Chapter 16

Immediate Snapshot Subdivisions

Abstract

Throughout this book, we have relied on the fact that image, the standard chromatic subdivision of the image-simplex image defined in Chapter 3, is indeed a subdivision of image. In this chapter, we give a rigorous proof of this claim.

Keywords

Schlegel diagram; Affinely independent; Cross-polytope; Polytope; Subdivision

Throughout this book, we have relied on the fact that image, the standard chromatic subdivision of the image-simplex image defined in Chapter 3, is indeed a subdivision of image. In this chapter, we give a rigorous proof of this claim.

The complex image captures all single-layer immediate snapshot executions for image processes. Recall that a single-layer immediate snapshot execution is given by a schedule image, where each image is the set of processes that participate in step image, the image are disjoint, and the complete set of processes image is their union. We call image an ordered partition of image.

16.1 A glimpse of discrete geometry

16.1.1 Polytopes

Recall from basic linear algebra that a hyperplane in image is a solution of a single linear equation image. Given such an equation, we also have two open half-spaces: the set of points for which image and the set for which image. It also defines two closed half-spaces: the unions of the hyperplane with the open half-spaces.

A image-dimensional convex polytope1 image is the convex hull of finitely many points in image, where we assume that not all points lie on the same hyperplane. A face of a polytope image is the intersection of image with a hyperplane that does not intersect the interior of image. An image-dimensional polytope image is bounded by a number of image-dimensional faces, which are themselves polytopes. In fact, image is an intersection of the closed half-spaces associated to its image-faces.

16.1.2 Schlegel diagrams

In general, it can be complicated to prove that one simplicial complex is a subdivision of another, even for a subdivision of a simplex. A straightforward argument would need to go into the technical details of topology of a geometric simplicial complex, possibly having to deal with explicit point descriptions as convex combinations of the vertices and so on.

Fortunately, in this case there is a short-cut: Schlegel diagrams. Informally, a Schlegel diagram is constructed by taking a “photograph” (perspective projection) of the polytope from a vantage point just outside of it, centered over a chosen image-face image. Since the polytope is convex, it is possible to choose the vantage point so that all the faces project onto image and the projections of disjoint faces are themselves disjoint.

Let us make this more specific. Pick a image-dimensional face image of the polytope image. As noted, image itself is a image-dimensional polytope obtained as an intersection of image with some hyperplane image so that the rest of the polytope lies entirely on one side of this hyperplane. Let image denote the open half-space bordered by image, which does not intersect the polytope image. Choose a point image in image very close to the barycenter of image (in fact, any point in the interior of image will do). Now project the boundary of the polytope image along the rays connecting it to image into the hyperplane image. If image is sufficiently close to the barycenter of image, the image of that projection will be contained in image. (In fact, topologically it will be precisely image.) Furthermore, by linearity, the images of the faces on the boundary of image, excluding image itself, will constitute a polyhedral subdivision of image, which we denote image. See Figure 16.1 for examples of Schlegel diagrams of a tetrahedron, cube, and dodecahedron.

image

Figure 16.1 Schlegel diagrams of tetrahedron, cube, and dodecahedron.

16.1.3 Schlegel diagrams of cross-polytopes

A polytope whose image-faces are simplices is said to be simplicial. If the polytope image is simplicial, then the Schlegeldiagram is a simplicial subdivision of the image-simplex image. We now consider a specific simplicial polytope in image. For image, let image denote the point whose image coordinate is image, and all other coordinates are image. Let image be the convex hull of the point set image. It is easy to see that these image points are in convex position and that the obtained polytope is simplicial. This is the so-called cross-polytope. Since for any pair of image-faces of image there exists a symmetry of image moving one of the faces to the other one, the Schlegel diagram will not depend on which face of image we choose, so we just write image. Examples of Schlegel diagrams for crosspolytopes of dimensions 1 and 2 are shown in Figure 16.2. Note that the boundary complex of image is precisely the simplicial join of image copies of the simplicial complex consisting of two points with no edge between them.

image

Figure 16.2 Schlegel diagrams of 1 and 2-dimensional cross-polytopes.

We shall need the following combinatorial description of the simplicial complex image. The set of vertices is indexed by image, where for every image, the pair image denotes the inner point of image corresponding to the image axis, whereas the pair image denotes the vertex of the image-simplex used as the initial face for constructing the Schlegel diagram, corresponding to the image axis. The image-dimensional simplices of image are all tuples image such that image.

Clearly, the advantage of using Schlegel diagrams is that one gets the fact that the diagram is a subdivision of the face for free. Figure 16.2 shows that image is isomorphic to image, whereas image is different from image. To get from image to image one needs to further subdivide each of the edges of the triangle and extend these subdivisions to the subdivision of image. For higher image, one needs to do this several times.

