Kramers Relation. Douglas H. Laurence. Department of Physical Sciences, Broward College, Davie, FL 33314

Size: px
Start display at page:

Download "Kramers Relation. Douglas H. Laurence. Department of Physical Sciences, Broward College, Davie, FL 33314"

Transcription

1 Kramers Relation Douglas H. Laurence Department of Physical Sciences, Browar College, Davie, FL 333 Introuction Kramers relation, name after the Dutch physicist Hans Kramers, is a relationship between expectation values of nearby powers of r for the hyrogen atom: s + n r s (s + )a r s + s [(l + ) s ]a r s = 0 The relation is very important when computing, specifically, perturbative corrections to the hyrogen spectrum, as those computations require expectation values of the raial Hamiltonian (which has powers of r such as r an r ) an potentially perturbative corrections that have higher (negative) powers of r. Having this relation hany makes a lot of those calculations go more quickly. This erivation is going to require the solution to the hyrogen atom to be known: the Hamiltonian, the wavefunctions, the energy spectrum, etc. To solve Kramers relation for all s > is straightforwar, an will be shown, but to solve for any s requires one of these s values to alreay be known, for instance r. The Feynman-Hellmann theorem allows for an easy computation of this, which I erive in the appenix, as well as apply to compute r explicitly, allowing for r s to be compute for all values of s using Kramers relation. The Derivation of the Relation The raial wave equation for the hyrogen atom is typically written as: where the energy is: H r R nl (r) = [ m r + m l(l + ) r ke r ] R nl (r) = E n R nl (r) () E n = m n a () where a is the Bohr raius, efine as /kme. A more useful form of the above equation, however, is to make the typical substitution u(r) = rr(r), an then express the raial wave equation as: [ l(l + ) u = r ar + ] n a u (3) Note that I ve roppe the labels of nl; these are implie by their presence in the above equation.

2 Notice the terms we have in the above equation: r, r, an r 0. If we multiply both sies by r s, then we ll get exactly the powers of r that we nee for Kramer s relation: [ r s u = l(l + )r s a rs + ] n a rs u Now what we nee to o is multiply both sies by u = u an integrate. Then, we ll have: ur s u r = l(l + ) r s a rs + n a rs () What we nee to o is to figure out how to eal with the integral on the left-han-sie. Luckily, this integral is set up so that it inclues a factor of ur s an a factor of u r. If we integrate by parts, it will take two steps to convert the u to a u, resulting in an integral like uf(r)ur i.e. an expectation value an uring those two steps, the power of r will rop by one or two, so we ll have powers like r s, r s, an r s, exactly as we like! Integration by parts makes perfect sense to use, then, to reuce the integral on the left-han-sie of the above equation into aitional factors of expectation values of these powers of r. First, note that the integral goes from r = 0 to r =, an u equals zero at both limits (because R ecreases exponentially as r, beating the factor of r that increases linearly), so the terms in the integration by parts that are evaluate at these limits will always result in zero, since they will have some epenence on u. Note that I ll be using the notation: wv = vw for the integration by parts; this way, my choice in how to perform the integration will be clear. For the first step of the integration process, I ll choose w = ur s an v = u r, so integration by parts yiels: ur s u r = u r s u r } {{ } I s ur s u r } {{ } I where I have calle the first integral on the right-han-sie I an the secon integral I for brevity. Each of these integrals will also nee to be evaluate. For I, I ll make the seemingly-o choice of w = (u ) an v = r s r; if I ha chosen something similar to before, like w = u r s an v = u r, I get a recursion relationship that wouln t be helpful. So, the integration by parts results in: I = u r s u r = s + (5) u r s+ u r (6) I alreay have an equation for u in terms of u (the raial wave equation), so ultimately I m going to be solving integrals like u r k u, so let s figure out what those integrals yiel before plugging u into the above equation. Choosing w = ur k an v = u r, integration by parts yiels: u r k ur = u r k ur k ur k ur Pulling the first integral to the left-han-sie an noting the secon integral is just the expectation value of r k, we fin: u r k ur = k rk

3 Now we want to plug our raial wave equation into I, equation (6), an use the above result to evaluate it: [ l(l + ) u r s+ u r = u r s+ r ar + ] n a ur = l(l + ) u r s ur u r s ur + a n a u r s+ ur Thus, the integral I equals: I = l(l + )(s ) = r s + s a rs s + n a rs l(l + )(s ) (s + ) r s s a(s + ) rs + n a rs We can evaluate the integral I with the formula above: I = s ur s u s(s ) r = r s So, our original integral, given by equation (5), is: ur s u l(l + )(s ) r = I I = r s s + (s + ) a(s + ) rs s(s ) n a rs + r s Now, going all the way back to the start, we see the above result is only the left-han-sie of equation (), so we can set it equal to the left-han-sie an solve: l(l + )(s ) (s + )... + r s + s(s ) s a(s + ) rs n a rs +... r s = l(l + ) r s a rs + n a rs If we multiply both sies by (s + ) an group everything to the left-han-sie, we arrive at: l(l + )(s ) r s + s (s + ) a rs n a r s + s(s )(s + ) r s l(l + )(s + ) r s + (s + ) a Notice that combining the r s terms gives a coefficient of: r s (s + ) n a r s = 0 l(l + )(s ) l(l + )(s ) + s(s )(s + ) = l(l + )s + s(s ) = s(l + l s + ) = s [ (l + ) s ] The coefficient of the r s term becomes (s + )/a, an the coefficient of the r s term becomes (s + )/n a. Putting this all together, our above equation becomes: s [ (l + ) s ] r s + (s + ) a r s (s + ) n a r s = 0 Finally, multiplying the above equation by a /, an re-orering from r s to r s, we have Kramers relation: s + n r s (s + )a r s + s [ (l + ) s ] a r s = 0 (7) 3

