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Euclidean similarities

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Euclidean similarities

You may recall that a pair of similar triangles are two triangles tex2html_wrap_inline5932 and tex2html_wrap_inline5934 with sides tex2html_wrap_inline5764 , tex2html_wrap_inline5938 , tex2html_wrap_inline5940 , i=1,2, respectively, for which after choosing the appropriate correspondence between the sides, the ratios of the corresponding lengths tex2html_wrap_inline5944 , tex2html_wrap_inline5946 , and tex2html_wrap_inline5948 are all the same. A similarity is a transformation of the plane that stretches all distances by exactly the same scale factor. A congruence or isometry (for ``equal distance'') is a transformation that leaves all distances exactly the same (i.e. the scale factor is 1). In this section, we would like to describe exactly what all the possible similarities are. Here we shall make reference to Barnsley [Bar93], Chapter III, section 2, although we shall adopt a less general approach.

We begin with the distance formula between two points tex2html_wrap_inline5950 and tex2html_wrap_inline5952 , given by Pythagoras' theorem:

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We think of transformations T of the plane as functions tex2html_wrap_inline5958 , and we are particularly interested in how transformations change distances in the plane. Properties related to distance are often called metrical. As it turns out, the key aspects of distance are shared by many formulas other than that provided by Pythagoras. There is a more general concept called a metric defined as follows:

  1. A metric is a function tex2html_wrap_inline5960 on pairs of points tex2html_wrap_inline5962 that takes only nonnegative real values.
  2. If tex2html_wrap_inline5964 , then tex2html_wrap_inline5966 .
  3. tex2html_wrap_inline5968 .
  4. For any three points tex2html_wrap_inline5970 , tex2html_wrap_inline5972 , tex2html_wrap_inline5974 , we have

    displaymath5976

    This is called the triangle inequality

For just about all arguments involving distance, these are the only properties we need to use. As it turns out, the concept of metric is useful even in subjects where ``distance'' doesn't seem to make sense, for instance, in symbolic dynamics we often introduce metrics on sets of strings in the symbols. For now, we will just work with Pythagoras' metric.

A similarity is a transformation that changes all distances by the same factor, that is:

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for all points tex2html_wrap_inline5970 , tex2html_wrap_inline5972 . The constant c>0 is the scaling factor of the similarity T. The basic example of a similarity is the dilation

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for positive c. This transformation stretches or shrinks all points by the same factor; the origin (0,0) is fixed by tex2html_wrap_inline5994 . Suppose T is any other similarity with scaling factor c. Consider the composition tex2html_wrap_inline6000 . Then tex2html_wrap_inline6002 . To ease our notation a little, we shall write

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so that we may write

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Thus, for two points tex2html_wrap_inline5970 , tex2html_wrap_inline5972 , we obtain

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A similarity with scaling factor 1 is called an isometry (for ``equal distance'') or congruence. Therefore, we conclude that any similarity may be composed with a dilation to obtain an isometry. We are left with determining the isometries.

The simplest example of an isometry is a translation

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where tex2html_wrap_inline6014 is a fixed point in tex2html_wrap_inline5808 . All points P are then shifted by the fixed amount tex2html_wrap_inline6014 . We may check that tex2html_wrap_inline6022 is an isometry by the computation

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after cancelling the tex2html_wrap_inline6014 terms.

If tex2html_wrap_inline6028 and tex2html_wrap_inline6030 are any two isometries, the composition tex2html_wrap_inline6032 is also an isometry, due to the calculation

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Let's now assume that T is an arbitrary isometry. Then T maps the origin 0 to some point tex2html_wrap_inline6014 . Consider the composition tex2html_wrap_inline6044 . Then tex2html_wrap_inline6046 . This shows that we can use a translation to modify any isometry into one that fixes the origin.

