LeChatelier Dynamics
|
|
- Vincent Mills
- 5 years ago
- Views:
Transcription
1 LeChatelier Dynamics Robert Gilmore Physics Department, Drexel University, Philaelphia, Pennsylvania 1914, USA (Date: June 12, 28, Levine Birthay Party: To be submitte.) Dynamics of the relaxation of a perturbe thermoynamic system to equilibrium is etermine by the generalize eigenvalue equation ( K αβ + λs αβ )y β =. Here S αβ is a matrix of linear response coefficients an K αβ is a matrix of kinetic coefficients. We escribe LeChatelier s Principle an both its static an ynamical symmetries, an treat cases in which there are multiple relaxation channels. The treatment simplifies when the relaxation channels have wiely separate time scales. I. INTRODUCTION LeChatelier s Principle is a statement about how a system in thermoynamic equilibrium respons to a perturbation. In brief, after the perturbation the system relaxes back to an equilibrium. This equilibrium is the highest possible entropy state, or the lowest possible energy state, that is available to the system uner the constraints that have been impose. If one or more relaxation channels are close, the new equilibrium will be ifferent from the original equilibrium. LeChatelier s Principle is usually state in qualitative terms. When it is escribe quantitatively it is almost always in terms of responses to a perturbation from equilibrium when a single reaction channel opens up [1, 2]. The case of intermeiate responses when there is a succession of relaxation channels with wiely separate time scales has been iscusse quantitatively in [3]. In this work we escribe the ynamical response of a system with any number of relaxation channels to an arbitrary perturbation. The relaxation time constants are etermine from a generalize eigenvalue equation. This equation involves the static linear response functions an their ynamic counterparts, the kinetic coefficients. The eigenvalues are well-efine functions of both sets of coefficients. The generalize eigenvalue equation is first expresse in the entropy representation. In this representation the entropy, S(t), continuously increases after the perturbation until the new equilibrium is reache. We then transform to the energy representation using what is for all practical purposes a similarity transformation. In this representation the internal energy, U(t), continuously ecreases after the perturbation until the new equilibrium is reache. Constraints that prevent the system from returning to its original equilibrium configuration are expresse naturally in this eigen-representation. Such constraints are represente by vanishing eigenvalues. Natural extensive variables, an their conjugate intensive variables, are summarize in Table I for the two ther- TABLE I: Natural conjugate variable pairs (Extensive, intensive) in the entropy an energy representations. Representation Entropy Energy X α y α E α i α U 1/T S T V P/T V P N µ/t N µ moynamic representations. Throughout we use contra- ( α ) an co- ( α ) variant notation for extensive an intensive thermoynamic variables. This notation is base on the geometric formulation of classical thermoynamics [4, 5, 6, 7]. In Sec. II we briefly review the properties of the matrices of static an ynamic coefficients, an then write own an justify the generalize eigenvalue equation that escribes LeChatelier ynamics. In Sec. III we transform to the more familiar energy representation. We illustrate how constraints are hanle in Sec. IV in terms of a simple example with a single relaxation channel. In Sec. V we review the symmetries that exist in single channel processes. They are of two types. One involves the ratios of asymptotic responses uner ual perturbations. The other involves a single relaxation time constant, also uner ual perturbations. In Sec. VI we treat the case in which there are multiple relaxation channels with wiely separate time scales. The results are summarize in Sec. VII. II. ASSUMPTIONS AND EQUATIONS - ENTROPY REPRESENTATION Two funamental equations escribe the ynamics of LeChatelier s Principle. In the entropy representation these are
2 2 δx α = S αβ δy β (Statics) (1) t δxα = K αβ δy β (Dynamics) (2) These equations escribe very ifferent physical processes. The first equation escribes static or aiabatic (meaning very slow) equilibrium processes. At equilibrium the entropy is a function of its natural extensive variables X (c.f., Table I). We assume there is an equilibrium for values X α of the extensive thermoynamic variables, an y α (X ) = S X (X α ) are the values of the conjugate intensive thermoynamic variables at this equilibrium. If the extensive variables are change to new values X α + δxα slowly, so that the system moves on the equilibrium surface S = S(X), the intensive variables will slowly change to new values y α (X ) + δy α. For small isplacements the linear relation between the isplacements of extensive an intensive thermoynamic variables is given by Eq. (1). The n n real symmetric matrix S αβ of( static susceptibilities is the inverse of the matrix S αβ = 2 S(X). This matrix is negative efinite at equilibrium, since the entropy is a maximum at X α X )X β equilibrium. The susceptibilities S αβ an S αβ are intrinsic to the thermoynamic system: they are inepenent of the container holing the material. The secon equation above relates forces to fluxes. The generalize forces are the ifferences in the intensive variables, δy β, across some sort of barrier separating the system of interest (A) from the outsie worl (B). The generalize fluxes, t δxβ, are the time rates of change of isplacements of the extensive variables as the system tries to relax to equilibrium: the highest available entropy state. Eq. (2) is a linearization of the general equation δx α = F α (δy) near the equilibrium