Computers Math

Recently, electric vehicles (EVs) are seen everywhere, from passenger cars, buses, to taxis. EVs have the advantage of being eco-friendly and having low maintenance costs; but their owners must remain wary of fatal accidents in case the battery runs out or reaches the end of its life. Therefore, precise capacity and lifespan predictions for the lithium-ion batteries — commonly used in EVs — are vital.
A POSTECH research team led by Professor Seungchul Lee, and Ph.D. candidate Sung Wook Kim (Department of Mechanical Engineering) collaborated with Professor Ki-Yong Oh of Hanyang University to develop a novel artificial intelligence (AI) technology that can accurately predict the capacity and lifespan of lithium-ion batteries. This research breakthrough, which considerably improved the prediction accuracy by merging physical domain knowledge with AI, has recently been published in Applied Energy, an international academic journal in the energy field.
There are two methods of predicting the battery capacity: a physics-based model, which simplifies the intricate internal structure of batteries, and an AI model, which uses the electrical and mechanical responses of batteries. However, the conventional AI model required large amounts of data for training. In addition, when applied to untrained data, its prediction accuracy was very low, which desperately called for the emergence of a next-generation AI technology.
To effectively predict battery capacity with less training data, the research team combined a feature extraction strategy that differs from conventional methods with physical domain knowledge-based neural networks. As a result, the battery prediction accuracy for testing batteries with various capacities and lifespan distributions improved by up to 20%. Its reliability was ensured by confirming the consistency of the results. These outcomes are anticipated to lay the foundation for applying highly dependable physical domain knowledge-based AI to various industries.
Professor Lee of POSTECH remarked, “The limitations of data-based AI have been overcome using physics knowledge. The difficulty of building big data has also been alleviated thanks to the development of the differentiated feature extraction technique.”
Professor Oh of Hanyang University added, “Our research is significant in that it will contribute in propagating EVs to the public by enabling accurate predictions of remaining lifespan of batteries in next-generational EVs.”
This study was supported by the Institute of Civil Military Technology Cooperation and the National Research Foundation of Korea.
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Materials provided by Pohang University of Science & Technology (POSTECH). Note: Content may be edited for style and length. More

