Lifeboat Foundation

When Russian nuclear inspectors traveled to the U.S. in the early 2000s, they were not allowed to directly examine classified nuclear weapon components, Professor Alex Glaser said. Instead, the inspectors were shown a radiation detector’s green light as confirmation that components were real.

The Russians were not convinced, Glaser said, noting that one said the only thing the test proved was that the Americans had a green LED with a battery connection.

Details about nuclear weapons remain among the world’s most highly guarded secrets. An expert dismantling a weapon, or even witnessing its destruction, can learn much about the warhead. On the other hand, without examining the weapon, it’s difficult to convince inspectors that a real weapon was destroyed. This has long been considered a problem for disarmament —how can countries convince others that a nuclear weapon is gone without revealing details about its arsenal?

A year marked by climate protests, political uncertainty and debate over the ethics of gene editing in human embryos proved challenging for science. But researchers also celebrated some exciting firsts — a quantum computer that can outperform its classical counterparts, a photo of a black hole and samples gathered from an asteroid.

Climate strikes, marsquakes and gaming AIs are among the year’s top stories.

Full Zoom video of Seeking Delphi™ host Mark Sackler’s interview with Strangeworks CEO, whurley, on the current state of the art in quantum computing.

Two physicists from the University of Luxembourg have now unambiguously shown that quantum-mechanical wavelike interactions are indeed crucial even at the scale of natural biological processes.

Quantum wavelike behaviour plays a key role in modern science and technology, with applications of quantum mechanics ranging from lasers and high-speed fiber communications, to quantum computers and photosynthesis in plants. A natural question is whether quantum wave phenomena could also be relevant for structure formation and dynamical processes in biological systems in living cells. This question has not been addressed convincingly up to now due to the lack of efficient quantum methods that are applicable to systems as large as whole proteins under physiological conditions (i.e. solvated in water and at room temperature).

Now writing in Science Advances, Prof. Alexandre Tkatchenko and doctoral researcher Martin Stöhr from the Department of Physics and Materials Science at the University of Luxembourg have investigated the folding process of proteins in water using a fully quantum-mechanical treatment for the first time. Protein folding is the physical process by which a chain of amino acids acquires its native biologically functional structure due to interactions between amino acids and the influence of surrounding water. A key novel finding of the present study is that the interaction between the protein and the surrounding water has to be described by quantum-mechanical wavelike behavior, which also turns out to be critical in the dynamics of the protein folding process.

Similarly, quantum computing started as a specialized field, only accessible to researchers and scientists. Today, millions of developers can access quantum processors via the cloud, bringing about a surge in early adoption and the identification of hundreds of early applications. We’re already seeing companies apply quantum computers in problems with potential real-world impact — everything from optimizing taxi routes to digital advertising.

A major catalyst for this momentum toward commercialization was the aforementioned emergence of cloud access to quantum computers at accessible price points. Now that the barriers to access have dramatically diminished, we’re seeing three key indicators emerge that signal quantum’s commercial viability: an increase in early adoption from category leaders, the emergence of entrepreneurial “quantum pioneers” and the rise of a supporting ecosystem in the form of independent software vendors (ISVs) and consulting firms.

Less than 3 million Bitcoin (BTC) remain to be mined, with the process expected to take around 121 years. Some allege however, that Google’s quantum computer, Sycamore, could do it in “less than 2 seconds”. But is that really possible?

One computer to rule them all

Despite having the most difficult network to mine, Bitcoin (BTC) could have met its match in the face of the Google’s quantum processor, Sycamore. According to one medium post, the device has enough computational power to mine all the remaining BTC in less than two seconds.

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Since the 1950s at least, researchers have speculated that the brain is a kind of computer in which neurons make up complex circuits that perform untold numbers of calculations every second. Decades later, neuroscientists know that these brain circuits exist, yet technical limitations have kept most details of their computations out of reach.

Now, neuroscientists reported December 12 in Cell, they may finally be able to reveal what circuits deep in the brain are up to, thanks in large part to a molecule that lights up brighter than ever before in response to subtle electrical changes that neurons use to perform their compuations.

Currently, one of the best ways to track neurons’ electrical activity is with molecules that light up in the presence of calcium ions, a proxy for a neuron spike, the moment when one neuron passes an electrical signal to another. But calcium flows too slowly to catch all the details of a neuron spike, and it doesn’t respond at all to the subtle electrical changes that lead up to a spike. (One alternative is to implant electrodes, but those implants ultimately damage neurons, and it isn’t practical to place electrodes in more than a handful of neurons at once in living animals.)

Humans have a maximum natural lifespan of only 38 years, according to researchers, who have discovered a way to estimate how long a species lives based on its DNA.

Scientists at Australia’s national science agency have developed a genetic ‘clock’ computer model that they claim can accurately estimate how long different vertebrates are likely to survive — including both living and extinct species.

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