#differentialequations — Public Fediverse posts

Happy (belated) #PiDay

https://chrisphan.com/posts/2026-03-14_happy_belated_pi_day.html

#WebAssembly #JavaScript #differentialEquations

A Brief Course Of Higher Mathematics by V.A. Kudryavtsev

The aim of this text is to set forth the essentials of higher mathematics and their applications in various fields. At present higher mathematics serves as the theoretical foundation for most branches of the natural, applied and engineering sciences. Therefore, every natural scientist must necessarily master its methods to be able to apply them for practical purposes.

Translated from the Russian by Leonid Levant

Many thanks to Guptaji for the scans and Balram Sharmaji of Kamgaar Prakashan for making this book available.

You can get the book here and here

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Contents

INTRODUCTION

Chapter 1. The Rectangular Coordinate System in the Plane and Its Application to Simple Problems
Sec. 1. Rectangular Coordinates of a Point in the Plane
Sec. 2. Transformation of Rectangular Coordinates
Sec. 3. The Distance Between Two Points in the Plane
Sec. 4. Dividing a Line Segment in a Given Ratio
Sec. 5. The Area of a Triangle
Exercises

Chapter 2. The Equation of a Line
Sec. 6. Sets
Sec. 7. The Method of Coordinates in the Plane
Sec. 8. The Line as a Set of Points
Sec. 9. The Equation of a Line in the Plane
Sec. 10. Constructing a Line on the Basis of Its Equation
Sec. 11. Some Elementary Problems
Sec. 12. Two Basic Problems of Plane Analytical Geometry
Sec. 13. Algebraic Lines
Exercises

Chapter 3. The Straight Line
Sec. 14. The Equation of a Straight Line
Sec. 15. The Angle Between Two Straight Lines
Sec. 16. The Equation of a Straight Line Passing Through a Given Point in a Given Direction
Sec. 17. The Equation of a Straight Line Passing Through Two Points (Two-Point Form)
Sec. 18. The Intercept Form of the Equation of a Straight Line
Sec. 19. The Point of Intersection of Two Straight Lines
Sec. 20. The Distance from a Point to a Straight Line
Exercises

Chapter 4. Second-Order Lines
Sec. 21. The Circle
Sec. 22. Central Second-Order Curves (Conics)
Sec. 23. Focal Properties of Central Curves of the Second Order
Sec. 24. The Ellipse as a Uniformly Compressed Circle
Sec. 25. The Asymptotes of a Hyperbola
Sec. 26. The Graph of Inverse Proportionality
Sec. 27. Noncentral Quadric Curves
Sec. 28. The Focal Property of the Parabola
Sec. 29. The Graph of a Quadratic Trinomial
Exercises

Chapter 5. Polar Coordinates. Parametric Equations of a Line
Sec. 30. Polar Coordinates
Sec. 31. Relationship Between Rectangular and Polar Coordinates
Sec. 32. Parametric Equations of a Line
Sec. 33. Parametric Equations of the Cycloid
Exercises

Chapter 6. Functions
Sec. 34. Constants and Variables
Sec. 35. The Concept of Function
Sec. 36. Simplest Functional Relations
1. Direct Proportional Relation
2. Linear Relation
3. Inverse Proportional Relation
4. Quadratic Relation
5. Sinusoidal Relation
Sec. 37. Methods of Representing Functions
1. The Analytical Method
2. The Tabular Method
3. The Graphical Method
Sec. 38. The Concept of Function of Several Variables
Sec. 39. Implicit Function
Sec. 40. Inverse Function
Sec. 41. Classification of Functions of One Argument
Sec. 42. The Graphs of the Basic Elementary Functions
Sec. 43. Interpolation of Functions
Exercises

Chapter 7. The Theory of Limits
Sec. 44. Real Numbers
Sec. 45. Errors of Approximate Numbers
Sec. 46. Limit of a Function
Sec. 47. One-Sided Limits of a Function
Sec. 48. Limit of a Sequence
Sec. 49. Infinitesimals
Sec. 50. Infinitely Large Quantities
Sec. 51. Basic Properties of Infinitesimals
Sec. 52. Basic Limit Theorems
Sec. 53. Some Tests for the Existence of the Limit of a Function
Sec. 54. The Limit of X
Sec. 55. The Number e
Sec. 56. Natural Logarithms
Sec. 57. Asymptotic Formulas
Exercises

Chapter 8. Continuity of Functions
Sec. 58. Increments of an Argument and a Function. Continuity of a Function
Sec. 59. Another Definition of the Continuity of a Function
Sec. 60. Continuity of Basic Elementary Functions
Sec. 61. Basic Theorems on Continuous Functions
Sec. 62. Evaluation of Indeterminacies
Sec. 63. Classification of the Points of Discontinuity of a Function
Exercises