4 3 Solutions of the Relation The main application of Kramers relation is that of computing perturbative corrections to the hyrogen atom, such as for the fine structure or hyperfine structure of hyrogen. In orer to see this in action, let s compute some particular solutions to Kramers relation. First, the s = 0 solution yiels: n r0 a r = 0 So, re-arranging, we fin the expectation value of /r: = r n a (8) Notice also the s = solution yiels: n r 3a r 0 + [ (l + ) ] a r = 0 Since we just foun r, we can solve the above for r. We ll see that setting s = will allow us to solve for r, an so on. However, we run into a problem when trying to go to larger negative powers of r s, such as trying to fin r (by setting s =, for instance): the best we ll be able to o is to fin an equation for r in terms of r 3. Going to progressively larger (negative) powers keeps the problem going unless we can solve for one along the chain, e.g. r or r 3, then Kramers relation will never allow us to solve for any value of s below. This is seen by checking the s = case: a r [ (l + ) ] a r 3 = 0 As we can see, without knowing either r or r 3, we can t solve for the other. A common way to circumvent this problem is to use the Feynman-Hellmann theorem to compute r, which allows for all subsequent solutions for s < to be foun using Kramers relation. The Feynman- Hellmann theorem, an the computation of r itself using the theorem, are presente in the appenix; I ll merely present the result here: r = (l + )n3 a (9) Knowing r, we can solve the above s = solution to Kramers relation for r 3 : r 3 = a[(l + ) ] r = [(l + ) l](l + )n3 a 3 Notice that (l + ) = l + l + = l(l + ), so the above equation results in: r 3 = l(l + )(l + (0) )n3 a 3 Now that the negative s solutions have been starte, one coul compute r s for all values of s using Kramers relation.

5 A Feynman-Hellmann Theorem Imagine we ha a Hamiltonian H with normalize eigenstates ψ such that: H ψ = E ψ If we consiere some parameter λ that we coul express the Hamiltonian, the states, an the energies in terms of, then the above equation woul become: This, for normalize states, means that: H(λ) ψ(λ) = E(λ) ψ(λ) () E(λ) = ψ(λ) H(λ) ψ(λ) Now we want to consier taking the erivative of the energy with respect to this parameter λ. Applying the prouct rule to the right-han-sie, we see that: ( ) ( ) E(λ) = λ λ ψ(λ) H(λ) ψ(λ) + ψ(λ) H(λ) λ ψ(λ) + ψ(λ) H(λ) λ ψ(λ) For the first an final terms on the right-han-sie of the above equation, we can apply H(λ) right-war an left-war, respectively, yieling: ( ) ( ) E(λ) = E(λ) λ λ ψ(λ) ψ(λ) + ψ(λ) H(λ) λ ψ(λ) + E(λ) ψ(λ) λ ψ(λ) Notice, then, that the first an thir terms above are simply an example of the prouct rule: ( ) ( ) λ ψ(λ) ψ(λ) + ψ(λ) λ ψ(λ) = λ ψ(λ) ψ(λ) Here s the final step of the erivation: recall that we require that the states be normalize. Thus, for any parameter λ, ψ(λ) ψ(λ) =, an so the above term equals zero. Therefore, our above equation for E/λ simply results in: E(λ) λ = ψ(λ) H(λ) λ ψ(λ) This equation is known as the Feynmann-Hellmann theorem. Using the Feynman-Hellmann theorem, I can erive many interesting results. Most important to this note is the erivation of r for the hyrogen atom. To o so, we ll express our (raial) Hamiltonian in the usual way: H = m r + m l(l + ) r e πɛ 0 r an we ll express the energy of a state ψ nlm in terms of n = j max + l +. This is because, in orer to compute r, we nee to choose λ = l in the Feynman-Hellmann theorem, so E nees to be expresse in terms of its epenence on l, which is hien in its epenence on n. In this respect, the energy is given by: E n = ma (j max + l + ) Technically the claim that this equation is true is the theorem. The woring that everyone uses just bothers me. () 5

6 As I sai above, we want to apply the Feynman-Hellmann theorem in the case of λ = l. So, first we ll calculate the erivative of E: E(l) l = ma (j max + l + ) 3 = mn 3 a where I have converte back from l epenence to n epenence because we no longer nee the l epenence to be explicit. Next, we ll calculate the erivative of H with respect to l: H(l) l = l + m r Finally, we ll compute the expectation value of this erivative: H(l) = (l + ) l m r = m ( l + ) r So, plugging our results into the Feynman-Hellmann theorem, we have: ( mn 3 a = l + ) m r from which r is very easily solve for: r = (l + )n3 a (3) 6

Quantum Mechanics in Three Dimensions

Quantum Mechanics in Three Dimensions Physics 342 Lecture 20 Quantum Mechanics in Three Dimensions Lecture 20 Physics 342 Quantum Mechanics I Monay, March 24th, 2008 We begin our spherical solutions with the simplest possible case zero potential.

More information

Linear First-Order Equations

Linear First-Order Equations 5 Linear First-Orer Equations Linear first-orer ifferential equations make up another important class of ifferential equations that commonly arise in applications an are relatively easy to solve (in theory)

More information

6 Wave equation in spherical polar coordinates

6 Wave equation in spherical polar coordinates 6 Wave equation in spherical polar coorinates We now look at solving problems involving the Laplacian in spherical polar coorinates. The angular epenence of the solutions will be escribe by spherical harmonics.

