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Archive for the ‘mathematics’ category: Page 83

Aug 14, 2022

Meteorites may have helped seed life on Earth

Posted by in categories: biological, chemistry, mathematics

Circa 2017


There are many theories about how life evolved on the planet Earth, from formation under a layer of ice, protected from the UV radiation above, to vents in the deep sea that provided hydrogen-rich molecules. But now one team of scientists has found quantitative results that support a theory that is literally out of this world. Organic molecules from meteorites that landed in small, warm pools of water may have delivered the ingredients necessary for life to form on Earth.

The team reached this conclusion through a mathematical model. They took data about planet formation, geology, biology and chemistry and inputted these factors into a grand quantitative model they had designed. Their results support the theory that RNA polymers formed in small, warm ponds of water. Meteorites contributed to this process by transferring enough organic molecules to these pools to ensure that RNA started self-replicating in at least one pool.

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Aug 14, 2022

Amplitudes and the Riemann Zeta Function

Posted by in categories: computing, information science, mathematics, quantum physics

Circa 2021 This gets very close to a master algorithm for math and helps with quantum computing too.


Abstract. Humans carrying the CORD7 (cone-rod dystrophy 7) mutation possess increased verbal IQ and working memory. This autosomal dominant syndrome is caused b.

Aug 11, 2022

We Might Already Speak the Same Language As ET

Posted by in categories: alien life, existential risks, mathematics, quantum physics

Alien communication could utilize quantum physics, so SETI needs a new way to listen.


The Fermi paradox, the “where is everybody?” puzzle, is a persistent question in the search for life in the universe. It asks why, if life is not exceedingly rare in the cosmos, it hasn’t shown up on our doorstep. Equally we might ask why we haven’t even heard from alien life, through radio signals or any other means. A part of the answer could be that our present work on the search for extraterrestrial intelligence is actually very limited. Estimates show that we’ve only examined the equivalent of a hot tub of water compared to all the world’s oceans in our combing through the electromagnetic information that rolls in from the cosmos.1

If you’re a glass-half-full kind of person you’ll see this as an opportunity, but the problem is that we don’t actually know what might be filling the glass in the first place. The vast majority of SETI studies look for structure in electromagnetic radiation, whether in amplitude or frequency modulations of radio waves, or regularity in pulses of light, or in multi-wavelength correlations. In other words, we assume that information might be sailing past us in representations built using classical physics. But what if that’s just wrong?

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Aug 10, 2022

Math error: A new study overturns 100-year-old understanding of color perception

Posted by in categories: computing, mathematics, physics, space

A new study corrects an important error in the 3D mathematical space developed by the Nobel Prize-winning physicist Erwin Schrödinger and others, and used by scientists and industry for more than 100 years to describe how your eye distinguishes one color from another. The research has the potential to boost scientific data visualizations, improve TVs and recalibrate the textile and paint industries.

“The assumed shape of color space requires a paradigm shift,” said Roxana Bujack, a computer scientist with a background in mathematics who creates scientific visualizations at Los Alamos National Laboratory. Bujack is lead author of the paper by a Los Alamos team in the Proceedings of the National Academy of Sciences on the mathematics of color perception.

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Aug 9, 2022

Quantum in 2027: Take a quantum leap into the future of IT

Posted by in categories: computing, mathematics, quantum physics

Quantum computing will change everything.

“I think I can safely say that nobody really understands quantum mechanics,” renowned physicist Richard Feynman stated once. That shouldn’t come as a big surprise as quantum physics has a reputation for being exceptionally enigmatic. This was the selling point for the quantum physicist Dr. Shohini Ghose from Wilfrid Laurier University.

Having always excelled at mathematics and physics, Ghose was always interested in mysteries, detective stories, and mathematics. This led her to an intense fascination with physics, as she quickly discovered that she could use mathematics to help solve the mysteries of the universe.

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Aug 7, 2022

New mapping method could aid exploration of moon, Mars and beyond

Posted by in categories: mapping, mathematics, space

Researchers find mathematical trick to combining planetary surface data.


Researchers have discovered a method for making high-resolution maps of planetary surfaces like the moon’s by combining available imagery and topography data.

Mapping the complex and diverse surface of a world like the moon in detailed resolution is challenging because laser altimeters, which measure changes in altitudes, operate at much lower resolution than cameras. And although photographs offer a sense of surface features, it’s difficult to translate images into specific heights and depths.

Aug 5, 2022

Quantum control for advanced technology: Past and present

Posted by in categories: engineering, mathematics, quantum physics

One of the cornerstones of the implementation of quantum technology is the creation and manipulation of the shape of external fields that can optimize the performance of quantum devices. Known as quantum optimal control, this set of methods comprises a field that has rapidly evolved and expanded over recent years.

A new review paper published in EPJ Quantum Technology and authored by Christiane P. Koch, Dahlem Center for Complex Quantum Systems and Fachbereich Physik, Freie Universität Berlin along with colleagues from across Europe assesses recent progress in the understanding of the controllability of quantum systems as well as the application of quantum control to quantum technologies. As such, it lays out a potential roadmap for future .

While quantum optimal control builds on conventional control theory encompassing the interface of applied mathematics, engineering, and physics, it must also factor in the quirks and counter-intuitive nature of quantum physics.

Aug 5, 2022

Artificial intelligence discovers new physics variables!

Posted by in categories: mathematics, physics, robotics/AI, space

Analysing pendulum videos, the artificial intelligence tool identified variables not present in current mathematics.


An artificial intelligence tool has examined physical systems and not surprisingly, found new ways of describing what it found.

How do we make sense of the universe? There’s no manual. There’s no prescription.

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Aug 5, 2022

Futureseek Daily Link Review; 05 August 2022

Posted by in categories: cosmology, cybercrime/malcode, economics, mathematics, particle physics, quantum physics, robotics/AI, space travel, surveillance

* At Long Last, Mathematical Proof That Black Holes Are Stable * Who Gets to Work in the Digital Economy? * Mice produce rat sperm with technique that could help conservation.

* Quantum computer can simulate infinitely many chaotic particles * Radar / AI & ML: Scaling False Peaks * Cyber security for the human world | George Loukas | TEDx.

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Aug 4, 2022

New algorithm aces university math course questions

Posted by in categories: education, information science, mathematics, robotics/AI

Multivariable calculus, differential equations, linear algebra—topics that many MIT students can ace without breaking a sweat—have consistently stumped machine learning models. The best models have only been able to answer elementary or high school-level math questions, and they don’t always find the correct solutions.

Now, a multidisciplinary team of researchers from MIT and elsewhere, led by Iddo Drori, a lecturer in the MIT Department of Electrical Engineering and Computer Science (EECS), has used a to solve university-level math problems in a few seconds at a human level.

The model also automatically explains solutions and rapidly generates new problems in university math subjects. When the researchers showed these machine-generated questions to , the students were unable to tell whether the questions were generated by an algorithm or a human.

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