Chapter 9. The Derivative of a Function
Sec. 64. A Tangent to a Curve – 159
Sec. 65. Velocity of a Moving Point – 161
Sec. 66. The Derivative Defined Generally – 163
Sec. 67. Other Applications of the Derivative – 166
Sec. 68. Relation Between the Continuity and Differentiability of a Function – 167
Sec. 69. The Notion of an Infinite Derivative – 169
Exercises – 169

Chapter 10. Basic Derivative Theorems
Sec. 70. Introductory Notes – 170
Sec. 71. The Derivatives of Certain Simple Functions – 170
Sec. 72. Basic Differentiation Rules – 174
Sec. 73. The Derivative of a Composite Function – 179
Sec. 74. The Derivative of an Inverse Function – 182
Sec. 75. The Derivative of an Implicit Function – 184
Sec. 76. The Derivative of a Logarithmic Function – 185
Sec. 77. A Logarithmic Derivative – 188
Sec. 78. The Derivative of an Exponential Function – 188
Sec. 79. The Derivative of a Power Function – 190
Sec. 80. The Derivatives of Inverse Trigonometric Functions – 191
Sec. 81. The Derivative of a Function Represented Parametrically – 193
Sec. 82. The Table of Differentiation Formulas – 194
Sec. 83. Derivatives of Higher Orders – 195
Sec. 84. Physical Meaning of the Second Derivative – 195
Exercises – 196

Chapter 11. Applications of Derivatives
Sec. 85. The Theorem About Finite Increments of a Function and Its Corollaries – 199
Sec. 86. Increase and Decrease of a Function of One Argument – 201
Sec. 87. L’Hospital’s Rule – 204
Sec. 88. Taylor’s Formula for a Polynomial – 208
Sec. 89. Binomial Formula – 210
Sec. 90. Taylor’s Formula for a Function – 211
Sec. 91. Maxima and Minima of a Function of One Variable – 213
Sec. 92. Concavity and Convexity of the Graph of a Function. Points of Inflection – 220
Sec. 93. Approximate Solution of Equations – 223
Sec. 94. Construction of Graphs of Functions – 227
Exercises – 230

Chapter 12. Differentials
Sec. 95. The Differential of a Function – 232
Sec. 96. Relation Between the Differential of a Function and Its Derivative. The Differential of the Independent Variable – 235
Sec. 97. The Geometrical Meaning of the Differential – 237
Sec. 98. The Physical Meaning of the Differential – 237
Sec. 99. Approximate Calculation of Small Increments of a Function – 238
Sec. 100. Equivalence of the Increment and Differential of a Function – 239
Sec. 101. Properties of the Differential – 242
Sec. 102. Differentials of Higher Orders – 245
Exercises – 247

Chapter 13. Indefinite Integral
Sec. 103. Antiderivative. Indefinite Integral – 248
Sec. 104. Basic Properties of the Indefinite Integral – 251
Sec. 105. Table of Simplest Indefinite Integrals – 253
Sec. 106. Independence of the Form of an Indefinite Integral of the Argument Chosen – 254
Sec. 107. Basic Integration Methods – 258
Sec. 108. Techniques for Integrating Rational Fractions with a Quadratic Denominator – 263
Sec. 109. Integration of Simplest Irrational Expressions – 267
Sec. 110. Integration of Trigonometric Functions – 269
Sec. 111. Integration of Certain Transcendental Functions – 271
Sec. 112. Cauchy’s Theorem. Some Important Integrals Inexpressible in Terms of Elementary Functions – 271
Exercises – 272

Chapter 14. The Definite Integral
Sec. 113. The Concept of the Definite Integral – 275
Sec. 114. A Definite Integral with a Variable Upper Limit – 277
Sec. 115. Geometrical Meaning of the Definite Integral – 279
Sec. 116. Physical Meaning of the Definite Integral – 281
Sec. 117. Basic Properties of the Definite Integral – 282
Sec. 118. The Mean Value Theorem – 286
Sec. 119. Integration by Parts in the Definite Integral – 288
Sec. 120. Change of Variable in the Definite Integral (Integration by Substitution) – 289
Sec. 121. The Definite Integral as the Limit of an Integral Sum – 291
Sec. 122. Approximate Evaluation of Definite Integrals – 293
Sec. 123. Simpson’s Formula – 296
Sec. 124. Improper Integrals – 297
Exercises – 299

