Energy behaviour of the Boris method for charged-particle dynamics

Size: px
Start display at page:

Download "Energy behaviour of the Boris method for charged-particle dynamics"

Transcription

1 Version of 25 April 218 Energy behaviour of the Boris metho for charge-particle ynamics Ernst Hairer 1, Christian Lubich 2 Abstract The Boris algorithm is a wiely use numerical integrator for the motion of particles in a magnetic fiel. This article proves near-conservation of energy over very long times in the special cases where the magnetic fiel is constant or the electric potential is quaratic. When none of these assumptions is satisfie, it is illustrate by numerical examples that the numerical energy can have a linear rift or its error can behave like a ranom walk. If the system has a rotational symmetry an the magnetic fiel is constant, then also the momentum is approximately preserve over very long times, but in a spatially varying magnetic fiel this is generally not satisfie. Keywors. Boris algorithm, charge particle, magnetic fiel, energy conservation, backwar error analysis, moifie ifferential equation. Mathematics Subject Classification (21): 65L6, 65P1, 78A35, 78M25 1 Dept. e Mathématiques, Univ. e Genève, CH-1211 Genève 24, Switzerlan, Ernst.Hairer@unige.ch 2 Mathematisches Institut, Univ. Tübingen, D-7276 Tübingen, Germany, Lubich@na.uni-tuebingen.e

2 2 E. Hairer, Ch. Lubich 1 Introuction For a particle with position x(t) R 3 moving in an electro-magnetic fiel, Newton s secon law together with Lorentz s force equation gives the secon orer ifferential equation (assuming suitable units) ẍ = ẋ B(x) + F (x). (1.1) Here, F (x) = U(x) is an electric fiel with the scalar potential U(x), an B(x) = A(x) is a magnetic fiel with the vector potential A(x) R 3. We assume throughout this paper that the forces are smooth functions of x. Denoting by v = ẋ the velocity of the particle, the energy is given by E(x, v) = 1 2 v 2 + U(x) (1.2) an it is conserve along solutions of (1.1). The simplest iscretization of (1.1) is the Boris metho [1] x n+1 2x n + x n 1 h 2 = x n+1 x n 1 2h B(x n ) U(x n ). (1.3) It is a symmetric, secon-orer numerical integrator. Its popularity is mostly ue to the fact that it is essentially explicit an has shown a goo long-time behaviour in many examples. It just requires the solution of a 3-imensional linear system which can be efficiently solve by a Roriguez formula. In the absence of the magnetic fiel, it reuces to the Störmer Verlet scheme (see [5, Section I.1.4] or [4]). The two-step formulation (1.3) is very sensitive to roun-off errors. For a practical implementation one introuces a velocity approximation for the ifference x n+1 x n, so that the Boris metho becomes x n+1 = x n + h v n+1/2 v n+1/2 = v n 1/2 + h v n B(x n ) h U(x n ), (1.4) where v n = 1 2 (v n+1/2 + v n 1/2 ) = 1 2h (x n+1 x n 1 ) is taken as the velocity approximation at the gri points. Given the initial values (x, v ), the metho is starte with v 1/2 = v + h 2 v B(x ) h 2 U(x ). It is known from [9] that the map (x n, v n 1/2 ) (x n+1, v n+1/2 ) is volumepreserving. Moreover, if the magnetic fiel B is constant, then with the momenta p n = v n + A(x n ), the map (x n, p n ) (x n+1, p n+1 ) is symplectic. This follows from the fact that the Boris metho is a variational integrator if an only if B is constant [2]. In Section 2 we escribe the backwar error analysis (moifie ifferential equation) for the Boris metho. We use this to show long-time nearconservation of the energy for two particular cases: if the magnetic fiel B is constant (Section 3), if the electric potential U is quaratic (Section 4).

3 Energy behaviour of the Boris metho for charge-particle ynamics 3 In Section 5 we then illustrate by numerical experiments that in the general situation the numerical energy can have a linear rift or its error can behave like a ranom walk. In Section 6 we iscuss the long-time near-conservation of angular momentum for systems with a rotational symmetry, which hols for constant B, but not in general. While we explain here that the Boris metho, espite some remarkable properties, is not fully satisfactory with regar to energy an momentum conservation (unless the magnetic fiel is constant), we mention that recently several classes of explicit methos for (1.1) were evelope that have longtime near-conservation of energy an momentum also for general non-constant magnetic fiels [3,7,1,11]. 2 Backwar error analysis The iea of backwar error analysis consists of searching for a moifie ifferential equation (as a formal series in powers of h) such that its solution y(t) formally satisfies y(nh) = x n, where x n represents the numerical solution obtaine by the Boris algorithm. Such a function has to satisfy y(t + h) 2y(t) + y(t h) y(t + h) y(t h) h 2 = B ( y(t) ) U ( y(t) ). 2h Expaning all appearing functions into powers of h yiels (omitting the obvious argument t) ÿ + h2... y +... = 12 (ẏ + h2... ) y +... B(y) U(y). (2.1) 6 For h =, the equation reuces to (1.1). The thir an higher erivatives can be recursively eliminate by repeately ifferentiating the equation an setting h to. This then gives the moifie ifferential equation, which is a secon-orer ifferential equation whose right-han sie is a formal series in even powers of the step size h with coefficient functions that epen on (y, ẏ): ÿ = ẏ B(y) U(y) + h 2 F 2 (y, ẏ) + h 4 F 4 (y, ẏ) To get a system of first orer moifie ifferential equations that is consistent with (1.4) we introuce the velocity approximation w(t) by y(t + h) y(t h) = 2h w(t), so that formally w(nh) = v n. Expaning into powers of h yiels the relation w = ẏ + h2... y + h4 3! 5! y(5) (2.2) The thir an higher erivatives of y can be expresse with the help of (2.1) in terms of (y, ẏ). This then permits us to express ẏ in terms of (y, w).

