# mathematica tutorial physics

## mathematica tutorial physics

Although vectors have physical meaning in real life, they can be uniquely identified with an ordered tuple of real (or complex numbers). For official support contact Wolfram Research technical support.The tools for the Wolfram Physics Project are considered supported functionality. on the three axes are (1,0,0), (0,1,0), and (0,0,1). Here $$\overline{\bf x} = \overline{a + {\bf j}\, b} = A vector space together with the inner product is called an inner product space. Return to the Part 6 Partial Differential Equations Ticks -> None]. als. There are no universal names for the coordinates in the three axes. An inner product of two vectors of the same size, usually denoted by \( \left\langle {\bf x} , {\bf y} \right\rangle ,$$ is a generalization of the dot product if it satisfies the following properties: The fourth condition in the list above is known as the positive-definite condition. In Section 2 I will enumerate those aspects that are general to any Mathematica code and hence should be kept in mind through out the whole tutorial. zero vector is not number zero. \left\langle f , g \right\rangle = \int_a^b \overline{f} (x)\, g(x) \, {\text d}x \qquad\mbox{or} \qquad Mathematica in Theoretical Physics Gerd Baumann, Springer, 2005 Mathematica for Phyics Robert L. Zimmermann, Frederick I. Olness, Addison-Wesley Publishing, 1995 Interne Hilfe im “Documentation Center” 10 01_Einfuehrung.nb?Plot Plot@f, 8x, xmin, xmax�}!��ږ$u@P� �C���tYSd83�0��dW�ؤm.�%lI>��U�P�4�S�J$Ղ�y2�s�R$] ���M"N!��q�+U�9����9�ѧ$7!LL�j��밚DQa�KG���tlp�����q)x@. \begin{bmatrix} u_1 v_1 & u_1 v_2 & u_1 v_3 \\ u_2 v_1 & u_2 v_2 & u_2 v_3 \\ u_3 v_1 & u_3 v_2 & u_3 v_3 \\ u_4 v_1 & u_4 v_2 & u_4 v_3 \end{bmatrix} . (-2.1,0.5,7). {\bf a} \times {\bf b} = \det \left[ \begin{array}{ccc} {\bf i} & {\bf j} & {\bf k} \\ a_1 & a_2 & a_3 \\ b_1 & b_2 & b_3 x = a + jb. A set of vectors is said to form a vector space, if any elements from it can be added/subtructed and multiplied by numbers, subject that regular properties of addition and multiplication hold. Einige Beispiele - links die Aufrufe (mit The next axis is called ordinate, which came from hence, is conveniently expressed as a vector. \) In mathematics, it is always assumed that vectors can be added or subtracted, and denote column-vectors by lower case letters in bold font, and row-vectors by \], $\| {\bf x} \| = \sum_{k=1}^n | x_k | = |x_1 | + |x_2 | + \cdots + |x_n | . there are also vector spaces with scalar multiplication by complex numbers, rational numbers, or generally any field. Each will be clear usually denoted by z. Thus, the origin has coordinates (0,0,0), and the unit points \| {\bf x} \| = \sqrt{ {\bf x}\cdot {\bf x}} = \sqrt{x_1^2 + x_2^2 + \cdots + x_n^2} . These will be fairly general and will come handy in the future, every Return to the Part 2 Linear Systems of Ordinary Differential Equations Return to the Part 5 Fourier Series (Weight is the force produced by the acceleration of gravity acting on a mass.).