Chapter 15. Applications of the Definite Integral
Sec. 125. Areas in Rectangular Coordinates – 301
Sec. 126. Areas in Polar Coordinates – 305
Sec. 127. The Arc Length in Rectangular Coordinates – 307
Sec. 128. The Arc Length in Polar Coordinates – 313
Sec. 129. Computing the Volume of a Solid by Known Cross Sections – 314
Sec. 130. The Volume of a Solid of Revolution – 316
Sec. 131. The Work of a Variable Force – 319
Sec. 132. Other Applications of the Definite Integral in Physics – 320
Exercises – 322

Chapter 16. Complex Numbers
Sec. 133. Arithmetic Operations on Complex Numbers – 325
Sec. 134. The Complex Plane – 326
Sec. 135. Theorems on the Modulus and Argument – 328
Sec. 136. Taking the Root from a Complex Number – 329
Sec. 137. The Concept of a Function of a Complex Variable – 331
Exercises – 332

Chapter 17. Determinants of Second and Third Order
Sec. 138. Second-Order Determinants – 335
Sec. 139. A System of Two Homogeneous Equations in Three Unknowns – 335
Sec. 140. Third-Order Determinants – 337
Sec. 141. Basic Properties of Determinants – 339
Sec. 142. A System of Three Linear Equations – 342
Sec. 143. A Homogeneous System of Three Linear Equations – 344
Sec. 144. A System of Linear Equations in Many Unknowns. Gauss’ Method – 346
Exercises – 349

Chapter 18. Fundamentals of Vector Algebra
Sec. 145. Scalars and Vectors – 351
Sec. 146. The Sum of Several Vectors – 352
Sec. 147. The Difference of Vectors – 353
Sec. 148. Multiplication of a Vector by a Scalar – 353
Sec. 149. Collinear Vectors – 354
Sec. 150. Coplanar Vectors – 355
Sec. 151. The Projection of a Vector on an Axis – 356
Sec. 152. The Rectangular Cartesian Coordinates in Space – 359
Sec. 153. The Length and Direction of a Vector – 360
Sec. 154. The Distance Between Two Points in Space – 361
Sec. 155. Operations on Vectors Represented in the Coordinate Form – 362
Sec. 156. Scalar Product of Two Vectors – 364
Sec. 157. Scalar Product of Vectors in the Coordinate Form – 366
Sec. 158. Vector Product of Vectors – 367
Sec. 159. Vector Product in the Coordinate Form – 369
Sec. 160. Triple Scalar Product – 371
Exercises – 373

Chapter 19. Fundamentals of Solid Analytic Geometry
Sec. 161. The Equations of a Surface and a Line in Space – 374
Sec. 162. The General Equation of a Plane – 380
Sec. 163. Angle Between Two Planes – 382
Sec. 164. Equations of a Straight Line in Space – 383
Sec. 165. The Derivative of a Vector Function – 387
Sec. 166. The Equation of a Sphere – 389
Sec. 167. The Equation of an Ellipsoid – 391
Sec. 168. The Equation of a Paraboloid of Revolution – 392
Exercises – 393

Chapter 20. Functions of Several Variables
Sec. 169. The Concept of a Function of Several Variables – 395
Sec. 170. Continuity – 398
Sec. 171. Partial Derivatives of the First Order – 401
Sec. 172. The Total Differential of a Function – 403
Sec. 173. Application of the Differential of a Function to Approximate Computations – 409
Sec. 174. Directional Derivatives – 410
Sec. 175. The Gradient – 413
Sec. 176. Partial Derivatives of Higher Orders – 417
Sec. 177. Test for the Total Differential – 418
Sec. 178. The Extremum (Maximum or Minimum) of a Function of Several Variables – 420
Sec. 179. An Absolute Extremum of a Function – 422
Sec. 180. Constructing Empirical Formulas by the Method of Least Squares – 424
Exercises – 428

Chapter 21. Series
Sec. 181. Examples of Infinite Series – 430
Sec. 182. Convergence of a Series – 431
Sec. 183. A Necessary Condition for Convergence of a Series – 435
Sec. 184. Comparison Tests – 437
Sec. 185. D’Alembert’s Test for Convergence – 440
Sec. 186. Absolute Convergence – 444
Sec. 187. Alternating Series. Leibniz’ Test – 446
Sec. 188. Power Series – 447
Sec. 189. Differentiation and Integration of Power Series – 450
Sec. 190. Expanding a Given Function into a Power Series – 450
Sec. 191. Maclaurin’s Series – 452
Sec. 192. Applying Maclaurin’s Series to Expanding Some Functions into Power Series – 453
Sec. 193. Applying Power Series to Approximate Calculations – 456
Sec. 194. Taylor’s Series – 459
Sec. 195. Series in a Complex Domain – 462
Sec. 196. Euler’s Formulas – 463
Sec. 197. Fourier Trigonometric Series – 464
Sec. 198. The Fourier Series of Even and Odd Functions – 473
Sec. 199. The Fourier Series of Nonperiodic Functions – 475
Exercises – 479