More information

23 Implicit differentiation

23 Implicit differentiation 23 Implicit ifferentiation 23.1 Statement The equation y = x 2 + 3x + 1 expresses a relationship between the quantities x an y. If a value of x is given, then a corresponing value of y is etermine. For

More information

Solving the Schrödinger Equation for the 1 Electron Atom (Hydrogen-Like)

Solving the Schrödinger Equation for the 1 Electron Atom (Hydrogen-Like) Stockton Univeristy Chemistry Program, School of Natural Sciences an Mathematics 101 Vera King Farris Dr, Galloway, NJ CHEM 340: Physical Chemistry II Solving the Schröinger Equation for the 1 Electron

More information

Section 7.1: Integration by Parts

Section 7.1: Integration by Parts Section 7.1: Integration by Parts 1. Introuction to Integration Techniques Unlike ifferentiation where there are a large number of rules which allow you (in principle) to ifferentiate any function, the

More information

Implicit Differentiation

Implicit Differentiation Implicit Differentiation Thus far, the functions we have been concerne with have been efine explicitly. A function is efine explicitly if the output is given irectly in terms of the input. For instance,

More information

d dx But have you ever seen a derivation of these results? We ll prove the first result below. cos h 1

d dx But have you ever seen a derivation of these results? We ll prove the first result below. cos h 1 Lecture 5 Some ifferentiation rules Trigonometric functions (Relevant section from Stewart, Seventh Eition: Section 3.3) You all know that sin = cos cos = sin. () But have you ever seen a erivation of

More information

Vectors in two dimensions

Vectors in two dimensions Vectors in two imensions Until now, we have been working in one imension only The main reason for this is to become familiar with the main physical ieas like Newton s secon law, without the aitional complication

More information

Implicit Differentiation

Implicit Differentiation Implicit Differentiation Implicit Differentiation Using the Chain Rule In the previous section we focuse on the erivatives of composites an saw that THEOREM 20 (Chain Rule) Suppose that u = g(x) is ifferentiable

More information

11.7. Implicit Differentiation. Introduction. Prerequisites. Learning Outcomes

11.7. Implicit Differentiation. Introduction. Prerequisites. Learning Outcomes Implicit Differentiation 11.7 Introuction This Section introuces implicit ifferentiation which is use to ifferentiate functions expresse in implicit form (where the variables are foun together). Examples

More information

Lagrangian and Hamiltonian Mechanics

Lagrangian and Hamiltonian Mechanics Lagrangian an Hamiltonian Mechanics.G. Simpson, Ph.. epartment of Physical Sciences an Engineering Prince George s Community College ecember 5, 007 Introuction In this course we have been stuying classical

More information

Lectures - Week 10 Introduction to Ordinary Differential Equations (ODES) First Order Linear ODEs

Lectures - Week 10 Introduction to Ordinary Differential Equations (ODES) First Order Linear ODEs Lectures - Week 10 Introuction to Orinary Differential Equations (ODES) First Orer Linear ODEs When stuying ODEs we are consiering functions of one inepenent variable, e.g., f(x), where x is the inepenent

More information

The Exact Form and General Integrating Factors

The Exact Form and General Integrating Factors 7 The Exact Form an General Integrating Factors In the previous chapters, we ve seen how separable an linear ifferential equations can be solve using methos for converting them to forms that can be easily

More information

Assignment 1. g i (x 1,..., x n ) dx i = 0. i=1

Assignment 1. g i (x 1,..., x n ) dx i = 0. i=1 Assignment 1 Golstein 1.4 The equations of motion for the rolling isk are special cases of general linear ifferential equations of constraint of the form g i (x 1,..., x n x i = 0. i=1 A constraint conition

More information

First Order Linear Differential Equations

First Order Linear Differential Equations LECTURE 6 First Orer Linear Differential Equations A linear first orer orinary ifferential equation is a ifferential equation of the form ( a(xy + b(xy = c(x. Here y represents the unknown function, y

More information

A. Incorrect! The letter t does not appear in the expression of the given integral

A. Incorrect! The letter t does not appear in the expression of the given integral AP Physics C - Problem Drill 1: The Funamental Theorem of Calculus Question No. 1 of 1 Instruction: (1) Rea the problem statement an answer choices carefully () Work the problems on paper as neee (3) Question

More information

Physics 5153 Classical Mechanics. The Virial Theorem and The Poisson Bracket-1

Physics 5153 Classical Mechanics. The Virial Theorem and The Poisson Bracket-1 Physics 5153 Classical Mechanics The Virial Theorem an The Poisson Bracket 1 Introuction In this lecture we will consier two applications of the Hamiltonian. The first, the Virial Theorem, applies to systems

More information

Implicit Differentiation. Lecture 16.