manifol [8]. The matrix K αβ of kinetic coefficients obeys the Onsager symmetry K αβ (t) = K βα ( t) [9] an is positive semiefinite. The kinetic coefficients K αβ are extrinsic: they epen on the container holing the material an can be change from one experiment to another. The positivity property of the matrix of kinetic coefficients can be seen by computing the time rate of change of the combine entropy of the two systems A + B: t (S A + S B ) = S A X α A + S B X α B t XA α t XB α = ((y A ) α (y B ) α )XA α /t = δy Kαβ α δy β (3) We have exploite conservation of extensive quantities: X α A + Xα B = Xα Tot = const., so that Ẋα A = Ẋα B. We point out here that by simple imensional consierations, the imensions ([ ]) of the kinetic coefficients are closely relate to the imensions of the corresponing equilibrium linear response coefficients: Kαβ] = [ [ ] S αβ (time) 1. We now assume that uner a suen perturbation from equilibrium X α Xα + Xα, the subsystem remains homogeneous (no soun waves) an the relation between the extensive an intensive variables given in Eq. (1) remains vali. In this case we can write Eq. (2) as t Sαγ δy γ = K αβ δy β (4) Since this is a linear equation we can assume an exponential time epenence of the form δy β (t) = δy β ( + )e λt. This leas irectly to a generalize eigenvalue equation ( Kαβ + λs αβ) δy β ( + ) = (5) The eigenvalues λ are nonnegative because S αβ is negative efinite an K αβ is positive semi-efinite. These are thermoynamic stability conitions. The number of inepenent ecay channels is the number of nonzero eigenvalues of this generalize eigenvalue equation. Equivalently, it is the number of nonzero eigenvalues of the matrix K αβ. The number of vanishing eigenvalues is the number of inepenent constraints preventing ecay. The eigenvectors v i with eigenvalues λ i an components v αi of this generalize eigenvalue equation are mutually orthogonal with respect to the metric S αβ an can be normalize as follows: v αi ( S αβ )v βj = δ ij v αi (+ K αβ (6) )v βj = λ i δ ij They evolve in time like v αi e λit. The time evolution of the intensive isplacements is given by δy α (t) = n a j v αj e λjt (7) j=1 The coefficients a j are etermine in the usual way - by matching initial conitions: S αβ δx β ( + ) = δy α ( + ) = v αj a j (8) an inverting this matrix relation. Equation (5) shows how the relaxation time scales λ 1 i are etermine as functions of both the static an kinetic coefficients. Equation (8) escribes how the initial conitions enter into the ynamics.
3 3 III. ENERGY REPRESENTATION The entropy an more familiar energy representation are relate by something like a similarity transformation. Specifically, the matrix transformation relating isplacements of the inepenent extensive variables in the two representations (c.f., Table I) is E α = R α β Xβ eg. S 1 P T T V = µ T 1 U V N 1 N (9) The intensive variables are relate by y = 1 T Rt i. In the energy representation the static an ynamic equations are δe α = U αβ δi β U = 1 T RSRt t δeα = K αβ δi β K = 1 T R KR t (1) The generalize eigenvalue equation in this representation is ( K αβ + λu αβ) δi β () = (11) The more familiar linear response coefficients in the ( ) energy representation are U αβ = 2 U(E) 1. E α E This matrix is positive efinite, since U is a minimum at equilib- β rium. Similarly, the kinetic coefficients K in this representation form a negative semiefinite matrix, by arguments similar to those surrouning Eq. (4). Since U an K are relate to S an K by ientical transformations, the eigenvalue spectrum is the same in both representations. This must be true on the basis of physical arguments. The eigenvectors iffer by the transformations in Eq. (1) involving the nonsingular change of basis matrix R α β. IV. CONSTRAINTS We illustrate what happens when constraints are place on the system by consiering a simple gas in a cyliner [2]. The generalize eigenvalue problem in the energy representation has the form {[ ] [ ]}( ) K 11 K 12 U K 21 K 22 + λ 11 U 12 T() U 21 U 22 = P() (12) The stanar linear response functions are [ ] [ ] U 11 U 12 CP /T V α U 21 U 22 = P V α P V β T (13) FIG. 1: The entropy is suenly increase insie a cyliner that is thoroughly insulate (K SS = ). The temperature, pressure, an volume evolve in time as shown in Fig. 2. [ ] U 11 U 12 1 [ ] [ ] U11 U U 21 U 22 = 12 T/CV 1/V α = S U 21 U 22 1/V α S 1/V β S (14) We have exhibite the negative signs explicitly for the negative semiefinite matrix of kinetic coefficients K, an we further take K to be iagonal. The matrix element K 11 = K SS is measure in entropy flux per unit temperature increase an K 22 = K V V efines the rate of volume change per unit ecrease in pressure. If the piston separating the gas in the cyliner from the reservoir is a goo insulator (Fig. 1), K 11 =, there is one constraint an one vanishing eigenvalue. ( The ) unnormalize eigenvector with λ 1 = λ S = is. The 1 secon eigenvalue is λ 2 = λ V = K 22 U( 22 an the ) corresponing unnormalize eigenvector is U 12 U 11. These two eigenvectrors are orthogonal uner the metric U. The intensive variables evolve in time like an
