Lifeboat Foundation

The single-loop contribution of Higgs bosons to the radiation shift of the energy of an electron moving in a homogeneous permanent magnetic field is calculated. On the basis of this contribution, the appropriate contribution to the anomalous magnetic moment of the electron and the probability of magnetic-braking radiation of Higgs bosons by an electron are found. The dependence of the mentioned quantities on the electron energy and the external field intensity is investigated.

Detecting landmines can be a challenging and slow process. Detecting them from a moving vehicle would make the process more speedy, but at the expense of accuracy.

At the Optical Society’s (OSA) Laser Congress, held 29 September—3 October 2019 in Vienna, Austria, researchers from the University of Mississippi, U.S.A., will report a new laser-based sensor that effectively detects buried objects even while the detector is in motion. This new device offers a significant improvement over existing technologies, which cannot be operated on the go and lose accuracy in the presence of external sources of sound or vibration.

Laser Doppler vibrometers (LDVs) combined with vibration excited in the ground have shown promise for detecting landmines and other buried objects, but their sensitivity to environmental vibrations mean they must be operated from a special stable platform. The device, called a Laser Multi Beam Differential Interferometric Sensor (LAMBDIS), provides comparable detection capabilities but is far less sensitive to motion, allowing it to be used aboard a moving vehicle.

Cambridge engineers have developed a new augmented reality (AR) head mounted display (HMD) that delivers a realistic 3D viewing experience, without the commonly associated side effects of nausea or eyestrain.

The device has an enlarged eye-box that is scalable and an increased field of view of 36º that is designed for a comfortable viewing experience. It displays images on the retina using pixel beam scanning which ensures the image stays in focus regardless of the distance that the user is fixating on. Details are reported in the journal Research.

Developed by researchers at the Centre for Advanced Photonics and Electronics (CAPE) in collaboration with Huawei European Research Centre, in Munich, the HMD uses partially reflective beam splitters to form an additional “exit pupil” (a virtual opening through which light travels). This, together with narrow pixel beams that travel parallel to each other, and which do not disperse in other directions, produces a high quality image that remains unaffected by changes in eye focus.

New technological devices are prioritizing non-invasive tracking of vital signs, not only for fitness monitoring, but also for the prevention of common health problems such as heart failure, hypertension and stress-related complications, among others. Wearables based on optical detection mechanisms are proving an invaluable approach for reporting on our bodies inner workings and have experienced a large penetration into the consumer market in recent years. Current wearable technologies, based on non-flexible components, do not deliver the desired accuracy and can only monitor a limited number of vital signs. To tackle this problem, conformable non-invasive optical-based sensors that can measure a broader set of vital signs are at the top of the end-users’ wish list.

In a recent study published in Science Advances, ICFO researchers have demonstrated a new class of flexible and transparent wearable devices that are conformable to the skin and can provide continuous and accurate measurements of multiple human vital signs. These devices can measure heart rate, respiration rate and blood pulse oxygenation, as well as exposure to UV radiation from the sun. While the device measures the different parameters, the read-out is visualized and stored on a mobile phone interface connected to the wearable via Bluetooth. In addition, the device can operate battery-free since it is charged wirelessly through the phone.

“It was very important for us to demonstrate the wide range of potential applications for our advanced light sensing technology through the creation of various prototypes, including the flexible and transparent bracelet, the health patch integrated on a mobile phone and the UV monitoring patch for sun exposure. They have shown to be versatile and efficient due to these unique features,” reports Dr. Emre Ozan Polat, first author of this publication.

“No organisms are more important to life as we know it than algae. In Slime, Ruth Kassinger gives this under-appreciated group its due. The result is engaging, occasionally icky, and deeply informative.”

—Elizabeth Kolbert, New York Times-bestselling author of the Pulitzer Prize-winner The Sixth Extinction

“A book full of delights and surprises. Algae are the hidden rulers of our world, giving us oxygen, food, and energy. This is a beautiful evocation of the many ways that our past and future are entangled in their emerald strands.”

The code used below is on GitHub.

In this project, we’ll be solving a problem familiar to any physics undergrad — using the Schrödinger equation to find the quantum ground state of a particle in a 1-dimensional box with a potential. However, we’re going to tackle this old standby with a new method: deep learning. Specifically, we’ll use the TensorFlow package to set up a neural network and then train it on random potential functions and their numerically calculated solutions.

Why reinvent the wheel (ground state)? Sure, it’s fun to see a new tool added to the physics problem-solving toolkit, and I needed the practice with TensorFlow. But there’s a far more compelling answer. We know basically everything there is to know about this topic already. The neural network, however, doesn’t know any physics. Crudely speaking, it just finds patterns. Suppose we examine the relative strength of connections between input neurons and output. The structure therein could give us some insight into how the universe “thinks” about this problem. Later, we can apply deep learning to a physics problem where the underlying theory is unknown. By looking at the innards of that neural network, we might learn something new about fundamental physical principles that would otherwise remain obscured from our view. Therein lies the true power of this approach: peering into the mind of the universe itself.

But no, it’s not as smart as a high school student.

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Classical computers struggle to crack modern encryption. But quantum computers using Shor’s Algorithm make short work of RSA cryptography. Find out how.