Sensors are a constant feature of our everyday lives. Although they often go unperceived, sensors provide critical information essential to modern healthcare, security, and environmental monitoring. Modern cars alone contain over 100 sensors and this number will only increase.
Quantum sensing is poised to revolutionise today’s sensors, significantly boosting the performance they can achieve. More precise, faster, and reliable measurements of physical quantities can have a transformative effect on every area of science and technology, including our daily lives.
However, the majority of quantum sensing schemes rely on special entangled or squeezed states of light or matter that are hard to generate and detect. This is a major obstacle to harnessing the full power of quantum-limited sensors and deploying them in real-world scenarios.
In a paper published today, a team of physicists at the Universities of Bristol, Bath and Warwick have shown it is possible to perform high precision measurements of important physical properties without the need for sophisticated quantum states of light and detection schemes.
The key to this breakthrough is the use of ring resonators — tiny racetrack structures that guide light in a loop and maximize its interaction with the sample under study. Importantly, ring resonators can be mass manufactured using the same processes as the chips in our computers and smartphones.
Alex Belsley, Quantum Engineering Technology Labs (QET Labs) PhD student and lead author of the work, said: “We are one step closer to all integrated photonic sensors operating at the limits of detection imposed by quantum mechanics.”
Employing this technology to sense absorption or refractive index changes can be used to identify and characterise a wide range of materials and biochemical samples, with topical applications from monitoring greenhouse gases to cancer detection.
Associate Professor Jonathan Matthews, co-Director of QET Labs and co-author of the work, stated: “We are really excited by the opportunities this result enables: we now know how to use mass manufacturable processes to engineer chip scale photonic sensors that operate at the quantum limit.”
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Researchers at the Niels Bohr Institute, University of Copenhagen, have improved the coherence time of a previously developed quantum membrane dramatically. The improvement will expand the usability of the membrane for a variety of different purposes. With a coherence time of one hundred milliseconds, the membrane can for example store sensitive quantum information for further processing in a quantum computer or network. The result has now been published in Nature Communications.
The quantum drum is now connected to a read-out unit
As a first step, the team of researchers has combined the membrane with a superconducting microwave circuit, which enables precise readouts from the membrane. That is, it has become “plugged in,” as required for virtually any application. With this development, the membrane can be connected to various other devices that process or transmit quantum information.
Cooling the quantum drum system to reach quantum ground state
Since the temperature of the environment determines the level of random forces disturbing the membrane, it is imperative to reach a sufficiently low temperature to prevent the quantum state of motion from being washed out. The researchers achieve this by means of a helium-based refrigerator. With the help of the microwave circuit, they can then control the quantum state of the membrane motion. In their recent work, the researchers could prepare the membrane in the quantum ground state, meaning that its motion is dominated by quantum fluctuations. The quantum ground state corresponds to an effective temperature of 0,00005 degrees above the absolute zero, which is −273.15 °C.
Applications for the plugged in quantum membrane are many
One could use a slightly modified version of this system that can feel forces from both microwave and optical signals to build a quantum transducer from microwave to optics. Quantum information can be transported at room temperature in optical fibers on kilometers without perturbations. On the other hand, the information is typically processed inside a cooling unit, capable of reaching sufficiently low temperatures for superconducting circuits like the membrane to operate. Connecting these two systems — superconducting circuits to optical fibers — could therefore enable the construction of a quantum internet: several quantum computers linked together with optical fibers. No computers have infinite space, so the possibility of distributing computational capabilities to connected quantum computers, would greatly enhance the capacity to solve complicated problems.
Gravity — not well understood in quantum mechanics, but crucial — can now be explored
The role of gravity in the quantum regime is a yet unanswered, fundamental question in physics. This is yet another place where the high coherence time of the membranes demonstrated here may be applied for study. One hypothesis in this area is that gravity has the potential to destroy some quantum states with time. With a device as big as the membrane, such hypotheses may be tested in the future.
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Photonics researchers have introduced a novel method to control a light beam with another beam through a unique plasmonic metasurface in a linear medium at ultra-low power. This simple linear switching method makes nanophotonic devices such as optical computing and communication systems more sustainable requiring low intensity of light.
All-optical switching is the modulation of signal light due to control light in such a way that it possesses the ON/OFF conversion function. In general, a light beam can be modulated with another intense laser beam in the presence of a nonlinear medium.
The switching method developed by the researchers is fundamentally based on the quantum optical phenomenon known as Enhancementof Index of Refraction (EIR).
“Our work is the first experimental demonstration of this effect on the optical system and its utilization for linear all-optical switching. The research also enlightens the scientific community to achieve loss-compensated plasmonic devices operating at resonance frequencies through extraordinary enhancement of refractive index without using any gain media or nonlinear processes,” says Humeyra Caglayan, Associate Professor (tenure track) in Photonics at Tampere University.
Optical switching enabled with ultrafast speed
High-speed switching and low-loss medium to avoid the strong dissipation of signal during propagation are the basis to develop integrated photonic technology where photons are utilized as information carriers instead of electrons. To realize on-chip ultrafast all-optical switch networks and photonic central processing units, all-optical switching must have ultrafast switching time, ultralow threshold control power, ultrahigh switching efficiency, and nanoscale feature size. More

The second century Alexandrian astronomer and mathematician Claudius Ptolemy had a grand ambition. Hoping to make sense of the motion of stars and the paths of planets, he published a magisterial treatise on the subject, known as the Almagest. Ptolemy created a complex mathematical model of the universe that seemed to recapitulate the movements of the celestial objects he observed.
Unfortunately, a fatal flaw lay at the heart of his cosmic scheme. Following the prejudices of his day, Ptolemy worked from the premise that the Earth was the center of the universe. The Ptolemaic universe, composed of complex “epicycles” to account for planet and star movements, has long since been consigned to the history books, though its conclusions remained the scientific dogma for over 1200 years.
The field of evolutionary biology is no less subject to misguided theoretical approaches, sometimes producing impressive models that nevertheless fail to convey the true workings of nature as it shapes the dizzying assortment of living forms on Earth.
A new study examines mathematical models designed to draw inferences about how evolution operates at the level of populations of organisms. The study concludes that such models must be constructed with the greatest care, avoiding unwarranted initial assumptions, weighing the quality of existing knowledge and remaining open to alternate explanations.
Failure to apply strict procedures in null model construction can lead to theories that seem to square with certain aspects of available data derived from DNA sequencing, yet fail to correctly elucidate underlying evolutionary processes, which are often highly complex and multifaceted.
Such theoretical frameworks may offer compelling but ultimately flawed pictures of how evolution actually acts on populations over time, be these populations of bacteria, shoals of fish, or human societies and their various migrations during prehistory. More