4 4 E. Hairer, Ch. Lubich Taking the inner prouct of (2.1) with ẏ or with w, we will prove in the next two sections that the Boris metho nearly preserves the energy over very long times if B is constant or if U is quaratic, as state in the following theorem. Theorem 2.1 Let the magnetic fiel B(x) an the scalar potential U(x) be arbitrarily ifferentiable functions of x, an suppose that the numerical solution (x n, v n ) of the Boris metho stays in a compact set that is inepenent of the step size h. In the case that one of the following two conitions is satisfie: the magnetic fiel B(x) = B is constant, or the scalar potential U(x) = 1 2 x Qx + q x is quaratic, then for arbitrary truncation number N 2, the eviation of the energy E(x, v) = 1 2 v v + U(x) along the numerical solution is boune by E(x n, v n ) E(x, v ) C N h 2 for nh h N, (2.3) where C N is inepenent of n an h as long as nh h N. Remark 2.1 If the level sets of the energy E(x, v) are compact, then the energy boun ensures, via an inuction argument, that the numerical solution of the Boris metho stays in a fixe compact set over times nh h N : if (2.3) hols true for n, then the numerical solution at step n + 1 has a istance to the energy surface of at most O(h) an hence stays in a compact set, so that by Theorem 2.1 the boun (2.3) hols also for n + 1 as long as (n + 1)h h N. 3 Moifie energy constant magnetic fiel To prove near-conservation of energy for the Störmer Verlet metho (in the absence of the magnetic fiel), one takes the scalar prouct of (2.1) with ẏ an thus fins a moifie energy that is close to E(x, v) [4]. In the present situation, this proceure yiels the following result. Theorem 3.1 There exist h-inepenent functions E 2j (x, v) such that the function E h (x, v) = E(x, v) + h 2 E 2 (x, v) + h 4 E 4 (x, v) +..., truncate at the O(h N ) term, satisfies t E h(y, ẏ) = h 2 ẏ (( 1... ) ) y + h2 3! 5! y(5) +... B(y) + O(h N ) (3.1) along solutions of the moifie ifferential equation (2.1). Proof Multiplie with ẏ T, even-orer erivatives of y give a total erivative: ẏ T y (2m) = t ( ẏ T y (2m 1) ÿ T y (2m 2) +... (y (m 1) ) T y (m+1) ± 1 2 (y(m) ) T y (m)).

5 Energy behaviour of the Boris metho for charge-particle ynamics 5 Multiplication of (2.1) with ẏ therefore yiels ( 1 2ẏ ẏ + U(y) + h2 (ẏ... y 1 2ÿ ÿ ) ) +... = h2 t 12 6 ẏ (... ) y B(y) The fact that ẏ is orthogonal to ẏ B(y) is use on the right-han sie. Expressing secon an higher erivatives of y with the help of the moifie ifferential equation proves the statement of the theorem. Corollary 3.1 If the magnetic fiel B(x) = B is constant, there exist h- inepenent functions Ẽ2j(x, v), such that the function Ẽ h (x, v) = E(x, v) + h 2 Ẽ 2 (x, v) + h 4 Ẽ 4 (x, v) +..., truncate at the O(h N ) term, satisfies tẽh(y, ẏ) = O(h N ) (3.2) along solutions of the moifie ifferential equation (2.1). Proof This follows from Theorem 3.1, because the expression ẏ ( y (k) B ) can be written as a total erivative for o values k = 2m + 1, namely as ( ẏ ( y (2m) B ) ÿ ( y (2m 1) B ) + ± (y (m 1) ) ( y (m+1) B )), t since (y (m) ) ( y (m) B ) =. This total erivative can be move to the other sie of (3.1) to obtain (3.2). If the numerical solution stays in a compact set that is inepenent of h, then Corollary 3.1 implies the long-time near-conservation of energy (2.3) by the stanar argument of writing the eviation of the moifie energy as a telescoping sum, Ẽ h (x n, v n ) Ẽh(x, v ) = n (Ẽh (x j, v j ) Ẽh(x j 1, v j 1 ) ), j=1 where each term in the sum is of size O(h N+1 ), uniformly for (x j, v j ) in the compact set. Alternatively to this proof of long-time near-conservation of energy in the case of constant B, (2.3) follows also from the known theory of symplectic integrators, e.g. [5, Chap. IX], since the Boris metho is known to be symplectic in the case of constant B.

6 6 E. Hairer, Ch. Lubich 4 Moifie energy quaratic electric potential Instea of ẏ, the equation (2.1) is now pre-multiplie with the expression in front of B(y). This implies that the term with the magnetic fiel isappears. Theorem 4.1 There exist h-inepenent functions E 2j (x, v) (ifferent from those of the previous section), such that the function E h (x, v) = E(x, v) + h 2 E 2 (x, v) + h 4 E 4 (x, v) +..., truncate at the O(h N ) term, satisfies t E h(y, ẏ) = h 2( 1... ) y + h2 3! 5! y(5) +... U(y) + O(h N ) (4.1) along solutions of the moifie ifferential equation (2.1). Proof The proof is similar to that of Theorem 3.1. One uses the fact that the scalar prouct y (k) y (l) is a total ifferential whenever k + l is o. Corollary 4.1 If the scalar potential is quaratic, U(x) = 1 2 x Qx+q x with a symmetric matrix Q, then there exist h-inepenent functions Ê2j(x, v) such that the function Ê h (x, v) = E(x, v) + h 2 Ê 2 (x, v) + h 4 Ê 4 (x, v) +..., truncate at the O(h N ) term, satisfies têh(y, ẏ) = O(h N ) (4.2) along solutions of the moifie ifferential equation (2.1). Proof This follows from Theorem 4.1, because the expression y (k) U(y) = y (k) (Qy + q) can be written as a total ifferential for o values of k. This result shows that for a quaratic potential U(x) = 1 2 x Qx + q x the energy is nearly preserve inepenently of the form of the magnetic fiel B(x), with the same relation as in (2.3). An even stronger result hols. Theorem 4.2 Let the scalar potential be quaratic, U(x) = 1 2 x Qx+q x with a symmetric matrix Q. Then, for every vector fiel B(x), the Boris metho (1.4) exactly conserves the iscrete moifie energy in the sense that E h (x, v) = 1 2 vt v + U(x) h 2 vt U(x) E h (x n+1, v n+1/2 ) = E h (x n, v n 1/2 ).

