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    ‘From Data to Quanta’ defends Niels Bohr’s view of quantum mechanics

    From Data to QuantaSlobodan PerovićUniv. of Chicago, $45

    Ever since Max Planck introduced the idea of the quantum to the world, physicists have argued about whether reality is more like sand or water.

    Planck’s famous 1900 discovery that energy is grainy — at least when absorbed or emitted — moved him to label those smallest bits of energy grains “quanta.” But he believed that once emitted, as in light from a fire, those grains merged into smooth, continuous waves, just as water seems a smooth liquid to human perception. Einstein, on the other hand, insisted that light quanta traveled through space on their own, behaving like particles later called photons.

    By the mid-1920s, both the wave and particle views of light had gained experimental support, with the additional paradox that electrons — supposedly particles — could sometimes disguise themselves as waves.

    Into this arena of controversy stepped the famed Danish physicist Niels Bohr, the pioneer of exploring the architecture of the atom. Bohr announced that resolving the wave-particle paradox required a new view of reality, in which both notions shared a role in explaining experimental phenomena. In experiments designed to observe waves, waves you would find, whether electrons or light. In experiments designed to detect particles, you’d see particles. But in no experiment could you demonstrate both at once. Bohr called this viewpoint the principle of complementarity, and it successfully guided the pursuit of quantum mechanics during the following decades.

    More recently, as philosopher Slobodan Perović recounts in From Data to Quanta, Bohr’s success has been questioned by some physicists and philosophers and even popular science writers (SN: 1/19/19, p. 26). Complementarity has been derided as an incoherent application of vague philosophy expressed in incomprehensible language. But as Perović’s investigations reveal, such criticisms are rarely rooted in any deep understanding of Bohr’s methods. Rather than Bohr’s philosophy contaminating his science, Perović argues, it is his opponents’ philosophical prejudices that have led to misstatements, misunderstandings and misrepresentations of Bohr’s physics. And Bohr can’t be understood by attempting to understand his philosophy, Perović asserts, because philosophy did not guide him — experiments did.

    In fact, Bohr’s drive to understand the wave-particle paradox was fueled by a deep devotion to comprehending the experimental evidence in its totality. It was the same approach the younger Bohr took when developing his model of the atom in 1913 (SN: 7/13/13, p. 20). Various experiments suggested properties of the atom that seemed irreconcilable. But Bohr forged those experimental clues into a “master hypothesis” that produced a thoroughly novel understanding of the atom and its structure.

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    Perović describes how Bohr’s process began with lower-level hypotheses stemming from features directly given by experiment. Spectral lines — different specific colors of light emitted by atoms — led to basic hypotheses that some vibratory process, of an atom itself or its constituents, produced electromagnetic radiation exhibiting precise patterns. Intermediate hypotheses about the structure of the atom did not explain such lines, though. And then Ernest Rutherford, on the basis of experiments in his lab, inferred that an atom was mostly empty space. It contained a dense, tiny central nucleus encompassing most of the mass, while lightweight electrons orbited at a distance. But that hypothesis didn’t mesh with the precise patterns of spectral lines. And such an atom would be unstable, persisting for less than a millisecond. From all these disparate experiment-based hypotheses, Bohr applied Planck’s quantum idea to construct a master hypothesis. He reconciled the spectral lines and Rutherford’s nuclear atom with a new atomic model, in which electrons maintained stability of the atom but jumped from one orbit to another, emitting specific patterns of spectral lines in the process.

    As Perović demonstrates, Bohr followed a similar course in arriving at complementarity. While numerous experiments showed that light was a wave, by the early 1920s other experiments established that X-rays, highly energetic light, collided with electrons just as though both were particles (momentum and energy were conserved in the collisions just as the particle view required). Bohr’s master hypothesis, complementarity, seemed the only way forward.

    Throughout the book, Perović relates how Bohr has been misinterpreted, his views misleadingly conflated with those of others (like John von Neumann and Werner Heisenberg), and his philosophy incorrectly portrayed as antirealist — suggesting that only observations brought reality into existence. Bohr never said any such thing, and in fact cautioned against using language so loosely.

    Perović’s account offers a thorough survey of other historical investigations into Bohr’s work and draws liberally from Bohr’s own writings. It’s a nuanced and insightful presentation of the interplay of experiment and theory in the scientific process. This book is not easy reading, though. It’s not the place to seek clear explanations of quantum physics and Bohr’s interpretation of it. Perović opts for scholarly thoroughness and careful reasoning with a propensity for long sentences. But then again, Bohr’s writings were no breeze, either. In fact, a major complaint against Bohr has been expressed by authors who say his writings are very difficult to understand. It’s unfortunate that so many seem to think that because they can’t understand Bohr, he must have been wrong. Perović’s book provides a useful antidote to that attitude.

