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ASInverse Trigonometric Derivatives & Integrals
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NAThe integration of \(e^{-x^{2}}\) (the Gaussian function) is considered one of the "hardest" or most famous non-elementary integrals because it has no antiderivative that can be expressed in terms of elementary functions. Mathematics Stack Exchange +1While the function \(f(x)=e^{-x^{2}}\) is perfectly smooth and continuous—meaning it is definitely integrable in the sense that an area under the curve exists—you cannot define its indefinite integral using standard functions like polynomials, exponentials, logarithms, or trigonometric functions. Mathematics Stack Exchange +1Here is why it is uniquely difficult: 1. No "Elementary" Antiderivative Most calculus integration techniques (like substitution or integration by parts) are designed to reverse-engineer differentiation. However, there is no elementary function \(F(x)\) that you can differentiate to get \(e^{-x^{2}}\). This has been formally proven using Liouville's theorem, which dictates that certain elementary functions do not have
The Gaussian integral, also known as the Euler–Poisson integral, is the integral of the Gaussian function
f(x)=e−x2
over the entire real line. Named after the German mathematician Carl Friedrich Gauss, the integral is
∫−∞∞e−x2dx=π.
@navamienterprises2614
3.0K
POHow the coordinate plane makes calculus make sense
Descartes did not invent calculus, but his coordinate plane made it intelligible. By giving functions a geometric home, it allowed change and accumulation to be seen rather than imagined.
Derivatives grow naturally out of slope. What begins as the rise over run of a line becomes the slope of a curve at a point, visible as a tangent line. Rates of change stop being abstract symbols and become geometric objects.
Integrals grow just as naturally out of area. Total change becomes the area under a curve, built from infinitely many tiny pieces that can be pictured and reasoned about.
Calculus works without graphs, but it becomes understandable because of them. The coordinate plane turns its central ideas into shapes we can see and study.
#calculus #coordinateplane #mathinmybackyard
@polymathematicnet
449.5K
MAThe Gaussian Integral: Why √π is Everywhere in Math & Science
Have you ever wondered why the "bell curve" has such a mathematically perfect area? Let's unpack one of the most elegant results in all of mathematics: ∫₋∞ᴵᴺᶠ e⁻ˣ² dx = √π.
It seems impossible at first—how can this beautifully smooth curve, fading to zero at both ends, have an area exactly equal to the square root of π? The function e⁻ˣ² has no elementary antiderivative (thank the Risch algorithm for that proof!), yet its definite integral over the entire real line yields this precise, fundamental constant.
The key insight? Go 2D. By squaring the integral, we get:
(∫ e⁻ˣ² dx)² = ∫∫ e⁻⁽ˣ²⁺ʸ²⁾ dx dy
Now, switch to polar coordinates (x² + y² = r²), and the area element dx dy becomes r dr dθ. The integral transforms into:
∫₀²π ∫₀ᴵᴺᶠ e⁻ʳ² r dr dθ
The r here is crucial—it comes from the Jacobian when changing coordinates. The angular part integrates to 2π, and with a clever substitution (u = r², du = 2r dr), the radial integral simplifies beautifully to 1/2. Multiply them: 2π × ½ = π.
Take the square root (since we squared at the beginning), and voilà: √π emerges.
This isn't just mathematical artistry—it's foundational. This integral normalizes the Gaussian distribution in statistics (giving us the famous 68–95–99.7 rule), calculates ground state probabilities in quantum mechanics, appears in heat and diffusion equations, and underpins the path integral formulation. From De Moivre's 1733 discovery to Gauss’s 1809 publication and Laplace’s contributions, this result connects geometry, calculus, and probability in one breathtaking equation.
@mathematisa
19
JOThe Analogy of the Non-Trivial Zeros Between the Equations of the Riemann Z Series or Function and the Mathematical Equations of Spiral Angles, Spirals, and Trigonometric Partitions
When we compare these methodologies, we observe that the equations derived from trigonometric partitions are precise in generating the graphical pattern of the Riemann Z function. These same equations express the angle as a function of angular velocity, time, frequency, the constant k, the modulus of length, or even through hyperbolic equations, while still reproducing the same graphical pattern of the Riemann Z function.
Using these equations, it is possible to generate any conformal mapping, construct the Riemann transform, and interpret the Riemann sphere.
In this video, I present comparisons between the non-trivial zeros, which pass extremely close to the point ( z = (0, 0i) ) and the trivial zeros, which do pass through the center at ( z = (0, 0i) ). In the Riemann Z function formulated through the trigonometric partitions of the chord, when the modulus of length equals zero, the equation tends to infinity, thereby creating a pole at the center of the complex plane and generating the apparent void in the graph where the lines cancel out. This behavior does not occur in the network equation.