7 Energy behaviour of the Boris metho for charge-particle ynamics 7 Proof Taking the scalar prouct of the lower relation of (1.4) with v n = (v n+1/2 + v n 1/2 )/2 yiels 1 2 v n+1/2 v n+1/2 1 2 v n 1/2 v n 1/2 = h 2 (v n+1/2 + v n 1/2 ) (Qx n + q). Aing the ientity U(x n+1 ) U(x n ) = 1 2 x n+1qx n x n Qx n + q (x n+1 x n ) 1 ) = hvn+1/2( 2 Q (x n+1 + x n ) + q an observing that the terms with hvn+1/2 Qx n cancel, this then proves the statement of the theorem. Remark 4.1 An interesting example (penning trap with asymmetric magnetic fiel), for which the Boris algorithm shows an unboune energy, is given in [8] (see also [7]) by ( ) U(x) = 5 x x x 2 3, B(x) = 1 1/3 x 2 x x 1 + x 3 x 2 x 1 with initial values x() = ( 1/3,, 1/2 ), v() = (, 1, ). Since the potential U(x) is quaratic, Theorem 4.2 applies. This shows that the energy can be unboune only if the numerical solution oes not stay in a compact set. Note that the level sets of the energy E(x, v) are not compact for this example. 5 Numerical experiments This section stuies the long-time behaviour of the numerical energy in the situation where the electric potential is non-quaratic an the magnetic fiel is non-constant. Inspire by the work [6], where a symmetric, non-symplectic, but volume-preserving integrator for molecular ynamics simulations is stuie, we expect that the following two situations can arise: a linear energy-rift of size O(h 2 t); a ranom walk behaviour for the error of the numerical energy. Before passing to the numerical experiments we write the moifie energies of Sections 3 an 4 in terms of y an w. We then have formally x n = y(nh) an v n = w(nh), where (x n, v n ) is the numerical solution obtaine by (1.4). For this we use the relation (2.2) connecting w with ẏ. We have E(y, ẏ) = E(y, w) + O(h 2 ). As a consequence of Theorems 3.1 an 4.1 the solution ( y(t), w(t) ) of the moifie ifferential equation is seen to satisfy ( ) E(y, w) + h 2 F (y, w) = h 2 G(y, w) + O(h 4 ). (5.1) t

8 8 E. Hairer, Ch. Lubich h 2 step size h =.1 Ten = 3 h 2 step size h =.2 Ten = 3 Fig. 5.1 Energy error E(x n, v n) E(x, v ) along numerical solution, for Example 5.1 In the following numerical experiments we plot E(x n, v n ). For both examples of this section we consier the scalar potential U(x) = x 3 1 x x4 1 + x x 4 3 (5.2) an initial values x() = (., 1.,.1), v() = (.9,.55..3). (5.3) The quartic terms imply that the level sets of the energy are compact, so that the exact solution of the problem exists an remains boune for all times. Example 5.1 (Linear rift in the energy) In aition to the scalar potential (5.2) an the initial values (5.3) we consier the magnetic fiel B(x) = 1 3 x 2 x x 2 2 x 1 x x 2 2 = x x 2 2. (5.4) We apply the Boris algorithm in its stabilize form (1.4) with step sizes h =.1 an h =.2. The error in the energy E(x n, v n ) E(x, v ) along the numerical solution is plotte in Figure 5.1 as a function of time. The vertical axis is scale by h 2. Since the figures for both step sizes are similar, we conclue that there is a linear rift of slope O(h 2 ) in the numerical energy, which is superpose by high oscillations of size O(h 2 ). This rift in the energy is somewhat expecte. Integrating the relation (5.1) shows that, in general, we have a linear rift boune by th 2 M, where M is an upper boun of G(y, w). The term h 2 F (y, w) gives rise to boune, high oscillations of size O(h 2 ).

9 Energy behaviour of the Boris metho for charge-particle ynamics h 2 step size h =.1 Ten = 3 h 2 step size h =.2 Ten = 3 Fig. 5.2 Energy error E(x n, v n) E(x, v ) along numerical solution, for Example 5.2 Example 5.2 (Ranom walk behaviour of the numerical energy) This time we consier the magnetic fiel B(x) = 1 x 2 3 x 2 2 x 2 3 x 2 1 = 1 x 2 x 3 x 1 + x 3. (5.5) 4 2 x 2 2 x 2 1 x 2 x 1 in aition to (5.2) an (5.3). We apply the Boris algorithm (1.4) with step sizes h =.1 an h =.2 on an interval of length T en = 3. To better appreciate the ranom walk behaviour, we compute the numerical solution for initial values, where v 3 () is replace by v 3 () + θ1 13. Here, θ is ranomly chosen in the interval [, 1]. Figure 5.2 shows the energy error of 41 trajectories. Thick lines inicate average an variance taken over 11 trajectories. This behaviour can be explaine as in [6]. Let us assume that the solution of the moifie ifferential equation is ergoic on an invariant set A with respect to an invariant measure µ. Then we have 1 lim t t t G ( y(s), w(s) ) s = A G(x, v) µ ( (x, v) ) for the function G(x, v) of (5.1). If the integral to the right is non-zero, we will have a linear rift of size O(th 2 ). However, if this integral vanishes, the error of the moifie energy will behave like a ranom walk. In aition to the O(h 2 ) term h 2 F (x, v) of (5.1) there will be a rift of size t h 2. 6 Momentum If the scalar an vector potentials have the invariance properties U(e τs x) = U(x) an e τs A(e τs x) = A(x) for all real τ (6.1)

