Computers Math

MIT physicists have discovered a new quantum bit, or “qubit,” in the form of vibrating pairs of atoms known as fermions. They found that when pairs of fermions are chilled and trapped in an optical lattice, the particles can exist simultaneously in two states — a weird quantum phenomenon known as superposition. In this case, the atoms held a superposition of two vibrational states, in which the pair wobbled against each other while also swinging in sync, at the same time.
The team was able to maintain this state of superposition among hundreds of vibrating pairs of fermions. In so doing, they achieved a new “quantum register,” or system of qubits, that appears to be robust over relatively long periods of time. The discovery, published today in the journal Nature, demonstrates that such wobbly qubits could be a promising foundation for future quantum computers.
A qubit represents a basic unit of quantum computing. Where a classical bit in today’s computers carries out a series of logical operations starting from one of either two states, 0 or 1, a qubit can exist in a superposition of both states. While in this delicate in-between state, a qubit should be able to simultaneously communicate with many other qubits and process multiple streams of information at a time, to quickly solve problems that would take classical computers years to process.
There are many types of qubits, some of which are engineered and others that exist naturally. Most qubits are notoriously fickle, either unable to maintain their superposition or unwilling to communicate with other qubits.
By comparison, the MIT team’s new qubit appears to be extremely robust, able to maintain a superposition between two vibrational states, even in the midst of environmental noise, for up to 10 seconds. The team believes the new vibrating qubits could be made to briefly interact, and potentially carry out tens of thousands of operations in the blink of an eye.
“We estimate it should take only a millisecond for these qubits to interact, so we can hope for 10,000 operations during that coherence time, which could be competitive with other platforms,” says Martin Zwierlein, the Thomas A. Frank Professor of Physics at MIT. “So, there is concrete hope toward making these qubits compute.”
Zwierlein is a co-author on the paper, along with lead author Thomas Hartke, Botond Oreg, and Ningyuan Jia, who are all members of MIT’s Research Laboratory of Electronics. More

Engineering researchers from North Carolina State University have demonstrated a new type of flexible, robotic grippers that are able to lift delicate egg yolks without breaking them, and that are precise enough to lift a human hair. The work has applications for both soft robotics and biomedical technologies.
The work draws on the art of kirigami, which involves both cutting and folding two-dimensional (2D) sheets of material to form three-dimensional (3D) shapes. Specifically, the researchers have developed a new technique that involves using kirigami to convert 2D sheets into curved 3D structures by cutting parallel slits across much of the material. The final shape of the 3D structure is determined in large part by the outer boundary of the material. For example, a 2D material that has a circular boundary would form a spherical 3D shape.
“We have defined and demonstrated a model that allows users to work backwards,” says Yaoye Hong, first author of a paper on the work and a Ph.D. student at NC State. “If users know what sort of curved, 3D structure they need, they can use our approach to determine the boundary shape and pattern of slits they need to use in the 2D material. And additional control of the final structure is made possible by controlling the direction in which the material is pushed or pulled.”
“Our technique is quite a bit simpler than previous techniques for converting 2D materials into curved 3D structures, and it allows designers to create a wide variety of customized structures from 2D materials,” says Jie Yin, corresponding author of the paper and an associate professor of mechanical and aerospace engineering at NC State.
The researchers demonstrated the utility of their technique by creating grippers capable of grabbing and lifting objects ranging from egg yolks to a human hair.
“We’ve shown that our technique can be used to create tools capable of grasping and moving even extremely fragile objects,” Yin says.
“Conventional grippers grasp an object firmly — they grab things by putting pressure on them,” Yin says. “That can pose problems when attempting to grip fragile objects, such as egg yolks. But our grippers essentially surround an object and then lift it — similar to the way we cup our hands around an object. This allows us to ‘grip’ and move even delicate objects, without sacrificing precision.”
However, the researchers note that there are a host of other potential applications, such as using the technique to design biomedical technologies that conform to the shape of a joint — like the human knee.