4 4 S Responses T V - P Time FIG. 2: Response of the perturbations to the experiment shown in Fig. 1.The single ecay time scale is etermine by λ 2 = K 22 U 22. [ ] [ ] [ ] T(t) = a P(t) 1 e t 1 + a 2 e λ2t U 12 U 11 (15) For this case S( + ) = S, V ( + ) = an Eq. (8) is explicitly [ ] [ ] [ ] [ ][ ] U11 U 12 S T( = + ) 1 U 12 a1 U 21 U 22 P( + = ) U 11 a 2 (16) The coefficients are a 1 = S/U 11, a 2 = S U 21 /U 11. The values of the two pairs of conjugate variables, uner the no heat flow constraint K 11 =, are given at t = + an t in Table II. The evolution of these perturbations is shown in Fig. 2. All variables except S have the same characteristic ecay time λ 1 V, since there is only one ecay channel. The ual constraint is illustrate in Fig. 3. In this case the piston is suenly isplace an maintaine fixe at its new position. This constraint is represente by setting K 22 = : the rate of volume change per negative unit pressure change is zero. In this case the zero eigenvalue is λ V = an the nonzero eigenvalue is λ S = K 11 U 11. The solution is compute as before, subject to initial conitions V ( + ) = V fixe an S( + ) =. The asymptotic behavior (t = +, t ) is summarize in Table II. As for the case shown in Fig. 1, all variables except V have the same characteristic ecay time λ 1 S, since there is only one ecay channel. The time evolution of these four variables is similar to that shown in Fig. 2, with the exchange ( S, T) ( V, P). If the ecay times are ientical (λ V in Fig. 1 an λ S in Fig. 3) the two processes exhibit ynamical symmetry as well as the asymptotic symmetry escribe in the next section. V. SYMMETRIES It is possible to compare proucts of extensive variables with their conjugate intensive variables, since all FIG. 3: The volume of a cyliner is suenly increase an the piston is glue at its new position (K V V = ). such proucts have the imensions of energy. Table II shows that the only nontrivial prouct of the responing variables is E r ( ) i r ( + ). This can be compare with the cross prouct of the forcing variables E f ( + ) i f ( ). above is The result in the two cases E r ( ) i r ( + ) E f ( + ) i f ( ) = Ufr U fr (17) This is true in general. The ratios of all such proucts are given by the elements of the LeChatelier matrix L αβ = U αβ U αβ = L βα [1, 2, 3]. This matrix is real an symmetric. Its iagonal matrix elements are greater than one [1, 2, 3, 7]. These are thermoynamic stability conitions. They provie quantitative expressions for LeChatelier s Direct Principle. If an extensive forcing variable is suenly change an hel constant, i f ( + )/ i f ( ) 1. Dually, if an intensive variable is suenly change an hel constant, E f ( )/ E f ( + ) 1 [1, 2, 3]. Further, the sum of the matrix elements L αβ in each row an in each column is equal to 1. Finally, if the forcing an responing variables are interchange, the cross ratios as given in Eq. (17) are equal, as seen in Table II. Further symmetries are present for systems with two egrees of freeom. In such cases the constraint requires one of the two eigenvalues to vanish. The two systems have ientical relaxation time scales provie the nonzero
5 5 TABLE II: Values of the thermoynamic variables uner constraints for a gas in a cyliner. Fig.1 Forcing Responing Channel Channel S T V P λ S = λ V = K 22 U 22 t = + S S U 11 S U 21 t S S/U 11 S U 21 /U 11 Fig.3 Responing Forcing Channel Channel S T V P λ S = K 11 U 11 λ V = t = + V U 12 V V U 22 t V U 12 /U 22 V V/U 22 eigenvalues are equal. The conition is that the nonzero kinetic coefficient K jj multiplie by the corresponing covariant matrix element U jj is the same for both experiments. Finally, if the initial perturbations, S in Fig. 1 an V in Fig. 3, obey ( S) 2 /U 11 = ( V ) 2 /U 22, the time epenence of the internal energy, U(t), is exactly the same for both experiments. to an excellent approximation. The components v αj of the jth eigenvector v j can be constructe irectly from the j (j 1) submatrix in the upper left-han corner of the matrix U of susceptibilities. The component v αj is the minor of this submatrix obtaine by removing row α. The three eigenvectors of Eq. (19) are, to a very goo approximation 1 U21 U 11 +(U21 U 32 U 31 U 22 ) (U 11 U 32 U 31 U 12 ) +(U 11 U 22 U 21 U 12 ) (21) The eigenvalues are easily etermine from these eigenvectors an Eq. (21). Extensive an Intensive Variables i³ E¹ i¹ i² E³ log (t) E² VI. CASCADING CONSTRAINTS V = [v αj ] = The three eigenvalues satisfy K jj v 2 jj = λ jv t j U v j = λ j v 11 v 12 v 13 v 22 v 23 v 33 j α,β=1 (19) v αj U αβ v βj (2) FIG. 4: Response of all thermoynamic variables when three channels have wiely separate time scales an the slowest extensive variable is perturbe. When there are multiple relaxation channels with wiely iffering time scales, the general solution that In Fig. 4 we illustrate the ynamics when there are mixes the static an ynamic coefficients given in Eq. (5) three channels with wiely separate relaxation time simplifies. For specificity we consier a system with three scales T 3 1, T an T 1 1 8, with T j = 1/λ j. egrees of freeom for which the matrix of kinetic coefficients is iagonal with K 11 /K 22 1 an K 22 /K In this figure the extensive variable with the longest relaxation time, E 1, is initially perturbe. Immeiately The equation etermining the eigenvalues/eigenvectors following the perturbation all three intensive variables of this problem is assume nonzero values while the remaining two extensive variables remain zero. K11 K 22 λ U11 U 12 U 13 U 21 U 22 U 23 v As t passes through the shortest time scale, T 3 1, 1 all three intensive variables relax to new values; the force v 2 = K 33 U 31 U 32 U 33 v 3 (18) The matrix of eigenvectors is upper triangular: with the shortest time scale, i 3, rops to zero. Its conjugate extensive variable E 3, rises to a nonzero value. Although i 1 an i 2 relax to new values, E 1 an E 2 remain unchange at the initial value an zero, respectively. As t passes through the intermeiate time scale T 2, the force i 2 rops to zero an its conjugate extensive variable, E 2, becomes nonzero. The extensive variable E 3 with the shorter time scale relaxes to a new value while the extensive variable E 1 with the longer time scale continues to remain unchange. Finally, as (if) t excees the longest time scale T 1 the corresponing force i 1 also rops to zero. At this point, all perturbations have relaxe to zero when no eigenvalues of the generalize eigenvalue equation are zero.