    Buy From Data to Quanta from Bookshop.org. Science News is a Bookshop.org affiliate and will earn a commission on purchases made from links in this article. More

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    Researchers use supercomputers for largest-ever turbulence simulations of its kind

    From designing new airplane wings to better understanding how fuel sprays ignite in a combustion engine, researchers have long been interested in better understanding how chaotic, turbulent motions impact fluid flows under a variety of conditions. Despite decades of focused research on the topic, physicists still consider a fundamental understanding of turbulence statistics to be among the last major unsolved challenges in physics.
    Due to its complexity, researchers have come to rely on a combination of experiments, semi-empirical turbulence models, and computer simulation to advance the field. Supercomputers have played an essential role in advancing researchers’ understanding of turbulence physics, but even today’s most computationally expensive approaches have limitations.
    Recently, researchers at the Technical University of Darmstadt (TU Darmstadt) led by Prof. Dr. Martin Oberlack and the Universitat Politècnica de València headed by Prof. Dr. Sergio Hoyas started using a new approach for understanding turbulence, and with the help of supercomputing resources at the Leibniz Supercomputing Centre (LRZ), the team was able to calculate the largest turbulence simulation of its kind. Specifically, the team generated turbulence statistics through this large simulation of the Navier-Stokes equations, which provided the critical data base for underpinning a new theory of turbulence.
    “Turbulence is statistical, because of the random behaviour we observe,” Oberlack said. “We believe Navier-Stokes equations do a very good job of describing it, and with it we are able to study the entire range of scales down to the smallest scales, but that is also the problem — all of these scales play a role in turbulent motion, so we have to resolve all of it in simulations. The biggest problem is resolving the smallest turbulent scales, which decrease inversely with Reynolds number (a number that indicates how turbulent a fluid is moving, based on a ratio of velocity, length scale, and viscosity). For airplanes like the Airbus A 380, the Reynolds number is so large and thus the smallest turbulent scales are so small that they cannot be represented even on the SuperMUC NG.”
    Statistical averages show promise for closing an unending equation loop
    In 2009, while visiting the University of Cambridge, Oberlack had an epiphany — while thinking about turbulence, he thought about symmetry theory, a concept that forms the fundamental basis to all areas of physics research. In essence, the concept of symmetry in mathematics demonstrates that equations can equal the same result even when being done in different arrangements or operating conditions. More

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    Time crystals leave the lab

    We have all seen crystals, whether a simple grain of salt or sugar, or an elaborate and beautiful amethyst. These crystals are made of atoms or molecules repeating in a symmetrical three-dimensional pattern called a lattice, in which atoms occupy specific points in space. By forming a periodic lattice, carbon atoms in a diamond, for example, break the symmetry of the space they sit in. Physicists call this “breaking symmetry.”
    Scientists have recently discovered that a similar effect can be witnessed in time. Symmetry breaking, as the name suggests, can arise only where some sort of symmetry exists. In the time domain, a cyclically changing force or energy source naturally produces a temporal pattern.
    Breaking of the symmetry occurs when a system driven by such a force faces a déjà vu moment, but not with the same period as that of the force. ‘Time crystals’ have in the past decade been pursued as a new phase of matter, and more recently observed under elaborate experimental conditions in isolated systems. These experiments require extremely low temperatures or other rigorous conditions to minimize undesired external influences, called noise.
    In order for scientists to learn more about time crystals and employ their potential in technology, they need to find ways to produce time crystalline states and keep them stable outside the laboratory.
    Cutting-edge research led by UC Riverside and published this week in Nature Communications has now observed time crystals in a system that is not isolated from its ambient environment. This major achievement brings scientists one step closer to developing time crystals for use in real-world applications.
    “When your experimental system has energy exchange with its surroundings, dissipation and noise work hand-in-hand to destroy the temporal order,” said lead author Hossein Taheri, an assistant research professor of electrical and computer engineering in UC Riverside’s Marlan and Rosemary Bourns College of Engineering. “In our photonic platform, the system strikes a balance between gain and loss to create and preserve time crystals.”
    The all-optical time crystal is realized using a disk-shaped magnesium fluoride glass resonator one millimeter in diameter. When bombarded by two laser beams, the researchers observed subharmonic spikes, or frequency tones between the two laser beams, that indicated breaking of temporal symmetry and creation of time crystals.
    The UCR-led team utilized a technique called self-injection locking of the two lasers to the resonator to achieve robustness against environmental effects. Signatures of the temporally repeating state of this system can readily be measured in the frequency domain. The proposed platform therefore simplifies the study of this new phase of matter.
    Without the need for a low temperature, the system can be moved outside a complex lab for field applications. One such application could be highly accurate measurements of time. Because frequency and time are mathematical inverses of each other, accuracy in measuring frequency enables accurate time measurement.
    “We hope that this photonic system can be utilized in compact and lightweight radiofrequency sources with superior stability as well as in precision timekeeping,” said Taheri.
    The open-access Nature Communications paper, “All-optical dissipative discrete time crystals,” is available here. Taheri was joined in the research by Andrey B. Matsko at NASA’s Jet Propulsion Laboratory, Lute Maleki at OEwaves Inc. in Pasadena, Calif., and Krzysztof Sacha at Jagiellonian University in Poland.
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    Materials provided by University of California – Riverside. Original written by Holly Ober. Note: Content may be edited for style and length. More

