The document summarizes Tejs's uvw method for analyzing inequalities involving three variables a, b, c. It presents the following key ideas:
1) The uvw method expresses the variables a, b, c in terms of three new variables u, v, w using certain formulas.
2) It proves that when u, v, and one of w, u, or v is fixed, the remaining variable has a global maximum and minimum value. The maximum is achieved only when two of a, b, c are equal.
3) It introduces qualitative estimations to avoid complications from square roots in the bounds on w. The maximum is often achieved when two variables are equal.
This document discusses partial differential equations and heat transfer problems. It provides an example of modeling heat flow through a straight bar using principles of physics. This leads to the derivation of the one-dimensional heat equation. Boundary and initial conditions are also discussed. Solutions are found using the method of separation of variables. The document also briefly discusses the wave equation and Fourier series, providing examples of their applications to problems of heat transfer and vibrating strings.
On Some Geometrical Properties of Proximal Sets and Existence of Best Proximi...BRNSS Publication Hub
The notion of proximal intersection property and diagonal property is introduced and used to establish some existence of the best proximity point for mappings satisfying contractive conditions.
The document summarizes the brachistochrone problem from calculus of variations. It introduces the brachistochrone curve as the curve of fastest descent under gravity between two points. The problem is then solved using tools from calculus of variations, arriving at the Euler-Lagrange equation. This equation shows that the brachistochrone curve between two points is a cycloid. Additionally, the document discusses that the cycloid is a tautochronic curve, meaning an object will take the same amount of time to slide from any point on it to the lowest point.
This document provides a summary of key concepts that must be known for AP Calculus, including:
- Curve sketching and analysis of critical points, local extrema, and points of inflection
- Common differentiation and integration rules like product rule, quotient rule, trapezoidal rule
- Derivatives of trigonometric, exponential, logarithmic, and inverse functions
- Concepts of limits, continuity, intermediate value theorem, mean value theorem, fundamental theorem of calculus
- Techniques for solving problems involving solids of revolution, arc length, parametric equations, polar curves
- Series tests like ratio test and alternating series error bound
- Taylor series approximations and common Maclaurin series
1. The document provides calculations for determining work done by electric fields on charges moving through various paths. It includes determining incremental work from given electric field expressions and calculating potentials from different charge distributions.
2. Key results include the work done on a 20 μC charge moving in different directions in a given electric field, the potential and potential difference from a uniform spherical charge distribution, and expressing the potential field of an infinite line charge with different references.
3. The final problem calculates the potential at a point from the combined electric fields of a uniform sheet charge, uniform line charge, and point charge, with the potential set to zero at a reference point.
The document summarizes key concepts from Chapter 3 of an electrostatics textbook. It includes examples of using Gauss's law to calculate electric flux and electric field for various charge distributions, including:
1) A charged penny, nickel, and dime suspended inside a metal paint can.
2) Point and line charges in space and calculating the electric flux density at a given point.
3) Cylindrical and spherical charge distributions and calculating total charge and electric flux density.
4) A volume charge distribution of constant density and calculating the electric field and flux density everywhere.
1) The document contains examples calculating various vector operations such as finding unit vectors, magnitudes, dot and cross products, and vector components.
2) It also contains examples finding vector fields, surfaces where vector field components are equal to scalars, and demonstrating properties of vector fields such as being everywhere parallel.
3) The document tests understanding of vector concepts through multiple practice problems.
This document discusses partial differential equations and heat transfer problems. It provides an example of modeling heat flow through a straight bar using principles of physics. This leads to the derivation of the one-dimensional heat equation. Boundary and initial conditions are also discussed. Solutions are found using the method of separation of variables. The document also briefly discusses the wave equation and Fourier series, providing examples of their applications to problems of heat transfer and vibrating strings.
On Some Geometrical Properties of Proximal Sets and Existence of Best Proximi...BRNSS Publication Hub
The notion of proximal intersection property and diagonal property is introduced and used to establish some existence of the best proximity point for mappings satisfying contractive conditions.
The document summarizes the brachistochrone problem from calculus of variations. It introduces the brachistochrone curve as the curve of fastest descent under gravity between two points. The problem is then solved using tools from calculus of variations, arriving at the Euler-Lagrange equation. This equation shows that the brachistochrone curve between two points is a cycloid. Additionally, the document discusses that the cycloid is a tautochronic curve, meaning an object will take the same amount of time to slide from any point on it to the lowest point.
This document provides a summary of key concepts that must be known for AP Calculus, including:
- Curve sketching and analysis of critical points, local extrema, and points of inflection
- Common differentiation and integration rules like product rule, quotient rule, trapezoidal rule
- Derivatives of trigonometric, exponential, logarithmic, and inverse functions
- Concepts of limits, continuity, intermediate value theorem, mean value theorem, fundamental theorem of calculus
- Techniques for solving problems involving solids of revolution, arc length, parametric equations, polar curves
- Series tests like ratio test and alternating series error bound
- Taylor series approximations and common Maclaurin series
1. The document provides calculations for determining work done by electric fields on charges moving through various paths. It includes determining incremental work from given electric field expressions and calculating potentials from different charge distributions.
2. Key results include the work done on a 20 μC charge moving in different directions in a given electric field, the potential and potential difference from a uniform spherical charge distribution, and expressing the potential field of an infinite line charge with different references.
3. The final problem calculates the potential at a point from the combined electric fields of a uniform sheet charge, uniform line charge, and point charge, with the potential set to zero at a reference point.
The document summarizes key concepts from Chapter 3 of an electrostatics textbook. It includes examples of using Gauss's law to calculate electric flux and electric field for various charge distributions, including:
1) A charged penny, nickel, and dime suspended inside a metal paint can.
2) Point and line charges in space and calculating the electric flux density at a given point.
3) Cylindrical and spherical charge distributions and calculating total charge and electric flux density.
4) A volume charge distribution of constant density and calculating the electric field and flux density everywhere.
1) The document contains examples calculating various vector operations such as finding unit vectors, magnitudes, dot and cross products, and vector components.
2) It also contains examples finding vector fields, surfaces where vector field components are equal to scalars, and demonstrating properties of vector fields such as being everywhere parallel.
3) The document tests understanding of vector concepts through multiple practice problems.
1) The document discusses integration as the reverse process of differentiation, and provides examples of integrating logarithmic and exponential functions.
2) Key points covered include integrating 1/x as ln(x), and exponential functions like e3x by using u-substitution and dividing the "tail" by the exponent.
3) The document also demonstrates integrating logarithmic expressions using u-substitution, letting the term in the denominator equal u and finding du.
This document discusses electromagnetic plane waves in various materials. It contains:
1) Derivations of plane wave solutions to Maxwell's equations and expressions for the electric and magnetic fields.
2) Examples calculating wave properties like wavelength, propagation velocity, and Poynting vector for different materials and field configurations.
3) Exercises finding field values at specific points given propagating plane wave descriptions.
The document summarizes the solution process for determining the deflection, bending moment, and stress of a simply supported beam subjected to an external forcing function. Natural frequencies are calculated as ωn = n^2π^2/L^2(EI/ρA). Mode shapes are sinusoidal functions of nπx/L. Forced response is determined using mode superposition, yielding a deflection proportional to sin(Ωt) and sin(ω1t) with spatial dependence of sin(πx/L). Bending moment and stress are derived from deflection and have the same functional forms.
Here the concept of "TRUE" is defined according to Alfred Tarski, and the concept "OCCURING EVENT" is derived from this definition.
