned to benefit from the massive potential of breakthrough new quantum computers when they come online. “Quantum computing is very promising, but not every problem in particle physics is suited to this mode of computing,” says Alberto Di Meglio, head of the CERN Quantum Technology Initiative (CERN QTI). “It’s important to ensure that we are ready and that we can accurately identify the areas where these technologies have the potential to be most useful for our community.” In terms of theoretical particle physics, the authors identify promising areas related to evolution of the quantum states, lattice-gauge theory, neutrino oscillations, and quantum field theories in general as well. The considered applications include quantum dynamics, hybrid quantum/classical algorithms for static problems in lattice gauge theory, optimisation, and classification. The lead authors of the paper CERN QTI’s Alberto Di Meglio, DESY’s Karl Jansen, and IBM Quantum’s Ivano Tavernelli, state that “with quantum computing we address problems in those areas that are very hard – or even impossible to tackle with classical methods. “In this way,” Jansen says, “we can explore the physical systems to which we still do not have access.” On the experimental side, the authors identify areas related to jet and track reconstruction, extraction of rare signals, for-and-beyond Standard Model problems, parton showers, and experiment simulation. These are then mapped to classification, regression, optimisation, and generation problems. Members of the working group behind this paper will now begin a process of selecting specific use cases from the activities listed in the paper to be taken forward through the CERN’s and DESY’s participation in the IBM Quantum Network, and collaboration with IBM Quantum, under its “100x100 Challenge”. IBM Quantum is long-standing collaborator to CERN QTI and the Center for Quantum Technologies and Applications (CQTA) at DESY.
Cosmologists are getting closer to understanding what the future and ultimate fate of the universe will be. Late last century, one of the most pressing issues in modern cosmology was to measure the deceleration rate of the universe. Given the amount of mass observed in the cosmos it was thought that it might be enough to cause an eventual contraction of the expansion. Remarkably, two independent teams of scientists found the exact opposite. The universe was not slowing down in its expansion, it was accelerating. This profound discovery lead to the Nobel prize in physics in 2011. However, understanding the implications of it remains challenging. One way to think about the accelerating universe is that there must be some kind of material (or field) that permeates the universe that exerts a negative pressure (or a repulsive gravity). We call this dark energy. This may sound a bit far-fetched, but independent experiments have been conducted to corroborate the acceleration of the universe and the existence of dark energy. From 2006, I was involved in the WiggleZ Dark Energy Survey – a scientific experiment to independently confirm the acceleration. Not only did we find that the acceleration is happening, but we provided compelling evidence that the cause of this was dark energy. We observed that dark energy was retarding the growth of massive superclusters of galaxies. The growth rate of superclusters like Virgo is providing strong evidence for the existence of dark energy.
We therefore think that dark energy is real. If the concept of dark energy and its repulsive gravitation force is too weird, then an alternative to consider is that perhaps our theory of gravitation needs to be modified. This might be achieved in in a similar way that relativity advanced Newtonian gravitation. Either way, we need new physics to explain it. The future Before turning to the very distant future, I will mention another relevant survey: GAMA. Using that survey, we found that the universe is slowing "dying". Put another way: the peak era of star formation is well behind us, and the universe is already fading. The more "immediate" future can be predicted with some certainty. Five billion years from now, the sun will enter its red giant phase. Depressingly, no more than two more billion years after that, it will consume Earth. After that, the relative strength of dark energy and how it might vary over time becomes important. The stronger and faster the repulsive force of dark energy is, the more likely it is that the universe will experience a Big Rip. Put bluntly: the Big Rip is what happens when the repulsive force of dark energy is able to overcome gravitation (and everything else). Bodies that are gravitationally bound (such as our local supercluster, our own Milky Way galaxy, our solar system, and eventually ourselves) become ripped apart and all that is left is (probably) lonesome patches of vacuum. The data from the WiggleZ survey and other experiments do not rule out the Big Rip, but push it in to the exceptionally far future (if at all). Somewhat more pressing is the heat death of the universe. As the universe carries on expanding, we will no longer be able to observe galaxies outside our local group (100 million years from now). Star formation will then cease in about 1-100 trillion years as the supply of gas needed will be exhausted. While there will be some stars around, these will run out of fuel in some 120 trillion years. All that is left at that point is stellar remnants: black holes, neutron stars, & white dwarfs being the prime examples. One hundred quintillion (10<sup>20) years from now, most of these objects will be swallowed up by the supermassive black holes at the heart of galaxies.