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    'Math neurons' identified in the brain

    The brain has neurons that fire specifically during certain mathematical operations. This is shown by a recent study conducted by the Universities of Tübingen and Bonn. The findings indicate that some of the neurons detected are active exclusively during additions, while others are active during subtractions. They do not care whether the calculation instruction is written down as a word or a symbol. The results have now been published in the journal Current Biology.
    Most elementary school children probably already know that three apples plus two apples add up to five apples. However, what happens in the brain during such calculations is still largely unknown. The current study by the Universities of Bonn and Tübingen now sheds light on this issue.
    The researchers benefited from a special feature of the Department of Epileptology at the University Hospital Bonn. It specializes in surgical procedures on the brains of people with epilepsy. In some patients, seizures always originate from the same area of the brain. In order to precisely localize this defective area, the doctors implant several electrodes into the patients. The probes can be used to precisely determine the origin of the spasm. In addition, the activity of individual neurons can be measured via the wiring.
    Some neurons fire only when summing up
    Five women and four men participated in the current study. They had electrodes implanted in the so-called temporal lobe of the brain to record the activity of nerve cells. Meanwhile, the participants had to perform simple arithmetic tasks. “We found that different neurons fired during additions than during subtractions,” explains Prof. Florian Mormann from the Department of Epileptology at the University Hospital Bonn.
    It was not the case that some neurons responded only to a “+” sign and others only to a “-” sign: “Even when we replaced the mathematical symbols with words, the effect remained the same,” explains Esther Kutter, who is doing her doctorate in Prof. Mormann’s research group. “For example, when subjects were asked to calculate ‘5 and 3’, their addition neurons sprang back into action; whereas for ‘7 less 4,’ their subtraction neurons did.”
    This shows that the cells discovered actually encode a mathematical instruction for action. The brain activity thus showed with great accuracy what kind of tasks the test subjects were currently calculating: The researchers fed the cells’ activity patterns into a self-learning computer program. At the same time, they told the software whether the subjects were currently calculating a sum or a difference. When the algorithm was confronted with new activity data after this training phase, it was able to accurately identify during which computational operation it had been recorded.
    Prof. Andreas Nieder from the University of Tübingen supervised the study together with Prof. Mormann. “We know from experiments with monkeys that neurons specific to certain computational rules also exist in their brains,” he says. “In humans, however, there is hardly any data in this regard.” During their analysis, the two working groups came across an interesting phenomenon: One of the brain regions studied was the so-called parahippocampal cortex. There, too, the researchers found nerve cells that fired specifically during addition or subtraction. However, when summing up, different addition neurons became alternately active during one and the same arithmetic task. Figuratively speaking, it is as if the plus key on the calculator were constantly changing its location. It was the same with subtraction. Researchers also refer to this as “dynamic coding.”
    “This study marks an important step towards a better understanding of one of our most important symbolic abilities, namely calculating with numbers,” stresses Mormann. The two teams from Bonn and Tübingen now want to investigate exactly what role the nerve cells found play in this.
    The study was funded by the German Research Foundation (DFG) and the Volkswagen Foundation.
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    Materials provided by University of Bonn. Note: Content may be edited for style and length. More

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    Mapping the quantum future with smart TV technology

    Scientists have created the first ever 2D map of the Overhauser field in organic LEDs, shedding light on the challenges we face in designing accurate quantum-based technologies
    Television used to be known as ‘the idiot box’. But the organic LEDs found in modern flat screens are far from stupid.
    In fact, they’re helping us to draw a map that could unlock the quantum future. No wonder they’re now called smart TVs.
    The emerging concept of quantum sensing has the potential to surpass existing technology in areas ranging from electronics and magnetic field detection to microscopy, global positioning systems and seismology.
    By taking advantage of quantum mechanics, new devices could be designed with unprecedented sensitivity and functionality.
    But for this to happen, greater understanding is required of the role played by spin, a fundamental quantum property of subatomic particles such as electrons. More