From here, we obtain operations on the events and properties of these operations and derive the main properties of the CLASSICAL PROB-ABILITY. PHYSICAL EVENTS are defined as the results of applying these operations to DOT EVENTS.
Next, the 3 + 1 vector of the PROBABILITY CURRENT and the EVENT STATE VECTOR are determined.
The presence in our universe of Planck's constant gives reason to\linebreak presume that our world is in a CONFINED SPACE. In such spaces, functions are presented by Fourier series. These presentations allow formulating the ENTANGLEMENT phenomenon.
Global Journal of Science Frontier Research: FMathematics and Decision Sciences Volume 18 Issue 2 Version 1.0 Year 2018
The document contains 10 problems involving electromagnetic induction and Maxwell's equations. Problem 10.1 involves calculating the voltage and current in a circuit with a changing magnetic flux. Problem 10.2 replaces a voltmeter with a resistor and calculates the resulting current. Problem 10.3 calculates the emf induced in closed paths with changing magnetic fluxes.
1) Four positive charges are located at the corners of a square in the xy-plane. A fifth positive charge is located 8cm from the others. The total force on the fifth charge is calculated to be 4.0x10-4 N directed along the z-axis.
2) Two charges of Q1 coulombs are located at z=±1. For a third charge Q2 to produce zero total electric field at (0,1,0), Q2 must lie along the y-axis at y=1±21/4|Q2|/Q1, where the sign depends on the sign of Q2.
3) The total force on a 50nC charge
This document contains summaries of 9 problems from Chapter 13 of an electromagnetic waves textbook. The problems involve calculating reflection and transmission coefficients at dielectric interfaces, as well as power densities, wave propagation, and standing wave ratios. Key steps and results are presented concisely.
The velocity of a vector function is the absolute value of its tangent vector. The speed of a vector function is the length of its velocity vector, and the arc length (distance traveled) is the integral of speed.
The document summarizes Green's theorem, Stokes' theorem, and Gauss' divergence theorem from vector calculus. Green's theorem relates a line integral around a closed curve to a double integral over the region bounded by the curve. Stokes' theorem relates a surface integral over a closed surface to a line integral around its boundary. Gauss' divergence theorem relates the flux of a vector field through a closed surface to the volume integral of the divergence over the enclosed region. An example application of Gauss' theorem to compute the flux of a vector field out of a unit sphere is also provided.
This document discusses inverse trigonometric functions including arcsine, arccosine, and arctangent. It explains that arcsine is the inverse of sine, with domain [-1,1] and range [-π/2, π/2]. Arccosine has domain [-1,1] and range [0,π]. Arctangent has domain (-∞, ∞) and range [-π/2, π/2]. The document also notes that applying the inverse function twice returns the original value, and the outer function's domain takes precedence when functions are composed. It recommends graphing the inverse trig functions to better understand their properties.
Program verification involves formally proving that a program satisfies certain properties, such as having no defects, by establishing that the program meets its specification. This is done by defining preconditions and postconditions and using weakest preconditions to reason about how the program transforms states. Testing involves running a program with sample inputs and checking that the outputs are as expected to find defects empirically.
This document provides lecture notes on complex analysis covering four units of content:
1) The index of a close curve, Cauchy's theorem, and entire functions.
2) Counting zeroes, meromorphic functions, and maximum principle.
3) Spaces of continuous and analytic functions, and behavior of functions.
4) Comparison of entire functions, analytic continuation, and harmonic functions.
It also provides definitions and theorems regarding integrals over rectifiable curves, winding numbers, and Cauchy's theorem. Exercises and proofs are included.
1. The document defines topological spaces and metric spaces. A topological space is a set endowed with a collection of open sets satisfying certain properties. A metric space is a topological space where the open sets are defined by a metric.
2. It then introduces Gauss's law, which states that the electric flux through a closed surface is proportional to the total charge enclosed by the surface.
3. Gauss's law can be applied to both discrete point charges and continuous charge distributions described by a charge density function.
The document provides definitions and examples for key linear algebra concepts such as vector spaces, subspaces, spanning sets, linear independence, bases, and dimension. It lists important vector space examples and provides guidance to practice problems to better understand the concepts. The document serves as a study guide for learning linear algebra terms and their applications.
Complex analysis and differential equationSpringer
This document introduces holomorphic functions and some of their key properties. It begins by defining limits, continuity, differentiability, and holomorphic functions. It then introduces the Cauchy-Riemann equations, which provide a necessary condition for differentiability involving the partial derivatives of the real and imaginary parts. Several examples are provided to illustrate these concepts. The document also discusses properties of derivatives of holomorphic functions and proves that differentiability implies continuity. It concludes by defining connected sets.
This document discusses Newtonian mechanics in Galilean spacetime. It begins by introducing some key concepts, including:
1) Galilean spacetime is the space and time framework for Newtonian mechanics, taking place in a physical space where objects move and events can be measured in time.
2) An affine space is like a vector space but without a fixed origin, where only differences between elements can be considered as vectors. Affine subspaces are subsets where differences lie in a vector subspace.
3) Maps between affine spaces that preserve the affine structure are called affine maps. Any affine map between vector spaces must have the form of a linear map plus a constant.
Double integrals are used to calculate properties of planar laminas such as mass, center of mass, and moments of inertia by integrating a density function over a region. The inner integral is evaluated first, treating the other variable as a constant. Properties include:
1) Total mass by double integrating the density function over the region.
2) Center of mass coordinates by taking moments about axes and dividing by total mass.
3) Moments of inertia by double integrating the distance squared from an axis times the density.
S1. Fixed point iteration is a numerical method for solving equations of the form x = g(x) by making an initial guess x0 and repeatedly substituting xn into the right side to obtain xn+1.
S2. The method converges if |g'(α)| < 1, where α is the root and g' is the derivative of g. This ensures the error decreases at each iteration.
S3. Examples show the method can converge rapidly, as in Newton's method, or diverge, depending on the properties of g near the root. Aitken extrapolation can provide a better estimate of the root than the current iterate xn.
The document introduces concepts related to vector spaces including vectors, linear independence, and subspaces. It provides examples in R3 involving determining if sets of vectors are linearly dependent or independent, finding representations of vectors as linear combinations of other vectors, and solving homogeneous and nonhomogeneous systems of equations involving vector coefficients. Key concepts are illustrated through a series of problems involving vectors in R3.
This document discusses using least squares approximation to fit linear and polynomial models to data. It introduces the concept of best approximation in a subspace and shows that the orthogonal projection of a vector onto the subspace is the best approximation. The document then applies these concepts to derive the normal equations and the least squares solution for linear and polynomial regression models. Examples are provided to illustrate fitting lines and curves to data using least squares.
I am Manuela B. I am a Linear Algebra Assignment Expert at mathsassignmenthelp.com. I hold a Master's in Mathematics from, the University of Warwick. I have been helping students with their assignments for the past 9 years. I solve assignments related to Linear Algebra.
Visit mathsassignmenthelp.com or email info@mathsassignmenthelp.com.
You can also call on +1 678 648 4277 for any assistance with Linear Algebra Assignment.
1) The document discusses integration as the reverse process of differentiation, and provides examples of integrating logarithmic and exponential functions.
2) Key points covered include integrating 1/x as ln(x), and exponential functions like e3x by using u-substitution and dividing the "tail" by the exponent.
3) The document also demonstrates integrating logarithmic expressions using u-substitution, letting the term in the denominator equal u and finding du.
This document discusses electromagnetic plane waves in various materials. It contains:
1) Derivations of plane wave solutions to Maxwell's equations and expressions for the electric and magnetic fields.
2) Examples calculating wave properties like wavelength, propagation velocity, and Poynting vector for different materials and field configurations.