Chapter 22. Differential Equations
Sec. 200. Basic Concepts – 481
Sec. 201. Differential Equations of the First Order – 484
Sec. 202. First-Order Equations with Variables Separable – 486
Sec. 203. Homogeneous Differential Equations of the First Order – 492
Sec. 204. Linear Differential Equations of the First Order – 495
Sec. 205. Euler’s Method – 500
Sec. 206. Differential Equations of the Second Order – 502
Sec. 207. Integrable Types of Second-Order Differential Equations – 504
Sec. 208. Reducing the Order of a Differential Equation – 510
Sec. 209. Integrating Differential Equations with the Aid of Power Series – 513
Sec. 210. Common Properties of the Solutions of Second-Order Linear Homogeneous Differential Equations – 514
Sec. 211. Second-Order Linear Homogeneous Differential Equations with Constant Coefficients – 517
Sec. 212. Second-Order Linear Nonhomogeneous Differential Equations with Constant Coefficients – 523
Sec. 213. Differential Equations Containing Partial Derivatives – 533
Sec. 214. Linear Differential Equations with Partial Derivatives – 536
Sec. 215. Deriving the Heat Conduction Equation – 538
Sec. 216. The Problem on Temperature Distribution in a Limited Rod – 540
Exercises – 543
Chapter 23. Line Integrals
Sec. 217. The Line Integral of the First Kind – 546
Sec. 218. The Line Integral of the Second Kind – 548
Sec. 219. The Physical Meaning of the Line Integral of the Second Kind – 552
Sec. 220. Condition Under Which the Line Integral of the Second Kind is Independent of Path – 554
Sec. 221. The Work Performed by a Potential Force – 556
Exercises – 557

Chapter 24. Double and Triple Integrals
Sec. 222. Double Integrals – 561
Sec. 223. The Double Integral in Rectangular Cartesian Coordinates – 564
Sec. 224. Expressing a Double Integral in Polar Coordinates – 571
Sec. 225. The Euler-Poisson Integral – 575
Sec. 226. Mean-Value Theorem – 576
Sec. 227. Geometrical Applications of the Double Integral – 578
Sec. 228. Physical Applications of the Double Integral – 579
Sec. 229. Triple Integrals – 584
Exercises – 588

Chapter 25. Fundamentals of the Theory of Probability
A. Basic Definitions and Theorems
Sec. 230. Random Events – 591
Sec. 231. Algebra of Events – 593
Sec. 232. The Classical Definition of Probability – 594
Sec. 233. The Statistical Definition of Probability – 597
Sec. 234. The Theorem on Addition of Probabilities – 598
Sec. 235. A Complete Group of Events – 599
Sec. 236. The Theorem on Multiplication of Probabilities – 600
Sec. 237. Bayes’ Formula – 603

B. Repeated Independent Trials
Sec. 238. Elements of Combinatorial Analysis – 604
Sec. 239. The Formula of Total Probability – 605
Sec. 240. The Binomial Law of Distribution of Probabilities – 607
Sec. 241. The Laplace Local Theorem – 608
Sec. 242. The Laplace Integral Theorem – 610
Sec. 243. Poisson’s Theorem – 614

C. Random Variables and Their Numerical Characteristics
Sec. 244. A Random Discrete Variable and Its Distribution Law – 615
Sec. 245. Mathematical Expectation – 617
Sec. 246. Basic Properties of Mathematical Expectation – 618
Sec. 247. Variance – 621
Sec. 248. Continuous Random Variables. Distribution Functions – 626
Sec. 249. Numerical Characteristics of a Continuous Random Variable – 630
Sec. 250. Uniform Distribution – 631
Sec. 251. Normal Distribution – 633
Exercises – 636

Chapter 26. The Concept of Linear Programming
Sec. 252. An n-Dimensional Vector Space – 639
Sec. 253. Sets in n-Dimensional Space – 641
Sec. 254. The Problem of Linear Programming – 645