Implicit Differentiation. Lecture 16. Implicit Differentiation. Lecture 16. We are use to working only with functions that are efine explicitly. That is, ones like f(x) = 5x 3 + 7x x 2 + 1 or s(t) = e t5 3, in which the function is escribe

More information

Lecture 6: Calculus. In Song Kim. September 7, 2011

Lecture 6: Calculus. In Song Kim. September 7, 2011 Lecture 6: Calculus In Song Kim September 7, 20 Introuction to Differential Calculus In our previous lecture we came up with several ways to analyze functions. We saw previously that the slope of a linear

More information

Markov Chains in Continuous Time

Markov Chains in Continuous Time Chapter 23 Markov Chains in Continuous Time Previously we looke at Markov chains, where the transitions betweenstatesoccurreatspecifietime- steps. That it, we mae time (a continuous variable) avance in

More information

Integration by Parts

Integration by Parts Integration by Parts 6-3-207 If u an v are functions of, the Prouct Rule says that (uv) = uv +vu Integrate both sies: (uv) = uv = uv + u v + uv = uv vu, vu v u, I ve written u an v as shorthan for u an

More information

Calculus of Variations

Calculus of Variations 16.323 Lecture 5 Calculus of Variations Calculus of Variations Most books cover this material well, but Kirk Chapter 4 oes a particularly nice job. x(t) x* x*+ αδx (1) x*- αδx (1) αδx (1) αδx (1) t f t

More information

Approximate Molecular Orbital Calculations for H 2. George M. Shalhoub

Approximate Molecular Orbital Calculations for H 2. George M. Shalhoub Approximate Molecular Orbital Calculations for H + LA SALLE UNIVESITY 9 West Olney Ave. Philaelphia, PA 94 shalhoub@lasalle.eu Copyright. All rights reserve. You are welcome to use this ocument in your

More information

Chapter 2 The Derivative Business Calculus 155

Chapter 2 The Derivative Business Calculus 155 Chapter The Derivative Business Calculus 155 Section 11: Implicit Differentiation an Relate Rates In our work up until now, the functions we neee to ifferentiate were either given explicitly, x such as

More information

Euler equations for multiple integrals

Euler equations for multiple integrals Euler equations for multiple integrals January 22, 2013 Contents 1 Reminer of multivariable calculus 2 1.1 Vector ifferentiation......................... 2 1.2 Matrix ifferentiation........................

More information

ensembles When working with density operators, we can use this connection to define a generalized Bloch vector: v x Tr x, v y Tr y

ensembles When working with density operators, we can use this connection to define a generalized Bloch vector: v x Tr x, v y Tr y Ph195a lecture notes, 1/3/01 Density operators for spin- 1 ensembles So far in our iscussion of spin- 1 systems, we have restricte our attention to the case of pure states an Hamiltonian evolution. Toay

More information

IMPLICIT DIFFERENTIATION

IMPLICIT DIFFERENTIATION IMPLICIT DIFFERENTIATION CALCULUS 3 INU0115/515 (MATHS 2) Dr Arian Jannetta MIMA CMath FRAS Implicit Differentiation 1/ 11 Arian Jannetta Explicit an implicit functions Explicit functions An explicit function

More information

1 Lecture 20: Implicit differentiation

1 Lecture 20: Implicit differentiation Lecture 20: Implicit ifferentiation. Outline The technique of implicit ifferentiation Tangent lines to a circle Derivatives of inverse functions by implicit ifferentiation Examples.2 Implicit ifferentiation

More information

Schrödinger s equation.

Schrödinger s equation. Physics 342 Lecture 5 Schröinger s Equation Lecture 5 Physics 342 Quantum Mechanics I Wenesay, February 3r, 2010 Toay we iscuss Schröinger s equation an show that it supports the basic interpretation of

More information

State-Space Model for a Multi-Machine System

State-Space Model for a Multi-Machine System State-Space Moel for a Multi-Machine System These notes parallel section.4 in the text. We are ealing with classically moele machines (IEEE Type.), constant impeance loas, an a network reuce to its internal

More information

Exam 2 Review Solutions

Exam 2 Review Solutions Exam Review Solutions 1. True or False, an explain: (a) There exists a function f with continuous secon partial erivatives such that f x (x, y) = x + y f y = x y False. If the function has continuous secon

More information

Sturm-Liouville Theory

Sturm-Liouville Theory LECTURE 5 Sturm-Liouville Theory In the three preceing lectures I emonstrate the utility of Fourier series in solving PDE/BVPs. As we ll now see, Fourier series are just the tip of the iceberg of the theory

More information

Construction of the Electronic Radial Wave Functions and Probability Distributions of Hydrogen-like Systems

Construction of the Electronic Radial Wave Functions and Probability Distributions of Hydrogen-like Systems Construction of the Electronic Raial Wave Functions an Probability Distributions of Hyrogen-like Systems Thomas S. Kuntzleman, Department of Chemistry Spring Arbor University, Spring Arbor MI 498 tkuntzle@arbor.eu

More information

0.1 Differentiation Rules

0.1 Differentiation Rules 0.1 Differentiation Rules From our previous work we ve seen tat it can be quite a task to calculate te erivative of an arbitrary function. Just working wit a secon-orer polynomial tings get pretty complicate

More information

Outline. MS121: IT Mathematics. Differentiation Rules for Differentiation: Part 1. Outline. Dublin City University 4 The Quotient Rule

Outline. MS121: IT Mathematics. Differentiation Rules for Differentiation: Part 1. Outline. Dublin City University 4 The Quotient Rule MS2: IT Mathematics Differentiation Rules for Differentiation: Part John Carroll School of Mathematical Sciences Dublin City University Pattern Observe You may have notice the following pattern when we

More information

0.1 The Chain Rule. db dt = db

0.1 The Chain Rule. db dt = db 0. The Chain Rule A basic illustration of the chain rules comes in thinking about runners in a race. Suppose two brothers, Mark an Brian, hol an annual race to see who is the fastest. Last year Mark won