6 6 The succession of steps is summarize in Table III. This table also inclues cases for which the extensive variables E 2 with intermeiate time scale, an E 3 with shortest time scale are initially perturbe. Throughout this relaxation process the linear relation Eq. (1) between extensive an intensive thermoynamic variables is maintaine. In the quiet regimes between time scales T j+1 t T j the three thermoynamic variables (labele with *) can be etermine from the three that are given explicitly in Table III by simple matrix methos previously introuce to simplify the computation of thermoynamic partial erivatives [5, 6]. When faster extensive thermoynamic variables are initially perturbe the relaxation takes place faster, as shown in Table 3. This comes about because the faster variables o not have sufficient time to fee into the slower extensive variables before they relax to zero. VII. CONCLUSIONS The ynamical aspects of LeChatelier s Principle are escribe by the generalize eigenvalue equation Eq. (5) in the linear response regime. The number of close an open relaxation channels is etermine by the number of zero an nonzero eigenvalues of the matrix of kinetic coefficients. The nonzero eigenvalues are complicate functions of the matrices of static an ynamic (kinetic) coefficients etermine through the generalize eigenvalue equation. These equations were constructe in both the entropy (Eq. (5)) an energy (Eq. (11)) representations. There is, as usual, a clean separation of the ynamics into the equations of motion an the initial conitions (Eq. 8). When there is a single relaxation channel there is only one ecay time scale. Uner such conitions the LeChatelier symmetries are exhibite [1, 2, 3]. These symmetries relate proucts of conjugate variables in the asymptotic limits t = + an t. If the nonzero kinetic coefficients are properly ajuste, so that the responing time scales in ual experiments are equal, there is also a ynamical symmetry. When two or more relaxation channels exist an are well-separate in time, the successive relaxations through each of the wiely separate time scales can be treate as if each was a single channel relaxation with a single time scale. In such cases the asymptotic an even the ynamical symmetries exist on each sie of the newlyopene relaxation channel, as shown in Fig. 4 an Table III. Acknowlegment: It is a pleasure to acknowlege the inspiration affore by Prof. R. D. Levine for this problem. TABLE III: Succession of steps as t increases when λ 1 λ 2 λ 3 or T 3 T 2 T 1 an the initial perturbation is in the extensive variable corresponing to the longest (top), intermeiate (mile) an shortest (bottom) time scale. Each matrix contains three pairs of extensive an conjugate intensive variables ( E α, i α ), orere by relaxation time scale from slowest (top) to fastest (bottom). t = + T 3 t T 2 t T 1 t E1, E 2, E 3, E1,, E 2,, E1,,, REFERENCES [1] R. Gilmore, LeChatelier Reciprocal Relations, J. Chem. Phys. 76, (1982). [2] R. Gilmore, LeChatelier Reciprocal Relations an the Mechanical Analog, Am. J. Phys. 51, (1983). [3] R. Gilmore an R. D. Levine, LeChatelier s Principle with Multiple Relaxation Channels, Phys. Rev. A33, (1986). [4] F. Weinhol, Metric Geometry of Equilibrium Thermoynamics, J. Chem. Phys. 63, (1975); Elementary Formal Structure of a Vector-algebraic Representation of Equilibrium Thermoynamics, J. Chem. Phys. 63, (1975). [5] R. Gilmore, Thermoynamic Partial Derivatives, J. Chem. Phys. 75, (1982). [6] R. Gilmore, Higher Thermoynamic Partial Derivatives, J. Chem. Phys. 77, (1982). [7] R. Gilmore, Catastrophe Theory for Scientists an Engineers, NY: Wiley, [8] C. Kittel, Elementary Statistical Physics, NY: Wiley, [9] L. Onsager, Reciprocal Relations in Irreversible Processes. I, Phys. Rev. 37, (1931); Reciprocal Relations in Irreversible Processes. II, Phys. Rev. 38, (1931).