Atoms do weird things when forced out of their comfort zones. Rice University engineers have thought up a new way to give them a nudge.
Materials theorist Boris Yakobson and his team at Rice’s George R. Brown School of Engineering have a theory that changing the contour of a layer of 2D material, thus changing the relationships between its atoms, might be simpler to do than previously thought.
While others twist 2D bilayers — two layers stacked together — of graphene and the like to change their topology, the Rice researchers suggest through computational models that growing or stamping single-layer 2D materials on a carefully designed undulating surface would achieve “an unprecedented level of control” over their magnetic and electronic properties.
They say the discovery opens a path to explore many-body effects, the interactions between multiple microscopic particles, including quantum systems.
The paper by Yakobson and two alumni, co-lead author Sunny Gupta and Henry Yu, of his lab appears in Nature Communications.
The researchers were inspired by recent discoveries that twisting or otherwise deforming 2D materials bilayers like bilayer graphene into “magic angles” induced interesting electronic and magnetic phenomena, including superconductivity. More

Birmingham scientists have revealed a new beam-steering antenna that increases the efficiency of data transmission for ‘beyond 5G’ — and opens up a range of frequencies for mobile communications that are inaccessible to currently used technologies.
Experimental results, presented today for the first time at the 3rd International Union of Radio Science Atlantic / Asia-Pacific Radio Science Meeting, show the device can provide continuous ‘wide-angle’ beam steering, allowing it to track a moving mobile phone user in the same way that a satellite dish turns to track a moving object, but with significantly enhanced speeds.
Devised by researchers from the University of Birmingham’s School of Engineering, the technology has demonstrated vast improvements in data transmissoin efficiency at frequencies ranging across the millimetre wave spectrum, specifically those identified for 5G (mmWave) and 6G, where high efficiency is currently only achievable using slow, mechanically steered antenna solutions.
For 5G mmWave applications, prototypes of the beam-steering antenna at 26 GHz have shown unprecedented data transmission efficiency.
The device is fully compatible with existing 5G specifications that are currently used by mobile communications networks. Moreover, the new technology does not require the complex and inefficient feeding networks required for commonly deployed antenna systems, instead using a low complexity system which improves performance and is simple to fabricate.
The beam-steering antenna was developed by Dr James Churm, Dr Muhammad Rabbani, and Professor Alexandros Feresidis, Head of the Metamaterials Engineering Laboratory, as a solution for fixed, base station antenna, for which current technology shows reduced efficiency at higher frequencies, limiting the use of these frequencies for long-distance transmission. More

In the fall of 2017, geology professor Patricia Gregg and her team had just set up a new volcanic forecasting modeling program on the Blue Waters and iForge supercomputers. Simultaneously, another team was monitoring activity at the Sierra Negra volcano in the Galapagos Islands, Ecuador. One of the scientists on the Ecuador project, Dennis Geist of Colgate University, contacted Gregg, and what happened next was the fortuitous forecast of the June 2018 Sierra Negra eruption five months before it occurred.
Initially developed on an iMac computer, the new modeling approach had already garnered attention for successfully recreating the unexpected eruption of Alaska’s Okmok volcano in 2008. Gregg’s team, based out of the University of Illinois Urbana-Champaign and the National Center for Supercomputing Applications, wanted to test the model’s new high-performance computing upgrade, and Geist’s Sierra Negra observations showed signs of an imminent eruption.
“Sierra Negra is a well-behaved volcano,” said Gregg, the lead author of a new report of the successful effort. “Meaning that, before eruptions in the past, the volcano has shown all the telltale signs of an eruption that we would expect to see like groundswell, gas release and increased seismic activity. This characteristic made Sierra Negra a great test case for our upgraded model.”
However, many volcanoes don’t follow these neatly established patterns, the researchers said. Forecasting eruptions is one of the grand challenges in volcanology, and the development of quantitative models to help with these trickier scenarios is the focus of Gregg and her team’s work.
Over the winter break of 2017-18, Gregg and her colleagues ran the Sierra Negra data through the new supercomputing-powered model. They completed the run in January 2018 and, even though it was intended as a test, it ended up providing a framework for understanding Sierra Negra’s eruption cycles and evaluating the potential and timing of future eruptions — but nobody realized it yet.
“Our model forecasted that the strength of the rocks that contain Sierra Negra’s magma chamber would become very unstable sometime between June 25 and July 5, and possibly result in a mechanical failure and subsequent eruption,” said Gregg, who also is an NCSA faculty fellow. “We presented this conclusion at a scientific conference in March 2018. After that, we became busy with other work and did not look at our models again until Dennis texted me on June 26, asking me to confirm the date we had forecasted. Sierra Negra erupted one day after our earliest forecasted mechanical failure date. We were floored.”
Though it represents an ideal scenario, the researchers said, the study shows the power of incorporating high-performance supercomputing into practical research. “The advantage of this upgraded model is its ability to constantly assimilate multidisciplinary, real-time data and process it rapidly to provide a daily forecast, similar to weather forecasting,” said Yan Zhan, a former Illinois graduate student and co-author of the study. “This takes an incredible amount of computing power previously unavailable to the volcanic forecasting community.” More