“Think of smart bandages or monitoring devices capable of bending and moving with your knee or elbow,” Yin says.
“This is proof-of-concept work that shows our technique works,” Yin says. “We’re now in the process of integrating this technique into soft robotics technologies to address industrial challenges. We are also exploring how this technique could be used to create devices that could be used to apply warmth to the human knee, which would have therapeutic applications.
“We’re open to working with industry partners to explore additional applications and to find ways to move this approach from the lab into practical use.”
Video of the technology can be found at https://youtu.be/1oEXhKBoYc8.
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Materials provided by North Carolina State University. Original written by Matt Shipman. Note: Content may be edited for style and length. More

New research from the Institute of Psychiatry, Psychology & Neuroscience (IoPPN) at King’s College London suggests that a virtual reality test in which participants “go to the shops” could offer a potentially promising way of effectively assessing functional cognition, the thinking and processing skills needed to accomplish complex everyday activities.
The research, published in the Journal of Medical Internet Research, uses a novel virtual reality shopping task called “VStore” to measure cognition, which asks participants to take part in tests designed to mirror the real world. Researchers hope that it will be able to test for age-related cognitive decline in the future.
The trial recruited 142 healthy individuals aged 20-79 years. Each participant was asked to “go to the shops,” first verbally recalling a list of 12 items, before being assessed for the amount of time it took to collect the items, as well as select the corresponding items on a virtual self-checkout machine, pay, and order coffee.
Cognition tests, such as those used to measure the deficits present in several neuropsychiatric disorders including Alzheimer’s disease, schizophrenia, and depression, are traditionally time-consuming and onerous. Vstore — the technology that the researchers used in this study — is designed to overcome these limitations to provide a more accurate, engaging, and cost-effective process to explore a person’s cognitive health.
The immersive environment (a virtual shop) mirrored the complexity of everyday life and meant that participants were better able to engage brain structures that are associated with spatial navigation, such as the hippocampus and entorhinal cortex, both of which can be affected in the early stages of Alzheimer disease.
Researchers were able to establish that Vstore effectively engages a range of key neuropsychological functions simultaneously, suggesting that the functional tasks embedded in virtual reality may engage a greater range of cognitive domains than standard assessments.
Prof Sukhi Shergill, the study’s lead author from King’s IoPPN and Kent and Medway Medical School (KMMS) said, “Virtual Reality appears to offer us significant advantages over more traditional pen-and-paper methods. The simple act of going to a shop to collect and pay for a list of items is something that we are all familiar with, but also actively engages multiple parts of the brain. Our study suggests that VStore may be suitable for evaluating functional cognition in the future. However, more works needs to be done before we can confirm this.”
Lilla Porffy, the study’s first author from King’s IoPPN said, “These are promising findings adding to a growing body of evidence showing that virtual reality can be used to measure cognition and related everyday functioning effectively and accurately. The next steps will be to confirm these results and expand research into conditions characterised by cognitive complaints and functional difficulties such as psychosis and Alzheimer’s Disease.”
This study was possible thanks to funding from the Medical Research Council and the National Institute for Health Research Maudsley Biomedical Research Centre. VStore was designed by Vitae VR.
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A Lancaster physicist has proposed a radical solution to the question of how a charged particle, such as an electron, responded to its own electromagnetic field.
This question has challenged physicists for over 100 years but mathematical physicist Dr Jonathan Gratus has suggested an alternative approach — published in the Journal of Physics A- with controversial implications.
It is well established that if a point charge accelerates it produces electromagnetic radiation. This radiation has both energy and momentum, which must come from somewhere. It is usually assumed that they come from the energy and momentum of the charged particle, damping the motion.
The history of attempts to calculate this radiation reaction (also known as radiation damping) date back to Lorentz in 1892. Major contributions were then made by many well known physicists including Plank, Abraham, von Laue, Born, Schott, Pauli, Dirac and Landau. Active research continues to this day with many articles published every year.
The challenge is that according to Maxwell’s equations, the electric field at the actual point where the point particle is, is infinite. Hence the force on that point particle should also be infinite.