Spurred on by quantum experiments that scramble the ordering of causes and their effects, some physicists are figuring out how to abandon causality altogether. Quantum researchers now have shown that quantum theory allows for transformations of black boxes that cannot be realized by inserting the input black boxes within a circuit in a pre-defined causal order. The simplest example of such a transformation is the classical switch of black boxes, where two input black boxes are arranged in two different orders conditionally on the value of a classical bit. The quantum version of this transformation-the quantum switch-produces an output circuit where the order of the connections is controlled by a quantum bit, which becomes entangled with the circuit structure. Simulating these transformations in a circuit with fixed causal structure requires either postselection, or an extra query to the input black boxes.
Researchers have developed a new high-purity single-photon source that can operate at room temperature. The source is an important step toward practical applications of quantum technology, such as highly secure communication based on quantum key distribution (QKD). "We developed an on-demand way to generate photons with high purity in a scalable and portable system that operates at room temperature," said Helen Zeng, a member of the research team from the University of Technology Sydney in Australia. "Our single-photon source could advance the development of practical QKD systems and can be integrated into a variety of real-world quantum photonic applications." In the Optica Publishing Group journal Optics Letters, Zeng and colleagues from Australia's University of New South Wales and Macquarie University describe their new single-photon source and show that it can produce over ten million single photons per second at room temperature. They also incorporated the single-photon source into a fully portable device that can perform QKD. The new single-photon source uniquely combines a 2-D material called hexagonal boron nitride with an optical component known as a hemispherical solid immersion lens, which increases the source's efficiency by a factor of six. Single photons at room temperature QKD offers impenetrable encryption for data communication by using the quantum properties of light to generate secure random keys for encrypting and decrypting data. QKD systems require robust and bright sources that emit light as a string of single photons. However, most of today's single-photon sources don't perform well unless operated at cryogenic temperatures hundreds of degrees below zero, which limits their practicality. Although hexagonal boron nitride has previously been used to create a single-photon source that operates at room temperature, until now researchers had not been able to achieve the efficiency needed for real-world application. "Most approaches used to improve hexagonal boron nitride single-photon sources rely on precisely positioning the emitter or using nano-fabrication," said Zeng. "This makes the devices complex, difficult to scale and not easy to mass produce." Zeng and colleagues set out to create a better solution by using a solid immersion lens to focus the photons coming from the single-photon emitter, allowing more photons to be detected. These lenses are commercially available and easy to fabricate. The researchers combined their new single-photon source with a custom-built portable confocal microscope that can measure the single photons at room temperature, creating a system that can perform QKD. The single-photon source and confocal microscope are housed inside a robust package that measures just 500 x 500 millimeters and weighs around 10 kilograms. The package is also engineered to deal with vibration and stray light. "Our streamlined device is easier to use and much smaller than traditional optical table setups, which often take up entire labs," said Zeng. "This allows the system to be used with a range of quantum computing schemes. It could also be adapted to work with existing telecommunications infrastructure."
Everything you can see, and everything you could possibly see, right now, assuming your eyes could detect all types of radiations around you -- is the observable universe. In light, the farthest we can see comes from the cosmic microwave background, a time 13.8 billion years ago when the universe was opaque like thick fog. Some neutrinos and gravitational waves that surround us come from even farther out, but humanity does not yet have the technology to detect them. The featured image illustrates the observable universe on an increasingly compact scale, with the Earth and Sun at the center surrounded by our Solar System, nearby stars, nearby galaxies, distant galaxies, filaments of early matter, and the cosmic microwave background. Cosmologists typically assume that our observable universe is just the nearby part of a greater entity known as "the universe" where the same physics applies. However, there are several lines of popular but speculative reasoning that assert that even our universe is part of a greater multiverse where either different physical constants occur, different physical laws apply, higher dimensions operate, or slightly different-by-chance versions of our standard universe exist.
Modern machine learning techniques, including deep learning, is rapidly being applied, adapted, and developed for high energy physics. The goal of this review document is to provide a nearly comprehensive list of citations for those developing and applying these approaches to experimental, phenomenological, or theoretical analyses. As a living document, it will be updated as often as possible to incorporate the latest developments. A list of proper (unchanging) reviews can be found within. Papers are grouped into a small set of topics to be as useful as possible. Suggestions are most welcome. The purpose of this site is to collect references for modern machine learning as applied to particle physics. A minimal number of categories is chosen in order to be as useful as possible. Note that papers may be referenced in more than one category. The fact that a paper is listed in this document does not endorse or validate its content - that is for the community (and for peer-review) to decide. Furthermore, the classification here is a best attempt and may have flaws - please let us know if (a) we have missed a paper you think should be included, (b) a paper has been misclassified, or (c) a citation for a paper is not correct or if the journal information is now available. In order to be as useful as possible, this document will continue to evolve so please check back before you write your next paper. If you find this review helpful, please consider citing it using {hepmllivingreview} in HEPML.bib.
