Astronomy - Revision history

BPeat at 17:37, 28 December 2025

2025-12-28T17:37:58Z

BPeat at 00:50, 20 March 2024

2024-03-20T00:50:22Z

BPeat at 03:55, 2 March 2024

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BPeat at 17:04, 16 September 2023

2023-09-16T17:04:59Z

BPeat at 10:40, 1 September 2023

2023-09-01T10:40:46Z

BPeat at 11:41, 17 August 2023

2023-08-17T11:41:02Z

BPeat: /* 1201 1202 Error */

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‎1201 1202 Error

BPeat: /* Apollo Computers */

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‎Apollo Computers

BPeat: /* Archive */

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‎Archive

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‎1201 1202 Error

← Older revision		Revision as of 17:37, 28 December 2025
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−	Astronomy is the study of celestial objects and phenomena beyond Earth's atmosphere. It encompasses everything from the smallest particles in space to the largest structures in the universe. In recent years, artificial intelligence (AI) has become an increasingly important tool in astronomy, helping scientists to make sense of the vast amounts of data generated by telescopes and other instruments. One area where AI is being applied in astronomy is in the analysis of star data. By training algorithms to identify patterns in the light emitted by stars, astronomers can use AI to more accurately classify stars and better understand their properties. AI is also being used to search for exoplanets, or planets outside of our solar system. By analyzing data from telescopes like NASA's Kepler and TESS, AI algorithms can detect the subtle changes in starlight that indicate the presence of an orbiting planet. Satellites and spacecraft are another area where AI is proving useful in astronomy. For example, NASA's Mars rovers are equipped with AI algorithms that help them navigate the Martian terrain and avoid obstacles. Similarly, the upcoming James Webb Space Telescope (JWST) will use AI to help optimize its observations, allowing it to detect more distant and faint objects than ever before. The sun and its behavior is also of great interest to astronomers, as its activity can have significant impacts on Earth's climate and technological infrastructure. AI is being used to analyze data from spacecraft like NASA's Solar Dynamics Observatory (SDO) to better understand the sun's magnetic fields and the processes that drive solar flares and other phenomena. In addition to studying celestial objects and phenomena, AI is also being used to detect and analyze gravitational waves, ripples in the fabric of spacetime caused by the acceleration of massive objects like black holes. The Laser Interferometer Gravitational-Wave Observatory (LIGO) uses AI algorithms to sift through the vast amounts of data generated by its detectors, looking for the telltale signals of gravitational waves.	+	Astronomy is the study of celestial objects and phenomena beyond Earth's atmosphere. It encompasses everything from the smallest particles in space to the largest structures in the universe. In recent years, artificial intelligence (AI) has become an increasingly important tool in astronomy, helping scientists to make sense of the vast amounts of data generated by telescopes and other instruments. One area where AI is being applied in astronomy is in the analysis of star data. By training algorithms to identify patterns in the light emitted by stars, astronomers can use AI to more accurately classify stars and better understand their properties. AI is also being used to search for exoplanets, or planets outside of our solar system. By analyzing data from telescopes like NASA's Kepler and TESS, AI algorithms can detect the subtle changes in starlight that indicate the presence of an orbiting planet. Satellites and spacecraft are another area where AI is proving useful in astronomy. For example, NASA's Mars rovers are equipped with AI algorithms that help them navigate the Martian terrain and avoid obstacles. Similarly, the upcoming James Webb Space Telescope (JWST) will use AI to help optimize its observations, allowing it to detect more distant and faint objects than ever before. The sun and its behavior is also of great interest to astronomers, as its activity can have significant impacts on Earth's climate and technological infrastructure. AI is being used to analyze data from spacecraft like NASA's Solar Dynamics Observatory (SDO) to better understand the sun's magnetic fields and the processes that drive solar flares and other phenomena. In addition to studying celestial objects and phenomena, AI is also being used to detect and analyze gravitational waves, ripples in the fabric of [[Time#Spacetime\|spacetime]] caused by the acceleration of massive objects like black holes. The Laser Interferometer Gravitational-Wave Observatory (LIGO) uses AI algorithms to sift through the vast amounts of data generated by its detectors, looking for the telltale signals of gravitational waves.