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 informationensembles 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 information19 Eigenvalues, Eigenvectors, Ordinary Differential Equations, and Control
19 Eigenvalues, Eigenvectors, Orinary Differential Equations, an Control This section introuces eigenvalues an eigenvectors of a matrix, an iscusses the role of the eigenvalues in etermining the behavior
More informationEuler 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 informationThe Ehrenfest Theorems
The Ehrenfest Theorems Robert Gilmore Classical Preliminaries A classical system with n egrees of freeom is escribe by n secon orer orinary ifferential equations on the configuration space (n inepenent
More informationand from it produce the action integral whose variation we set to zero:
Lagrange Multipliers Monay, 6 September 01 Sometimes it is convenient to use reunant coorinates, an to effect the variation of the action consistent with the constraints via the metho of Lagrange unetermine
More informationAverage value of position for the anharmonic oscillator: Classical versus quantum results
verage value of position for the anharmonic oscillator: Classical versus quantum results R. W. Robinett Department of Physics, The Pennsylvania State University, University Park, Pennsylvania 682 Receive
More informationCalculus 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 informationCalculus 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 informationDiagonalization 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 informationDesigning Information Devices and Systems II Fall 2017 Note Theorem: Existence and Uniqueness of Solutions to Differential Equations
EECS 6B Designing Information Devices an Systems II Fall 07 Note 3 Secon Orer Differential Equations Secon orer ifferential equations appear everywhere in the real worl. In this note, we will walk through
More informationThe 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 informationTMA 4195 Matematisk modellering Exam Tuesday December 16, :00 13:00 Problems and solution with additional comments
Problem F U L W D g m 3 2 s 2 0 0 0 0 2 kg 0 0 0 0 0 0 Table : Dimension matrix TMA 495 Matematisk moellering Exam Tuesay December 6, 2008 09:00 3:00 Problems an solution with aitional comments The necessary
More informationG j dq i + G j. q i. = a jt. and
Lagrange Multipliers Wenesay, 8 September 011 Sometimes it is convenient to use reunant coorinates, an to effect the variation of the action consistent with the constraints via the metho of Lagrange unetermine
More informationFree 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 informationLecture 2 Lagrangian formulation of classical mechanics Mechanics
Lecture Lagrangian formulation of classical mechanics 70.00 Mechanics Principle of stationary action MATH-GA To specify a motion uniquely in classical mechanics, it suffices to give, at some time t 0,
More informationIntroduction to the Vlasov-Poisson system
Introuction to the Vlasov-Poisson system Simone Calogero 1 The Vlasov equation Consier a particle with mass m > 0. Let x(t) R 3 enote the position of the particle at time t R an v(t) = ẋ(t) = x(t)/t its
More informationChapter 2 Lagrangian Modeling
Chapter 2 Lagrangian Moeling The basic laws of physics are use to moel every system whether it is electrical, mechanical, hyraulic, or any other energy omain. In mechanics, Newton s laws of motion provie
More informationJointly continuous distributions and the multivariate Normal
Jointly continuous istributions an the multivariate Normal Márton alázs an álint Tóth October 3, 04 This little write-up is part of important founations of probability that were left out of the unit Probability
More informationImplicit 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 information05 The Continuum Limit and the Wave Equation
Utah State University DigitalCommons@USU Founations of Wave Phenomena Physics, Department of 1-1-2004 05 The Continuum Limit an the Wave Equation Charles G. Torre Department of Physics, Utah State University,
More informationA Note on Modular Partitions and Necklaces
A Note on Moular Partitions an Neclaces N. J. A. Sloane, Rutgers University an The OEIS Founation Inc. South Aelaie Avenue, Highlan Par, NJ 08904, USA. Email: njasloane@gmail.com May 6, 204 Abstract Following
More informationinflow outflow Part I. Regular tasks for MAE598/494 Task 1
MAE 494/598, Fall 2016 Project #1 (Regular tasks = 20 points) Har copy of report is ue at the start of class on the ue ate. The rules on collaboration will be release separately. Please always follow the
More informationAssignment 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 informationLinear 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 informationProblem Sheet 2: Eigenvalues and eigenvectors and their use in solving linear ODEs
Problem Sheet 2: Eigenvalues an eigenvectors an their use in solving linear ODEs If you fin any typos/errors in this problem sheet please email jk28@icacuk The material in this problem sheet is not examinable
More informationThe total derivative. Chapter Lagrangian and Eulerian approaches
Chapter 5 The total erivative 51 Lagrangian an Eulerian approaches The representation of a flui through scalar or vector fiels means that each physical quantity uner consieration is escribe as a function
More informationSlide10 Haykin Chapter 14: Neurodynamics (3rd Ed. Chapter 13)
Slie10 Haykin Chapter 14: Neuroynamics (3r E. Chapter 13) CPSC 636-600 Instructor: Yoonsuck Choe Spring 2012 Neural Networks with Temporal Behavior Inclusion of feeback gives temporal characteristics to
More informationMany problems in physics, engineering, and chemistry fall in a general class of equations of the form. d dx. d dx
Math 53 Notes on turm-liouville equations Many problems in physics, engineering, an chemistry fall in a general class of equations of the form w(x)p(x) u ] + (q(x) λ) u = w(x) on an interval a, b], plus
More informationSturm-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 informationSchrödinger 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 informationConservation Laws. Chapter Conservation of Energy
20 Chapter 3 Conservation Laws In orer to check the physical consistency of the above set of equations governing Maxwell-Lorentz electroynamics [(2.10) an (2.12) or (1.65) an (1.68)], we examine the action
More informationPhysics 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 informationSeparation 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 informationSome functions and their derivatives
Chapter Some functions an their erivatives. Derivative of x n for integer n Recall, from eqn (.6), for y = f (x), Also recall that, for integer n, Hence, if y = x n then y x = lim δx 0 (a + b) n = a n
More informationQubit channels that achieve capacity with two states
Qubit channels that achieve capacity with two states Dominic W. Berry Department of Physics, The University of Queenslan, Brisbane, Queenslan 4072, Australia Receive 22 December 2004; publishe 22 March
More information4. Important theorems in quantum mechanics
TFY4215 Kjemisk fysikk og kvantemekanikk - Tillegg 4 1 TILLEGG 4 4. Important theorems in quantum mechanics Before attacking three-imensional potentials in the next chapter, we shall in chapter 4 of this
More informationQuantum mechanical approaches to the virial
Quantum mechanical approaches to the virial S.LeBohec Department of Physics an Astronomy, University of Utah, Salt Lae City, UT 84112, USA Date: June 30 th 2015 In this note, we approach the virial from
More informationNOTES ON EULER-BOOLE SUMMATION (1) f (l 1) (n) f (l 1) (m) + ( 1)k 1 k! B k (y) f (k) (y) dy,
NOTES ON EULER-BOOLE SUMMATION JONATHAN M BORWEIN, NEIL J CALKIN, AND DANTE MANNA Abstract We stuy a connection between Euler-MacLaurin Summation an Boole Summation suggeste in an AMM note from 196, which
More informationLecture Introduction. 2 Examples of Measure Concentration. 3 The Johnson-Lindenstrauss Lemma. CS-621 Theory Gems November 28, 2012
CS-6 Theory Gems November 8, 0 Lecture Lecturer: Alesaner Mąry Scribes: Alhussein Fawzi, Dorina Thanou Introuction Toay, we will briefly iscuss an important technique in probability theory measure concentration
More information12.11 Laplace s Equation in Cylindrical and
SEC. 2. Laplace s Equation in Cylinrical an Spherical Coorinates. Potential 593 2. Laplace s Equation in Cylinrical an Spherical Coorinates. Potential One of the most important PDEs in physics an engineering
More informationPartial Differential Equations
Chapter Partial Differential Equations. Introuction Have solve orinary ifferential equations, i.e. ones where there is one inepenent an one epenent variable. Only orinary ifferentiation is therefore involve.