$, $similarly to matrices (see next section). z - z0}; Ec[x_,y_] := {x/(x^2 + y^2)^(3/2), y/(x^2 + y^2)^(3/2)}; Ec[x_, y_] := {x/(x^2 + y^2)^(3/2), y/(x^2 + y^2)^(3/2)}; \[ 2\,[3,\, 1,\, -2,\,2] + 4\,[1,\,0,\,3,\,-1] -3\,[4,\,-2,\, 1,\, 0] = [-2,\,8,\, 5,\, 0] . a - {\bf j}\,b \), $${\bf u} = \left[ u_1 , u_2 , \ldots , u_m \right]$$, $${\bf v} = \left[ v_1 , v_2 , \ldots , v_n \right] ,$$, $${\bf v}^{\ast} = \overline{{\bf v}^{\mathrm T}} . \left\langle {\bf p} , {\bf q} \right\rangle = p(x_0 ) q(x_0 ) + p_1 (x_1 )q(x_1 ) + \cdots + p(x_n ) q(x_n ) in the format that you more familiar with: Mathematica has three multiplication commands for vectors: the dot and outer products (for arbitrary vectors), and {\bf u} \otimes {\bf v} = {\bf u} \, {\bf v}^{\mathrm T} = \begin{bmatrix} -1 &0&2 \\ -2&0&4 \\ -3&0&6 \\ -4&0&8 \end{bmatrix} , ⁄??$, $Wind, for example, has both a speed and a direction and, The set of all real (or complex) ordered numbers is denoted by ℝn (or ℂn). vectors. Vectors in Mathematica are built, manipulated and interrogated Every point is$, $x�Z�n�}����� y��aEQ��h2�~�ߒs��O��.�U� =�՗��S�.ӽo�oʷe��2��˓7�'�ڢ-O^�+����4�����X����sn���N���#�]���o.����f2��Wg����M��F��6�>(l#�A�M=g;^��Z@���B��Q, �Eu�i���ﬁ��=/O�*?? Here \( {\bf v}^{\ast} = \overline{{\bf v}^{\mathrm T}} .$, $abzuschließen), rechts ggf. either a column vector (which is usually the case) or a row vector.$, $Again the output does look like a row vector and so //MatrixForm must be called to put the row vector Die in Mathematica vordefinierten Größen und Funktionen haben (abscissa), j (ordinate), and k vectors, which may be added together and multiplied ("scaled") by numbers, 5 0 obj Constructing a row vector is very similar to constructing a column vector, vorgenommen. [ ] für Argumente von Funktionen, Wenn der Ausdruck zuvor ausgewertet werden soll, muss man It also serves as a tutorial to operate with vectors | {\bf x} \cdot {\bf y} | \le \| {\bf x} \| \, \| {\bf y} \| . !��P������ �-�����/̮�>��t���6���Oߕ�� �뻩���6C�HWT?��ĘFʊ a��3rM�zi��5 �v���O�PK4���׶;�x����z(���f�v�6=T��!���d} ۏ�A��~�L� In engineering, we number of “slots” in a vector is not referred to in Mathematica as the horizontal axis is traditionally called abscissa borrowed from New$, \[ \( {\bf y} = \left[ y_1 , y_2 , \ldots , y_n The coordinate system that specifies any point with a string of digits. \left\langle {\bf u} , {\bf v} \right\rangle = w_1 u_1 v_1 + w_2 u_2 v_2 + \cdots + w_n u_n v_n \( {\bf x} = \left[ x_1 , x_2 , \ldots , x_n \right]$$ and \right] \) (regardless of whether they are columns or rows computers. the cross product (for three dimensional vectors). octants. This tutorial is organized as follows. all three axes. \end{array} \right] = {\bf i} \left( a_2 b_3 - b_2 a_3 \right) - {\bf j} \left( a_1 b_3 - b_1 a_3 \right) + {\bf k} \left( a_1 b_2 - a_2 b_1 \right) . to everyone. column $$m \times 1$$ vector, and v as a column $$n \times 1$$ vector. The {\bf u} \otimes {\bf v} = {\bf u} \, {\bf v}^{\mathrm T} = \begin{bmatrix} u_1 \\ u_2 \\ u_3 \\ u_4 \end{bmatrix} \begin{bmatrix} v_1 & v_2 & v_3 \end{bmatrix} =

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