Ultrafast electron microscope opens up new avenues for the development of sensors and quantum devices. Everyone who has ever been to the Grand Canyon can relate to having strong feelings from being close to one of nature's edges. Similarly, scientists at the U.S. Department of Energy's (DOE) Argonne National Laboratory have discovered that nanoparticles of gold act unusually when close to the edge of a one-atom thick sheet of carbon, called graphene. This could have big implications for the development of new sensors and quantum devices. This new discovery was made possible with a newly established ultrafast electron microscope (UEM) at Argonne's Center for Nanoscale Materials (CNM), a DOE Office of Science User Facility. The UEM enables the visualization and investigation of phenomena at the nanoscale and on time frames of less than a trillionth of a second. This discovery could make a splash in the growing field of plasmonics, which involves light striking a material surface and triggering waves of electrons, known as plasmonic fields. "With these ultrafast capabilities, there is no telling what we might see as we tweak different materials and their properties." -- Haihua Liu, Argonne nanoscientist. For years, scientists have been pursuing development of plasmonic devices with a wide range of applications -- from quantum information processing to optoelectronics (which combine light-based and electronic components) to sensors for biological and medical purposes. To do so, they couple two-dimensional materials with atomic-level thickness, such as graphene, with nanosized metal particles. Understanding the combined plasmonic behavior of these two different types of materials requires understanding exactly how they are coupled. In a recent study from Argonne, researchers used ultrafast electron microscopy to look directly at the coupling between gold nanoparticles and graphene. "Surface plasmons are light-induced electron oscillations on the surface of a nanoparticle or at an interface of a nanoparticle and another material," said Argonne nanoscientist Haihua Liu. "When we shine a light on the nanoparticle, it creates a short-lived plasmonic field. The pulsed electrons in our UEM interact with this short-lived field when the two overlap, and the electrons either gain or lose energy. Then, we collect those electrons that gain energy using an energy filter to map the plasmonic field distributions around the nanoparticle." In studying the gold nanoparticles, Liu and his colleagues discovered an unusual phenomenon. When the nanoparticle sat on a flat sheet of graphene, the plasmonic field was symmetric. But when the nanoparticle was positioned close to a graphene edge, the plasmonic field concentrated much more strongly near the edge region. "It's a remarkable new way of thinking about how we can manipulate charge in the form of a plasmonic field and other phenomena using light at the nanoscale," Liu said. "With ultrafast capabilities, there's no telling what we might see as we tweak different materials and their properties."
Materials scientists can now shuffle layered compounds together, much like combining two different decks of cards. The technique, recently discovered by a team of researchers at the U.S. Department of Energy's Ames Laboratory, is leading to development of new materials with unusual electron transport properties that have potential applications in next-generation quantum technologies. The discovered technique has shown another unexpected and promising application in new materials design. The "reshuffling" approach can generate thermally stable three-dimensional (3D) heterostructures from layered transition metal dichalcogenides (TMDCs). These are van der Waals materials composed of metal nanolayers sandwiched between two other layers of chalcogens—sulfur, selenium, or tellurium. Similar to graphite, these compounds can be exfoliated into 2D layers, which display unique electron transport properties and quantum phenomena. "TMDCs are very intriguing to researchers as a possibility for applications in renewable energy, catalysis and optoelectronics, to name only a few," said project leader Viktor Balema, a Senior Scientist in the Divisions of Materials Sciences and Engineering at Ames Laboratory. "Our goal in research has been the development of such re-assembly methods for these layered materials, which are not only efficient, but also scalable and cost effective in production." Researchers at Ames Laboratory have been successful in overcoming one of the major challenges of composing these layered materials—the difficulty of sandwiching together atomically dissimilar, incommensurate, materials—through the use of mechanochemistry that is facilitated by ball milling. "Now, we have demonstrated that we can mechanochemically design novel layered heterostructures, control their composition and tune their properties," said Ihor Hlova, a scientist in the Divisions of Materials Sciences and Engineering at Ames Laboratory. "This opens a way to a variety of different combinations—the possibilities are basically unlimited."
