Lifeboat Foundation

During sleep and awake rest, the neocortex generates large-scale slow-wave (SW) activity. Here, we report that the claustrum coordinates neocortical SW generation. We established a transgenic mouse line that enabled the genetic interrogation of a subpopulation of claustral glutamatergic neurons. These neurons received inputs from and sent outputs to widespread neocortical areas. The claustral neuronal firings mostly correlated with cortical SW activity. In vitro optogenetic stimulation of the claustrum induced excitatory postsynaptic responses in most neocortical neurons, but elicited action potentials primarily in inhibitory interneurons. In vivo optogenetic stimulation induced a synchronized down-state featuring prolonged silencing of neural activity in all layers of many cortical areas, followed by a down-to-up state transition. In contrast, genetic ablation of claustral neurons attenuated SW activity in the frontal cortex. These results demonstrate a crucial role of claustral neurons in synchronizing inhibitory interneurons across wide cortical areas for the spatiotemporal coordination of SW activity.

A list of authors and their affiliations appears at the end of the paper New-particle formation is a major contributor to urban smog^1,2, but how it occurs in cities is often puzzling³. If the growth rates of urban particles are similar to those found in cleaner environments (1–10 nanometres per hour), then existing understanding suggests that new urban particles should be rapidly scavenged by the high concentration of pre-existing particles. Here we show, through experiments performed under atmospheric conditions in the CLOUD chamber at CERN, that below about +5 degrees Celsius, nitric acid and ammonia vapours can condense onto freshly nucleated particles as small as a few nanometres in diameter. Moreover, when it is cold enough (below −15 degrees Celsius), nitric acid and ammonia can nucleate directly through an acid–base stabilization mechanism to form ammonium nitrate particles. Given that these vapours are often one thousand times more abundant than sulfuric acid, the resulting particle growth rates can be extremely high, reaching well above 100 nanometres per hour. However, these high growth rates require the gas-particle ammonium nitrate system to be out of equilibrium in order to sustain gas-phase supersaturations. In view of the strong temperature dependence that we measure for the gas-phase supersaturations, we expect such transient conditions to occur in inhomogeneous urban settings, especially in wintertime, driven by vertical mixing and by strong local sources such as traffic. Even though rapid growth from nitric acid and ammonia condensation may last for only a few minutes, it is nonetheless fast enough to shepherd freshly nucleated particles through the smallest size range where they are most vulnerable to scavenging loss, thus greatly increasing their survival probability. We also expect nitric acid and ammonia nucleation and rapid growth to be important in the relatively clean and cold upper free troposphere, where ammonia can be convected from the continental boundary layer and nitric acid is abundant from electrical storms^4,5.

Temporal changes of inner-core (IC) seismic phases have been confirmed with high-quality waveform doublets. However, the nature of the temporal changes is still controversial. We investigated systematically the temporal changes of IC refracted (PKIKP) and reflected (PKiKP) waves with a large data set of waveform doublets. We used non-IC reference phase (mainly SKP), which eliminated ambiguity where the temporal changes come from. We found that the temporal changes have always started at refracted PKIKP and the travel time changes correlate better with PKIKP. Changes in reflected PKiKP can be easily contaminated by the strong and time-varying PKIKP and coda wave trains and therefore are not reliable indicators for IC boundary changes. Combining with previous observations, we conclude that the temporal changes come mostly (if not all) from the IC interior and IC surface changes as the sole source suggested previously can be ruled out. The differential rotation of the IC shifting its heterogeneous uppermost structures is the simplest and most reasonable explanation for the origin of the time-varying IC waves. A rotation rate of about 0.05–0.1° per year with possible decadal fluctuation can reconcile all temporal change observations from body waves, IC scattering, and normal mode data.