More information

Math 1271 Solutions for Fall 2005 Final Exam

Math 1271 Solutions for Fall 2005 Final Exam Math 7 Solutions for Fall 5 Final Eam ) Since the equation + y = e y cannot be rearrange algebraically in orer to write y as an eplicit function of, we must instea ifferentiate this relation implicitly

More information

Review of Differentiation and Integration for Ordinary Differential Equations

Review of Differentiation and Integration for Ordinary Differential Equations Schreyer Fall 208 Review of Differentiation an Integration for Orinary Differential Equations In this course you will be expecte to be able to ifferentiate an integrate quickly an accurately. Many stuents

More information

Chapter 1 Overview: Review of Derivatives

Chapter 1 Overview: Review of Derivatives Chapter Overview: Review of Derivatives The purpose of this chapter is to review the how of ifferentiation. We will review all the erivative rules learne last year in PreCalculus. In the net several chapters,

More information

Solutions to Math 41 Second Exam November 4, 2010

Solutions to Math 41 Second Exam November 4, 2010 Solutions to Math 41 Secon Exam November 4, 2010 1. (13 points) Differentiate, using the metho of your choice. (a) p(t) = ln(sec t + tan t) + log 2 (2 + t) (4 points) Using the rule for the erivative of

More information

Lecture XII. where Φ is called the potential function. Let us introduce spherical coordinates defined through the relations

Lecture XII. where Φ is called the potential function. Let us introduce spherical coordinates defined through the relations Lecture XII Abstract We introuce the Laplace equation in spherical coorinates an apply the metho of separation of variables to solve it. This will generate three linear orinary secon orer ifferential equations:

More information

Further Differentiation and Applications

Further Differentiation and Applications Avance Higher Notes (Unit ) Prerequisites: Inverse function property; prouct, quotient an chain rules; inflexion points. Maths Applications: Concavity; ifferentiability. Real-Worl Applications: Particle

More information

SYDE 112, LECTURE 1: Review & Antidifferentiation

SYDE 112, LECTURE 1: Review & Antidifferentiation SYDE 112, LECTURE 1: Review & Antiifferentiation 1 Course Information For a etaile breakown of the course content an available resources, see the Course Outline. Other relevant information for this section

More information

Physics 115C Homework 4

Physics 115C Homework 4 Physics 115C Homework 4 Problem 1 a In the Heisenberg picture, the ynamical equation is the Heisenberg equation of motion: for any operator Q H, we have Q H = 1 t i [Q H,H]+ Q H t where the partial erivative

More information

The Explicit Form of a Function

The Explicit Form of a Function Section 3 5 Implicit Differentiation The Eplicit Form of a Function The normal way we see function notation has f () on one sie of an equation an an epression in terms of on the other sie. We know the

More information

Calculus of Variations

Calculus of Variations Calculus of Variations Lagrangian formalism is the main tool of theoretical classical mechanics. Calculus of Variations is a part of Mathematics which Lagrangian formalism is base on. In this section,

More information

Two formulas for the Euler ϕ-function

Two formulas for the Euler ϕ-function Two formulas for the Euler ϕ-function Robert Frieman A multiplication formula for ϕ(n) The first formula we want to prove is the following: Theorem 1. If n 1 an n 2 are relatively prime positive integers,

More information

Final Exam Study Guide and Practice Problems Solutions

Final Exam Study Guide and Practice Problems Solutions Final Exam Stuy Guie an Practice Problems Solutions Note: These problems are just some of the types of problems that might appear on the exam. However, to fully prepare for the exam, in aition to making

More information

1 Heisenberg Representation

1 Heisenberg Representation 1 Heisenberg Representation What we have been ealing with so far is calle the Schröinger representation. In this representation, operators are constants an all the time epenence is carrie by the states.

More information

q = F If we integrate this equation over all the mass in a star, we have q dm = F (M) F (0)

q = F If we integrate this equation over all the mass in a star, we have q dm = F (M) F (0) Astronomy 112: The Physics of Stars Class 4 Notes: Energy an Chemical Balance in Stars In the last class we introuce the iea of hyrostatic balance in stars, an showe that we coul use this concept to erive

More information

Math 1B, lecture 8: Integration by parts

Math 1B, lecture 8: Integration by parts Math B, lecture 8: Integration by parts Nathan Pflueger 23 September 2 Introuction Integration by parts, similarly to integration by substitution, reverses a well-known technique of ifferentiation an explores

More information

MATH 205 Practice Final Exam Name:

MATH 205 Practice Final Exam Name: MATH 205 Practice Final Eam Name:. (2 points) Consier the function g() = e. (a) (5 points) Ientify the zeroes, vertical asymptotes, an long-term behavior on both sies of this function. Clearly label which

More information

Related Rates. Introduction. We are familiar with a variety of mathematical or quantitative relationships, especially geometric ones.