3) Exercises finding field values at specific points given propagating plane wave descriptions.
The document summarizes the solution process for determining the deflection, bending moment, and stress of a simply supported beam subjected to an external forcing function. Natural frequencies are calculated as ωn = n^2π^2/L^2(EI/ρA). Mode shapes are sinusoidal functions of nπx/L. Forced response is determined using mode superposition, yielding a deflection proportional to sin(Ωt) and sin(ω1t) with spatial dependence of sin(πx/L). Bending moment and stress are derived from deflection and have the same functional forms.
Here the concept of "TRUE" is defined according to Alfred Tarski, and the concept "OCCURING EVENT" is derived from this definition.
From here, we obtain operations on the events and properties of these operations and derive the main properties of the CLASSICAL PROB-ABILITY. PHYSICAL EVENTS are defined as the results of applying these operations to DOT EVENTS.
Next, the 3 + 1 vector of the PROBABILITY CURRENT and the EVENT STATE VECTOR are determined.
The presence in our universe of Planck's constant gives reason to\linebreak presume that our world is in a CONFINED SPACE. In such spaces, functions are presented by Fourier series. These presentations allow formulating the ENTANGLEMENT phenomenon.
Global Journal of Science Frontier Research: FMathematics and Decision Sciences Volume 18 Issue 2 Version 1.0 Year 2018
The document contains 10 problems involving electromagnetic induction and Maxwell's equations. Problem 10.1 involves calculating the voltage and current in a circuit with a changing magnetic flux. Problem 10.2 replaces a voltmeter with a resistor and calculates the resulting current. Problem 10.3 calculates the emf induced in closed paths with changing magnetic fluxes.
1) Four positive charges are located at the corners of a square in the xy-plane. A fifth positive charge is located 8cm from the others. The total force on the fifth charge is calculated to be 4.0x10-4 N directed along the z-axis.
2) Two charges of Q1 coulombs are located at z=±1. For a third charge Q2 to produce zero total electric field at (0,1,0), Q2 must lie along the y-axis at y=1±21/4|Q2|/Q1, where the sign depends on the sign of Q2.
3) The total force on a 50nC charge
This document contains summaries of 9 problems from Chapter 13 of an electromagnetic waves textbook. The problems involve calculating reflection and transmission coefficients at dielectric interfaces, as well as power densities, wave propagation, and standing wave ratios. Key steps and results are presented concisely.
The velocity of a vector function is the absolute value of its tangent vector. The speed of a vector function is the length of its velocity vector, and the arc length (distance traveled) is the integral of speed.
The document summarizes Green's theorem, Stokes' theorem, and Gauss' divergence theorem from vector calculus. Green's theorem relates a line integral around a closed curve to a double integral over the region bounded by the curve. Stokes' theorem relates a surface integral over a closed surface to a line integral around its boundary. Gauss' divergence theorem relates the flux of a vector field through a closed surface to the volume integral of the divergence over the enclosed region. An example application of Gauss' theorem to compute the flux of a vector field out of a unit sphere is also provided.
This document discusses inverse trigonometric functions including arcsine, arccosine, and arctangent. It explains that arcsine is the inverse of sine, with domain [-1,1] and range [-π/2, π/2]. Arccosine has domain [-1,1] and range [0,π]. Arctangent has domain (-∞, ∞) and range [-π/2, π/2]. The document also notes that applying the inverse function twice returns the original value, and the outer function's domain takes precedence when functions are composed. It recommends graphing the inverse trig functions to better understand their properties.
Program verification involves formally proving that a program satisfies certain properties, such as having no defects, by establishing that the program meets its specification. This is done by defining preconditions and postconditions and using weakest preconditions to reason about how the program transforms states. Testing involves running a program with sample inputs and checking that the outputs are as expected to find defects empirically.
This document provides lecture notes on complex analysis covering four units of content:
1) The index of a close curve, Cauchy's theorem, and entire functions.
2) Counting zeroes, meromorphic functions, and maximum principle.
3) Spaces of continuous and analytic functions, and behavior of functions.
4) Comparison of entire functions, analytic continuation, and harmonic functions.
It also provides definitions and theorems regarding integrals over rectifiable curves, winding numbers, and Cauchy's theorem. Exercises and proofs are included.
1. The document defines topological spaces and metric spaces. A topological space is a set endowed with a collection of open sets satisfying certain properties. A metric space is a topological space where the open sets are defined by a metric.
2. It then introduces Gauss's law, which states that the electric flux through a closed surface is proportional to the total charge enclosed by the surface.
3. Gauss's law can be applied to both discrete point charges and continuous charge distributions described by a charge density function.
The document provides definitions and examples for key linear algebra concepts such as vector spaces, subspaces, spanning sets, linear independence, bases, and dimension. It lists important vector space examples and provides guidance to practice problems to better understand the concepts. The document serves as a study guide for learning linear algebra terms and their applications.
Complex analysis and differential equationSpringer
This document introduces holomorphic functions and some of their key properties. It begins by defining limits, continuity, differentiability, and holomorphic functions. It then introduces the Cauchy-Riemann equations, which provide a necessary condition for differentiability involving the partial derivatives of the real and imaginary parts. Several examples are provided to illustrate these concepts. The document also discusses properties of derivatives of holomorphic functions and proves that differentiability implies continuity. It concludes by defining connected sets.
This document discusses Newtonian mechanics in Galilean spacetime. It begins by introducing some key concepts, including:
1) Galilean spacetime is the space and time framework for Newtonian mechanics, taking place in a physical space where objects move and events can be measured in time.
2) An affine space is like a vector space but without a fixed origin, where only differences between elements can be considered as vectors. Affine subspaces are subsets where differences lie in a vector subspace.
3) Maps between affine spaces that preserve the affine structure are called affine maps. Any affine map between vector spaces must have the form of a linear map plus a constant.
Double integrals are used to calculate properties of planar laminas such as mass, center of mass, and moments of inertia by integrating a density function over a region. The inner integral is evaluated first, treating the other variable as a constant. Properties include:
1) Total mass by double integrating the density function over the region.
2) Center of mass coordinates by taking moments about axes and dividing by total mass.
3) Moments of inertia by double integrating the distance squared from an axis times the density.
S1. Fixed point iteration is a numerical method for solving equations of the form x = g(x) by making an initial guess x0 and repeatedly substituting xn into the right side to obtain xn+1.
S2. The method converges if |g'(α)| < 1, where α is the root and g' is the derivative of g. This ensures the error decreases at each iteration.
S3. Examples show the method can converge rapidly, as in Newton's method, or diverge, depending on the properties of g near the root. Aitken extrapolation can provide a better estimate of the root than the current iterate xn.
The document introduces concepts related to vector spaces including vectors, linear independence, and subspaces. It provides examples in R3 involving determining if sets of vectors are linearly dependent or independent, finding representations of vectors as linear combinations of other vectors, and solving homogeneous and nonhomogeneous systems of equations involving vector coefficients. Key concepts are illustrated through a series of problems involving vectors in R3.
This document discusses using least squares approximation to fit linear and polynomial models to data. It introduces the concept of best approximation in a subspace and shows that the orthogonal projection of a vector onto the subspace is the best approximation. The document then applies these concepts to derive the normal equations and the least squares solution for linear and polynomial regression models. Examples are provided to illustrate fitting lines and curves to data using least squares.
I am Manuela B. I am a Linear Algebra Assignment Expert at mathsassignmenthelp.com. I hold a Master's in Mathematics from, the University of Warwick. I have been helping students with their assignments for the past 9 years. I solve assignments related to Linear Algebra.