More informationELEC3114 Control Systems 1
ELEC34 Control Systems Linear Systems - Moelling - Some Issues Session 2, 2007 Introuction Linear systems may be represente in a number of ifferent ways. Figure shows the relationship between various representations.
More informationarxiv:physics/ v2 [physics.ed-ph] 23 Sep 2003
Mass reistribution in variable mass systems Célia A. e Sousa an Vítor H. Rorigues Departamento e Física a Universiae e Coimbra, P-3004-516 Coimbra, Portugal arxiv:physics/0211075v2 [physics.e-ph] 23 Sep
More informationCapacity Analysis of MIMO Systems with Unknown Channel State Information
Capacity Analysis of MIMO Systems with Unknown Channel State Information Jun Zheng an Bhaskar D. Rao Dept. of Electrical an Computer Engineering University of California at San Diego e-mail: juzheng@ucs.eu,
More informationMath 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 informationA Note on Exact Solutions to Linear Differential Equations by the Matrix Exponential
Avances in Applie Mathematics an Mechanics Av. Appl. Math. Mech. Vol. 1 No. 4 pp. 573-580 DOI: 10.4208/aamm.09-m0946 August 2009 A Note on Exact Solutions to Linear Differential Equations by the Matrix
More informationA note on the Mooney-Rivlin material model
A note on the Mooney-Rivlin material moel I-Shih Liu Instituto e Matemática Universiae Feeral o Rio e Janeiro 2945-97, Rio e Janeiro, Brasil Abstract In finite elasticity, the Mooney-Rivlin material moel
More informationMEASURES WITH ZEROS IN THE INVERSE OF THEIR MOMENT MATRIX
MEASURES WITH ZEROS IN THE INVERSE OF THEIR MOMENT MATRIX J. WILLIAM HELTON, JEAN B. LASSERRE, AND MIHAI PUTINAR Abstract. We investigate an iscuss when the inverse of a multivariate truncate moment matrix
More informationHomework 7 Due 18 November at 6:00 pm
Homework 7 Due 18 November at 6:00 pm 1. Maxwell s Equations Quasi-statics o a An air core, N turn, cylinrical solenoi of length an raius a, carries a current I Io cos t. a. Using Ampere s Law, etermine
More informationGeneralization of the persistent random walk to dimensions greater than 1
PHYSICAL REVIEW E VOLUME 58, NUMBER 6 DECEMBER 1998 Generalization of the persistent ranom walk to imensions greater than 1 Marián Boguñá, Josep M. Porrà, an Jaume Masoliver Departament e Física Fonamental,
More informationG4003 Advanced Mechanics 1. We already saw that if q is a cyclic variable, the associated conjugate momentum is conserved, L = const.