10 1 E. Hairer, Ch. Lubich with a skew-symmetric matrix S, then the momentum M(x, v) = ( v + A(x) ) Sx (6.2) is conserve along solutions of the ifferential equation (1.1). This can be shown by scalarly multiplying (1.1) with Sx an noting that the skew-symmetry of S yiels x Sẍ = t (xt Sẋ) an the invariance properties (6.1) imply S U(x) = an x S(ẋ B(x)) = t (x SA(x)). Theorem 6.1 If the vector an scalar potentials have the invariance properties (6.1), then there exist h-inepenent functions M 2j (x, v) such that the function M h (x, v) = M(x, v) + h 2 M 2 (x, v) + h 4 M 4 (x, v) +..., truncate at the O(h N ) term, satisfies (( 1 t M h(y, ẏ) = h 2 y... ) ) S y + h2 3! 5! y(5) +... B(y) + O(h N ) (6.3) along solutions of the moifie ifferential equation (2.1). Proof We multiply (2.1) with y S an note that y S y (k) can be written as a total ifferential for even values of k, an y S U(y) =. This yiels the state result in the same way as in Theorem 3.1. When B(x) = B oes not epen on x, then A(x) = 1 2x B (up to a constant vector) an the above invariance properties are satisfie if S is the skew-symmetric matrix that emboies the cross prouct with B, i.e., Sv = v B, an U is invariant uner rotations with the axis B, so that U(x) B = for all x. The conserve momentum then reas M(x, v) = v (x B) 1 2 x B 2. Corollary 6.1 If the magnetic fiel B(x) = B is constant an U(x) B = for all x, then there exist h-inepenent functions M 2j (x, v), such that the function M h (x, v) = M(x, v) + h 2 M2 (x, v) + h 4 M4 (x, v) +..., truncate at the O(h N ) term, satisfies t M h (y, ẏ) = O(h N ) (6.4) along solutions of the moifie ifferential equation (2.1). Proof This follows from Theorem 6.1, since for constant B we have with Sy = y B that (y B) (y (k) B) can be written as a total ifferential for o values of k.

11 Energy behaviour of the Boris metho for charge-particle ynamics 11 If the numerical solution stays in a compact set that is inepenent of h, then Corollary 3.1 implies, for arbitrary positive integers N, that M(x n, v n ) = M(x, v ) + O(h 2 ) for nh Ch N, (6.5) where the constant symbolize by the O-notation is inepenent of n an h with nh Ch N. Acknowlegement. We thank our colleague Martin Ganer for rawing our attention to the long-time behaviour of the Boris algorithm. The research for this article has been partially supporte by the Fons National Suisse, Project No References 1. J. P. Boris. Relativistic plasma simulation-optimization of a hybri coe. Proceeing of Fourth Conference on Numerical Simulations of Plasmas, pages 3 67, November C. L. Ellison, J. W. Burby, an H. Qin. Comment on Symplectic integration of magnetic systems : A proof that the Boris algorithm is not variational. J. Comput. Phys., 31: , E. Hairer an C. Lubich. Symmetric multistep methos for charge particle ynamics. SMAI J. Comput. Math., 3:25 218, E. Hairer, C. Lubich, an G. Wanner. Geometric numerical integration illustrate by the Störmer Verlet metho. Acta Numerica, 12:399 45, E. Hairer, C. Lubich, an G. Wanner. Geometric Numerical Integration. Structure- Preserving Algorithms for Orinary Differential Equations. Springer Series in Computational Mathematics 31. Springer-Verlag, Berlin, 2n eition, E. Hairer, R.I. McLachlan, an R.D. Skeel. On energy conservation of the simplifie Takahashi Imaa metho. M2AN Math. Moel. Numer. Anal., 43(4): , Yang He, Zhaoqi Zhou, Yajuan Sun, Jian Liu, an Hong Qin. Explicit K-symplectic algorithms for charge particle ynamics. Phys. Lett. A, 381(6): , C. Knapp, A. Kenl, A. Koskela, an A. Ostermann. Splitting methos for time integration of trajectories in combine electric an magnetic fiels. Phys. Rev. E, 92:6331, Dec H. Qin, S. Zhang, J. Xiao, J. Liu, Y. Sun, an W. M. Tang. Why is Boris algorithm so goo? Physics of Plasmas, 2(8): , M. Tao. Explicit high-orer symplectic integrators for charge particles in general electromagnetic fiels. J. Comput. Phys., 327: , Ruili Zhang, Hong Qin, Yifa Tang, Jian Liu, Yang He, an Jianyuan Xiao. Explicit symplectic algorithms base on generating functions for charge particle ynamics. Physical Review E, 94(1):1325, 216.

Symmetric multistep methods for charged-particle dynamics

Symmetric multistep methods for charged-particle dynamics Version of 12 September 2017 Symmetric multistep methods for charged-particle dynamics Ernst Hairer 1, Christian Lubich 2 Abstract A class of explicit symmetric multistep methods is proposed for integrating

More information

the solution of ()-(), an ecient numerical treatment requires variable steps. An alternative approach is to apply a time transformation of the form t

the solution of ()-(), an ecient numerical treatment requires variable steps. An alternative approach is to apply a time transformation of the form t Asymptotic Error Analysis of the Aaptive Verlet Metho Stephane Cirilli, Ernst Hairer Beneict Leimkuhler y May 3, 999 Abstract The Aaptive Verlet metho [7] an variants [6] are time-reversible schemes for

