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Article 39 Why an electron does not fall into the nucleus in terms of the strong and weak nuclear forces.

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It can be shown one may able to derive the strong and weak nuclear forces and the internal geometry of protons and neutrons in terms of the orientation of…

Electrons in the atom do enter the nucleus. In fact, electrons in the s states tend to peak at the nucleus. Electrons are not little balls that can fall into the nucleus under electrostatic attraction. Rather, electrons are quantized wavefunctions that spread out in space and can sometimes act like particles in limited ways. An electron in an atom spreads out according to its energy. The states with more energy are more spread out. All electron states overlap with the nucleus, so the concept of an electron “falling into” or “entering” the nucleus does not really make sense. Electrons are always partially in the nucleus.

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Computers have come so far in terms of their power and potential, rivaling and even eclipsing human brains in their ability to store and crunch data, make predictions and communicate. But there is one domain where human brains continue to dominate: energy efficiency.

“The most efficient computers are still approximately four orders of magnitude — that’s 10,000 times — higher in energy requirements compared to the human brain for specific tasks such as image processing and recognition, although they outperform the brain in tasks like mathematical calculations,” said UC Santa Barbara electrical and computer engineering Professor Kaustav Banerjee, a world expert in the realm of nanoelectronics. “Making computers more energy efficient is crucial because the worldwide energy consumption by on-chip electronics stands at #4 in the global rankings of nation-wise energy consumption, and it is increasing exponentially each year, fueled by applications such as artificial intelligence.” Additionally, he said, the problem of energy inefficient computing is particularly pressing in the context of global warming, “highlighting the urgent need to develop more energy-efficient computing technologies.”

Neuromorphic computing has emerged as a promising way to bridge the energy efficiency gap. By mimicking the structure and operations of the human brain, where processing occurs in parallel across an array of low power-consuming neurons, it may be possible to approach brain-like energy efficiency.

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The standard theory of cosmology—which says 95% of the universe is made up of unknown stuff we can’t see—has passed its strictest test yet. The first results released from an instrument designed to study the cosmic effects of mysterious dark energy confirm that, to the nearest 1%, the universe has evolved over the past 11 billion years just as theorists have predicted.

The findings, presented today in a series of talks at the American Physical Society meeting in Sacramento, California, and the Moriond meeting in Italy, as well as in a set of preprints posted to arXiv, come from the Dark Energy Spectroscopic Instrument (DESI), which has logged more than 6 million galaxies in deep space to construct the largest 3D map of the universe yet compiled.

“It’s a tremendous instrument and a major result,” says Eric Gawiser, a cosmologist at Rutgers University who was not involved with the work. “The universe DESI is finding is very sensible, with tantalizing hints of a more interesting one.”

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