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Why are neutrinos so light?


Did you know that every second more than 100 trillion tiny particles called neutrinos pass through your body without causing any harm? These mysterious particles are produced abundantly throughout the universe in events like nuclear reactions in the sun, radioactive decays in the Earth’s crust, and in high-energy collisions in space. In particular, these subatomic particles play a crucial role in the explosive deaths of stars known as supernovae, where they act as the driving force behind the explosion. Despite their abundance in the universe, they are incredibly difficult to detect directly in experiments since they pass right through any matter and only interact extremely rarely. At the LHC, their existence can only be inferred indirectly by summing up the energy of all other particles produced from the proton collisions and looking for missing energy that has been carried away by the neutrino, which escaped the experiment undetected.

Neutrinos are a type of fundamental particle known as a lepton and they are electrically neutral. They stand out among fundamental particles because of their peculiar characteristics. Not only do they interact exceptionally rarely, but they also possess a minuscule mass, approximately 500,000 times lighter than that of an electron. One possible explanation for the smallness of their mass is given by the “seesaw” mechanism. According to this theory, there exist additional new fundamental particles that are electrically neutral. The mechanism postulates that the masses of these new particles, known as “heavy neutral leptons” (HNLs), are mathematically linked to those of the normal neutrinos, like two sides of a seesaw. The theory also predicts that the HNLs will “mix” with their known cousins, neutrinos. This means that a neutrino, produced in an LHC collision, can change into an HNL, and the HNL can then decay back into known particles that the LHC experiments can detect!

The seesaw explanation for the neutrino mass is particularly attractive and various searches for HNLs have been performed at the LHC and by other experiments in the past (see an example where CMS muon detectors are exploited in such a search). The CMS Collaboration has recently published a new search that makes the assumption that the mixing between the HNLs and neutrinos is very small. In this special case, the HNL can be “long lived” and travel macroscopic distances away from the collision point before decaying. Experiments can then take advantage of the unusual signatures from these “displaced” particle decays when trying to find evidence for the existence of HNLs.

Intel debuts new chip focused on addressing quantum computing’s wiring bottleneck.

Intel’s millikelvin quantum research control chip, code-named Pando Tree, establishes Intel as the first semiconductor manufacturer to demonstrate the distribution of cryogenic silicon spin qubit control electronics…


Sushil Subramanian is a research scientist at Intel where he works on integrated circuits and systems for qubit control in quantum computers. Co-author Stefano Pellerano is a senior principal engineer and lab director of the RF and Mixed-Signal Circuits Lab where he leads the research and development effort on cryogenic electronics for qubit control.

Researchers at EPFL have discovered that by shining different wavelengths (colors) of light on a material called magnetite, they can change its state, e.g., making it more or less conducive to electricity. The discovery could lead to new ways of designing new materials for electronics such as memory storage, sensors, and other devices that rely on fast and efficient material responses.

As a supplement to optical super-resolution microscopy techniques, computational super-resolution methods have demonstrated remarkable results in alleviating the spatiotemporal imaging trade-off. However, they commonly suffer from low structural fidelity and universality. Therefore, we herein propose a deep-physics-informed sparsity framework designed holistically to synergize the strengths of physical imaging models (image blurring processes), prior knowledge (continuity and sparsity constraints), a back-end optimization algorithm (image deblurring), and deep learning (an unsupervised neural network). Owing to the utilization of a multipronged learning strategy, the trained network can be applied to a variety of imaging modalities and samples to enhance the physical resolution by a factor of at least 1.67 without requiring additional training or parameter tuning.

A trio of physicists, two with Uniwersytet Jagielloński in Poland and one with Swinburne University of Technology in Australia, are proposing the use of temporal printed circuit boards made using time crystals as a way to solve error problems on quantum computers. Krzysztof Giergiel, Krzysztof Sacha and Peter Hannaford have written a paper describing their ideas, which is currently available on the arXiv preprint server.

A collaboration of Professor Szameit’s research group at the University of Rostock with researchers from the Albert-Ludwigs-Universität Freiburg has succeeded in stabilizing the interference of two photons in optical chips with the concept of topologically protected wave propagation. The research results are published in Science.

A group that says they hacked software company CDK Global is demanding tens of millions of dollars in ransom, Bloomberg reported.

CDK, which provides software to car dealerships in North America, intends to pay the ransom but discussions are subject to change, according to Bloomberg’s report which cited a person familiar with the situation.

The source said the group behind the hack is believed to be based in eastern Europe, Bloomberg reported.