More information

Lie symmetry and Mei conservation law of continuum system

Lie symmetry and Mei conservation law of continuum system Chin. Phys. B Vol. 20, No. 2 20 020 Lie symmetry an Mei conservation law of continuum system Shi Shen-Yang an Fu Jing-Li Department of Physics, Zhejiang Sci-Tech University, Hangzhou 3008, China Receive

More information

Lecture 2 Lagrangian formulation of classical mechanics Mechanics

Lecture 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 information

Lagrangian and Hamiltonian Dynamics

Lagrangian 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 information

Introduction to the Vlasov-Poisson system

Introduction 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 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

Switching Time Optimization in Discretized Hybrid Dynamical Systems

Switching Time Optimization in Discretized Hybrid Dynamical Systems Switching Time Optimization in Discretize Hybri Dynamical Systems Kathrin Flaßkamp, To Murphey, an Sina Ober-Blöbaum Abstract Switching time optimization (STO) arises in systems that have a finite set

More information

19 Eigenvalues, Eigenvectors, Ordinary Differential Equations, and Control

19 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 information

Least-Squares Regression on Sparse Spaces

Least-Squares Regression on Sparse Spaces Least-Squares Regression on Sparse Spaces Yuri Grinberg, Mahi Milani Far, Joelle Pineau School of Computer Science McGill University Montreal, Canaa {ygrinb,mmilan1,jpineau}@cs.mcgill.ca 1 Introuction

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

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

Mathematical Review Problems

Mathematical Review Problems Fall 6 Louis Scuiero Mathematical Review Problems I. Polynomial Equations an Graphs (Barrante--Chap. ). First egree equation an graph y f() x mx b where m is the slope of the line an b is the line's intercept

More information

2.1 Derivatives and Rates of Change

2.1 Derivatives and Rates of Change 1a 1b 2.1 Derivatives an Rates of Change Tangent Lines Example. Consier y f x x 2 0 2 x-, 0 4 y-, f(x) axes, curve C Consier a smooth curve C. A line tangent to C at a point P both intersects C at P an

More information

Chapter 6: Energy-Momentum Tensors

Chapter 6: Energy-Momentum Tensors 49 Chapter 6: Energy-Momentum Tensors This chapter outlines the general theory of energy an momentum conservation in terms of energy-momentum tensors, then applies these ieas to the case of Bohm's moel.

More information

A new proof of the sharpness of the phase transition for Bernoulli percolation on Z d

A new proof of the sharpness of the phase transition for Bernoulli percolation on Z d A new proof of the sharpness of the phase transition for Bernoulli percolation on Z Hugo Duminil-Copin an Vincent Tassion October 8, 205 Abstract We provie a new proof of the sharpness of the phase transition

More information

Table of Common Derivatives By David Abraham

Table 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 information

θ x = f ( x,t) could be written as

θ x = f ( x,t) could be written as 9. Higher orer PDEs as systems of first-orer PDEs. Hyperbolic systems. For PDEs, as for ODEs, we may reuce the orer by efining new epenent variables. For example, in the case of the wave equation, (1)

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

Optimization of a point-mass walking model using direct collocation and sequential quadratic programming

Optimization of a point-mass walking model using direct collocation and sequential quadratic programming Optimization of a point-mass walking moel using irect collocation an sequential quaratic programming Chris Dembia June 5, 5 Telescoping actuator y Stance leg Point-mass boy m (x,y) Swing leg x Leg uring

More information

4. Important theorems in quantum mechanics

4. 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 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

Conservation Laws. Chapter Conservation of Energy

Conservation 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 information

arxiv: v1 [cond-mat.stat-mech] 9 Jan 2012

arxiv: 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 information

Lower Bounds for the Smoothed Number of Pareto optimal Solutions

Lower Bounds for the Smoothed Number of Pareto optimal Solutions Lower Bouns for the Smoothe Number of Pareto optimal Solutions Tobias Brunsch an Heiko Röglin Department of Computer Science, University of Bonn, Germany brunsch@cs.uni-bonn.e, heiko@roeglin.org Abstract.

More information

Survey Sampling. 1 Design-based Inference. Kosuke Imai Department of Politics, Princeton University. February 19, 2013

Survey 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 information

Time-of-Arrival Estimation in Non-Line-Of-Sight Environments

Time-of-Arrival Estimation in Non-Line-Of-Sight Environments 2 Conference on Information Sciences an Systems, The Johns Hopkins University, March 2, 2 Time-of-Arrival Estimation in Non-Line-Of-Sight Environments Sinan Gezici, Hisashi Kobayashi an H. Vincent Poor

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

How the potentials in different gauges yield the same retarded electric and magnetic fields

How the potentials in different gauges yield the same retarded electric and magnetic fields How the potentials in ifferent gauges yiel the same retare electric an magnetic fiels José A. Heras a Departamento e Física, E. S. F. M., Instituto Politécnico Nacional, México D. F. México an Department

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

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

Chapter 2 Lagrangian Modeling

Chapter 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 information

Lecture Introduction. 2 Examples of Measure Concentration. 3 The Johnson-Lindenstrauss Lemma. CS-621 Theory Gems November 28, 2012

Lecture 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 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

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

6 General properties of an autonomous system of two first order ODE

6 General properties of an autonomous system of two first order ODE 6 General properties of an autonomous system of two first orer ODE Here we embark on stuying the autonomous system of two first orer ifferential equations of the form ẋ 1 = f 1 (, x 2 ), ẋ 2 = f 2 (, x

More information

ELEC3114 Control Systems 1

ELEC3114 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 information

MARKO NEDELJKOV, DANIJELA RAJTER-ĆIRIĆ

MARKO NEDELJKOV, DANIJELA RAJTER-ĆIRIĆ GENERALIZED UNIFORMLY CONTINUOUS SEMIGROUPS AND SEMILINEAR HYPERBOLIC SYSTEMS WITH REGULARIZED DERIVATIVES MARKO NEDELJKOV, DANIJELA RAJTER-ĆIRIĆ Abstract. We aopt the theory of uniformly continuous operator