Visit mathsassignmenthelp.com or email info@mathsassignmenthelp.com.
You can also call on +1 678 648 4277 for any assistance with Linear Algebra Assignment.
This document provides solutions to homework problems from a complex analysis course. It analyzes the differentiability of several complex functions by checking if they satisfy the Cauchy-Riemann equations. For differentiable functions, it computes their derivatives according to the Cauchy-Riemann theorem. The solutions involve defining real and imaginary parts of functions, taking partial derivatives, and applying limits.
The document defines matrices and their properties, including symmetric, skew-symmetric, and determinant. It provides examples of solving systems of equations using matrices and their inverses. It also discusses properties of determinants, including properties related to symmetric and skew-symmetric matrices. Inverse trigonometric functions are defined, including their domains, ranges, and relationships between inverse functions using addition and subtraction formulas. Sample problems are provided to solve systems of equations and evaluate determinants.
The document contains solutions to 4 geometry problems:
1) It is proven that if points D, E, F divide sides of triangle ABC proportionally, then ABC is equilateral.
2) It is shown that all but a finite number of natural numbers can be written as the sum of 3 numbers where one divides the next.
3) It is proven that if two polynomials P and Q have a common rational root r, then r must be an integer.
4) It is shown that given any 5 vertices of a regular 9-sided polygon, 4 can be chosen to form a trapezium.
Are you in search of trustworthy and affordable assistance for your Linear Algebra assignments? Look no further! Our team of experienced math experts specializing in Linear Algebra is here to provide you with reliable help. Whether your assignment is big or small, we offer personalized assistance to ensure that all work is completed to the highest standard. Our prices are competitive and tailored to be student-friendly, making it easier for you to access the help you need.
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Pythagorean triples are whole number sets that satisfy the Pythagorean theorem, where a2 + b2 = c2. The document discusses properties of Pythagorean triples and how they relate to rational points on the unit circle. It presents theorems showing that every basic Pythagorean triple corresponds to a rational point on the unit circle, and vice versa. Formulas are derived for generating Pythagorean triples from a given rational slope of a line passing through (-1,0) and a point on the unit circle. The document also briefly discusses 60-degree triangles, whose sides satisfy the equation c2 = a2 + b2 - ab, relating to an ellipse rather than a circle.
The document defines dot products and related concepts for vectors in R3. It shows that the dot product of two vectors v and w is defined as v1w1 + v2w2 + v3w3. It proves properties of dot products, including that the dot product is commutative and distributive over vector addition and scalar multiplication. It then introduces the angle between two vectors and proves that the dot product is equal to the product of the vector magnitudes and the cosine of the angle between them.
This document is a solution to a physics problem set composed and formatted by E.A. Baltz and M. Strovink. It contains solutions to 6 problems using vector algebra and trigonometry. The document uses concepts like the law of cosines, dot products, cross products, and vector identities to break vectors into components and calculate angles between vectors. It also applies these concepts to problems involving vectors representing locations on a sphere and wind resistance problems for airplanes.
1) The document contains solutions to 4 problems involving sequences, triangles, and number theory.
2) In problem 1, it is shown that if P and Q are points of intersection of lines drawn from a point M inside a triangle ABC to its circumcircle, then PQ is parallel to one of the sides of ABC.
3) Problem 2 finds all natural numbers n such that n^2 does not divide (n-2)!. The solutions are primes, twice a prime, and 8 and 9.
4) Problem 3 solves a system of equations and finds the only real solution is x=y=z=1/3.
The document discusses connecting best approximation theory to least squares approximation through a motivating example involving weighing fiddler crabs submerged in saline over time. It explores using least squares to fit a line or curve of best fit to the crab weight data. The document then provides mathematical proofs showing that the orthogonal projection of a vector onto a subspace is the best approximation within that subspace, and that the least squares solution minimizes the residual vector.
This document summarizes research on the existence of best proximity points for mappings between subsets of metric spaces.
The paper introduces the concepts of proximal intersection property and diagonal property for pairs of subsets, and proves that every pair of subsets in a Hilbert space satisfies the diagonal property. It establishes the existence of best proximity points for contractive mappings between subsets that satisfy the proximal intersection property or diagonal property.
This document provides solved assignments for MCS-013 from Ignou in 2011. It includes truth tables and answers to questions about conditional connectives, proofs, rational and irrational numbers, Boolean algebra, logic circuits, sets, Venn diagrams, and counterexamples. Specifically, it gives examples of direct proofs, finds whether 17 is rational or irrational, explains how Boolean algebra is used in logic circuit design, draws Venn diagrams, and illustrates the use of a counterexample.
I am Duncan V. I am a Calculus Homework Expert at mathshomeworksolver.com. I hold a Master's in Mathematics from Manchester, United Kingdom. I have been helping students with their homework for the past 8 years. I solve homework related to Calculus.
Visit mathhomeworksolver.com or email support@mathhomeworksolver.com.
You can also call on +1 678 648 4277 for any assistance with Calculus Homework.
Solution Strategies for Equations that Arise in Geometric (Clifford) AlgebraJames Smith
Drawing mainly upon exercises from Hestenes's New Foundations for Classical Mechanics, this document presents, explains, and discusses common solution strategies. Included are a list of formulas and a guide to nomenclature.
See also:
http://www.slideshare.net/JamesSmith245/rotations-of-vectors-via-geometric-algebra-explanation-and-usage-in-solving-classic-geometric-construction-problems-version-of-11-february-2016 ;
http://www.slideshare.net/JamesSmith245/resoluciones-de-problemas-de-construccin-geomtricos-por-medio-de-la-geometra-clsica-y-el-lgebra-geomtrica-vectorial ;
http://www.slideshare.net/JamesSmith245/solution-of-the-special-case-clp-of-the-problem-of-apollonius-via-vector-rotations-using-geometric-algebra ;
http://www.slideshare.net/JamesSmith245/solution-of-the-ccp-case-of-the-problem-of-apollonius-via-geometric-clifford-algebra ;
http://www.slideshare.net/JamesSmith245/a-very-brief-introduction-to-reflections-in-2d-geometric-algebra-and-their-use-in-solving-construction-problems ;
http://www.slideshare.net/JamesSmith245/solution-of-the-llp-limiting-case-of-the-problem-of-apollonius-via-geometric-algebra-using-reflections-and-rotations ;
http://www.slideshare.net/JamesSmith245/simplied-solutions-of-the-clp-and-ccp-limiting-cases-of-the-problem-of-apollonius-via-vector-rotations-using-geometric-algebra ;
http://www.slideshare.net/JamesSmith245/additional-solutions-of-the-limiting-case-clp-of-the-problem-of-apollonius-via-vector-rotations-using-geometric-algebra ;
http://www.slideshare.net/JamesSmith245/an-additional-brief-solution-of-the-cpp-limiting-case-of-the-problem-of-apollonius-via-geometric-algebra-ga .
This document contains 6 problems and their solutions from a Regional Mathematical Olympiad competition in 2010. Problem 1 involves proving that the area of one triangle is the geometric mean of the areas of two other triangles in a hexagon with concurrent diagonals. Problem 2 proves that if three quadratic polynomials have a common root, then their coefficients must be equal. Problem 3 counts the number of 4-digit numbers divisible by 4 but not 8 having non-zero digits. Problem 4 finds the smallest positive integers whose reciprocals satisfy certain relationships. Problem 5 proves that the reflection of a point in a line lies on a side of a triangle. Problem 6 determines the number of values of n where an is greater than an+1 for a defined sequence
The document summarizes an inequality originally proven by T. Andreescu and G. Dospinescu. This inequality, presented as Theorem 1, is shown to be useful for proving several other interesting inequalities in a simple way. Applications of Theorem 1 include proving inequalities involving sums of powers and expressions divided by sums. The document concludes by listing additional inequalities that can be solved using the techniques demonstrated.