	Finding: Autonomy needs to evolve at a systems level to integrate and harmonize subsystems to make decisions and execute planned operations on remote yet complex planetary science and astrobiology missions. Machine learning/artificial intelligence can support the implementation of autonomy in such environments. [https://nap.nationalacademies.org/catalog/26522/origins-worlds-and-life-a-decadal-strategy-for-planetary-science Origins, Worlds, and Life, A Decadal Strategy for Planetary Science and Astrobiology 2023-2032, (2022) \| National Academies of Sciences] ... ~ 780 pages see General Technology Areas; Autonomy, [[Quantum]] Computing and Artificial Intelligence/Machine Learning		Finding: Autonomy needs to evolve at a systems level to integrate and harmonize subsystems to make decisions and execute planned operations on remote yet complex planetary science and astrobiology missions. Machine learning/artificial intelligence can support the implementation of autonomy in such environments. [https://nap.nationalacademies.org/catalog/26522/origins-worlds-and-life-a-decadal-strategy-for-planetary-science Origins, Worlds, and Life, A Decadal Strategy for Planetary Science and Astrobiology 2023-2032, (2022) \| National Academies of Sciences] ... ~ 780 pages see General Technology Areas; Autonomy, [[Quantum]] Computing and Artificial Intelligence/Machine Learning

@@ Line 675: / Line 675: @@
 * Using [[Generative AI|generative]] modeling to investigate the physical changes that galaxies undergo as they evolve. (The software they used treats the [[latent]] space somewhat differently from the way a [[Generative AI|generative]] adversarial network treats it, so it is not technically a GAN, though similar.) . [https://www.quantamagazine.org/how-artificial-intelligence-is-changing-science-20190311/ How Artificial Intelligence Is Changing Science | Dan Falk - Quanta Magazine]
 * [https://www.impactlab.net/2019/07/18/worldss-first-ai-universe-simulator-knows-thing-it-shouldnt/ Worlds’s first AI universe simulator knows things it shouldn’t | Thomas Frey]
-* [[Metaverse]]
+* [[Immersive Reality]] ... [[Metaverse]] ... [[Omniverse]] ... [[Transhumanism]] ... [[Religion]]
 {|<!-- T -->

@@ Line 734: / Line 734: @@
 The Apollo 11 mission utilized several onboard computers for navigation, guidance, and control:
-* <b>Apollo Guidance Computer (AGC)</b>: The AGC was the main computer system responsible for guiding and controlling the spacecraft. It was designed by MIT Instrumentation Laboratory and built by Raytheon. The AGC was one of the earliest digital computers and used core rope memory for its software.
+* <b>Apollo Guidance Computer (AGC)</b>: The AGC was the main computer system responsible for guiding and controlling the spacecraft. It was designed by MIT Instrumentation Laboratory and built by Raytheon. The AGC was one of the earliest digital computers and used core rope [[memory]] for its software.
 * <b>Apollo Command Module (CM) Computer</b>: The command module, where the astronauts lived during the mission, was equipped with its own computer. This computer was responsible for various functions related to navigation, guidance, and communication.

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 [https://news.google.com/search?q=Simulation+modelling+galaxy+space+universe+artificial+intelligence+deep+machine+learning ...News search]
-* Using [[Generative AI|generative]] modeling to investigate the physical changes that galaxies undergo as they evolve. (The software they used treats the latent space somewhat differently from the way a [[Generative AI|generative]] adversarial network treats it, so it is not technically a GAN, though similar.) . [https://www.quantamagazine.org/how-artificial-intelligence-is-changing-science-20190311/ How Artificial Intelligence Is Changing Science | Dan Falk - Quanta Magazine]
+* Using [[Generative AI|generative]] modeling to investigate the physical changes that galaxies undergo as they evolve. (The software they used treats the [[latent]] space somewhat differently from the way a [[Generative AI|generative]] adversarial network treats it, so it is not technically a GAN, though similar.) . [https://www.quantamagazine.org/how-artificial-intelligence-is-changing-science-20190311/ How Artificial Intelligence Is Changing Science | Dan Falk - Quanta Magazine]
 * [https://www.impactlab.net/2019/07/18/worldss-first-ai-universe-simulator-knows-thing-it-shouldnt/ Worlds’s first AI universe simulator knows things it shouldn’t | Thomas Frey]
 * [[Metaverse]]

@@ Line 26: / Line 26: @@
 * [[Time#Deep-Space Positioning System (DPS)|Deep-Space Positioning System (DPS)]]
 * [[Video/Image]] ... [[Vision]] ... [[Enhancement]] ... [[Fake]] ... [[Reconstruction]] ... [[Colorize]] ... [[Occlusions]] ... [[Predict image]] ... [[Image/Video Transfer Learning]]
 * [https://python4astronomers.github.io/ Practical Python for Astronomers | GitHub]
 * [https://open.nasa.gov/ OpenNASA]