More information

Generalization of the persistent random walk to dimensions greater than 1

Generalization 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 information

Energy Splitting Theorems for Materials with Memory

Energy Splitting Theorems for Materials with Memory J Elast 2010 101: 59 67 DOI 10.1007/s10659-010-9244-y Energy Splitting Theorems for Materials with Memory Antonino Favata Paolo Poio-Guiugli Giuseppe Tomassetti Receive: 29 July 2009 / Publishe online:

More information

Optimized Schwarz Methods with the Yin-Yang Grid for Shallow Water Equations

Optimized Schwarz Methods with the Yin-Yang Grid for Shallow Water Equations Optimize Schwarz Methos with the Yin-Yang Gri for Shallow Water Equations Abessama Qaouri Recherche en prévision numérique, Atmospheric Science an Technology Directorate, Environment Canaa, Dorval, Québec,

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

JUST THE MATHS UNIT NUMBER DIFFERENTIATION 2 (Rates of change) A.J.Hobson

JUST 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 information

NOTES 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 (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 information

Stable and compact finite difference schemes

Stable and compact finite difference schemes Center for Turbulence Research Annual Research Briefs 2006 2 Stable an compact finite ifference schemes By K. Mattsson, M. Svär AND M. Shoeybi. Motivation an objectives Compact secon erivatives have long

More information

. ISSN (print), (online) International Journal of Nonlinear Science Vol.6(2008) No.3,pp

. ISSN (print), (online) International Journal of Nonlinear Science Vol.6(2008) No.3,pp . ISSN 1749-3889 (print), 1749-3897 (online) International Journal of Nonlinear Science Vol.6(8) No.3,pp.195-1 A Bouneness Criterion for Fourth Orer Nonlinear Orinary Differential Equations with Delay

More information

FLUCTUATIONS IN THE NUMBER OF POINTS ON SMOOTH PLANE CURVES OVER FINITE FIELDS. 1. Introduction

FLUCTUATIONS IN THE NUMBER OF POINTS ON SMOOTH PLANE CURVES OVER FINITE FIELDS. 1. Introduction FLUCTUATIONS IN THE NUMBER OF POINTS ON SMOOTH PLANE CURVES OVER FINITE FIELDS ALINA BUCUR, CHANTAL DAVID, BROOKE FEIGON, MATILDE LALÍN 1 Introuction In this note, we stuy the fluctuations in the number

More information

Numerical Integrator. Graphics

Numerical Integrator. Graphics 1 Introuction CS229 Dynamics Hanout The question of the week is how owe write a ynamic simulator for particles, rigi boies, or an articulate character such as a human figure?" In their SIGGRPH course notes,

More information

Agmon Kolmogorov Inequalities on l 2 (Z d )

Agmon Kolmogorov Inequalities on l 2 (Z d ) Journal of Mathematics Research; Vol. 6, No. ; 04 ISSN 96-9795 E-ISSN 96-9809 Publishe by Canaian Center of Science an Eucation Agmon Kolmogorov Inequalities on l (Z ) Arman Sahovic Mathematics Department,

More information

Math 300 Winter 2011 Advanced Boundary Value Problems I. Bessel s Equation and Bessel Functions

Math 300 Winter 2011 Advanced Boundary Value Problems I. Bessel s Equation and Bessel Functions Math 3 Winter 2 Avance Bounary Value Problems I Bessel s Equation an Bessel Functions Department of Mathematical an Statistical Sciences University of Alberta Bessel s Equation an Bessel Functions We use

More information

LATTICE-BASED D-OPTIMUM DESIGN FOR FOURIER REGRESSION

LATTICE-BASED D-OPTIMUM DESIGN FOR FOURIER REGRESSION The Annals of Statistics 1997, Vol. 25, No. 6, 2313 2327 LATTICE-BASED D-OPTIMUM DESIGN FOR FOURIER REGRESSION By Eva Riccomagno, 1 Rainer Schwabe 2 an Henry P. Wynn 1 University of Warwick, Technische

More information

An Optimal Algorithm for Bandit and Zero-Order Convex Optimization with Two-Point Feedback

An Optimal Algorithm for Bandit and Zero-Order Convex Optimization with Two-Point Feedback Journal of Machine Learning Research 8 07) - Submitte /6; Publishe 5/7 An Optimal Algorithm for Banit an Zero-Orer Convex Optimization with wo-point Feeback Oha Shamir Department of Computer Science an

More information

A Note on Exact Solutions to Linear Differential Equations by the Matrix Exponential

A 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 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

Approximate Reduction of Dynamical Systems

Approximate Reduction of Dynamical Systems Proceeings of the 4th IEEE Conference on Decision & Control Manchester Gran Hyatt Hotel San Diego, CA, USA, December 3-, 6 FrIP.7 Approximate Reuction of Dynamical Systems Paulo Tabuaa, Aaron D. Ames,

More information

Optimal Variable-Structure Control Tracking of Spacecraft Maneuvers

Optimal 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

APPROXIMATE SOLUTION FOR TRANSIENT HEAT TRANSFER IN STATIC TURBULENT HE II. B. Baudouy. CEA/Saclay, DSM/DAPNIA/STCM Gif-sur-Yvette Cedex, France

APPROXIMATE 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 information

A Modification of the Jarque-Bera Test. for Normality

A Modification of the Jarque-Bera Test. for Normality Int. J. Contemp. Math. Sciences, Vol. 8, 01, no. 17, 84-85 HIKARI Lt, www.m-hikari.com http://x.oi.org/10.1988/ijcms.01.9106 A Moification of the Jarque-Bera Test for Normality Moawa El-Fallah Ab El-Salam