Related Rates. Introduction. We are familiar with a variety of mathematical or quantitative relationships, especially geometric ones. Relate Rates Introuction We are familiar with a variety of mathematical or quantitative relationships, especially geometric ones For example, for the sies of a right triangle we have a 2 + b 2 = c 2 or

More information

Differentiation ( , 9.5)

Differentiation ( , 9.5) Chapter 2 Differentiation (8.1 8.3, 9.5) 2.1 Rate of Change (8.2.1 5) Recall that the equation of a straight line can be written as y = mx + c, where m is the slope or graient of the line, an c is the

More information

The Principle of Least Action

The Principle of Least Action Chapter 7. The Principle of Least Action 7.1 Force Methos vs. Energy Methos We have so far stuie two istinct ways of analyzing physics problems: force methos, basically consisting of the application of

More information

Lecture 10 Notes, Electromagnetic Theory II Dr. Christopher S. Baird, faculty.uml.edu/cbaird University of Massachusetts Lowell

Lecture 10 Notes, Electromagnetic Theory II Dr. Christopher S. Baird, faculty.uml.edu/cbaird University of Massachusetts Lowell Lecture 10 Notes, Electromagnetic Theory II Dr. Christopher S. Bair, faculty.uml.eu/cbair University of Massachusetts Lowell 1. Pre-Einstein Relativity - Einstein i not invent the concept of relativity,

More information

Year 11 Matrices Semester 2. Yuk

Year 11 Matrices Semester 2. Yuk Year 11 Matrices Semester 2 Chapter 5A input/output Yuk 1 Chapter 5B Gaussian Elimination an Systems of Linear Equations This is an extension of solving simultaneous equations. What oes a System of Linear

More information

Some vector algebra and the generalized chain rule Ross Bannister Data Assimilation Research Centre, University of Reading, UK Last updated 10/06/10

Some vector algebra and the generalized chain rule Ross Bannister Data Assimilation Research Centre, University of Reading, UK Last updated 10/06/10 Some vector algebra an the generalize chain rule Ross Bannister Data Assimilation Research Centre University of Reaing UK Last upate 10/06/10 1. Introuction an notation As we shall see in these notes the

More information

Solutions to Practice Problems Tuesday, October 28, 2008

Solutions to Practice Problems Tuesday, October 28, 2008 Solutions to Practice Problems Tuesay, October 28, 2008 1. The graph of the function f is shown below. Figure 1: The graph of f(x) What is x 1 + f(x)? What is x 1 f(x)? An oes x 1 f(x) exist? If so, what

More information

VIBRATIONS OF A CIRCULAR MEMBRANE

VIBRATIONS OF A CIRCULAR MEMBRANE VIBRATIONS OF A CIRCULAR MEMBRANE RAM EKSTROM. Solving the wave equation on the isk The ynamics of vibrations of a two-imensional isk D are given by the wave equation..) c 2 u = u tt, together with the

More information

MA 2232 Lecture 08 - Review of Log and Exponential Functions and Exponential Growth

MA 2232 Lecture 08 - Review of Log and Exponential Functions and Exponential Growth MA 2232 Lecture 08 - Review of Log an Exponential Functions an Exponential Growth Friay, February 2, 2018. Objectives: Review log an exponential functions, their erivative an integration formulas. Exponential

More information

The derivative of a function f(x) is another function, defined in terms of a limiting expression: f(x + δx) f(x)

The derivative of a function f(x) is another function, defined in terms of a limiting expression: f(x + δx) f(x) Y. D. Chong (2016) MH2801: Complex Methos for the Sciences 1. Derivatives The erivative of a function f(x) is another function, efine in terms of a limiting expression: f (x) f (x) lim x δx 0 f(x + δx)

More information

3.7 Implicit Differentiation -- A Brief Introduction -- Student Notes

3.7 Implicit Differentiation -- A Brief Introduction -- Student Notes Fin these erivatives of these functions: y.7 Implicit Differentiation -- A Brief Introuction -- Stuent Notes tan y sin tan = sin y e = e = Write the inverses of these functions: y tan y sin How woul we

More information

1 dx. where is a large constant, i.e., 1, (7.6) and Px is of the order of unity. Indeed, if px is given by (7.5), the inequality (7.

1 dx. where is a large constant, i.e., 1, (7.6) and Px is of the order of unity. Indeed, if px is given by (7.5), the inequality (7. Lectures Nine an Ten The WKB Approximation The WKB metho is a powerful tool to obtain solutions for many physical problems It is generally applicable to problems of wave propagation in which the frequency

More information

ay (t) + by (t) + cy(t) = 0 (2)

ay (t) + by (t) + cy(t) = 0 (2) Solving ay + by + cy = 0 Without Characteristic Equations, Complex Numbers, or Hats John Tolle Department of Mathematical Sciences Carnegie Mellon University Pittsburgh, PA 15213-3890 Some calculus courses

More information

. Using a multinomial model gives us the following equation for P d. , with respect to same length term sequences.

. Using a multinomial model gives us the following equation for P d. , with respect to same length term sequences. S 63 Lecture 8 2/2/26 Lecturer Lillian Lee Scribes Peter Babinski, Davi Lin Basic Language Moeling Approach I. Special ase of LM-base Approach a. Recap of Formulas an Terms b. Fixing θ? c. About that Multinomial

More information

d dx [xn ] = nx n 1. (1) dy dx = 4x4 1 = 4x 3. Theorem 1.3 (Derivative of a constant function). If f(x) = k and k is a constant, then f (x) = 0.

d dx [xn ] = nx n 1. (1) dy dx = 4x4 1 = 4x 3. Theorem 1.3 (Derivative of a constant function). If f(x) = k and k is a constant, then f (x) = 0. Calculus refresher Disclaimer: I claim no original content on this ocument, which is mostly a summary-rewrite of what any stanar college calculus book offers. (Here I ve use Calculus by Dennis Zill.) I

More information

Diagonalization of Matrices Dr. E. Jacobs

Diagonalization of Matrices Dr. E. Jacobs Diagonalization of Matrices Dr. E. Jacobs One of the very interesting lessons in this course is how certain algebraic techniques can be use to solve ifferential equations. The purpose of these notes is