← Older revision		Revision as of 11:41, 17 August 2023
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	<b>Challenge:</b>		<b>Challenge:</b>
−	Today, active collision avoidance among orbiting satellites has become a routine task in space operations, relying on validated, accurate and timely space surveillance data. For a typical satellite in Low Earth Orbit, hundreds of alerts are issued every week corresponding to possible close encounters between a satellite and another space object (in the form of conjunction data messages CDMs). After automatic processing and filtering, there remain about 2 actionable alerts per spacecraft and week, requiring detailed follow-up by an analyst. On average, at the European Space Agency, more than one collision avoidance manoeuvre is performed per satellite and year. In this challenge, you are tasked to build a model to predict the final collision risk estimate between a given satellite and a space object (e.g. another satellite, space debris, etc). To do so, you will have access to a database of real-world conjunction data messages (CDMs) carefully prepared at ESA. Learn more about the challenge and the data.	+	Today, active collision avoidance among orbiting satellites has become a routine task in space operations, relying on validated, accurate and timely space surveillance data. For a typical satellite in Low Earth Orbit, hundreds of alerts are issued every week corresponding to possible close encounters between a satellite and another space object (in the form of conjunction data messages CDMs). After automatic processing and filtering, there remain about 2 actionable alerts per spacecraft and week, requiring detailed follow-up by an analyst. On average, at the European Space Agency, more than one collision avoidance manoeuvre is performed per satellite and year. In this challenge, you are tasked to build a model to predict the final collision risk estimate between a given satellite and a space object (e.g. another satellite, space debris, etc). To do so, you will have access to a [[database]] of real-world conjunction data messages (CDMs) carefully prepared at ESA. Learn more about the challenge and the data.

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 == 1201 1202 Error ==
-The "Apollo 1202 Error" refers to a critical error that occurred during the Apollo 11 moon landing mission on July 20, 1969. The error code "1202" was a program alarm that appeared on the guidance computer of the lunar module just seconds before Neil Armstrong was about to touch down on the lunar surface. The error was triggered by an overloaded guidance computer, which was receiving more data than it could process <i><b>due to a radar switch being in the wrong position</b></i>. Despite the error, the mission controllers at NASA's Mission Control Center in Houston, Texas, and the astronauts aboard the lunar module proceeded with the landing. The guidance computer's software and the quick thinking of the mission controllers allowed them to resolve the issue and continue with the descent. Armstrong manually piloted the lunar module to a safe landing spot with only about 30 seconds of fuel remaining. He famously radioed back to Mission Control, "Houston, Tranquility Base here. The Eagle has landed." The Apollo 11 mission was a historic achievement, as it marked the first time humans successfully landed on the moon and returned safely to Earth. The 1202 Error is a reminder of the challenges and ingenuity involved in such complex and pioneering endeavors.  Margaret Hamilton was the Director of the Software Engineering Division of MIT Instrumentation Laboratory, which was responsible for developing the software for the Apollo guidance and navigation systems. Margaret Hamilton's team had designed the software with a priority system that allowed the computer to handle essential tasks first and manage the overload gracefully. The software's ability to prioritize critical functions and manage non-essential tasks helped prevent a mission abort. Margaret Hamilton's innovative approach to software development, which included concepts like error recovery and priority-based processing, played a crucial role in the success of the Apollo 11 landing. Her work and the efforts of her team demonstrated the importance of robust software engineering in complex and high-stakes missions.
+The "Apollo 1202 Error" refers to a critical error that occurred during the Apollo 11 moon landing mission on July 20, 1969. The error code "1202" was a program alarm that appeared on the guidance computer of the lunar module just seconds before Neil Armstrong was about to touch down on the lunar surface. The error was triggered by an overloaded guidance computer, which was receiving more data than it could process <i><b>due to a radar switch being in the wrong position</b></i>. Despite the error, the mission controllers at NASA's Mission Control Center in Houston, Texas, and the astronauts aboard the lunar module proceeded with the landing. The guidance computer's software and the quick thinking of the mission controllers allowed them to resolve the issue and continue with the descent. Armstrong manually piloted the lunar module to a safe landing spot with only about 30 seconds of fuel remaining. He famously radioed back to Mission Control, "Houston, Tranquility Base here. The Eagle has landed." The Apollo 11 mission was a historic achievement, as it marked the first time humans successfully landed on the moon and returned safely to Earth. The 1202 Error is a reminder of the challenges and ingenuity involved in such complex and pioneering endeavors.  [[Creatives#Margaret Elaine Hamilton|Margaret Hamilton]] was the Director of the Software Engineering Division of MIT Instrumentation Laboratory, which was responsible for developing the software for the Apollo guidance and navigation systems. [[Creatives#Margaret Elaine Hamilton|Margaret Hamilton's]] team had designed the software with a priority system that allowed the computer to handle essential tasks first and manage the overload gracefully. The software's ability to prioritize critical functions and manage non-essential tasks helped prevent a mission abort. [[Creatives#Margaret Elaine Hamilton|Margaret Hamilton's]] innovative approach to software development, which included concepts like error recovery and priority-based processing, played a crucial role in the success of the Apollo 11 landing. Her work and the efforts of her team demonstrated the importance of robust software engineering in complex and high-stakes missions.
 <youtube>cmAc7t7tAlc</youtube>