APPENDICES
A. Most Important Constants – 650
B. List of Formulas (Classified and Explained) – 650
I. Plane Analytic Geometry – 650
II. Differential Calculus—Functions of One Variable – 652
III. Integral Calculus – 654
IV. Complex Numbers, Determinants, and Systems of Simultaneous Equations – 658
V. Elements of Vector Algebra – 660
VI. Solid Analytic Geometry – 661
VII. Differential Calculus—Functions of Several Variables – 662
VIII. Series – 663
IX. Differential Equations – 666
X. Line Integrals – 668
XI. Double and Triple Integrals – 669
XII. Probability Theory – 671

ANSWERS – 674
SUBJECT INDEX – 684

Wolfram Blog: Finally… a Wolfram U Course for Everyone on Partial Differential Equations!. “Today, I am happy to announce a free interactive course, Introduction to Partial Differential Equations, that will help students all over the world master this important subject. This course introduces partial differential equations (PDEs) from scratch and covers the most important types and their […]

Equations Of The Mixed Type by A.V. Bitsadze

The theory of equations of mixed type originated in the fundamental researches of the Italian mathematician Francesco Tricomi, which were published in the twenties of this century. Owing to the importance of its applications, the discussion of problems concerned with equations of mixed type has become, in the last ten years, one of the central problems in the theory of partial differential equations.

The present work is not meant to be a summary of all results in this field, especially since the number of results increases with great speed; nevertheless, the reader of this monograph will obtain an idea of the present state of the theory of equations of mixed type.

This book was developed from a series of lectures dealing with certain fundamental questions in the theory of equations of mixed type, which the Author delivered in scientific establishments in the Chinese People’s Republic at the end of 1957 and the beginning of 1958.

Translated by P. Zador

Translation edited by I. N. Sneddon

You can get the book here and here.

CONTENTS

Foreword ix

Introduction xi

1. General remarks on linear partial differential equations of mixed type 1

1. Equation of the second order with two independent variables 1

2. The theory of Cibrario 3

3. Systems of two first order equations 12

4. Linear systems of partial differential equations of the second order with two independent variables 17

2. The study of the solutions of second order hyperbolic equations with initial conditions given along the lines of parabolicity 20

1. The Riemann function for a second order hyperbolic linear equation 20

2. A class of hyperbolic systems of second order linear equations 27

3. The Cauchy problem for hyperbolic equations with given initial conditions on the line of parabolic degeneracy 32

4. Generalizations 41

3. The study of the solutions of second order elliptic equations for a domain, the boundary of which includes a segment of the curve of parabolic degeneracy 44

1. The linear elliptic partial differential equation of the second order 44

2. Elliptic systems of second order 49

3. The Dirichlet problem for second order elliptic equations in a domain, the boundary of which includes a segment of the curve of parabolic degeneracy 58

4. Some other problems and generalizations 66

4. The problem of Tricomi 71

1. The statement of the problem of Tricomi 72

2. The extremal principle and the uniqueness of the solution of problem T 74

3. Solution of problem T by means of the method of integral equations 78

4. Continuation. The proof for the existence of a solution of the integral equations obtained in the preceding paragraph 90

5. Other methods for solving problem T 94

6. Examples and generalizations 103

5. Other mixed problems 112

1. The mixed problem M 112

2. The proof of the uniqueness of solution for problem M 113

3. Concerning the existence of the solution of problem M 117

4. The general mixed problem 124

5. The problem of Frankl 135

6. Short indication of some important generalizations and applications 141

References 151

Index 157

#1964 #differentialEquations #mathematics #solutionsToDifferentialEquations #sovietLiterature #tricomiProblem

On Pi Day 2025, as you might recall, I introduced you (more or less) to 3Blue1Brown. Also known as Grant Sanderson.

If there's any better source of animated math presentations, than Mr. Sanderson, I'm unaware of it.

Key word: "animated." In addition, he is a warm, enthusiastic teacher. And of course he knows his stuff well—how else could he have made the truly fantastic animations?

I haven't watched them all yet. But so far, I especially like 2016's BUT WHAT IS THE RIEMANN ZETA FUNCTION? VISUALIZING ANALYTIC CONTINUATION and 2019's DIFFERENTIAL EQUATIONS, A TOURIST'S GUIDE | DE1.

I may never again be able to ponder some ideas they convey, without seeing those animations in my head. They're that perfect.

So give those two videos a try, if you're comfortable enough with the one I had shared on Pi Day...if now you want a couple which are more challenging. Maybe unforgettable, too.

#3Blue1Brown
#RiemannZetaFunction
#DifferentialEquations
#learning

https://mindly.social/@setsly/114161481212443838

https://www.youtube.com/watch?v=sD0NjbwqlYw

https://www.youtube.com/watch?v=p_di4Zn4wz4

A cycloidal pendulum - one suspended from the cusp of an inverted cycloid - is isochronous, meaning its period is constant regardless of the amplitude of the swing. Please find the proof using energy methods: Lagrange's equations (in the images attached to the reply).

