The Chemistry Maths Book, Second Edition

(Grace) #1

566 Chapter 20Numerical methods


20.4 Interpolation


Interpolation is the process of finding a function whose graph goes through a number


of given points. In Figure 20.3 the points represent the (n 1 + 11 ) number pairs


(x


0

, y


0

), (x


1

, y


1

), (x


2

, y


2

), = (x


n

,y


n

) (20.15)


and the dashed curve represents a continuous functiony 1 = 1 f(x)such thaty


i

1 = 1 f(x


i

)


for the number pairs (20.15).


The numbers themselves may, for example, be the results of measurements of


concentration and time in a kinetics experiment, or of pressure and temperature in


a study of the thermodynamic properties of a fluid. Alternatively, they may be the


tabulated values of a function that cannot be expressed in simple functional form.


The object of interpolation is to find a ‘simple’ function that can be used to find


intermediate points in the interval (x


0

, y


0

)to(x


n

, y


n

) (outside this interval the process


is extrapolation). Important uses of interpolation are in numerical integration (Section


20.5), whereby a function that cannot be integrated by the methods described in


Chapters 5 and 6 is approximated by a simpler function that can be so integrated, and


in the numerical solution of differential equations (Section 20.9).


Polynomial interpolation


Given (n 1 + 11 ) points, it is possible to find a unique polynomialp


n

of degree n,


p


n

(x) 1 = 1 a


0

1 + 1 a


1

x 1 + 1 a


2

x


2

1 +1-1+ 1 a


n

x


n

(20.16)


that passes through all the points. For example, through any two points there is a


unique straight line (n 1 = 11 ), and through any three points there is a unique quadratic


(n 1 = 12 ).


2

.

..

...

..

...

..

....
...
..
...
...
..
...
...
.

..
...
..
...
...
..
...
...
.

...............
........
......

.

.......

.......

.......

y


x


f(x)?


x


0

x


1

x


2

x


3

x


n

y


0

y


1

y


2

y


3

y


n

···






















....

....

...

...

.....

...

......

.....

......

.....

.....

......

.........

......

.............

................

..................

.............

.........

....

..........

.

........

...

...

.......

.

..

.....

....

..

.....

....

.

....

....

..

.

....

....

..

...

....

....

Figure 20.3


2

The theoretical basis for polynomial interpolation, and one of the important theorems of modern analysis,


is Weierstrass’ theorem: ‘Iff(x)is an arbitrary continuous function defined in the intervala 1 ≤ 1 x 1 ≤ 1 b, it is always


possible to approximatef(x)over the whole interval as closely as we please by a power polynomial of sufficiently


high degree’. The essential requirement is continuity; the function may have infinitely many maxima and minima,


and need not have a derivative at any point in the interval. Karl Weierstrass (1815–1897), professor at Berlin, made


important and influential contributions to analysis.

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