More information

1 The Derivative of ln(x)

1 The Derivative of ln(x) Monay, December 3, 2007 The Derivative of ln() 1 The Derivative of ln() The first term or semester of most calculus courses will inclue the it efinition of the erivative an will work out, long han, a number

More information

The Three-dimensional Schödinger Equation

The Three-dimensional Schödinger Equation The Three-imensional Schöinger Equation R. L. Herman November 7, 016 Schröinger Equation in Spherical Coorinates We seek to solve the Schröinger equation with spherical symmetry using the metho of separation

More information

Math Notes on differentials, the Chain Rule, gradients, directional derivative, and normal vectors

Math Notes on differentials, the Chain Rule, gradients, directional derivative, and normal vectors Math 18.02 Notes on ifferentials, the Chain Rule, graients, irectional erivative, an normal vectors Tangent plane an linear approximation We efine the partial erivatives of f( xy, ) as follows: f f( x+

More information

Applications of the Wronskian to ordinary linear differential equations

Applications of the Wronskian to ordinary linear differential equations Physics 116C Fall 2011 Applications of the Wronskian to orinary linear ifferential equations Consier a of n continuous functions y i (x) [i = 1,2,3,...,n], each of which is ifferentiable at least n times.

More information

Math Implicit Differentiation. We have discovered (and proved) formulas for finding derivatives of functions like

Math Implicit Differentiation. We have discovered (and proved) formulas for finding derivatives of functions like Math 400 3.5 Implicit Differentiation Name We have iscovere (an prove) formulas for fining erivatives of functions like f x x 3x 4x. 3 This amounts to fining y for 3 y x 3x 4x. Notice that in this case,

More information

Free rotation of a rigid body 1 D. E. Soper 2 University of Oregon Physics 611, Theoretical Mechanics 5 November 2012

Free rotation of a rigid body 1 D. E. Soper 2 University of Oregon Physics 611, Theoretical Mechanics 5 November 2012 Free rotation of a rigi boy 1 D. E. Soper 2 University of Oregon Physics 611, Theoretical Mechanics 5 November 2012 1 Introuction In this section, we escribe the motion of a rigi boy that is free to rotate

More information

Ordinary Differential Equations

Ordinary Differential Equations Orinary Differential Equations Example: Harmonic Oscillator For a perfect Hooke s-law spring,force as a function of isplacement is F = kx Combine with Newton s Secon Law: F = ma with v = a = v = 2 x 2

More information

Separation of Variables

Separation of Variables Physics 342 Lecture 1 Separation of Variables Lecture 1 Physics 342 Quantum Mechanics I Monay, January 25th, 2010 There are three basic mathematical tools we nee, an then we can begin working on the physical

More information

Robust Forward Algorithms via PAC-Bayes and Laplace Distributions. ω Q. Pr (y(ω x) < 0) = Pr A k

Robust Forward Algorithms via PAC-Bayes and Laplace Distributions. ω Q. Pr (y(ω x) < 0) = Pr A k A Proof of Lemma 2 B Proof of Lemma 3 Proof: Since the support of LL istributions is R, two such istributions are equivalent absolutely continuous with respect to each other an the ivergence is well-efine

More information

Chapter 3 Notes, Applied Calculus, Tan

Chapter 3 Notes, Applied Calculus, Tan Contents 3.1 Basic Rules of Differentiation.............................. 2 3.2 The Prouct an Quotient Rules............................ 6 3.3 The Chain Rule...................................... 9 3.4

More information

Lecture 16: The chain rule

Lecture 16: The chain rule Lecture 6: The chain rule Nathan Pflueger 6 October 03 Introuction Toay we will a one more rule to our toolbo. This rule concerns functions that are epresse as compositions of functions. The iea of a composition

More information

Differentiability, Computing Derivatives, Trig Review. Goals:

Differentiability, Computing Derivatives, Trig Review. Goals: Secants vs. Derivatives - Unit #3 : Goals: Differentiability, Computing Derivatives, Trig Review Determine when a function is ifferentiable at a point Relate the erivative graph to the the graph of an

More information

Define each term or concept.

Define each term or concept. Chapter Differentiation Course Number Section.1 The Derivative an the Tangent Line Problem Objective: In this lesson you learne how to fin the erivative of a function using the limit efinition an unerstan

More information

Math 180, Exam 2, Fall 2012 Problem 1 Solution. (a) The derivative is computed using the Chain Rule twice. 1 2 x x

Math 180, Exam 2, Fall 2012 Problem 1 Solution. (a) The derivative is computed using the Chain Rule twice. 1 2 x x . Fin erivatives of the following functions: (a) f() = tan ( 2 + ) ( ) 2 (b) f() = ln 2 + (c) f() = sin() Solution: Math 80, Eam 2, Fall 202 Problem Solution (a) The erivative is compute using the Chain

More information

Armenian Transformation Equations For Relativity

Armenian Transformation Equations For Relativity Armenian Transformation Equations For Relativity Robert Nazaryan an Haik Nazaryan 00th Anniversary of the Special Relativity Theory This Research one in Armenia 968-988, Translate from the Armenian Manuscript

More information

Angles-Only Orbit Determination Copyright 2006 Michel Santos Page 1

Angles-Only Orbit Determination Copyright 2006 Michel Santos Page 1 Angles-Only Orbit Determination Copyright 6 Michel Santos Page 1 Abstract This ocument presents a re-erivation of the Gauss an Laplace Angles-Only Methos for Initial Orbit Determination. It keeps close