16.1.4 Extending subdivisions of simplices

To generalize the construction to higher dimensions, we need the following standard fact about simplicial complexes. Let image be an arbitrary simplicial complex, and let image be any simplex of image. Recall that the (closed) star of image is the union of all simplices that contain image, denoted by image. The complex image is the union of image and the deletion image. The intersection of these two pieces is precisely the join of the link image with the boundary image. The closed star itself is the simplicial join of image with its link (see Section 3.3).

Now assume that image is a subdivision of image that only subdivides the interior of image while leaving the boundary of image unchanged. A Schlegel diagram is an example of such a subdivision. In this case, the join of image with image is a subdivision of image.

Fact 16.1.1

Whenever we have a join of two simplicial complexes image, we can replace image with any simplicial subdivision image and the obtained complex image will be a subdivision of image. One can see this geometrically if one remembers the realization of the join from Section 3.3. Indeed, when image and image are embedded in complementary dimensions and the join is obtained by drawing all the line segments connecting points in image and in image, then it is immediate that replacing image with its subdivision will subdivide the join.

Back to our subdivision: We notice that since it does not change the link of image, and it does not change the boundary image, it will also not change their join. Since this is precisely the space along which we attach image, we can extend our local subdivision to a global subdivision of the entire image.

We now have all the tools at hand to describe how to obtain the chromatic subdivision image. Start with image. Subdivide it as a Schlegel diagram of the cross-polytope. Proceed with the faces of image of codimension image; replace them with corresponding Schlegel diagrams and extend these subdivisions using the argument above to the global subdivision of the entire complex. After this, proceed to do the same for the faces of image of codimension image and so on. We denote the simplicial complexes constructed in this way by image. In short: To go from image to image, we replace all boundary simplices of codimension image of the original simplex image with Schlegel diagrams image and then extend this to the subdivision of the entire image as described previously.

We are now ready to give a combinatorial description of the simplicial structure that we get at every step of the process.

Proposition 16.1.2

For image, the simplicial complex image has the following combinatorial description:

• The vertices of image are indexed by pairs image such that image, and either image or image.

• The image-simplices of image are indexed by all sets of image vertices corresponding to tuples image, with image, satisfying the following conditions:

(1) image

(2) image whenever image and image

(3) image

Proof

First we note that for image, we get only vertices image, with image, i.e., the vertices image. These form a single image-simplex; so our combinatorial description is correct for image.

Let us now show that for image, the transformation from image to image produces the combinatorial simplicial structure described in the proposition. For convenience, we define image to be the minimal index such that image, and set image.

First we consider what happens to vertices. For every simplex of image of codimension image, i.e., for every subset image such that image, we add new vertices image, where image. This is consistent with the Schlegel construction and with the description of the set of vertices of image.

Next we analyze what happens with the image-simplices. Many image-simplices stay intact. Those that get subdivided are of the form image such that image. Each such image gets replaced by new image-simplices, which are obtained as follows: Choose a non-empty subset image. For ease of presentation, we can reindex the vertices so that there exists image such that image, i.e., image. Then the new simplex is

image

We have image and image. To see that this is exactly what happens when Schlegel diagrams are extended to the entire complex, one can think of the part image as the maximal face of the corresponding cross-polytope indexed by the tuple image. In the Schlegel constructions it gets replaced by simplices indexed by all possible nonempty subsets of image. Then the extension of these subdivisions to the entire complex corresponds to appending this with the rest of the vertices, which is exactly what we do. The obtained image-simplices are precisely those occurring in our description of the image-simplices of image, where the order of the vertices is given by the construction. image

Corollary 16.1.3

image.

Proof

For image we have image, which means that there is at most one singleton set among image. We see that the vertices of image are all the pairs image for image, image, whereas a set of image vertices forms a image-simplex if and only if it can be ordered into a tuple image satisfying image, image, and image whenever image. In other words, the conditions for the sets of image vertices to form image-simplices translate precisely into our previous description of the simplicial complex image.  image

Remark 16.1.4

For image, the transient simplicial complexes image can also be given a distributed computing interpretation. Namely, we consider all the executions where in the initial stage a certain number of processes, numbering at most image, will only perform the write operation, with the rest of processes functioning normally and performing a write with the immediate snapshot read operation. In particular, the views of those first “write-only” processes consist solely of their own names. Note that this also explains the equality image, since it does not matter whether the first process also reads or not after it wrote its name into the shared memory.

16.2 Chapter notes

The material in this chapter is adapted from Kozlov [101].

More information on Schlegel diagrams can be found in Grunbaum [74] and more on cross-polytope in Coxeter [42].

16.3 Exercises

Exercise 16.1

Let image denote the number of image-simplices in the chromatic subdivision image. Give recursive formulas for the numbers image. Can you estimate their asymptotics? What is the answer in the special cases image and image?

Exercise 16.2

Describe the links of vertices in image as complexes constructed from standard chromatic subdivisions of simplices of lower dimension. How many different types of links are there?

Exercise 16.3

Describe the links of image-simplices of image for arbirary image, using standard chromatic subdivisions of simplices of lower dimension.


1This is a special case of what is called polytope in some literature, which will be sufficient for our purposes.

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