G4003 Avance Mechanics 1 The Noether theorem We alreay saw that if q is a cyclic variable, the associate conjugate momentum is conserve, q = 0 p q = const. (1) This is the simplest incarnation of Noether
More informationThe 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 informationQuantum 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 informationApplications 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 informationMath 342 Partial Differential Equations «Viktor Grigoryan
Math 342 Partial Differential Equations «Viktor Grigoryan 6 Wave equation: solution In this lecture we will solve the wave equation on the entire real line x R. This correspons to a string of infinite
More informationHyperbolic Systems of Equations Posed on Erroneous Curved Domains
Hyperbolic Systems of Equations Pose on Erroneous Curve Domains Jan Norström a, Samira Nikkar b a Department of Mathematics, Computational Mathematics, Linköping University, SE-58 83 Linköping, Sween (
More information'HVLJQ &RQVLGHUDWLRQ LQ 0DWHULDO 6HOHFWLRQ 'HVLJQ 6HQVLWLYLW\,1752'8&7,21
Large amping in a structural material may be either esirable or unesirable, epening on the engineering application at han. For example, amping is a esirable property to the esigner concerne with limiting
More informationExamining Geometric Integration for Propagating Orbit Trajectories with Non-Conservative Forcing
Examining Geometric Integration for Propagating Orbit Trajectories with Non-Conservative Forcing Course Project for CDS 05 - Geometric Mechanics John M. Carson III California Institute of Technology June
More informationFirst 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 information1 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 informationarxiv: v1 [cond-mat.stat-mech] 9 Jan 2012
arxiv:1201.1836v1 [con-mat.stat-mech] 9 Jan 2012 Externally riven one-imensional Ising moel Amir Aghamohammai a 1, Cina Aghamohammai b 2, & Mohamma Khorrami a 3 a Department of Physics, Alzahra University,
More informationAPPROXIMATE SOLUTION FOR TRANSIENT HEAT TRANSFER IN STATIC TURBULENT HE II. B. Baudouy. CEA/Saclay, DSM/DAPNIA/STCM Gif-sur-Yvette Cedex, France
APPROXIMAE SOLUION FOR RANSIEN HEA RANSFER IN SAIC URBULEN HE II B. Bauouy CEA/Saclay, DSM/DAPNIA/SCM 91191 Gif-sur-Yvette Ceex, France ABSRAC Analytical solution in one imension of the heat iffusion equation
More informationarxiv:nlin/ v1 [nlin.cd] 21 Mar 2002
Entropy prouction of iffusion in spatially perioic eterministic systems arxiv:nlin/0203046v [nlin.cd] 2 Mar 2002 J. R. Dorfman, P. Gaspar, 2 an T. Gilbert 3 Department of Physics an Institute for Physical
More informationMath 115 Section 018 Course Note
Course Note 1 General Functions Definition 1.1. A function is a rule that takes certain numbers as inputs an assigns to each a efinite output number. The set of all input numbers is calle the omain of
More informationSurvey Sampling. 1 Design-based Inference. Kosuke Imai Department of Politics, Princeton University. February 19, 2013
Survey Sampling Kosuke Imai Department of Politics, Princeton University February 19, 2013 Survey sampling is one of the most commonly use ata collection methos for social scientists. We begin by escribing
More informationRank, Trace, Determinant, Transpose an Inverse of a Matrix Let A be an n n square matrix: A = a11 a1 a1n a1 a an a n1 a n a nn nn where is the jth col
Review of Linear Algebra { E18 Hanout Vectors an Their Inner Proucts Let X an Y be two vectors: an Their inner prouct is ene as X =[x1; ;x n ] T Y =[y1; ;y n ] T (X; Y ) = X T Y = x k y k k=1 where T an
More informationNested Saturation with Guaranteed Real Poles 1
Neste Saturation with Guarantee Real Poles Eric N Johnson 2 an Suresh K Kannan 3 School of Aerospace Engineering Georgia Institute of Technology, Atlanta, GA 3332 Abstract The global stabilization of asymptotically
More informationDesigning Information Devices and Systems II Spring 2018 J. Roychowdhury and M. Maharbiz Discussion 2A
EECS 6B Designing Information Devices an Systems II Spring 208 J. Roychowhury an M. Maharbiz Discussion 2A Secon-Orer Differential Equations Secon-orer ifferential equations are ifferential equations of
More informationOptimal CDMA Signatures: A Finite-Step Approach
Optimal CDMA Signatures: A Finite-Step Approach Joel A. Tropp Inst. for Comp. Engr. an Sci. (ICES) 1 University Station C000 Austin, TX 7871 jtropp@ices.utexas.eu Inerjit. S. Dhillon Dept. of Comp. Sci.
More informationA Second Time Dimension, Hidden in Plain Sight
A Secon Time Dimension, Hien in Plain Sight Brett A Collins. In this paper I postulate the existence of a secon time imension, making five imensions, three space imensions an two time imensions. I will
More informationMath 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 informationRelation between the propagator matrix of geodesic deviation and the second-order derivatives of the characteristic function
Journal of Electromagnetic Waves an Applications 203 Vol. 27 No. 3 589 60 http://x.oi.org/0.080/0920507.203.808595 Relation between the propagator matrix of geoesic eviation an the secon-orer erivatives
More informationCONSERVATION PROPERTIES OF SMOOTHED PARTICLE HYDRODYNAMICS APPLIED TO THE SHALLOW WATER EQUATIONS
BIT 0006-3835/00/4004-0001 $15.00 200?, Vol.??, No.??, pp.?????? c Swets & Zeitlinger CONSERVATION PROPERTIES OF SMOOTHE PARTICLE HYROYNAMICS APPLIE TO THE SHALLOW WATER EQUATIONS JASON FRANK 1 an SEBASTIAN
More informationCharacteristic classes of vector bundles
Characteristic classes of vector bunles Yoshinori Hashimoto 1 Introuction Let be a smooth, connecte, compact manifol of imension n without bounary, an p : E be a real or complex vector bunle of rank k
More informationFinal 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 informationON THE MEANING OF LORENTZ COVARIANCE
Founations of Physics Letters 17 (2004) pp. 479 496. ON THE MEANING OF LORENTZ COVARIANCE László E. Szabó Theoretical Physics Research Group of the Hungarian Acaemy of Sciences Department of History an
