Formally, it does not make sense to talk about whether or not a single group is quasirandom. The strict definition of quasirandomness will apply to
sequences of groups, but first bipartite graph quasirandomness must be defined. The motivation for considering sequences of groups stems from its connections with
graphons, which are defined as limits of graphs in a certain sense. Fix a real number p \in [0, 1]. A sequence of bipartite graphs (G_n) (here n is allowed to skip integers as long as n tends to infinity) with G_n having n vertices, vertex parts A_n and B_n, and (p + o(1)) | A_n | | B_n | edges is
quasirandom if any of the following equivalent conditions hold: • For every bipartite graph H with vertex parts A' and B', the number of labeled copies of H in G_n with A' embedded in A and B' embedded in B is \left(p^{e(H)} + o(1)\right) | A | ^ | B | ^ . Here, the function o(1) is allowed to depend on H. • The number of
closed, labeled walks of length 4 in G_n starting in A_n is (p^4 + o(1))| A_n |^2 | B_n |^2. • The number of edges between A' and B' is p | A' | | B' | + n^2 o(1) for any pair of subsets A' \subseteq A_n and B' \subseteq B_n. • \sum\limits_{a_1, a_2 \in A_n} N(a_1, a_2)^2 = (p^4 + o(1)) | A_n |^2 | B_n |^2, where N(u, v) denotes the number of common
neighbors of u and v. • \sum\limits_{b_1, b_2 \in B_n} N(b_1, b_2)^2 = (p^4 + o(1)) | A_n |^2 | B_n |^2. • The largest
eigenvalue of G_n's
adjacency matrix is (p + o(1)) \sqrt and all other eigenvalues have magnitude at most \sqrto(1). It is a result of Chung–Graham–Wilson that each of the above conditions is equivalent. Such graphs are termed quasirandom because each condition asserts that the quantity being considered is approximately what one would expect if the bipartite graph was generated according to the
Erdős–Rényi random graph model; that is, generated by including each possible edge between A_n and B_n independently with probability p. Though quasirandomness can only be defined for sequences of graphs, a notion of c-quasirandomness can be defined for a specific graph by allowing an error tolerance in any of the above definitions of graph quasirandomness. To be specific, given any of the equivalent definitions of quasirandomness, the o(1) term can be replaced by a small constant c > 0, and any graph satisfying that particular modified condition can be termed c-quasirandom. It turns out that c-quasirandomness under any condition is equivalent to c^k-quasirandomness under any other condition for some absolute constant k \geq 1. The next step for defining group quasirandomness is the Cayley graph. Bipartite Cayley graphs give a way from translating quasirandomness in the graph-theoretic setting to the group-theoretic setting. Given a finite group \Gamma and a subset S \subseteq \Gamma, the
bipartite Cayley graph \operatorname{BiCay}(\Gamma, S) is the bipartite graph with vertex sets A and B, each labeled by elements of G, whose edges a \sim b are between vertices whose ratio ab^{-1} is an element of S. == Definition ==