More information

ALGEBRAIC AND ANALYTIC PROPERTIES OF ARITHMETIC FUNCTIONS

ALGEBRAIC AND ANALYTIC PROPERTIES OF ARITHMETIC FUNCTIONS ALGEBRAIC AND ANALYTIC PROPERTIES OF ARITHMETIC FUNCTIONS MARK SCHACHNER Abstract. When consiere as an algebraic space, the set of arithmetic functions equippe with the operations of pointwise aition an

More information

Computing Exact Confidence Coefficients of Simultaneous Confidence Intervals for Multinomial Proportions and their Functions

Computing Exact Confidence Coefficients of Simultaneous Confidence Intervals for Multinomial Proportions and their Functions Working Paper 2013:5 Department of Statistics Computing Exact Confience Coefficients of Simultaneous Confience Intervals for Multinomial Proportions an their Functions Shaobo Jin Working Paper 2013:5

More information

A simple model for the small-strain behaviour of soils

A simple model for the small-strain behaviour of soils A simple moel for the small-strain behaviour of soils José Jorge Naer Department of Structural an Geotechnical ngineering, Polytechnic School, University of São Paulo 05508-900, São Paulo, Brazil, e-mail:

More information

Abstract A nonlinear partial differential equation of the following form is considered:

Abstract A nonlinear partial differential equation of the following form is considered: M P E J Mathematical Physics Electronic Journal ISSN 86-6655 Volume 2, 26 Paper 5 Receive: May 3, 25, Revise: Sep, 26, Accepte: Oct 6, 26 Eitor: C.E. Wayne A Nonlinear Heat Equation with Temperature-Depenent

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

Approximate reduction of dynamic systems

Approximate reduction of dynamic systems Systems & Control Letters 57 2008 538 545 www.elsevier.com/locate/sysconle Approximate reuction of ynamic systems Paulo Tabuaa a,, Aaron D. Ames b, Agung Julius c, George J. Pappas c a Department of Electrical

More information

We G Model Reduction Approaches for Solution of Wave Equations for Multiple Frequencies

We G Model Reduction Approaches for Solution of Wave Equations for Multiple Frequencies We G15 5 Moel Reuction Approaches for Solution of Wave Equations for Multiple Frequencies M.Y. Zaslavsky (Schlumberger-Doll Research Center), R.F. Remis* (Delft University) & V.L. Druskin (Schlumberger-Doll

More information

Topic 7: Convergence of Random Variables

Topic 7: Convergence of Random Variables Topic 7: Convergence of Ranom Variables Course 003, 2016 Page 0 The Inference Problem So far, our starting point has been a given probability space (S, F, P). We now look at how to generate information

More information

Optimization of Geometries by Energy Minimization

Optimization of Geometries by Energy Minimization Optimization of Geometries by Energy Minimization by Tracy P. Hamilton Department of Chemistry University of Alabama at Birmingham Birmingham, AL 3594-140 hamilton@uab.eu Copyright Tracy P. Hamilton, 1997.

More information

ON THE OPTIMALITY SYSTEM FOR A 1 D EULER FLOW PROBLEM

ON THE OPTIMALITY SYSTEM FOR A 1 D EULER FLOW PROBLEM ON THE OPTIMALITY SYSTEM FOR A D EULER FLOW PROBLEM Eugene M. Cliff Matthias Heinkenschloss y Ajit R. Shenoy z Interisciplinary Center for Applie Mathematics Virginia Tech Blacksburg, Virginia 46 Abstract

More information

ON THE RIEMANN EXTENSION OF THE SCHWARZSCHILD METRICS

ON THE RIEMANN EXTENSION OF THE SCHWARZSCHILD METRICS ON THE RIEANN EXTENSION OF THE SCHWARZSCHILD ETRICS Valerii Dryuma arxiv:gr-qc/040415v1 30 Apr 004 Institute of athematics an Informatics, AS R, 5 Acaemiei Street, 08 Chisinau, olova, e-mail: valery@ryuma.com;

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

Dynamics of the synchronous machine

Dynamics of the synchronous machine ELEC0047 - Power system ynamics, control an stability Dynamics of the synchronous machine Thierry Van Cutsem t.vancutsem@ulg.ac.be www.montefiore.ulg.ac.be/~vct These slies follow those presente in course

More information

Tractability results for weighted Banach spaces of smooth functions

Tractability results for weighted Banach spaces of smooth functions Tractability results for weighte Banach spaces of smooth functions Markus Weimar Mathematisches Institut, Universität Jena Ernst-Abbe-Platz 2, 07740 Jena, Germany email: markus.weimar@uni-jena.e March

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

Adaptive Gain-Scheduled H Control of Linear Parameter-Varying Systems with Time-Delayed Elements

Adaptive Gain-Scheduled H Control of Linear Parameter-Varying Systems with Time-Delayed Elements Aaptive Gain-Scheule H Control of Linear Parameter-Varying Systems with ime-delaye Elements Yoshihiko Miyasato he Institute of Statistical Mathematics 4-6-7 Minami-Azabu, Minato-ku, okyo 6-8569, Japan

More information

PHYS 414 Problem Set 2: Turtles all the way down

PHYS 414 Problem Set 2: Turtles all the way down PHYS 414 Problem Set 2: Turtles all the way own This problem set explores the common structure of ynamical theories in statistical physics as you pass from one length an time scale to another. Brownian

More information

All s Well That Ends Well: Supplementary Proofs

All 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 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

arxiv: v1 [physics.class-ph] 20 Dec 2017

arxiv: v1 [physics.class-ph] 20 Dec 2017 arxiv:1712.07328v1 [physics.class-ph] 20 Dec 2017 Demystifying the constancy of the Ermakov-Lewis invariant for a time epenent oscillator T. Pamanabhan IUCAA, Post Bag 4, Ganeshkhin, Pune - 411 007, Inia.