Background:
The standard pendulum period of \(2\pi\sqrt{L/g}\) or frequency \(\sqrt{g/L}\) holds only for small oscillations. The frequency becomes smaller as the amplitude grows. If you want to build a pendulum whose frequency is independent of the amplitude, you should hang it from the cusp of a cycloid of a certain size, as shown in the gif. As the string wraps partially around the cycloid, the effect decreases the length of the string in the air, increasing the frequency back up to a constant value.

In more detail:
A cycloid is the path taken by a point on the rim of a rolling wheel. The upside-down cycloid in the gif can be parameterized by \((x, y)=R(\theta-\sin\theta, -1+\cos\theta)\), where \(\theta=0\) corresponds to the cusp. Consider a pendulum of length \(L=4R\) hanging from the cusp, and let \(\alpha\) be the angle the string makes with the vertical, as shown (in the proof).

#Pendulum #Cycloid #Period #Frequency #SHM #TimePeriod #CycloidalPendulum #Lagrange #Cusp #Energy #KineticEnergy #PotentialEnergy #Lagrangian #Length #Math #Maths #Physics #Mechanics #ClassicalMechanics #Amplitude #CircularFrequency #Motion #Vibration #HarmonicMotion #Parameter #ParemeterizedEquation #GoverningEquations #Equation #Equations #DifferentialEquations #Calculus

Splash-free urinals: Design through physics and differential equations

https://academic.oup.com/pnasnexus/article/4/4/pgaf087/8098745?login=false

#HackerNews #SplashFreeUrinals #DesignThroughPhysics #DifferentialEquations #Innovation #Invention

I could watch forever ... #LorenzAttractor #ButterflyEffect #JavaScript #p5js #DifferentialEquations #math #visualization #computergraphics #dynamicsystems

L'Hôpital's rule is when you're trying to calculate the derivative of a complex function. Not only you fail, but the function beats you up, steals your lunch money, and sends you to the hospital.

#math #calculus #DifferentialEquations #LHôpitalsRule #AbjectFailure #MathJoke

WHY VARIATION OF PARAMETERS WORKS

This is more conceptual than a proof, but I find it comforting.

Consider the equation:

y' - y = xe^x

The solution will consist of a Homogeneous Solution and a Particular Solution; add the two for the complete solution.

The Homogeneous Solution is the solution that, when you run it through the left side of the equation, it always goes to zero. So you need the Homogeneous Solution for the same reason you need the "+ C" in antiderivatives: even if it's kind of the boring throwaway part of the solution, it is still part of the complete solution.

But Variation of Parameters finds another use for the Homogeneous Solution. Let us suppose that the Particular Solution is the Homogeneous Solution times a function "u". Well, if you feed the Particular Solution through the left side of the equation, the Homogeneous Solution part will tend to go away, leaving "u". So then you can multiply "u" by the Homogeneous Solution, and you've got your Particular Solution.

It kind of reminds me of how Taylor Series work. In a Taylor Series, you have a function that you can think of as secretly containing a multitude of polynomial terms, and the trick is finding a way to torture the function into confessing the coefficients on each polynomial term. In the case of Taylor it's done by iteratively differentiating and then setting "x" to zero, thus leaving a constant that is the coefficient for a given polynomial. (There's also that "n!" term but that's just details.)

Or Fourier Series: a periodic function secretly contains a multitude of sine and cosine terms, and again you find a way to torture it into confessing the coefficients on each sine / cosine. In that case the torture technique involves integration.

And in the case of Variation of Parameters, the torture technique is, we know what part of the particular solution gets burned away by the left side of the equation; the charred skeleton that remains is the other part of the particular solution.

#DifferentialEquations #VariationOfParameters #diffeq

i wonder if it's possible to make a video game that would teach kids the intuition behind the "butterfly effect" by making each subsequent level's initial conditions determined by the outcome of the previous level, in such a way that the gameplay would guide you towards understanding that tiny decisions made on the first level will have huge consequences on level two, etc. #chaos #butterflyEffect #chaosTheory #deterministic #systems #nonlinear #differentialEquations #bifurcation cc @JamesGleick

Whenever I walk to/from home, I have to walk up/down an inclined street; I noticed that the asphalt floor has different curvatures depending on how near it is of a bend, and I try to find a less steep incline while walking.

This got me inspiration for the few questions below. Any simple explanations, and related links, are welcome.

