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Astronomers at MIT and elsewhere have detected a strange and persistent radio signal from a distant galaxy that appears to flicker with surprising regularity. The signal is classified as a rapid radio burst, or FRB — a very powerful burst of radio waves of unknown astrophysical origin, which usually lasts a few milliseconds at most. However, this new signal lasted up to three seconds, about 1,000 times longer than the FRB average. Within this window, the team detected bursts of radio waves that repeated every 0.2 seconds in a clear periodic pattern, similar to a heartbeat. The researchers have labeled the signal FRB 20191221A, and it is currently the most durable FRB, with the clearest periodic pattern, detected to date. The source of the signal lies in a distant galaxy, a few billion light years from Earth. Exactly what the source is remains a mystery, although astronomers suspect the signal could be from a radio pulsar or a magnetar, both types of neutron stars – the cores of gian

Astronomers at MIT and universities in Canada and the United States have detected a strange and persistent radio signal from a distant galaxy that seems to flicker with surprising regularity. The signal is classified as a rapid radio burst, or FRB — a very powerful burst of radio waves of unknown astrophysical origin, which usually lasts a few milliseconds at most. However, this new signal lasted up to three seconds, about 1,000 times longer than the FRB average. Within this window, the team detected bursts of radio waves that repeated every 0.2 seconds in a clear periodic pattern, similar to a heartbeat. The researchers have labeled the signal FRB 20191221A, and it is currently the most durable FRB, with the clearest periodic pattern, detected to date. The source of the signal lies in a distant galaxy, a few billion light years from Earth. Exactly what the source is remains a mystery, although astronomers suspect the signal could be from a radio pulsar or a magnetar, both types of

It takes a lot of time and money to diagnose Alzheimer’s disease. After running a lengthy face-to-face neuropsychological exam, the doctor must copy, review, and analyze each response in detail. But researchers at Boston University have developed a new tool that could automate the process and eventually allow it to move online. Their machine learning-powered computational model can detect cognitive impairment from audio recordings of neuropsychological-tests; no in-person appointment required. Their findings were published in Alzheimer’s & Dementia: Journal of the Alzheimer’s Association . “This approach brings us one step closer to early intervention,” said Ioannis Paschalidis, co-author of the paper and BU College of Engineering Distinguished Professor of Engineering. He said faster early detection of Alzheimer’s could prompt larger clinical trials that focus on individuals in the early stages of the disease and potentially enable clinical interventions that slow cognitive

By David L. Chandler, Massachusetts Institute of Technology 10 July 2022 Scientists at MIT have developed a method to enable such quantum sensors to detect arbitrary frequencies, without losing their ability to measure nanometer-scale features. The new method is described in a paper published in the journal Physical Review X by graduate student Guoqing Wang, professor of nuclear science and engineering and of physics Paola Cappellaro, and four others at MIT and Lincoln Laboratory. The team has already applied for patent protection for the new method. Although quantum sensors can take many forms, at their essence they’re systems in which some particles are in such a delicately balanced state that they are affected by even tiny variations in the fields they are exposed to. These can take the form of neutral atoms, trapped ions, and solid-state spins, and research using such sensors has grown rapidly. For example, physicists use them to investigate exotic states of matter, including so-