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

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

Dot trajectories in the superposition of random screens: analysis and synthesis

Dot trajectories in the superposition of random screens: analysis and synthesis 1472 J. Opt. Soc. Am. A/ Vol. 21, No. 8/ August 2004 Isaac Amiror Dot trajectories in the superposition of ranom screens: analysis an synthesis Isaac Amiror Laboratoire e Systèmes Périphériques, Ecole

More information

ORDINARY DIFFERENTIAL EQUATIONS AND SINGULAR INTEGRALS. Gianluca Crippa

ORDINARY DIFFERENTIAL EQUATIONS AND SINGULAR INTEGRALS. Gianluca Crippa Manuscript submitte to AIMS Journals Volume X, Number 0X, XX 200X Website: http://aimsciences.org pp. X XX ORDINARY DIFFERENTIAL EQUATIONS AND SINGULAR INTEGRALS Gianluca Crippa Departement Mathematik

More information

Backward error analysis

Backward error analysis Backward error analysis Brynjulf Owren July 28, 2015 Introduction. The main source for these notes is the monograph by Hairer, Lubich and Wanner [2]. Consider ODEs in R d of the form ẏ = f(y), y(0) = y

More information

The canonical controllers and regular interconnection

The canonical controllers and regular interconnection Systems & Control Letters ( www.elsevier.com/locate/sysconle The canonical controllers an regular interconnection A.A. Julius a,, J.C. Willems b, M.N. Belur c, H.L. Trentelman a Department of Applie Mathematics,

More information

model considered before, but the prey obey logistic growth in the absence of predators. In

model considered before, but the prey obey logistic growth in the absence of predators. In 5.2. First Orer Systems of Differential Equations. Phase Portraits an Linearity. Section Objective(s): Moifie Preator-Prey Moel. Graphical Representations of Solutions. Phase Portraits. Vector Fiels an

More information

Introduction to Markov Processes

Introduction to Markov Processes Introuction to Markov Processes Connexions moule m44014 Zzis law Gustav) Meglicki, Jr Office of the VP for Information Technology Iniana University RCS: Section-2.tex,v 1.24 2012/12/21 18:03:08 gustav

More information

Witten s Proof of Morse Inequalities

Witten 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 information

Application of the homotopy perturbation method to a magneto-elastico-viscous fluid along a semi-infinite plate

Application of the homotopy perturbation method to a magneto-elastico-viscous fluid along a semi-infinite plate Freun Publishing House Lt., International Journal of Nonlinear Sciences & Numerical Simulation, (9), -, 9 Application of the homotopy perturbation metho to a magneto-elastico-viscous flui along a semi-infinite

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

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

CONSERVATION PROPERTIES OF SMOOTHED PARTICLE HYDRODYNAMICS APPLIED TO THE SHALLOW WATER EQUATIONS

CONSERVATION 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 information

ANALYSIS OF A GENERAL FAMILY OF REGULARIZED NAVIER-STOKES AND MHD MODELS

ANALYSIS OF A GENERAL FAMILY OF REGULARIZED NAVIER-STOKES AND MHD MODELS ANALYSIS OF A GENERAL FAMILY OF REGULARIZED NAVIER-STOKES AND MHD MODELS MICHAEL HOLST, EVELYN LUNASIN, AND GANTUMUR TSOGTGEREL ABSTRACT. We consier a general family of regularize Navier-Stokes an Magnetohyroynamics

More information

Experimental Robustness Study of a Second-Order Sliding Mode Controller

Experimental Robustness Study of a Second-Order Sliding Mode Controller Experimental Robustness Stuy of a Secon-Orer Sliing Moe Controller Anré Blom, Bram e Jager Einhoven University of Technology Department of Mechanical Engineering P.O. Box 513, 5600 MB Einhoven, The Netherlans

More information

SINGULAR PERTURBATION AND STATIONARY SOLUTIONS OF PARABOLIC EQUATIONS IN GAUSS-SOBOLEV SPACES

SINGULAR PERTURBATION AND STATIONARY SOLUTIONS OF PARABOLIC EQUATIONS IN GAUSS-SOBOLEV SPACES Communications on Stochastic Analysis Vol. 2, No. 2 (28) 289-36 Serials Publications www.serialspublications.com SINGULAR PERTURBATION AND STATIONARY SOLUTIONS OF PARABOLIC EQUATIONS IN GAUSS-SOBOLEV SPACES

More information

The continuity equation

The continuity equation Chapter 6 The continuity equation 61 The equation of continuity It is evient that in a certain region of space the matter entering it must be equal to the matter leaving it Let us consier an infinitesimal

More information

On the Inclined Curves in Galilean 4-Space

On the Inclined Curves in Galilean 4-Space Applie Mathematical Sciences Vol. 7 2013 no. 44 2193-2199 HIKARI Lt www.m-hikari.com On the Incline Curves in Galilean 4-Space Dae Won Yoon Department of Mathematics Eucation an RINS Gyeongsang National

More information

there is no special reason why the value of y should be fixed at y = 0.3. Any y such that

there is no special reason why the value of y should be fixed at y = 0.3. Any y such that 25. More on bivariate functions: partial erivatives integrals Although we sai that the graph of photosynthesis versus temperature in Lecture 16 is like a hill, in the real worl hills are three-imensional

More information

Conservation laws a simple application to the telegraph equation

Conservation laws a simple application to the telegraph equation J Comput Electron 2008 7: 47 51 DOI 10.1007/s10825-008-0250-2 Conservation laws a simple application to the telegraph equation Uwe Norbrock Reinhol Kienzler Publishe online: 1 May 2008 Springer Scienceusiness

More information

Sparse Reconstruction of Systems of Ordinary Differential Equations

Sparse Reconstruction of Systems of Ordinary Differential Equations Sparse Reconstruction of Systems of Orinary Differential Equations Manuel Mai a, Mark D. Shattuck b,c, Corey S. O Hern c,a,,e, a Department of Physics, Yale University, New Haven, Connecticut 06520, USA

More information