Given a #differentiable surface within R^3, and two distinct points in it, there are infinitely many differentiable paths from one point to another, remaining on the surface. At each point of the #path, one can find the path's local #curvature. Then:

- Find a path that minimizes the supreme of the curvature. In other words, find the "flattest" path.

- Find a path that minimizes the variation of the curvature. In other words, find a path that "most resembles" a circle arc.

Are these tasks always possible within the given conditions? Are any stronger conditions needed? Are there cases with an #analytic solution, or are they possible only with numerical approximations?

#Analysis #DifferentialGeometry #Calculus #DifferentialEquations #NumericalMethods

Whenever I walk to/from home, I have to walk up/down an inclined street; I noticed that the asphalt floor has different curvatures depending on how near it is of a bend, and I try to find a less steep incline while walking.

This got me inspiration for the few questions below. Any simple explanations, and related links, are welcome.

Given a #differentiable surface within R^3, and two distinct points in it, there are infinitely many differentiable paths from one point to another, remaining on the surface. At each point of the #path, one can find the path's local #curvature. Then:

- Find a path that minimizes the supreme of the curvature. In other words, find the "flattest" path.

- Find a path that minimizes the variation of the curvature. In other words, find a path that "most resembles" a circle arc.

Are these tasks always possible within the given conditions? Are any stronger conditions needed? Are there cases with an #analytic solution, or are they possible only with numerical approximations?

#Analysis #DifferentialGeometry #Calculus #DifferentialEquations #NumericalMethods

Whenever I walk to/from home, I have to walk up/down an inclined street; I noticed that the asphalt floor has different curvatures depending on how near it is of a bend, and I try to find a less steep incline while walking.

This got me inspiration for the few questions below. Any simple explanations, and related links, are welcome.

Given a #differentiable surface within R^3, and two distinct points in it, there are infinitely many differentiable paths from one point to another, remaining on the surface. At each point of the #path, one can find the path's local #curvature. Then:

- Find a path that minimizes the supreme of the curvature. In other words, find the "flattest" path.

- Find a path that minimizes the variation of the curvature. In other words, find a path that "most resembles" a circle arc.

Are these tasks always possible within the given conditions? Are any stronger conditions needed? Are there cases with an #analytic solution, or are they possible only with numerical approximations?

#Analysis #DifferentialGeometry #Calculus #DifferentialEquations #NumericalMethods

Whenever I walk to/from home, I have to walk up/down an inclined street; I noticed that the asphalt floor has different curvatures depending on how near it is of a bend, and I try to find a less steep incline while walking.

This got me inspiration for the few questions below. Any simple explanations, and related links, are welcome.

Given a #differentiable surface within R^3, and two distinct points in it, there are infinitely many differentiable paths from one point to another, remaining on the surface. At each point of the #path, one can find the path's local #curvature. Then:

- Find a path that minimizes the supreme of the curvature. In other words, find the "flattest" path.

- Find a path that minimizes the variation of the curvature. In other words, find a path that "most resembles" a circle arc.

Are these tasks always possible within the given conditions? Are any stronger conditions needed? Are there cases with an #analytic solution, or are they possible only with numerical approximations?

#Analysis #DifferentialGeometry #Calculus #DifferentialEquations #NumericalMethods

Whenever I walk to/from home, I have to walk up/down an inclined street; I noticed that the asphalt floor has different curvatures depending on how near it is of a bend, and I try to find a less steep incline while walking.

This got me inspiration for the few questions below. Any simple explanations, and related links, are welcome.

Given a #differentiable surface within R^3, and two distinct points in it, there are infinitely many differentiable paths from one point to another, remaining on the surface. At each point of the #path, one can find the path's local #curvature. Then:

- Find a path that minimizes the supreme of the curvature. In other words, find the "flattest" path.

- Find a path that minimizes the variation of the curvature. In other words, find a path that "most resembles" a circle arc.

Are these tasks always possible within the given conditions? Are any stronger conditions needed? Are there cases with an #analytic solution, or are they possible only with numerical approximations?

#Analysis #DifferentialGeometry #Calculus #DifferentialEquations #NumericalMethods

from "Present State of the Lanchester Theory of Combat" by Ladislav Dolanský (1964)

https://pubsonline.informs.org/doi/10.1287/opre.12.2.344?utm_source=dlvr.it&utm_medium=mastodon

#math #differentialequations

LINEAR TRANSPORT EQUATION
The linear transport equation (LTE) models the variation of the concentration of a substance flowing at constant speed and direction. It's one of the simplest partial differential equations (PDEs) and one of the few that admits an analytic solution.