More information

The Press-Schechter mass function

The Press-Schechter mass function The Press-Schechter mass function To state the obvious: It is important to relate our theories to what we can observe. We have looke at linear perturbation theory, an we have consiere a simple moel for

More information

Ψ(x) = c 0 φ 0 (x) + c 1 φ 1 (x) (1) Ĥφ n (x) = E n φ n (x) (2) Ψ = c 0 φ 0 + c 1 φ 1 (7) Ĥ φ n = E n φ n (4)

Ψ(x) = c 0 φ 0 (x) + c 1 φ 1 (x) (1) Ĥφ n (x) = E n φ n (x) (2) Ψ = c 0 φ 0 + c 1 φ 1 (7) Ĥ φ n = E n φ n (4) 1 Problem 1 Ψx = c 0 φ 0 x + c 1 φ 1 x 1 Ĥφ n x = E n φ n x E Ψ is the expectation value of energy of the state 1 taken with respect to the hamiltonian of the system. Thinking in Dirac notation 1 an become

More information

Unit #4 - Inverse Trig, Interpreting Derivatives, Newton s Method

Unit #4 - Inverse Trig, Interpreting Derivatives, Newton s Method Unit #4 - Inverse Trig, Interpreting Derivatives, Newton s Metho Some problems an solutions selecte or aapte from Hughes-Hallett Calculus. Computing Inverse Trig Derivatives. Starting with the inverse

More information

PHYS852 Quantum Mechanics II, Spring 2010 HOMEWORK ASSIGNMENT 8: Solutions. Topics covered: hydrogen fine structure

PHYS852 Quantum Mechanics II, Spring 2010 HOMEWORK ASSIGNMENT 8: Solutions. Topics covered: hydrogen fine structure PHYS85 Quantum Mechanics II, Spring HOMEWORK ASSIGNMENT 8: Solutions Topics covered: hydrogen fine structure. [ pts] Let the Hamiltonian H depend on the parameter λ, so that H = H(λ). The eigenstates and

More information

7.1 Support Vector Machine

7.1 Support Vector Machine 67577 Intro. to Machine Learning Fall semester, 006/7 Lecture 7: Support Vector Machines an Kernel Functions II Lecturer: Amnon Shashua Scribe: Amnon Shashua 7. Support Vector Machine We return now to

More information

4.2 First Differentiation Rules; Leibniz Notation

4.2 First Differentiation Rules; Leibniz Notation .. FIRST DIFFERENTIATION RULES; LEIBNIZ NOTATION 307. First Differentiation Rules; Leibniz Notation In this section we erive rules which let us quickly compute the erivative function f (x) for any polynomial

More information

Short Intro to Coordinate Transformation

Short Intro to Coordinate Transformation Short Intro to Coorinate Transformation 1 A Vector A vector can basically be seen as an arrow in space pointing in a specific irection with a specific length. The following problem arises: How o we represent

More information

Math 2163, Practice Exam II, Solution

Math 2163, Practice Exam II, Solution Math 63, Practice Exam II, Solution. (a) f =< f s, f t >=< s e t, s e t >, an v v = , so D v f(, ) =< ()e, e > =< 4, 4 > = 4. (b) f =< xy 3, 3x y 4y 3 > an v =< cos π, sin π >=, so

More information

Math Chapter 2 Essentials of Calculus by James Stewart Prepared by Jason Gaddis

Math Chapter 2 Essentials of Calculus by James Stewart Prepared by Jason Gaddis Math 231 - Chapter 2 Essentials of Calculus by James Stewart Prepare by Jason Gais Chapter 2 - Derivatives 21 - Derivatives an Rates of Change Definition A tangent to a curve is a line that intersects

More information

Derivatives and the Product Rule

Derivatives and the Product Rule Derivatives an the Prouct Rule James K. Peterson Department of Biological Sciences an Department of Mathematical Sciences Clemson University January 28, 2014 Outline Differentiability Simple Derivatives

More information

PDE Notes, Lecture #11

PDE Notes, Lecture #11 PDE Notes, Lecture # from Professor Jalal Shatah s Lectures Febuary 9th, 2009 Sobolev Spaces Recall that for u L loc we can efine the weak erivative Du by Du, φ := udφ φ C0 If v L loc such that Du, φ =

More information

Section 2.1 The Derivative and the Tangent Line Problem

Section 2.1 The Derivative and the Tangent Line Problem Chapter 2 Differentiation Course Number Section 2.1 The Derivative an the Tangent Line Problem Objective: In this lesson you learne how to fin the erivative of a function using the limit efinition an unerstan

More information

Strauss PDEs 2e: Section Exercise 6 Page 1 of 5

Strauss PDEs 2e: Section Exercise 6 Page 1 of 5 Strauss PDEs 2e: Section 4.3 - Exercise 6 Page 1 of 5 Exercise 6 If a 0 = a l = a in the Robin problem, show that: (a) There are no negative eigenvalues if a 0, there is one if 2/l < a < 0, an there are

More information

Pure Further Mathematics 1. Revision Notes

Pure Further Mathematics 1. Revision Notes Pure Further Mathematics Revision Notes June 20 2 FP JUNE 20 SDB Further Pure Complex Numbers... 3 Definitions an arithmetical operations... 3 Complex conjugate... 3 Properties... 3 Complex number plane,

More information

Chapter 5. Factorization of Integers

Chapter 5. Factorization of Integers Chapter 5 Factorization of Integers 51 Definition: For a, b Z we say that a ivies b (or that a is a factor of b, or that b is a multiple of a, an we write a b, when b = ak for some k Z 52 Theorem: (Basic

More information