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Archive for the ‘mathematics’ category: Page 30

Sep 19, 2023

Strange Mathematical Pattern Found in The Cells of The Human Body

Posted by in categories: biotech/medical, mathematics, neuroscience

From the oxygen-carrying corpuscles in our blood to the branching neurons that govern our thoughts, our body is built of a dazzling variety of cells.

Researchers from institutions in Germany, Canada, Spain, and the US have published a comprehensive study of how many individual cells of each type there are in typical bodies.

Based on an exhaustive analysis of over 1,500 published sources, most adult males contain a total of around 36 trillion cells, while adult females tend to have some 28 trillion cells. A 10-year-old child, by comparison, would have in the region of 17 trillion.

Sep 19, 2023

Fact Check: Do Warp Drive Engines Violate the Laws of Physics?

Posted by in categories: alien life, mathematics, physics

The universe is bigger than you think.

This means any deep-space future awaiting humanity outside our solar system will remain beyond the span of a single life until we develop a means of propulsion that outclasses conventional rockets. And, when three studies rocked the world earlier this year, it felt like a dream come true: Warp drive was no longer science fiction, potentially unlocking a theoretical basis to build faster-than-light warp drive engines that could cut a trip to Mars down to minutes.

However, a recent study shared in a preprint journal cast doubt on the theory, pointing to a gap in the math that could put the viability of a physical warp drive back into the realm of speculation.

Sep 19, 2023

Physicists Create New Magnetic Material to Unleash Quantum Computing

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

Quantum behavior is a strange, fragile thing that hovers on the edge of reality, between a world of possibility and a Universe of absolutes. In that mathematical haze lies the potential of quantum computing; the promise of devices that could quickly solve algorithms that would take classic computers too long to process.

For now, quantum computers are confined to cool rooms close to absolute zero (−273 degrees Celsius) where particles are less likely to tumble out of their critical quantum states.

Breaking through this temperature barrier to develop materials that still exhibit quantum properties at room temperatures has long been the goal of quantum computing. Though the low temperatures help keep the particle’s properties from collapsing out of their useful fog of possibility, the bulk and expense of the equipment limits their potential and ability to be scaled up for general use.

Sep 17, 2023

DeepMind discovers that AI large language models can optimize their own prompts

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

When people program new deep learning AI models — those that can focus on the right features of data by themselves — the vast majority rely on optimization algorithms, or optimizers, to ensure the models have a high enough rate of accuracy. But one of the most commonly used optimizers — derivative-based optimizers— run into trouble handling real-world applications.

In a new paper, researchers from DeepMind propose a new way: Optimization by PROmpting (OPRO), a method that uses AI large language models (LLM) as optimizers. The unique aspect of this approach is that the optimization task is defined in natural language rather than through formal mathematical definitions.

The researchers write, “Instead of formally defining the optimization problem and deriving the update step with a programmed solver, we describe the optimization problem in natural language, then instruct the LLM to iteratively generate new solutions based on the problem description and the previously found solutions.”

Sep 17, 2023

Brain Asymmetry Driven by Task Complexity

Posted by in categories: biotech/medical, life extension, mathematics, robotics/AI

A mathematical model shows how increased intricacy of cognitive tasks can break the mirror symmetry of the brain’s neural network.

The neural networks of animal brains are partly mirror symmetric, with asymmetries thought to be more common in more cognitively advanced species. This assumption stems from a long-standing theory that increased complexity of neural tasks can turn mirror-symmetric neural circuits into circuits existing in only one side of the brain. This hypothesis has now received support from a mathematical model developed by Luís Seoane at the National Center for Biotechnology in Spain [1]. The researcher’s findings could help explain how the brain’s architecture is shaped not only by cognitively demanding tasks but also by damage or aging.