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RHEOLOGY Physical pharmaceutics-II notes for B.pharm 4th sem students
The uvw method
1. The uvw method - Tejs
The uvw method
by Mathias Bæk Tejs Knudsen
1
2. The uvw method - Tejs 1 BASIC CONCEPTS
1 Basic Concepts
The basic concept of the method is this:
With an inequality in the numbers a, b, c ∈ R, we write everything in terms of 3u =
a + b + c, 3v2
= ab + bc + ca, w3
= abc. The condition a, b, c ≥ 0 is given in many inequalities.
In this case, we see that u, v2
, w3
≥ 0. But if this is not the case, u, v2
, w3
might be negative.
E.g. a = −1, b = −2, c = 3 we get 3v2
= −7. So don’t be confused! Sometimes v2
can be
negative!
The Idiot-Theorem: u ≥ v ≥ w, when a, b, c ≥ 0.
Proof: 9u2
− 9v2
= a2
+ b2
+ c2
− ab − bc − ca = 1
2
P
cyc(a − b)2
≥ 0. And hence u ≥ v.
From the AM-GM inequality we see that v2
= ab+bc+ca
3
≥
3
√
a2b2c2 = w2
, and hence v ≥ w,
which concludes u ≥ v ≥ w.
The idiot-theorem is usually of little use alone, but it is important to know.
Sometimes we introduce the ratio t = u2
: v2
. If u > 0, v = 0 we define t = ∞, and if
u < 0, v = 0 we define t = −∞. If u = v = 0 we set t = 1. When a, b, c ≥ 0, we see that
t ≥ 1. And we always see that |t| ≥ 1.
The UVW-Theorem: Given u, v2
, w3
∈ R: ∃a, b, c ∈ R such that 3u = a + b + c,
3v2
= ab + bc + ca, w3
= abc if and only if:
u2
≥ v2
and w3
∈
h
3uv2
− 2u3
− 2
p
(u2 − v2)3, 3uv2
− 2u3
+ 2
p
(u2 − v2)3
i
Proof: Define f(t) = t3
− 3ut2
+ 3v2
t − w3
. Let a, b, c be its roots. By vietés formulas we
see that 3u = a + b + c, 3v2
= ab + bc + ca, w3
= abc.
Lemma 1: a, b, c ∈ R ⇐⇒ (a − b)(b − c)(c − a) ∈ R.
Proof of lemma 1: It’s trivial to see that a, b, c ∈ R ⇒ (a − b)(b − c)(c − a) ∈ R. Then
I’ll show a, b, c /
∈ R ⇒ (a − b)(b − c)(c − a) /
∈ R. Let z /
∈ R be a complex number such that
f(z) = 0. Then f(z) = f(z) = 0 = 0, so if z is a complex root in f(t), so is z. Assume wlog
because of symmetry that a = z, b = z. Then (a − b)(b − c)(c − a) = −(z − z)|z − c|2
/
∈ R.
The last follows from (a − b)(b − c)(c − a) 6= 0, i(z − z) ∈ R, and |z − c|2
∈ R.
It’s obvious that x ∈ R ⇐⇒ x2
∈ [0; +∞). So ∃a, b, c ∈ R such that 3u = a+b+c, 3v3
=
ab + bc + ca, w3
= abc if and only if (a − b)2
(b − c)2
(c − a)2
≥ 0, where a, b, c are the roots
of f(t).
But (a − b)2
(b − c)2
(c − a)2
= 27(−(w3
− (3uv2
− 2u3
))2
+ 4(u2
− v2
)3
) ≥ 0 ⇐⇒
4(u2
− v2
)3
≥ (w3
− (3uv2
− 2u3
))2
. From this we would require u2
≥ v2
. But 4(u2
− v2
)3
≥
(w3
− (3uv2
− 2u3
))2
⇐⇒
2
p
(u2 − v2)3 ≥ |w3
− (3uv2
− 2u3
)|
When w3
≥ (3uv2
− 2u3
) it’s equivalent to:
w3
≤ 3uv2
− 2u3
+ 2
p
(u2 − v2)3
When w3
≤ (3uv2
− 2u3
) it’s equivalent to:
w3
≥ 3uv2
− 2u3
− 2
p
(u2 − v2)3
So (a − b)2
(b − c)2
(c − a)2
≥ 0 ⇐⇒ w3
∈ [3uv2
− 2u3
; 3uv2
− 2u3
+ 2
p
(u2 − v2)3] ∩
2
3. The uvw method - Tejs 2 QUALITATIVE ESTIMATIONS
[3uv2
−2u3
−2
p
(u2 − v2)3; 3uv2
−2u3
] ⇐⇒ w3
∈ [3uv2
−2u3
−2
p
(u2 − v2)3; 3uv2
−2u3
+
2
p
(u2 − v2)3] and u2
≥ v2
.
The Positivity-Theorem: a, b, c ≥ 0 ⇐⇒ u, v2
, w3
≥ 0
Proof: The case a, b, c ≥ 0 ⇒ u, v2
, w3
≥ 0 is obvious. Now the proof of a < 0 or b < 0
or c < 0 ⇒ u < 0 or v2
< 0 or w3
< 0. If there is an odd number of negative numbers in
(a, b, c) then w3
is negative. Else there is two negative. Assume wlog because of symmetry
a ≥ 0, b, c < 0. Let b = −x, c = −y. So 3u = a − x − y, 3v2
= xy − a(x + y), and x, y > 0.
u ≥ 0 ⇐⇒ a ≥ x + y. If a ≥ x + y then xy − a(x + y) ≤ −x2
− xy − y2
, and hence not both
u and v2
can be positive, and we are done.
Theorem: All symetric polynomials in a, b, c can be written in terms of u, v2
, w3
. (No one
dividing. E.g. the term u
w3 is not allowed)
Proof: Well-known.. Use induction, and the fact that an
+ bn
+ cn
always can be re-
pressented in terms of u, v2
, w3
. (Will post full proof later)
2 Qualitative estimations
It can be really tedious to write everything in terms of u, v2
, w3
. Because of this it can be
really useful to know some qualitative estimations.
We already have some bounds on w3
, but they are not always (that is, almost never)
”nice”. The squareroot tend to complicate things, so there is needed a better way, than to
use the bounds always!
If you haven’t noticed: Many inequalities have equality when a = b = c. Some have when
a = b, c = 0, and some again for a = b = kc for some k. There are rarely equality for instance
when a = 3, b = 2, c = 1 - although it happens.
There is a perfectly good reason for this: When we fix two of u, v2
, w3
, then the third
assumes it’s maximum if and only if two of a, b, c are equal!
This is really the nicest part of this paper. (I have never seen this idea applied before!)
It is not important to memorize the full proof. Both II, III will be very close to I
(actually i copy-pasted most of it, just to save time). Just remember the main ideas!
”Tejs’s Theorem”:p Assume that we are given the constraint a, b, c ≥ 0. Then the
following is true:
(I) When we have fixed u, v2
and there exists at least one value of w3
such that there
exists a, b, c ≥ 0 corresponding to u, v2
, w3
: Then w3
has a global maximum and minimum.
w3
assumes maximum only when two of a, b, c are equal, and minimum either when two of
a, b, c are equal or when one of them are zero.
