Editing Spectral sequence (section)

== Discovery and motivation ==

Motivated by problems in algebraic topology, Jean Leray introduced the notion of a [[sheaf (mathematics)|sheaf]] and found himself faced with the problem of computing [[sheaf cohomology]]. To compute sheaf cohomology, Leray introduced a computational technique now known as the [[Leray spectral sequence]]. This gave a relation between cohomology groups of a sheaf and cohomology groups of the [[direct image of a sheaf|pushforward of the sheaf]]. The relation involved an infinite process. Leray found that the cohomology groups of the pushforward formed a natural [[chain complex]], so that he could take the cohomology of the cohomology. This was still not the cohomology of the original sheaf, but it was one step closer in a sense. The cohomology of the cohomology again formed a chain complex, and its cohomology formed a chain complex, and so on. The limit of this infinite process was essentially the same as the cohomology groups of the original sheaf.

It was soon realized that Leray's computational technique was an example of a more general phenomenon. Spectral sequences were found in diverse situations, and they gave intricate relationships among homology and cohomology groups coming from geometric situations such as [[fibration]]s and from algebraic situations involving [[derived functor]]s. While their theoretical importance has decreased since the introduction of [[derived category|derived categories]], they are still the most effective computational tool available. This is true even when many of the terms of the spectral sequence are incalculable.

Unfortunately, because of the large amount of information carried in spectral sequences, they are difficult to grasp. This information is usually contained in a rank three lattice of [[abelian group]]s or [[module (mathematics)|modules]]. The easiest cases to deal with are those in which the spectral sequence eventually collapses, meaning that going out further in the sequence produces no new information. Even when this does not happen, it is often possible to get useful information from a spectral sequence by various tricks.