Given \(\mathbf{c}\in\mathbb{R}^n\) and \(g:\mathbb{R}^n\to\mathbb{R}\), the following Cauchy problem models a substance flowing at constant speed in the direction \(\mathbf{c}\).
\[\begin{cases}
u_t+\mathbf{c}\cdot\nabla u=0,\ \mathbf{x}\in\mathbb{R}^n,\ t\in\mathbb{R}\\
u(\mathbf{x},0)=g(\mathbf{x}),\ \mathbf{x}\in\mathbb{R}^n
\end{cases}\]
If \(g\) is continuously differentiable, then \(\exists u:\mathbb{R}^n\times\mathbb{R}\to\mathbb{R}\) solution of the Cauchy problem, and it is given by
\[u(\mathbf{x},t)=g(\mathbf{x}-\mathbf{c}t)\]

#LinearTransportEquation #LinearTransport #Cauchy #CauchyProblem #PDE #PDEs #CauchyModel #Math #Maths #Mathematics #Linear #LinearPDE #TransportEquation #DifferentialEquations

I am excited to see "Splitting methods for differential equations" by Sergio Blanes, Fernando Casas and Ander Murua on arXiv: https://arxiv.org/abs/2401.01722

This is a review article to be published in the excellent Acta Numerica. It discusses numerical methods for solving differential equations which can be split in several parts that are easier to solve. In formulas, the (ordinary or partial) differential equation is 𝑑𝑢/𝑑𝑡 = 𝑓(𝑢) and the splitting is 𝑓(𝑢) = 𝑓₁(𝑢) + 𝑓₂(𝑢).

For people that don't do numerical analysis or computational mathematics, it may be helpful to think of the Lie–Trotter product formula
\[ e^{A+B} = \lim_{n\to\infty} (e^{A/n}e^{B/n})^n. \]
This is the simplest splitting method. Part of the game is to find formulas that converge faster.

#NumericalAnalysis #DifferentialEquations #SplittingMethods

It's almost the end of this year's gathering. Our final session of talks featured Adam Townsend, who showed us how we can use differential equations to make beautiful moving patterns - you can explore them yourselves at https://visualpde.com. We also heard from Hannah Gray, who was inspired by playing http://heardledecades.com to talk about whether men sing more songs (spoiler alert: yes, but it's better now than it was in the 1950s!) Last but absolutely not least, Colin Wright talked about the twist of a Moebius Rollercoaster: https://en.wikipedia.org/wiki/Grand_National_(roller_coaster) #mathsjam #maths #differentialequations #movingpatterns #skittles #uniqueness #moebius #rollercoasters #music #domensingmore

from "A Differential Equation with Non-Unique Solutions" by Philip Hartman (1963)

https://www.jstor.org/stable/2313120?utm_source=dlvr.it&utm_medium=mastodon

#math #differentialequations

It’s been a week so a #reintroduction now with more #hashtags

I am naura. Been here a week and looks like i am here to stay. born and grew up in #SoCal. I am in the #SFbayarea right now. I am in my 40s and a stay at home mom.

Some hobbies i’ve had are processing wool using the #spinningwheel, #knitting, #crocheting, #crossstitching, #drawing, #cooking -

My only consistent fandom has been #StarTrek. My favorite is #StarTrekVOY and i am a die hard JC shipper. Right now i need #warehouse13 to be rebooted!!!!!

I also love #math specifically #linearAlgebra and #differentialEquations visually.

I guess that’s it for now :)

#LateDignosedADHD. #MajorDepressiveDisorder
#Medicated
#endthestigma

Have you already taken a look at the newest paper of our workshop participants?🤠

Stefano Almi, Marco Morandotti, Francesco Solombrino: Optimal control problems in transport dynamics with additive noise
https://arxiv.org/pdf/2303.04877.pdf

#DifferentialEquations #OptimizationandControl

@univienna @stem_univie

(for the video click at https://twitter.com/ESIVienna/status/1678690316377833472)
@PoliTOnews

Beautiful PDE visualization tool!

Here's a reaction-diffusion system with a pic of Turing himself as the initial condition.

https://visualpde.com/sim/?preset=Alan

#Mathematics #DifferentialEquations #PDEs #ODEs

Top Math Prize Awarded for Describing the Dynamics of the Flow of Rivers and the Melting of Ice - Scientific American
https://www.scientificamerican.com/article/top-math-prize-awarded-for-describing-the-dynamics-of-the-flow-of-rivers-and-the-melting-of-ice/#

I hated diff-EQ at University, because I found the topic unapproachably difficult. So I have to admire someone brave enough too take on the field professionally and make significant enough progress to win the Abel Prize

#mathematics #differentialEquations