Connect with us

Published

on

Canada based Astrophotographer Ronald Brecher has captured a stunning view of the Messier 63 or the ‘Sunflower Galaxy’ . Brecher’s deep-sky portrait reveals incredible detail in the arms of the spiral galaxy, the patterning and structure of which bear a striking resemblance to the head of a cosmic sunflower. M63 appears to be formed from many fragmented arms arranged around its bright core, as opposed to the well-defined, sweeping structures that characterize ‘grand design’ spiral galaxies like NGC 3631, or Bode’s Galaxy.

Imaging the Sunflower Galaxy

According to report by NASA, the M63 can be seen shining with the radiation cast out by a multitude of giant newly-birthed white-blue stars, the light from which travelled for some 27 million light-years to reach Earth.

Brecher imaged the Sunflower Galaxy from his backyard observatory near the city of Guelph in southwestern Ontario, Canada. He imaged it as the moon progressed towards its first quarter phase on the nights of April 17-28 using his Celestron 14″ EDGE HD telescope in conjunction with a monochrome astronomy camera, and a host of helpful peripherals. A little over 13 hours was spent capturing 158 exposures of the galaxy with red, green, blue and hydrogen-alpha filters, the data from which was processed using the astrophoto editing software PixInsight.

Observing M63 in the Night Sky

May happens to be the best month in which to view the Sunflower Galaxy, which will be visible as a faint smudge of light in smaller telescopes under good viewing conditions.

One way to locate the patch of sky containing M63 is to find the bright stars Arcturus, in the constellation Bootes, and Dubhe, which forms the pouring tip of the pan in the ‘Big Dipper’ asterism. The Sunflower Galaxy can be found half way between the two. Use a stargazing app if you need help finding the stars.

Continue Reading

Science

AI Model Learns to Predict Human Gait for Smarter, Pre-Trained Exoskeleton Control

Published

on

By

Scientists at Georgia Tech have created an AI technique that pre-trains exoskeleton controllers using existing human motion datasets, removing the need for lengthy lab-based retraining. The system predicts joint behavior and assistance needs, enabling controllers that work as well as hand-tuned versions. This advance accelerates prototype development and could improve…

Continue Reading

Science

Scientists Build One of the Most Detailed Digital Simulations of the Mouse Cortex Using Japan’s Fugaku Supercomputer

Published

on

By

Researchers from the Allen Institute and Japan’s University of Electro-Communications have built one of the most detailed mouse cortex simulations ever created. Using Japan’s Fugaku supercomputer, the team modeled around 10 million neurons and 26 billion synapses, recreating realistic structure and activity. The virtual cortex offers a new platform for studying br…

Continue Reading

Science

UC San Diego Engineers Create Wearable Patch That Controls Robots Even in Chaotic Motion

Published

on

By

UC San Diego engineers have developed a soft, AI-enabled wearable patch that can interpret gestures with high accuracy even during vigorous or chaotic movement. The armband uses stretchable sensors, a custom deep-learning model, and on-chip processing to clean motion signals in real time. This breakthrough could enable intuitive robot control for rehabilitation, indus…

Continue Reading

Trending