← Older revision		Revision as of 00:06, 15 August 2023
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	= Apollo Computers =		= Apollo Computers =
		+	* [https://en.wikipedia.org/wiki/Apollo_Guidance_Computer Apollo Guidance Computer (AGC) \| Wikipedia]
		+
		+	The Apollo 11 mission utilized several onboard computers for navigation, guidance, and control:
		+
		+	* <b>Apollo Guidance Computer (AGC)</b>: The AGC was the main computer system responsible for guiding and controlling the spacecraft. It was designed by MIT Instrumentation Laboratory and built by Raytheon. The AGC was one of the earliest digital computers and used core rope memory for its software.
		+
		+	* <b>Apollo Command Module (CM) Computer</b>: The command module, where the astronauts lived during the mission, was equipped with its own computer. This computer was responsible for various functions related to navigation, guidance, and communication.
		+
		+	* <b>Lunar Module (LM) Computer</b>: The lunar module, used for landing on the moon, also had its own computer. The LM computer played a critical role in the descent and landing phase of the mission.

	<youtube>ndvmFlg1WmE</youtube>		<youtube>ndvmFlg1WmE</youtube>

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 |}<!-- B -->
-= Archive =
+= Apollo Computers =
 <youtube>ndvmFlg1WmE</youtube>

← Older revision		Revision as of 00:02, 15 August 2023
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	The "Apollo 1202 Error" refers to a critical error that occurred during the Apollo 11 moon landing mission on July 20, 1969. The error code "1202" was a program alarm that appeared on the guidance computer of the lunar module just seconds before Neil Armstrong was about to touch down on the lunar surface. The error was triggered by an overloaded guidance computer, which was receiving more data than it could process <i><b>due to a radar switch being in the wrong position</b></i>. Despite the error, the mission controllers at NASA's Mission Control Center in Houston, Texas, and the astronauts aboard the lunar module proceeded with the landing. The guidance computer's software and the quick thinking of the mission controllers allowed them to resolve the issue and continue with the descent. Armstrong manually piloted the lunar module to a safe landing spot with only about 30 seconds of fuel remaining. He famously radioed back to Mission Control, "Houston, Tranquility Base here. The Eagle has landed." The Apollo 11 mission was a historic achievement, as it marked the first time humans successfully landed on the moon and returned safely to Earth. The 1202 Error is a reminder of the challenges and ingenuity involved in such complex and pioneering endeavors. Margaret Hamilton was the Director of the Software Engineering Division of MIT Instrumentation Laboratory, which was responsible for developing the software for the Apollo guidance and navigation systems. Margaret Hamilton's team had designed the software with a priority system that allowed the computer to handle essential tasks first and manage the overload gracefully. The software's ability to prioritize critical functions and manage non-essential tasks helped prevent a mission abort. Margaret Hamilton's innovative approach to software development, which included concepts like error recovery and priority-based processing, played a crucial role in the success of the Apollo 11 landing. Her work and the efforts of her team demonstrated the importance of robust software engineering in complex and high-stakes missions.		The "Apollo 1202 Error" refers to a critical error that occurred during the Apollo 11 moon landing mission on July 20, 1969. The error code "1202" was a program alarm that appeared on the guidance computer of the lunar module just seconds before Neil Armstrong was about to touch down on the lunar surface. The error was triggered by an overloaded guidance computer, which was receiving more data than it could process <i><b>due to a radar switch being in the wrong position</b></i>. Despite the error, the mission controllers at NASA's Mission Control Center in Houston, Texas, and the astronauts aboard the lunar module proceeded with the landing. The guidance computer's software and the quick thinking of the mission controllers allowed them to resolve the issue and continue with the descent. Armstrong manually piloted the lunar module to a safe landing spot with only about 30 seconds of fuel remaining. He famously radioed back to Mission Control, "Houston, Tranquility Base here. The Eagle has landed." The Apollo 11 mission was a historic achievement, as it marked the first time humans successfully landed on the moon and returned safely to Earth. The 1202 Error is a reminder of the challenges and ingenuity involved in such complex and pioneering endeavors. Margaret Hamilton was the Director of the Software Engineering Division of MIT Instrumentation Laboratory, which was responsible for developing the software for the Apollo guidance and navigation systems. Margaret Hamilton's team had designed the software with a priority system that allowed the computer to handle essential tasks first and manage the overload gracefully. The software's ability to prioritize critical functions and manage non-essential tasks helped prevent a mission abort. Margaret Hamilton's innovative approach to software development, which included concepts like error recovery and priority-based processing, played a crucial role in the success of the Apollo 11 landing. Her work and the efforts of her team demonstrated the importance of robust software engineering in complex and high-stakes missions.

−	~~<youtube>z4cn93H6sM0</youtube>~~
	<youtube>cmAc7t7tAlc</youtube>		<youtube>cmAc7t7tAlc</youtube>