A mirror-symmetric neural network is useful when controlling body parts that are themselves mirror symmetric, such as arms and legs. Moreover, the presence of duplicate circuits on each side of the brain can help increase computing accuracy and offer a replacement circuit if one becomes faulty. However, the redundancy created by such duplication can lead to increased energy consumption. This trade-off raises an important question: Does the optimal degree of mirror symmetry depend on the complexity of the cognitive tasks performed by the neural network?

Sep 16, 2023

Life-Changing Cystic Fibrosis Treatment Wins $3-Million Breakthrough Prize

Posted by in categories: biotech/medical, mathematics

A trio of scientists who developed the combination drug Trikafta are among the winners of five major awards in life sciences, physics and mathematics.

Sep 16, 2023

If you’d bought Apple shares instead of iPhones, you’d now have $147,000

Posted by in categories: mathematics, mobile phones

What would happen if, instead of buying the newest iPhone every time Apple launches one, you bought that same amount of Apple stock? There is a tweet floating around saying that if you had bought Apple shares instead of an iPhone every time they came out, you’d have hundreds of millions of dollars. The math is off (if you’d spent $20k on Apple stock when the rumors of the iPhone first started, you’d have $1.5 million today, at best) but in any case – it’d only make sense if you were clairvoyant in 2007, and knew when Apple would be launching phones, and at which price.

I figured a more fair way of calculating it would be to imagine buy a top-of-the-line iPhone every time Apple releases a new iPhone, or spend the same amount on Apple stock. If you had done that, by my calculations, you’d have spent around $16,000 on iPhones over the years (that’s around $20,000 in today’s dollars). If you’d bought Apple shares instead, you’d today have $147,000 or so — or a profit of around $131,000.

Sep 15, 2023

Mathematicians find 12,000 new solutions to ‘unsolvable’ 3-body problem

Posted by in category: mathematics

Calculating the way three things orbit each other is notoriously tricky — but a new study may reveal 12,000 new ways to make it work.

Sep 14, 2023

We’ve Been Misreading a Major Law of Physics For The Past 300 Years

Posted by in categories: mathematics, physics

When Isaac Newton inscribed onto parchment his now-famed laws of motion in 1,687, he could have only hoped we’d be discussing them three centuries later.

Writing in Latin, Newton outlined three universal principles describing how the motion of objects is governed in our Universe, which have been translated, transcribed, discussed and debated at length.

But according to a philosopher of language and mathematics, we might have been interpreting Newton’s precise wording of his first law of motion slightly wrong all along.

Sep 14, 2023

Toward a Complete Theory of Crystal Vibrations

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

A new set of equations captures the dynamical interplay of electrons and vibrations in crystals and forms a basis for computational studies.

Although a crystal is a highly ordered structure, it is never at rest: its atoms are constantly vibrating about their equilibrium positions—even down to zero temperature. Such vibrations are called phonons, and their interaction with the electrons that hold the crystal together is partly responsible for the crystal’s optical properties, its ability to conduct heat or electricity, and even its vanishing electrical resistance if it is superconducting. Predicting, or at least understanding, such properties requires an accurate description of the interplay of electrons and phonons. This task is formidable given that the electronic problem alone—assuming that the atomic nuclei stand still—is already challenging and lacks an exact solution. Now, based on a long series of earlier milestones, Gianluca Stefanucci of the Tor Vergata University of Rome and colleagues have made an important step toward a complete theory of electrons and phonons [1].

At a low level of theory, the electron–phonon problem is easily formulated. First, one considers an arrangement of massive point charges representing electrons and atomic nuclei. Second, one lets these charges evolve under Coulomb’s law and the Schrödinger equation, possibly introducing some perturbation from time to time. The mathematical representation of the energy of such a system, consisting of kinetic and interaction terms, is the system’s Hamiltonian. However, knowing the exact theory is not enough because the corresponding equations are only formally simple. In practice, they are far too complex—not least owing to the huge number of particles involved—so that approximations are needed. Hence, at a high level, a workable theory should provide the means to make reasonable approximations yielding equations that can be solved on today’s computers.

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