Mysterious radio signal reveals intricate core of galaxy cluster

Mysterious radio signal reveals intricate core of galaxy cluster

A puzzling radio emission from a galactic cluster located in the constellation may come from the 1.66 million light-year-long radio tail of its dominating central galaxy. 

The team that made this discovery also found evidence of mergers between galaxies in the cluster Abell 1213, which is in the constellation of Ursa Major and is located around 647 million light-years from Earth. The findings are the result of astronomers investigating an anomalous radio emission from Abell 1213. In 2009, observations with the Very Large Array (VLA), comprised of 28 radio antennas spread across the Plains of New Mexico, revealed the presence of a diffuse extended emission from the cluster.

This was initially believed to be from a radio halo, a large-scale source of diffuse (spread out) radio emissions found at the heart of a select few galactic clusters that are created when electrons moving in a circle are accelerated to near-light

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Get Ahead of the Game: 10 Core Artificial Intelligence AI Concepts to Supercharge Your Future

Get Ahead of the Game: 10 Core Artificial Intelligence AI Concepts to Supercharge Your Future

Artificial intelligence (AI) automation has already significantly impacted many aspects of our life. Artificial intelligence, from Siri and Alexa to (nearly) self-driving cars, will rule the future.

Yet, as AI develops, its implications could become even more serious. There is a lot of discussion about AI, which has left many people perplexed about how it will affect our future.

Here are seven ways that automation and artificial intelligence will change the future, for better or worse.

🔥 Recommended Read: Leveraging TensorLeap for Effective Transfer Learning: Overcoming Domain Gaps

Business In-depth Learning

A more advanced version of machine learning than traditional machine learning is deep learning. The goal of machine learning is to quickly examine enormous volumes of data. A machine learning system improves as it analyses more data.

With deep learning, the learning process for AI systems becomes more complex. Because they aid in critical reasoning, neural networks are complex.

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