We may now work with an isometry T that fixes 0. Consider the point T(1,0). Since (1,0) is at distance 1 from the origin, the same should be true for T(1,0). Using a little trigonometry, this means tex2html_wrap_inline6056 for some angle tex2html_wrap_inline6058 . We now pull another isometry out of the hat

displaymath6060

This clearly has the property that tex2html_wrap_inline6062 . Also, we can check that tex2html_wrap_inline6064 . That it's an isometry as well takes a bit of stamina to prove

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after observing that tex2html_wrap_inline6066 . Now the most important part is that tex2html_wrap_inline6068 . Thus, when we compose tex2html_wrap_inline6070 , we obtain an isometry that not only fixes 0 but also (1,0). Our trigonometry has guided us to the transformation tex2html_wrap_inline6076 that rotates the plane clockwise through an angle of tex2html_wrap_inline6058 about the origin.

Finally, we are left to consider isometries T that fix both the points (0,0) and (1,0). To finish the job, we must resurrect the old Side-Side-Side criterion of Euclidean geometry that says that any two triangles with the same sides are congruent. For our purposes this says that given distances d((0,0), P) and d((1,0),P) there is exactly zero, one or two solution points P=(x,y). If the triangle inequality tex2html_wrap_inline6092 is violated, there are no solutions. If there is a solution P=(x,0) on the horizontal axis, there is only one solution. If there is a solution P=(x,y) with tex2html_wrap_inline6098 , there is exactly one other solution (x,-y), the reflection through the horizontal axis. The relevance of this fact to our isometry is that

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since T fixes both (0,0) and (1,0). It follows that, for P=(x,y), either T(P)=(x,y) or T(P)=(x,-y). We would hope that this choice of T(P) be consistent for all (x,y). To prove this requires an investigation into the continuity of isometries. We will leave that task for courses on real analysis, and simply say that isometries are perforce continuous maps from tex2html_wrap_inline5808 to itself. Moreover, this fact implies that either T(x,y)=(x,y) for all (x,y) or T(x,y)=(x,-y) for all (x,y). Let's define W(x,y)=(x,-y).

We have at last completed a stage-by-stage dissection of similarities of tex2html_wrap_inline5808 . Working backwards, we see that we have shown that all similarities can be represented as a composition of a dilation, a translation, a rotation, and possibly the reflection W.

THEOREM: Every similarity tex2html_wrap_inline6134 may be expressed in the form

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for some c>0, tex2html_wrap_inline6140 , and angle tex2html_wrap_inline6058 .

We caution the reader that in the process of rewriting our previous analysis into the statement of the theorem we have taken advantage of the fact that the inverse maps to tex2html_wrap_inline6022 and tex2html_wrap_inline6076 are tex2html_wrap_inline6148 and tex2html_wrap_inline6150 , respectively. Thus, the constants tex2html_wrap_inline6014 and tex2html_wrap_inline6058 in the theorem are actually the opposites of the ones that arose in the analysis. We should also point out that tex2html_wrap_inline5994 is the inverse map to tex2html_wrap_inline6158 . The similarities of the first form in the theorem are called orientation-preserving (because they preserve the notions of left and right), while those of the second form are called orientation-reversing.

Coincidentally, all the similarities have the form

displaymath6160

for some constants a,b,c,d,e,f. These are known as affine linear transformations, or affine maps for short. Not all affine maps are similarities. Commonly, they stretch distances by one factor in one direction and by a different factor in a different direction. In matrix form (we beg the reader's indulgence in introducing a few concepts from linear algebra without a thorough explanation), an affine linear map may be written

displaymath6164

Writing vectors in boldface tex2html_wrap_inline6166 , we may write affine maps as tex2html_wrap_inline6168 , where A is a tex2html_wrap_inline6172 matrix and tex2html_wrap_inline6174 is a constant vector. The mapping tex2html_wrap_inline6176 is a translation, and so is an isometry. Therefore, the question of whether or not tex2html_wrap_inline6178 is a similarity depends entirely on the matrix A. It's a similarity if and only if there is a constant c>0 such that

  equation836

for all vectors tex2html_wrap_inline6184 . In the exercises, we pose the problem of converting this condition into an equation involving solely the matrix A.

While we shall limit ourselves to two dimensions, some of the most interesting considerations are higher-dimensional. However, the classification of similarities of tex2html_wrap_inline6188 for tex2html_wrap_inline6190 is not terribly much different from what we have just done. Translations and dilations are exactly analogous; there are a few more degrees of freedom in the rotations.


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