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New trends in physics teaching, v.4; The ... - unesdoc - Unesco

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<strong>New</strong> Trends <strong>in</strong> Physics Teach<strong>in</strong>g IV<br />

change to a system, which can be imag<strong>in</strong>ed happen<strong>in</strong>g, not a formal play with permutations<br />

(though above it was cast <strong>in</strong> a generalized way, it need not be). Incidentally, it avoids the use of<br />

Stirl<strong>in</strong>g’s approximation as well.<br />

Distributions: most probable and average<br />

As we saw, Gurney uses Wmax and so the most probable distribution; not S2 and the average<br />

distribution. This creates the problem that sooner or later he and others who take that approach<br />

have to argue that A In Wmax A In S2, s<strong>in</strong>ce they really need AS = k In S2.<br />

More seriously, as Gurney himself br<strong>in</strong>gs out very well, it is only changes <strong>in</strong> 52 <strong>in</strong> an <strong>in</strong>teract<strong>in</strong>g<br />

system that have any <strong>in</strong>terpretation. That is, if parts X and Y of a system are <strong>in</strong>dependent, then<br />

‘X = ’ total<br />

but the same is not true for W,,,. Thus even to <strong>in</strong>troduce temperature on Gurney’s approach<br />

(through thermal equilibrium between two systems), S2 has to be used.<br />

Variations on Gurney<br />

Powles extends the <strong>in</strong>formal <strong>in</strong>troductory use of Gurney’s arguments by numerical examples<br />

(Powles, 1968). He calculates by enumerat<strong>in</strong>g states the most probable and the average distributions,<br />

go<strong>in</strong>g so far as to calculate the specific heat capacity of a five-oscillator E<strong>in</strong>ste<strong>in</strong> solid. Such<br />

examples seem likely to be of considerable value <strong>in</strong> develop<strong>in</strong>g an <strong>in</strong>tuitive idea of the subject,<br />

and must be welcome <strong>in</strong> a topic nomially ridden with algebra and short on reality.<br />

Sherw<strong>in</strong> offers a much more radically worked out version of Gurney’s arguments, also (unlike<br />

Powles) exploit<strong>in</strong>g the unit-change method. Like Powles, he uses extensive numerical examples,<br />

enumerat<strong>in</strong>g states. In these examples, temperature is given a qualitative statistical sense, as a<br />

measure of the probable direction of spontaneous energy flow, s<strong>in</strong>ce the examples <strong>in</strong>clude two<br />

systems com<strong>in</strong>g to thermal equilibrium.<br />

He also uses W, rather than CL, and this means that he has to do a difficult sum over an<br />

<strong>in</strong>f<strong>in</strong>ite number of exponential terms to obta<strong>in</strong> the specific heat capacity. This calculation is<br />

much easier with S2 (cf Bent 1965, Nuffield Advanced Physics, 1972). However, it is <strong>in</strong> Sherw<strong>in</strong><br />

that one major advantage of the E<strong>in</strong>ste<strong>in</strong> solid is clear. Given that the arguments lead to an<br />

exponentially graded distribution, temperature can be <strong>in</strong>troduced as related to the gradient:<br />

the hotter the solid, the shallower the grad<strong>in</strong>g, so T appears as a divisor <strong>in</strong> exp(-E/kT).<br />

BENT’S APPROACH<br />

Bent deserves a discussion of his own, because, although like Gurney he uses the E<strong>in</strong>ste<strong>in</strong> solid<br />

and unit-change arguments, he uses them to operate on S2 rather than Wmax, and because he<br />

offers a total pattern of teach<strong>in</strong>g which has flair, is dist<strong>in</strong>ctive, and has some rare merits.<br />

<strong>The</strong> boxed parts of figure 8 show Bent’s statistical arguments, to be compared with figure 7<br />

(Gurney). He has a unique, if not totally conv<strong>in</strong>c<strong>in</strong>g, argument by <strong>in</strong>duction from small numbers<br />

to the expression<br />

S2 = (N-l+q)! /(N-l)! (q)!<br />

168

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