(II) When we have fixed u, w3
and there exists at least one value of v2
such that there
exists a, b, c ≥ 0 corresponding to u, v2
, w3
: Then v2
has a global maximum and minimum. v2
assumes maximum only when two of a, b, c are equal, and minimum only when two of a, b, c
are equal.
3
4. The uvw method - Tejs 2 QUALITATIVE ESTIMATIONS
(III) When we have fixed v2
, w3
and there exists at least one value of u such that there
exists a, b, c ≥ 0 corresponding to u, v2
, w3
: Then u has a global maximum and minimum. u
assumes maximum only when two of a, b, c are equal, and minimum only when two of a, b, c
are equal.
Proof:
(I) We’ll use something from the earlier proofs(The lemma from the UVW-theorem plus
the positivity theorem): There exists a, b, c ≥ 0 corresponding to u, v2
, w3
if and only if
−(w3
− 3uv2
+ 2u3
)2
+ 4(u2
− v2
)3
, u, v2
, w3
≥ 0 (Hence u, v2
≥ 0, and we will implicitly
assume w3
≥ 0 in the following.). Setting x = w3
it is equivalent to p(x) = Ax2
+Bx+C ≥ 0
for some A, B, C ∈ R. (Remember we have fixed u, v2
) Since A = −1 we see A < 0. Since
there exists x ∈ R such that p(x) ≥ 0 and obviously p(x) < 0 for sufficiently large x, we
conclude that it must have at least one positive root. Let α be the largest positive root, then
it is obvious that p(x) < p(α) = 0 ∀x > α. That is: The biggest value x can attain is α, so
x = w3
≤ α. This can be attained by the previous proof, and it does so only when two of
a, b, c are equal (because (a − b)(b − c)(c − a) = 0). Let β be the smallest positive root of
p(x). If p(x) < 0 when x ∈ [0; β) then x is at least β and x = w3
≥ β, with equality only
if two of a, b, c are equal, since (a − b)(b − c)(c − a) = 0. If p(x) ≥ 0 when x ∈ [0; β) then
x = w3
≥ 0 with equality when one of a, b, c are zero, since w3
= abc = 0.
(II) We’ll use something from the earlier proofs(The lemma from the UVW-theorem
plus the positivity theorem): There exists a, b, c ≥ 0 corresponding to u, v2
, w3
if and only if
−(w3
−3uv2
+2u3
)2
+4(u2
−v2
)3
, u, v2
, w3
≥ 0 (Hence u, w3
≥ 0, and we will implicitly assume
v2
≥ 0 in the following.). Setting x = v2
it is equivalent to p(x) = Ax3
+ Bx2
+ Cx + D ≥ 0
for some A, B, C ∈ R. (Remember we have fixed u, w3
) Since A = −4 we see A < 0. Since
there exists x ∈ R such that p(x) ≥ 0 and obviously p(x) < 0 for sufficiently large x, we
conclude that it must have at least one positive root. Let α be the largest positive root, then
it is obvious that p(x) < p(α) = 0 ∀x > α. That is: The biggest value x can attain is α, so
x = v2
≤ α. This can be attained by the previous proof, and it does so only when two of
a, b, c are equal (because (a − b)(b − c)(c − a) = 0). Let β be the smallest positive root of
p(x). If p(x) < 0 when x ∈ [0; β) then x is at least β and x = v2
≥ β, with equality only
if two of a, b, c are equal, since (a − b)(b − c)(c − a) = 0. If p(x) ≥ 0 when x ∈ [0; β) then
x = v2
≥ 0 with equality when two of a, b, c are zero, since 3v2
= ab + bc + ca = 0, and then
two of them have to be equal.
(II) We’ll use something from the earlier proofs(The lemma from the UVW-theorem
plus the positivity theorem): There exists a, b, c ≥ 0 corresponding to u, v2
, w3
if and only if
−(w3
−3uv2
+2u3
)2
+4(u2
−v2
)3
, u, v2
, w3
≥ 0 (Hence v2
, w3
≥ 0, and we will implicitly assume
u ≥ 0 in the following.). Setting x = u it is equivalent to p(x) = Ax3
+ Bx2
+ Cx + D ≥ 0
for some A, B, C ∈ R. (Remember we have fixed v2
, w3
) Since A = −4w3
we see A < 0.
Since there exists x ∈ R such that p(x) ≥ 0 and obviously p(x) < 0 for sufficiently large x,
we conclude that it must have at least one positive root. Let α be the largest positive root,
then it is obvious that p(x) < p(α) = 0 ∀x > α. That is: The biggest value x can attain is
4
5. The uvw method - Tejs 4 APPLICATIONS
α, so x = u ≤ α. This can be attained by the previous proof, and it does so only when two
of a, b, c are equal (because (a − b)(b − c)(c − a) = 0). Let β be the smallest positive root
of p(x). If p(x) < 0 when x ∈ [0; β) then x is at least β and x = u ≥ β, with equality only
if two of a, b, c are equal, since (a − b)(b − c)(c − a) = 0. If p(x) ≥ 0 when x ∈ [0; β) then
x = u ≥ 0 with equality when all three of a, b, c are zero, since 3u = a + b + c = 0, and then
two of them have to be equal.
Corrolar: Every symmetric inequality of degree ≤ 5 has only to be proved when a = b
and a = 0.
Proof: Since it can be written as the symmetric functions it is linear in w3
. Hence it is
either increasing or decreasing. So we only have to check it when two of a, b, c are equal or
when one of them are zero. Because of symmetry we can wlog assume a = b or c = 0.
3 Shortcuts
I will write some well known identities. It would be very tedious if you had to argument that
a2
+ b2
+ c2
= 9u2
− 6v2
every time you used it, wouldn’t it?
The ”must remember”:
(a − b)2
(b − c)2
(c − a)2
= 27(−(w3
− 3uv2
+ 2u3
)2
+ 4(u2
− v2
)3
)
Schur’s ineq for third degree:
P
cyc a(a − b)(a − c) ≥ 0 ⇐⇒ w3
+ 3u3
≥ 4uv2
.
Some random identities:
(a − b)(b − c)(c − a) =
P
cyc b2
a − ab2
a2
+ b2
+ c2
= (a + b + c)2
− 2(ab + bc + ca) = 9u2
− 6v2
(ab)2
+ (bc)2
+ (ca)2
= (ab + bc + ca)2
− 2abc(a + b + c) = 9v4
− 6uw3
a3
+b3
+c3
−3abc = (a+b+c)(a2
+b2
+c2
−ab−bc−ca) ⇐⇒ a3
+b3
+c3
= 27u3
−27uv2
+3w3
a4
+ b4
+ c4
= (a2
+ b2
+ c2
)2
− 2((ab)2
+ (bc)2
+ (ca)2
) = (9u2
− 6v2
)2
− 2(9v2
− 6uw3
) =
81u4
− 108u2
v2
+ 18v4
+ 12uw3
4 Applications
The uvw-method is (unlike for instance complex numbers in geometry :p) not always the
best choice. When dealing with squareroots, inequalities of a very high degree og simply non-
symmetric or more than 4 variable inequalities, you probably want to consider using another
technique. (But e.g. there is a solution to one with a square root here, so it is possible.)
I will show some examples of the use of the uvw-method. Most of the problems will also
have solutions without using the uvw-method, but I will not provide those.
IMO prob. 3, 06: Determine the least real number M such that the inequality
10. The uvw method - Tejs 4 APPLICATIONS
holds for all real numbers a, b and c
Solution:
Notice the identity ab(a2
−b2
)+bc(b2
−c2
)+ca(c2
−a2
) = (a−b)(b−c)(a−c)(a+b+c).