Various methods have been used to renormalise away this infinity. This leads to the well established Lorentz-Abraham-Dirac equation.
Unfortunately, this equation has well known pathological solutions. For example, a particle obeying this equation may accelerate forever with no external force or accelerate before any force is applied. There is also the quantum version of radiation damping. Ironically, this is one of the few phenomena where the quantum version occurs at lower energies than the classical one.
Physicists are actively searching for this effect. This requires `colliding’ very high energy electrons and powerful laser beams, a challenge as the biggest particle accelerators are not situated near the most powerful lasers. However, firing lasers into plasmas will produce high energy electron, which can then interact with the laser beam. This only requires a powerful laser. Current results show that quantum radiation reaction does exist.
The alternative approach is to consider many charged particles, where each particle responds to the fields of all the other charged particles, but not itself. This approach was hitherto dismissed, since it was assumed that this would not conserve energy and momentum.
However, Dr Gratus shows that this assumption is false, with the energy and momentum of one particle’s radiation coming from the external fields used to accelerate it.
He said: “The controversial implications of this result is that there need not be classical radiation reaction at all. We may therefore consider the discovery of quantum radiation reaction as similar to the discovery of Pluto, which was found following predictions based on discrepancies in the motion of Neptune. Corrected calculations showed there were no discrepancies. Similarly radiation reaction was predicted, found and then shown not to be needed.”
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Researchers in the Stephenson School of Biomedical Engineering, Gallogly College of Engineering, at the University of Oklahoma have developed a framework published in Science Advances that solves the challenge of bridging experimental and computer sciences to better predict peptide structures. Peptide-based materials have been used in energy, security and health fields for the past two decades.
Handan Acar, Ph.D., the Peggy and Charles Stephenson Assistant Professor of Biomedical Engineering at OU, teamed up with Andrew White, Ph.D., an associate professor of chemical engineering at the University of Rochester, to introduce a new strategy to study fundamentals of molecular engineering. Seren Hamsici, a doctoral student in Acar’s lab, is the first author of the study.
Proteins are responsible for the structure, function and regulation of the body’s organs and tissues. They are formed by amino acids and come together in different interactions, called intermolecular interactions, that are essential to how proteins perform different roles in the body. When these protein interactions behave abnormally, medical issues result, such as when they clump together to form plaques in the brain that leads to Alzheimer’s Disease.
“In the peptide-engineering field, the general approach is to take those natural proteins and make incremental changes to identify the properties of the end aggregated products, and then find an application for which the identified properties would be useful,” Acar said. “However, there are more than 500 natural and unnatural amino acids. Especially when you consider the size of the peptides, this approach is just not practical.”
Machine learning has great potential to counter this challenge, but Acar says the complex way peptides assemble and disassemble has prevented artificial intelligence methods from being effective so far.
“Clearly, computational methods, such as machine learning, are necessary,” she said. “Yet, the peptide aggregation is very complex. It is currently not possible to identify the effects of individual amino acids with computational methods.”
To counter those challenges, the research team came up with a new approach. They developed a framework that would help bridge materials science and engineering research with computational science to lay the groundwork for artificial intelligence and machine learning advancements. More

Plaque formation in the arteries carrying blood to the head and neck is a serious medical problem, potentially leading to strokes and heart attacks. In Physics of Fluids, by AIP Publishing, engineers from China use fluid dynamics simulations to study the effect of exercise at various ages on plaque formation.
It has been known for years that exercise and age affect the formation of plaques through a process known as atherosclerosis. What has not been fully understood, however, is how the geometrical features of the arteries affect plaque formation, although a dilated region in the inner carotid branch, the sinus, appears to be a vulnerable site.
“It is commonly accepted that the disturbed flow induces atherosclerosis,” said author Xiaolei Yang.
To study this, the authors considered two arterial geometries, one with a bulging outer artery and the other without, and modeled the effect of exercise and age on blood flow through the two model arteries.