More informationSources and Sinks of Available Potential Energy in a Moist Atmosphere. Olivier Pauluis 1. Courant Institute of Mathematical Sciences
Sources an Sinks of Available Potential Energy in a Moist Atmosphere Olivier Pauluis 1 Courant Institute of Mathematical Sciences New York University Submitte to the Journal of the Atmospheric Sciences
More informationII. First variation of functionals
II. First variation of functionals The erivative of a function being zero is a necessary conition for the etremum of that function in orinary calculus. Let us now tackle the question of the equivalent
More informationRobust 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 information2 The governing equations. 3 Statistical description of turbulence. 4 Turbulence modeling. 5 Turbulent wall bounded flows
1 The turbulence fact : Definition, observations an universal features of turbulence 2 The governing equations PART VII Homogeneous Shear Flows 3 Statistical escription of turbulence 4 Turbulence moeling
More informationExam 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 informationLagrangian and Hamiltonian Dynamics
Lagrangian an Hamiltonian Dynamics Volker Perlick (Lancaster University) Lecture 1 The Passage from Newtonian to Lagrangian Dynamics (Cockcroft Institute, 22 February 2010) Subjects covere Lecture 2: Discussion
More informationTable of Common Derivatives By David Abraham
Prouct an Quotient Rules: Table of Common Derivatives By Davi Abraham [ f ( g( ] = [ f ( ] g( + f ( [ g( ] f ( = g( [ f ( ] g( g( f ( [ g( ] Trigonometric Functions: sin( = cos( cos( = sin( tan( = sec
More informationEntanglement is not very useful for estimating multiple phases
PHYSICAL REVIEW A 70, 032310 (2004) Entanglement is not very useful for estimating multiple phases Manuel A. Ballester* Department of Mathematics, University of Utrecht, Box 80010, 3508 TA Utrecht, The
More informationu t v t v t c a u t b a v t u t v t b a
Nonlinear Dynamical Systems In orer to iscuss nonlinear ynamical systems, we must first consier linear ynamical systems. Linear ynamical systems are just systems of linear equations like we have been stuying
More informationSemiclassical analysis of long-wavelength multiphoton processes: The Rydberg atom
PHYSICAL REVIEW A 69, 063409 (2004) Semiclassical analysis of long-wavelength multiphoton processes: The Ryberg atom Luz V. Vela-Arevalo* an Ronal F. Fox Center for Nonlinear Sciences an School of Physics,
More informationAll s Well That Ends Well: Supplementary Proofs
All s Well That Ens Well: Guarantee Resolution of Simultaneous Rigi Boy Impact 1:1 All s Well That Ens Well: Supplementary Proofs This ocument complements the paper All s Well That Ens Well: Guarantee
More information1. The electron volt is a measure of (A) charge (B) energy (C) impulse (D) momentum (E) velocity
AP Physics Multiple Choice Practice Electrostatics 1. The electron volt is a measure of (A) charge (B) energy (C) impulse (D) momentum (E) velocity. A soli conucting sphere is given a positive charge Q.
More informationLinear Algebra- Review And Beyond. Lecture 3
Linear Algebra- Review An Beyon Lecture 3 This lecture gives a wie range of materials relate to matrix. Matrix is the core of linear algebra, an it s useful in many other fiels. 1 Matrix Matrix is the
More informationCalculus and optimization
Calculus an optimization These notes essentially correspon to mathematical appenix 2 in the text. 1 Functions of a single variable Now that we have e ne functions we turn our attention to calculus. A function
More informationSimple Derivation of the Lindblad Equation
Simple Derivation of the Linbla Equation Philip Pearle - arxiv:120.2016v1 10-apr 2012 April 10,2012 Abstract The Linbla equation is an evolution equation for the ensity matrix in quantum theory. It is
More informationStrength Analysis of CFRP Composite Material Considering Multiple Fracture Modes
5--XXXX Strength Analysis of CFRP Composite Material Consiering Multiple Fracture Moes Author, co-author (Do NOT enter this information. It will be pulle from participant tab in MyTechZone) Affiliation
More informationPort-Hamiltonian systems: an introductory survey
Port-Hamiltonian systems: an introuctory survey Arjan van er Schaft Abstract. The theory of port-hamiltonian systems provies a framework for the geometric escription of network moels of physical systems.
More informationWitten s Proof of Morse Inequalities
Witten s Proof of Morse Inequalities by Igor Prokhorenkov Let M be a smooth, compact, oriente manifol with imension n. A Morse function is a smooth function f : M R such that all of its critical points
More informationLectures - 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 informationJUST THE MATHS UNIT NUMBER DIFFERENTIATION 2 (Rates of change) A.J.Hobson
JUST THE MATHS UNIT NUMBER 10.2 DIFFERENTIATION 2 (Rates of change) by A.J.Hobson 10.2.1 Introuction 10.2.2 Average rates of change 10.2.3 Instantaneous rates of change 10.2.4 Derivatives 10.2.5 Exercises
More informationApplications of First Order Equations
Applications of First Orer Equations Viscous Friction Consier a small mass that has been roppe into a thin vertical tube of viscous flui lie oil. The mass falls, ue to the force of gravity, but falls more
More informationCHARACTERISTICS OF A DYNAMIC PRESSURE GENERATOR BASED ON LOUDSPEAKERS. Jože Kutin *, Ivan Bajsić
Sensors an Actuators A: Physical 168 (211) 149-154 oi: 1.116/j.sna.211..7 211 Elsevier B.V. CHARACTERISTICS OF A DYNAMIC PRESSURE GENERATOR BASED ON LOUDSPEAKERS Jože Kutin *, Ivan Bajsić Laboratory of
More informationOptimal Variable-Structure Control Tracking of Spacecraft Maneuvers
Optimal Variable-Structure Control racking of Spacecraft Maneuvers John L. Crassiis 1 Srinivas R. Vaali F. Lanis Markley 3 Introuction In recent years, much effort has been evote to the close-loop esign
More information