So we should prove (after squaring):
(a − b)2
(b − c)2
(c − a)2
(a + b + c)2
≤ M2
(a2
+ b2
+ c2
)4
Introduce the notations: 3u = a + b + c, 3v2
= ab + bc + ca, w3
= abc, u2
= tv2
. (Thus
t2
≥ 1) (Notice that it is possible that v2
≤ 0, so we don’t necesarily have v ∈ R, but always
v2
∈ R)
Obviously a2
+ b2
+ c2
= 9u2
− 6v2
and (a − b)2
(b − c)2
(c − a)2
= 33
(−(w3
− (3uv2
−
2u3
))2
+ 4(u2
− v2
)3
)
So we just have to prove:
35
· u2
· (−(w3
− (3uv2
− 2u3
))2
+ 4(u2
− v2
)3
) ≤ M2
(9u2
− 6v2
)4
⇐⇒
3u2
(−(w3
− (3uv2
− 2u3
))2
+ 4(u2
− v2
)3
) ≤ M2
(3u2
− 2v2
)4
.
Now −(w3
− (3uv2
− 2u3
))2
≤ 0. So it suffices to prove that:
12u2
(u2
− v2
)3
≤ M2
(3u2
− 2v2
)4
Divide through with v8
:
12t(t − 1)3
≤ M2
(3t − 2)4
If t is positive, then t ≥ 1:
M2
≥ 12t(t−1)3
(3t−2)4
Consider the function f(t) = 12t(t−1)3
(3t−2)4 .
Then f0
(t) = 12(t−1)2(t+2)
(3t−2)5 0∀t ∈ [1; +∞).
So we just need to consider the expression 12t(t−1)3
(3t−2)4 as t → +∞.
Writing it as 12t(t−1)3
(3t−2)4 =
12(1− 1
t
)3
(3− 2
t
)4 . It’s obvious that 12t(t−1)3
(3t−2)4 → 4
27
when t → +∞. So if t is
positive then M ≥ 2
3
√
3
Now assume t is negative. Then t ≤ −1:
M2
≥ 12t(t−1)3
(3t−2)4
Consider the function f(t) = 12t(t−1)3
(3t−2)4 .
Then f0
(t) = 12(t−1)2(t+2)
(3t−2)5 .
So we have a maximum when t = −2:
f(−2) = 34
29
So M2
≥ 34
29 ⇐⇒ M ≥ 9
16
√
2
.
Since 9
16
√
2
≥ 2
3
√
3
we get that M = 9
16
√
2
fullfilles the condition. To prove that M is a
minimum, we have to find numbers a, b, c such that equality is archeived.
Looking at when we have minimum. (w3
= 3uv2
− 2u3
and v2
= u2
−2
) We get that roots
in the polynomial x3
− 6x2
− 6x + 28 will satisfy the minimum. But x3
− 6x2
− 6x + 28 =
(x−2)(x2
−4x+14), so we can easily find a, b, c. Indeed when (a, b, c) = (2, 2+3
√
2, 2−3
√
2)
there is equality and M = 9
16
√
2
is the minimum!
6
11. The uvw method - Tejs 4 APPLICATIONS
Note: Sometimes it can be very time consuming to find the roots of a third degree
polynomial. So if you just prove that u2
≥ v2
and w3
∈ [3uv2
− 2u3
− 2
p
(u2 − v2)3; 3uv2
−
2u3
+2
p
(u2 − v2)3], then you can say that the polynomial has three real roots for sure, even
though you cannot tell exactly what they are. (It is very easy to do so in this example since
w3
= 3uv2
− 2u3
)
From V. Q. B. Can: Let a, b, c be nonnegative real numbers such that ab+bc+ca = 1.
Prove that
1
2a + 2bc + 1
+
1
2b + 2ca + 1
+
1
2c + 2ab + 1
≥ 1
Solution:
This is a solution, which shows the full power of the uvw method. There is almost no
calculation involved, and it is very easy to get the idea!
It’s obvious equivalent to:
P
cyc(2a + 2bc + 1)(2b + 2ca + 1) ≥
Q
cyc(2a + 2bc + 1)
Now fix u, v2
. Since LHS is of degree four and RHS is of degree six, there must exist
A, B, C, D, E such that LHS = Aw3
+ B and RHS = Cw6
+ Dw3
+ E. And we easily see
C = 8 0. So we have to prove g(w3
) = −Cw6
+ (D − A)w3
+ (B − E) ≥ 0, which is
obviously concave in w3
. We only have to check the case where g(w3
) are minimal. That is:
Either when w3
are minimal or maximal. So we only have to check the case where two of
a, b, c are equal, or the case where one of a, b, c are zero.
It is left to the reader to prove these trivial cases.
Unknown origin: Let a, b, c ≥ 0, such that a + b + c = 3. Prove that:
(a2
b + b2
c + c2
a)(ab + bc + ca) ≤ 9
Solution:
Remark: This solution belongs to Micheal Rozenberg (aka Arqady) and can be found at:
http://www.mathlinks.ro/viewtopic.php?p=1276520#1276520
Let a + b + c = 3u, ab + ac + bc = 3v2
, abc = w3
and u2
= tv2
.
Hence, t ≥ 1 and (a2
b + b2
c + c2
a)(ab + bc + ca) ≤ 9 ⇔
⇔ 3u5
≥ (a2
b + b2
c + c2
a)v2
⇔
⇔ 6u5
− v2
P
cyc(a2
b + a2
c) ≥ v2
P
cyc(a2
b − a2
c) ⇔
⇔ 6u5
− 9uv4
+ 3v2
w3
≥ (a − b)(a − c)(b − c)v2
.
(a − b)2
(a − c)2
(b − c)2
≥ 0 gives w3
≥ 3uv2
− 2u3
− 2
p
(u2 − v2)3.
Hence, 2u5
− 3uv4
+ v2
w3
≥ 2u5
− 3uv4
+ v2
3uv2
− 2u3
− 2
p
(u2 − v2)3
≥ 0 because
2u5
− 3uv4
+ v2
3uv2
− 2u3
− 2
p
(u2 − v2)3
≥ 0 ⇔
⇔ u5
− u3
v2
≥ v2
p
(u2 − v2)3 ⇔ t3
− t + 1 ≥ 0, which is true.
Hence, 6u5
− 9uv4
+ 3v2
w3
≥ 0 and enough to prove that
(6u5
− 9uv4
+ 3v2
w3
)2
≥ v4
(a − b)2
(a − c)2
(b − c)2
.
7
12. The uvw method - Tejs 4 APPLICATIONS
Since, (a − b)2
(a − c)2
(b − c)2
= 27(3u2
v4
− 4v6
+ 6uv2
w3
− 4u3
w3
− w6
)
we obtain (6u5
− 9uv4
+ 3v2
w3
)2
≥ v4
(a − b)2
(a − c)2
(b − c)2
⇔
⇔ v4
w6
+ uv2
(u4
+ 3u2
− 6v4
)w3
+ u10
− 3u6
v4
+ 3v10
≥ 0.
Id est, it remains to prove that u2
v4
(u4
+ 3u2
− 6v4
)2
− 4v4
(u10
− 3u6
v4
+ 3v10
) ≤ 0.
But u2
v4
(u4
+ 3u2
− 6v4
)2
− 4v4
(u10
− 3u6
v4
+ 3v10
) ≤ 0 ⇔
⇔ t(t2
+ 3t − 6)2
− 4(t5
− 3t3
+ 3) ≤ 0 ⇔ (t − 1)2
(t3
− 4t + 4) ≥ 0, which is true.