Two main arteries carrying blood to the head and neck, known as the carotid arteries, branch off from a single large artery at a position near the thyroid gland. One branch, the internal carotid artery, or ICA, carries blood inside the cranium to the brain, while the external carotid artery remains outside the cranium and brings blood to the neck, face, and scalp.
Just above the bifurcation, the ICA bulges outward, forming a region known as a sinus that is sensitive to blood pressure changes and helps regulate blood flow and heart rate.
“Our work investigated the patterns of disturbed blood flow in two different model carotids, one with high risk geometrical factors and the other without,” co-author Xinyi He said.
She explained high-risk factors include high flare and low proximal curvature in the sinus. Flare is defined as the ratio of the maximum cross section in the sinus bulb to its minimal value, while proximal curvature measures how much the artery curves above the bifurcation point.
To model exercise, the authors digitized blood flow measurements from individuals in three different age groups: 32-34, 54-55, and 62-63. These digitized flowrates were used as input to their computational model.
“Overall, the effects of exercise are different for different people. Particularly, we show that exercising decreases the reversed flow volume for the 62-63 age group with the low-risk carotid, which is probably related to the decrease of systolic time interval,” said Yang.
He said this suggests that evaluating the effect of exercise on atherosclerosis requires consideration of patient-specific geometries and ages.
“For the current findings to become helpful, the analysis should be coupled to physiological and chemical processes occurring at the cellular level,” Yang said, indicating this would be the subject of the group’s future work.
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Quantum computers are expected to be disruptive and potentially impact many industry sectors. So researchers in the United Kingdom and the Netherlands decided to explore two very different quantum problems: breaking the encryption of Bitcoin (a digital currency) and simulating the molecule responsible for biological nitrogen fixation.
In AVS Quantum Science, from AIP Publishing, the researchers describe a tool they created to determine how big a quantum computer needs to be to solve problems like these and how long it will take.
“The majority of existing work within this realm focuses on a particular hardware platform, superconducting devices, like those IBM and Google are working toward,” said Mark Webber, of the University of Sussex. “Different hardware platforms will vary greatly on key hardware specifications, such as the rate of operations and the quality of control on the qubits (quantum bits).”
Many of the most promising quantum advantage use cases will require an error-corrected quantum computer. Error correction enables running longer algorithms by compensating for inherent errors inside the quantum computer, but it comes at the cost of more physical qubits.
Pulling nitrogen out of the air to make ammonia for fertilizers is extremely energy-intensive, and improvements to the process could impact both world food scarcity and the climate crisis. Simulation of relevant molecules is currently beyond the abilities of even the world’s fastest supercomputers but should be within the reach of next-gen quantum computers.
“Our tool automates the calculation of the error-correction overhead as a function of key hardware specifications,” Webber said. “To make the quantum algorithm run faster, we can perform more operations in parallel by adding more physical qubits. We introduce extra qubits as needed to reach the desired runtime, which is critically dependent on the rate of operations at the physical hardware level.”
Most quantum computing hardware platforms are limited, because only qubits right next to each other can interact directly. In other platforms, such as some trapped ion designs, the qubits are not in fixed positions and can instead be physically moved around — meaning each qubit can interact directly with a wide set of other qubits. More

Scientists have developed an artificial intelligence (AI) system that can analyse eye scans taken during a routine visit to an optician or eye clinic and identify patients at a high risk of a heart attack.
Doctors have recognised that changes to the tiny blood vessels in the retina are indicators of broader vascular disease, including problems with the heart.
In the research, led by the University of Leeds, deep learning techniques were used to train the AI system to automatically read retinal scans and identify those people who, over the following year, were likely to have a heart attack.
Deep learning is a complex series of algorithms that enable computers to identify patterns in data and to make predictions.
Writing in the journal Nature Machine Intelligence, the researchers report that the AI system had an accuracy of between 70% and 80% and could be used as a second referral mechanism for in-depth cardiovascular investigation.
The use of deep learning in the analysis of retinal scans could revolutionise the way patients are regularly screened for signs of heart disease. More