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    Quest for quantum materials through better measurement of quantum entanglement

    A research team from the Department of Physics, the University of Hong Kong (HKU) has developed a new algorithm to measure entanglement entropy, advancing the exploration of more comprehensive laws in quantum mechanics, a move closer towards actualisation of application of quantum materials.
    This pivotal research work has recently been published in Physical Review Letters.
    Quantum materials play a vital role in propelling human advancement. The search for more novel quantum materials with exceptional properties has been pressing among the scientific and technology community.
    2D Moire materials such as twisted bilayer graphene are having a far-reaching role in the research of novel quantum states such as superconductivity which suffers no electronic resistance. They also play a role in the development of “quantum computers” that vastly outperforming the best supercomputers in existence.
    But materials can only arrive at “quantum state” , i.e. when thermal effects can no longer hinder quantum fluctuations which trigger the quantum phase transitions between different quantum states or quantum phases, at extremely low temperatures (near Absolute Zero, -273.15°C) or under exceptional high pressure. Experiments testing when and how atoms and subatomic particles of different substances “communicate and interact with each other freely through entanglement” in quantum state are therefore prohibitively costly and difficult to execute.
    The study is further complicated by the failure of classical LGW (Landau, Ginzburg, Wilson) framework to describe certain quantum phase transitions, dubbed Deconfined Quantum Critical Points (DQCP). The question then arises whether DQCP realistic lattice models can be found to resolve the inconsistencies between DQCP and QCP. Dedicated exploration of the topic produces copious numerical and theoretical works with conflicting results, and a solution remains elusive. More

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    Combining traditional mandala coloring and brain sensing technologies to aid mindfulness

    Combining centuries-old traditional mandala colouring with cutting-edge computing and brain sensing technologies could lead to new ways of helping people achieve mindfulness.
    Mandalas are geometric configurations of shapes that have their origins in Buddhist traditions. The colouring of mandala shapes is increasingly popular as a way for people to attempt ‘mindfulness’, a way of being present in the moment, and which has been associated with helping people to improve their mental health and wellbeing.
    Human-computer interaction researchers from Lancaster University have developed a new prototype that can monitor people’s brain signals while they are colouring mandalas and produce real-time feedback on a peripheral display to represent levels of mindfulness.
    The researchers, who specialise in thinking about how new computing technologies can be designed to help people, believe systems like these could be developed to aid the learning, and training, of focused attention mindfulness techniques and help people deal with stress, depression and other affective health disorders.
    In the first part of their study, the researchers interviewed experienced mandala practicioners to find out about the special qualities of mandala colouring, and how they can be used to achieve mindfulness, and based the prototype on their findings.
    The prototype, called ‘Anima’, included a tablet device for users to colour mandala shapes, a wearable EEG headset* that reads wearers’ brain signals, and a second display in the shape of an artists’ palette, that is placed in the user’s periphery. More

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    Freshwater ice can melt into scallops and spikes

    Water’s wacky density leads to strange effects that researchers are still uncovering.

    Typically, liquids become denser the more they cool. But freshwater is densest at 4° Celsius. As it cools below that temperature, the water becomes less dense and rises. As a result, ice columns submerged in liquid water can melt into three different shapes, depending on the water’s temperature, researchers report in the Jan. 28 Physical Review Letters.  

    “Almost everything” about the findings was surprising, says mathematician Leif Ristroph of New York University.

    Ristroph and colleagues anchored ultrapure ice cylinders up to 30 centimeters long in place and submerged them in tanks of water at temperatures from 2° to 10° C.

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    The ice melted into smooth, downward-pointing spikes if placed in water lower than about 5° C. Simulations showed “a strange thing — that the cold liquid water near the ice is actually buoyant” due to being less dense than the rest of the water in the tank, Ristroph says. So that upward flow draws warmer water closer to the ice’s base, causing it to melt faster than the top.  

    The opposite occurred above about 7° C; the ice formed an upward-pointing spike. That’s because colder water near the ice is denser than the surrounding water and sinks, pulling in warmer water at the top of the ice and causing it to melt faster than the bottom, simulations showed. This matches “what your intuition would expect,” Ristroph says. 

    Between about 5° to 7° C, the ice melted into scalloped columns. “Basically, the water is confused,” Ristroph says, so it forms different layers, some of which tend to rise and others which tend to sink, depending on their density. Ultimately, the water organizes into “swirls or vortices of fluid that carve the weird ripples into the ice.”

    More work is needed to understand the complex interplay of factors that may generate these and other shapes on ice melting in nature (SN: 4/9/21). More