Done!
Unknown origin: If x, y, z are non-negative reals such that xy + yz + zx = 1, then:
1
x+y
+ 1
y+z
+ 1
z+x
≥ 5
2
Solution:
The constraint is 3v2
= 1, and after multiplying with (x + y)(y + z)(z + x) we the ineq is
a symmetric polynomial of degree 3. Since the constraint doesn’t involve w3
, and 3 ≤ 5 we
only have to prove it for x = y and x = 0. These are left for the reader.
This one is equivalent to the following: Given the non-obtuse 4ABC with sides a, b, c
and circumradius R, prove the following:
ab
c
+ bc
a
+ ca
a
≥ 5R
Do you see why?
Unknown origin: Let a, b, c ≥ 1 and a + b + c = 9. Prove that
√
ab + bc + ca ≥
√
a +
√
b +
√
c.
Solution: Let a = (1 + x)2
, b = (1 + y)2
, c = (1 + z)2
such that x, y, z ≥ 0. Introduce
3u = x + y + z, 3v2
= xy + yz + zx, w3
= xyz. Then the constraint is a + b + c = (a + b +
c)2
− 2(ab + bc + ca) + 2(a + b + c) + 3 = (3u)2
− 6v2
+ 6u + 3 = 9 ⇐⇒ 3u2
+ 2u − 2v2
= 3.
After squaring we have to prove:
P
cyc(1 + x)2
(1 + y)2
≥
P
cyc(1 + x)
2
Since this is a symmetric polynomial inequality of degree ≤ 5 with a constraint not
involving w3
, we only have to prove it for x = y and x = 0. That is b = a, c = 9−2a, a ∈ [1; 4]
and a = 1.
These cases are left to the reader. (Note: The constraint a, b, c ≥ 1 are far from the best.
Actually the best is about a, b, c ≥ 0.1169..)
Unknown origin: For every a, b, c ≥ 0, no two which are zero, the following holds:
1
a2 + b2
+
1
b2 + c2
+
1
c2 + a2
≥
10
(a + b + c)2
Solution: It’s equivalent to:
(a + b + c)2
P
cyc(a2
+ b2
)(b2
+ c2
)
− 10(a2
+ b2
)(b2
+ c2
)(c2
+ a2
) ≥ 0
Note that:
P
cyc(a2
+ b2
)(b2
+ c2
) =
P
cyc b4
+ 2a2
b2
+
P
cyc(ab)2
= (a2
+ b2
+ c2
)2
+ 9v4
− 6uw3
=
(9u2
− 6v2
)2
+ 9v4
− 6uw3
8
13. The uvw method - Tejs 4 APPLICATIONS
And (a + b + c)2
= 9u2
, and:
(a2
+ b2
)(b2
+ c2
)(c2
+ a2
) = (a2
+ b2
+ c2
)(a2
b2
+ b2
c2
+ c2
a2
) − a2
b2
c2
= (9u2
− 6v2
)(9v4
−
6uw3
) − w6
= 9(9u2
v4
− 6v6
− 6u3
w3
+ 4uv2
w3
) − w6
Hence we should prove:
27u2
(27u4
− 36u2
v2
+ 15v4
− 2uw3
) − 90(9u2
v4
− 6v6
− 6u3
w3
+ 4uv2
w3
) + 10w6
≥ 0
Or:
g(w3
) = 10w6
+ w3
(486u3
− 360uv2
) + E ≥ 0
where E = 27u2
(27u4
− 36u2
v2
+ 15v4
) − 90(9u2
v4
− 6v6
)
Then g0
(w3
) = 20w3
+ 486u3
− 360uv2
= 20w3
+ 126u3
+ 360u(u2
− v2
) ≥ 0
(Since u, v2
, w3
≥ 0 and u2
≥ v2
)
Hence the expression is increasing in w3
. If we fix u, v2
we only have to prove it for a
minimized value of w3
, but w3
is minimized only when two of a, b, c are equal or when one
of a, b, c are zero.
First the case where two of a, b, c are equal.(Assume that a, b, c 0 since that will be the
other case) Wlog because of symmetry assume a = b. Define t = a
c
. Upon multiplying with
c2
we only have to prove:
1
2t2 + 2
t2+1
≥ 10
(2t+1)2 ⇐⇒
f(t) = 20t3
− 11t2
+ 4t + 1 ≥ 0
f0
(t) = 60t2
− 22t + 4 = 60 t − 11
60
2
+ 119
60
0
Since f(t) is increasing it shows that f(t) ≥ f(0) = 1 0∀t ∈ (0; +∞)
Now the case where one of a, b, c are zero. Wlog because of symmetry assume that c = 0.
Define t = a
b
. After multiplying with b2
we have to prove:
1
t2+1
+ 1
t2 + 1 ≥ 10
(t+1)2 ⇐⇒
t6
+ 2t5
− 6t4
+ 6t3
− 6t2
+ 2t + 1 = (t − 1)2
(t4
+ 3t3
+ 4t2
+ 3t + 1) ≥ 0
Which is obvious :) Equality iff a = b, c = 0 or permutations.
Hungktn:
a2
+ b2
+ c2
ab + bc + ca
+
8abc
(a + b)(b + c)(c + a)
≥ 2
Solution: Writing in terms of u, v2
, w3
we should prove:
3u2−2v2
v2 + 8w3
9uv2−w3 ≥ 2 ⇐⇒
u2
v2 + 24uv2
9uv2−w3 ≥ 12
Fixing u, v2
it is thus clearly enough to prove it when w3
is minimized. So we will prove
it when two of a, b, c are equal and when one of them are zero. Assume wlog because of
symmetry that a = b. Introducing t = c
a
we only have to prove:
2+t2
1+2t
+ 4t
t2+2t+1
≥ 2 ⇐⇒
t2
(t − 1)2
≥ 0
Now to the other case: Assume wlog because of symmetry a = 0. Then it becomes:
b2+c2
bc
≥ 2
9
14. The uvw method - Tejs 5 PRACTICE
Which is just AM-GM. Equality when a = b = c or a = b, c = 0 and permutations.
5 Practice
Unknown origin: For all a, b, c ≥ 0 such, prove:
a4
+ b4
+ c4
ab + bc + ca
+
3abc
a + b + c
≥ 2
(a2
+ b2
+ c2
)
3
Stronger version:
5
a4
+ b4
+ c4
ab + bc + ca
+ 9
3abc
a + b + c
≥ 14
(a2
+ b2
+ c2
)
3
Romania Junior Balkan TST ’09: When a + b + c = 3, a, b, c ≥ 0 prove:
a + 3
3a + bc
+
b + 3
3b + ca
+
c + 3
3c + ab
≥ 3
Unknown origin: When 1
a
+ 1
b
+ 1
c
= 1, a, b, c ≥ 0 prove:
(1 − a)(1 − b)(1 − c) ≥ 8
Unknown origin: When a, b, c ≥ 0 prove:
a5
+ b5
+ c5
+ abc(ab + bc + ca) ≥ a2
b2
(a + b) + b2
c2
(b + c) + c2
a2
(c + a)
Indonesia 2nd TST, 4th Test, Number 4: When a, b, c 0 and ab + bc + ca = 3
prove that:
3 +
(a − b)2
+ (b − c)2
+ (c − a)2
2
≥
a + b2
c2
b + c
+
b + c2
a2
c + a
+
c + a2
b2
a + b
≥ 3
Unknown origin: When a, b, c 0 and a + b + c = 3 find the minimum of:
(3 + 2a2
)(3 + 2b2
)(3 + 2c2
)
10