@josemauricio.orellanadiaz
136
MAMultiple Integrals: Double Integrals - another sample exercise. #multiple #INTEGRAL #double #INTEGRAL #sample #exercises
@magnanaohandeil
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BIderivatives and a few applications (ODEs, PDEs, gradients, approximations...). how do you feel about 2016 (really 2018, with regards to this song) nostalgia? source videos: Phanimations Why Runge-Kutta is SO Much Better Than Euler's Method, OptWhiz Gradients, Hessians, and All Those Derivative Tests, 3Blue1Brown Differential equations, a tourist's guide | DE1, Mathematical Visual Proofs Visualizing Derivatives on Multivariable Surface Plots, 3Blue1Brown But what is a partial differential equation? | DE2.
Abell, M.A., & Braselton, J.P. (2018). Introductory Differential Equations (Fifth Edition). Chapter 6 - Systems of Differential Equations.
"6.8 Numerical Methods: Euler's Method, Runge-Kutta Method, Computer Algebra Systems and Other Software.
Because it may be difficult or even impossible to construct an explicit solution to some systems of differential equations, we now turn our attention to some numerical methods that are used to construct solutions to systems of differential equations. Euler's method for approximation, which was discussed for first order equations, can be extended to include systems of first order equations. The initial value problem dx/dt=f(t,x,y)dy/dt=g(t,x,y)x(t0)=x0,y(t0)=y0 is approximated at each step by the recursive relationship based on the Taylor series expansion of x and y with stepsize h,
As you have seen throughout this text Leonhard Euler (1707–1783) made such significant contributions to mathematics that he may have been the best and most prolific mathematician to have ever liven, yet."
#math #calculus #derivatives #odes #differentialequations
@biochemedits
5.6K
MAHere is an example of how to find the tangent plane to the graph of a function of two variables at a given point using partial derivatives #math #calculus #multivariablecalculus #tangentplane
@mathandcobb
301.2K
MA✨ Master ALL Differentiation Formulas in 14 Seconds! ✨
This reel visualizes the fundamental engine of calculus: the derivative. Watch as we graph a function and instantly transform it into its derivative, revealing the exact rate of change at every point.
From the power rule (xⁿ) to exponentials (eˣ), trigonometry (sin, cos, tan), and beyond—see every major function and its derivative side-by-side. This is the core visual intuition that makes calculus click.
SAVE this ultimate visual cheat sheet for your studies! 🚀
#differentiation #math #fyp #trigonometry #likeme #mathematics #views
Which function's transformation is the most satisfying? 👇
@mathematisa
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MEVisual Trigonometry 📐✨
Watch how an angle on the unit circle transforms directly into the sine, cosine, and tangent graphs. A perfect bridge between theory and visual understanding.
#trigonometry #maths #graphicalrepresentation #education #learning #geometry #algebra #calculus #visualization #ssc #chatgpt #gemini #study #mathematics #engineering #science #university #learning #stem #students
@mechanismworld
17
BYEstimating area and volume is one of the foundational problems that led to the development of calculus. The key idea begins with summation: breaking a complex shape into many smaller, simpler pieces and adding them together.
Using summation, the region under a curve or surface can be approximated by dividing the domain into a finite number of subintervals. Over each interval, a rectangular (or box-shaped) approximation is formed, with its height determined by the function value at a chosen point. Adding the areas or volumes of these pieces produces a Riemann sum, which provides an estimate of the total region. However, because curved boundaries are being approximated with flat shapes, the result contains error. The approximation improves as more subdivisions are used, but it remains an estimate as long as the pieces have nonzero width.
Integration formalizes this process by taking summation to its ultimate limit. Instead of using a fixed number of rectangles, the width of each subdivision is allowed to shrink toward zero. As the number of pieces approaches infinity, the summation becomes an integral, and the approximation becomes exact. Integration therefore represents the precise accumulation of infinitely many infinitesimal contributions, capturing continuous change in a way that finite summation cannot.
In higher dimensions, the same principle applies: volumes under surfaces can be estimated using 3D sums of small boxes, and calculated exactly through double or triple integrals. Integration is essentially the perfected form of summation, providing exact solutions in physics, engineering, and geometry.
#Calculus #Integration #Summation #RiemannSum #MultivariableCalculus #3DMath #VolumeUnderSurface #AreaEstimation #STEMEducation #EngineeringMath #MathematicalModeling #HigherMath #Physics #ContinuousSystems #MathConcepts
@bytebrain.tv
398
VONapier's inequality is an important result in mathematics that compares exponential and linear growth, showing that the exponential function always grows faster than a corresponding linear expression. It helps formalize the idea that exponential behavior quickly outpaces simple addition, which is why it appears in calculus, analysis, and proofs involving limits and growth rates. The inequality is closely connected to the constant e and provides intuition for why exponential functions play such a central role in continuous growth, optimization, and natural processes. By capturing this comparison rigorously, Napier's inequality strengthens our understanding of how different types of growth behave.
#napierinequality #mathexplained #calculusideas #mathanalysis
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