A recent study led by Princeton University researchers, in collaboration with University of Maryland and IBM, explored the architectural design of quantum computers (QC). In a paper presented at the 2019 ACM/IEEE International Symposium on Computer Architecture, the researchers performed the largest real-system evaluation of quantum computers to date, using seven quantum computers from IBM, Rigetti and the University of Maryland. The researchers developed new software to compile from QC applications to hardware prototypes; on error-prone early-stage QC hardware, this compiler delivers up to 28 times improvement in program correctness rates compared to industry compilers. The study stresses the importance of careful instruction set design, rich connectivity topologies and the need to co-design applications and hardware to achieve the best performance from fledgling QC systems.
Via Scott Turner
Fiber optic technology is the holy grail of high-speed, long-distance telecommunications. Still, with the continuing exponential growth of internet traffic, researchers are warning of a capacity crunch. In AVS Quantum Science, researchers from the National Institute of Standards and Technology and the University of Maryland show how quantum-enhanced receivers could play a critical role in addressing this challenge. The scientists developed a method to enhance receivers based on quantum physics properties to dramatically increase network performance while significantly reducing the error bit rate (EBR) and energy consumption. Fiber optic technology relies on receivers to detect optical signals and convert them into electrical signals. The conventional detection process, largely as a result of random light fluctuations, produces 'shot noise,' which decreases detection ability and increases EBR. To accommodate this problem, signals must continually be amplified as pulsating light becomes weaker along the optic cable, but there is a limit to maintaining adequate amplification when signals become barely perceptible. Quantum-enhanced receivers that process up to two bits of classical information and can overcome the shot noise have been demonstrated to improve detection accuracy in laboratory environments. In these and other quantum receivers, a separate reference beam with a single-photon detection feedback is used so the reference pulse eventually cancels out the input signal to eliminate the shot noise. The researchers' enhanced receiver, however, can decode as many as four bits per pulse, because it does a better job in distinguishing among different input states. To accomplish more efficient detection, they developed a modulation method and implemented a feedback algorithm that takes advantage of the exact times of single photon detection. Still, no single measurement is perfect, but the new holistically designed communication system yields increasingly more accurate results on average. "We studied the theory of communications and the experimental techniques of quantum receivers to come up with a practical telecommunication protocol that takes maximal advantage of the quantum measurement," author Sergey Polyakov said. "With our protocol, because we want the input signal to contain as few photons as possible, we maximize the chance that the reference pulse updates to the right state after the very first photon detection, so at the end of the measurement, the EBR is minimized."
Sometimes, it’s easy for a computer to predict the future. Simple phenomena, such as how sap flows down a tree trunk, are straightforward and can be captured in a few lines of code using what mathematicians call linear differential equations. But in nonlinear systems, interactions can affect themselves: When air streams past a jet’s wings, the air flow alters molecular interactions, which alter the air flow, and so on. This feedback loop breeds chaos, where small changes in initial conditions lead to wildly different behavior later, making predictions nearly impossible — no matter how powerful the computer.
Via Complexity Digest
Tokamaks, devices that use magnetic fields to confine plasma into torus-shaped chamber, could play a crucial role in the development of highly performing nuclear fusion reactors. The ITER tokamak, which is set to be the largest nuclear tokamak in the world, is particularly likely to shape the way in which nuclear reactors will be fabricated in the future. ITER is a highly complex technology that uses entirely new strategies, which means that those building it are confronting challenges that have never been faced before. To facilitate the design and operation of the ITER tokamak, scientists worldwide have been conducting what are known as nuclear analyses, which are aimed at theoretically examining its outcomes and potential. So far, nuclear analyses based on data gathered by the ITER reactor have relied on detailed but partial models that only represent specific parts of the tokamak. However, these models present limitations and unquantified uncertainties that become evident as the design of the machine advances. Those related to its safety and operation are of particular relevance. With this in mind, researchers at Universidad Nacional de Educación a Distancia (UNED) have recently developed E-lite, a detailed and realistic Monte Carlo N-particle transport (MCNP) model of the ITER tokamak. This model, presented in a paper published in Nature Energy, has the potential to dramatically improve the reliability and precision of nuclear analyses assessing this magnetic fusion device. "Due to the computational limitations of a couple of decades ago, the ITER neutronics community worldwide, including ourselves (the TECF3IR research team at UNED), have so far been working using partial models of the ITER tokamak," Rafael Juarez, one of the researchers who carried out the study, told Phys.org. "Since then, however, computer power has evolved significantly. Furthermore, in recent years, the computational codes that we use have undergone advances as well, some of them enabled by TECF3IR."
Via Theo J. Mertzimekis
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