Quantum illumination uses entangled signal-idler photon pairs to boost the detection efficiency of low-reflectivity objects in environments with bright thermal noise. Its advantage is particularly evident at low signal powers, a promising feature for applications such as noninvasive biomedical scanning or low-power short-range radar. Here, we experimentally investigate the concept of quantum illumination at microwave frequencies. We generate entangled fields to illuminate a room-temperature object at a distance of 1 m in a free-space detection setup. We implement a digital phase-conjugate receiver based on linear quadrature measurements that outperforms a symmetric classical noise radar in the same conditions, despite the entanglement-breaking signal path. Starting from experimental data, we also simulate the case of perfect idler photon number detection, which results in a quantum advantage compared with the relative classical benchmark. Our results highlight the opportunities and challenges in the way toward a first room-temperature application of microwave quantum circuits.

Quantum sensing is well developed for photonic applications (1) in line with other advanced areas of quantum information (2–5). Quantum optics has been, so far, the most natural and convenient setting for implementing the majority of protocols in quantum communication, cryptography, and metrology (6). The situation is different at longer wavelengths, such as tetrahertz or microwaves, for which the current variety of quantum technologies is more limited and confined to cryogenic environments. With the exception of superconducting quantum processing (7), no microwave quanta are typically used for applications such as sensing and communication. For these tasks, high-energy and low-loss optical and telecom frequency signals represent the first choice and form the communication backbone in the future vision of a hybrid quantum internet (8–10).

Despite this general picture, there are applications of quantum sensing that are naturally embedded in the microwave regime. This is exactly the case with quantum illumination (QI) (11–17) for its remarkable robustness to background noise, which, at room temperature, amounts to ∼10³ thermal quanta per mode at a few gigahertz. In QI, the aim is to detect a low-reflectivity object in the presence of very bright thermal noise. This is accomplished by probing the target with less than one entangled photon per mode, in a stealthy noninvasive fashion, which is impossible to reproduce with classical means. In the Gaussian QI protocol (12), the light is prepared in a two-mode squeezed vacuum state with the signal mode sent to probe the target, while the idler mode is kept at the receiver.

Instead of shutting down, Sweden opted for much milder measures to stop the spread of the coronavirus. The idea looked appealing, with the possibility of containing the pandemic at a much lower economic cost. So far, however, the statistics suggest the Swedish model is more disaster than panacea.

Army researchers predict quantum computer circuits that will no longer need extremely cold temperatures to function could become a reality after about a decade.

For years, solid-state quantum technology that operates at room temperature seemed remote. While the application of transparent crystals with optical nonlinearities had emerged as the most likely route to this milestone, the plausibility of such a system always remained in question.

Now, Army scientists have officially confirmed the validity of this approach. Dr. Kurt Jacobs, of the U.S. Army Combat Capabilities Development Command’s Army Research Laboratory, working alongside Dr. Mikkel Heuck and Prof. Dirk Englund, of the Massachusetts Institute of Technology, became the first to demonstrate the feasibility of a quantum logic gate comprised of photonic circuits and optical crystals.

Vesselin Dimitrov’s proof of the Schinzel-Zassenhaus conjecture quantifies the way special values of polynomials push each other apart.

NASA and the makers of “Kerbal Space Program 2” are looking for gamers with the right stuff to recreate SpaceX’s Demo-2 Crew Dragon mission.

Brain injuries can vary greatly in their severity, but assessing the extent of the damage is far from a simple undertaking. Scientists in the UK have developed a new AI algorithm that could help narrow the margin for error, with the ability to detect and categorize different types of brain lesions to gauge the impact of an injury.

One of the tools doctors use to assess brain injuries is a CT scan, which can reveal signs of damage, such as lesions, on the brain. But analyzing these scans to reach a diagnosis is a time-consuming process for radiologists, and given the complex nature of the organ, it can see tell-tale signs often overlooked.

“CT is an incredibly important diagnostic tool, but it’s rarely used quantitatively,” said Professor David Menon, from the University of Cambridge and senior author of the new study. “Often, much of the rich information available in a CT scan is missed, and as researchers, we know that the type, volume and location of a lesion on the brain are important to patient outcomes.”