Category Archives: Science & Mathematics

Solving Euler’s formula for polyhedra, Navier-Stokes equations, and Feynman path integral using Python

Euler’s formula, the Navier-Stokes equations, and the Feynman path integral are three important concepts in the fields of mathematics and physics. Just to clarify, they are not a tall connected to one another directly, however, they are all related to our understanding of the world around us. We will be using the Python programming language to explore and solve these concepts. My assumption is that you understand all these formula’s and hence attempting to solve it using Python.

Euler’s formula is a tool that helps us understand the structure of three-dimensional shapes called polyhedra. It tells us the relationship between the number of vertices, edges, and faces that make up a polyhedron.

The Navier-Stokes equations, on the other hand, are used to study the movement of fluids. These equations are a set of mathematical statements that describe how fluids behave and are used to model the flow of liquids and gases in many different situations.

The Feynman path integral, named after physicist Richard Feynman, is a way of understanding the behavior of particles at the quantum level. It allows physicists to make predictions about the actions of particles by considering all of the possible paths they might take and calculating the chances of each one occurring.

Solving Euler’s formula for polyhedra using Python code

This is a Python function that checks if a three-dimensional shape, called a polyhedron, follows a certain rule called Euler’s formula. To use the function, you need to give it three whole numbers, which represent the number of flat faces, straight edges, and points on the polyhedron. The function will then tell you if the polyhedron follows Euler’s formula by giving you either ‘True’ or ‘False’:

def satisfies_euler(V, E, F):
  return V - E + F == 2
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Solving 5 mathematical Conjecture puzzles with Python code

There are many complex math puzzles that have stumped mathematicians and puzzle enthusiasts alike. Here are 5 mathematical conjecture puzzles that I have attempted to explain and solve using Python:

The Collatz Conjecture

The Collatz conjecture is a mathematical problem that involves a sequence of positive integers that are generated according to a specific rule. The conjecture states that for any positive integer, the sequence will eventually reach the number 1, regardless of the starting number.

Here is a simple Python function that generates the Collatz sequence for a given starting number:

def collatz(n):
    while n != 1:
        print(n, end=", ")
        if n % 2 == 0:
            n = n // 2
        else:
            n = 3*n + 1
    print(1)

To use this function, you would simply call it with a positive integer as the argument, like this:

collatz(10)

This would output the following sequence:

10, 5, 16, 8, 4, 2, 1

The conjecture has been verified for many starting numbers, but it has not been proven for all positive integers. Despite much effort, a general proof or counterexample has not yet been found.

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Indian Traditional mathematics equations in Python Code

Indian mathematics has a rich history dating back thousands of years. Some of the key contributions of traditional Indian mathematics include the development of the decimal place-value system and the concept of zero, as well as the development of various equations, trigonometry and algebra. In this article we will attempt to reproduce these equations using Python code.

The Pythagorean theorem

The Pythagorean theorem which states that in a right triangle, the square of the length of the hypotenuse (the side opposite the right angle) is equal to the sum of the squares of the other two sides:

a^2 + b^2 = c^2
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How mathematics is helping in the fight against climate change?

Mathematics plays a critical role in understanding and addressing climate change. Mathematical models are used to simulate and predict the impacts of climate change, as well as to evaluate the effectiveness of different strategies for mitigating and adapting to these impacts.

For example, mathematical models can be used to predict the trajectory of carbon dioxide and other greenhouse gases in the atmosphere, to model the impacts of different levels of greenhouse gas emissions on global temperatures and weather patterns, and to evaluate the costs and benefits of different options for reducing greenhouse gas emissions. In addition, mathematical techniques are used to optimize the design and operation of renewable energy systems and to evaluate the potential for different technologies to contribute to the transition to a low-carbon economy.

Finally, mathematics is used to analyze and interpret the large and complex datasets generated by climate and weather observations and experiments, and to extract insights and inform decision-making about climate change.

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