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Paley Graphs: Algebraic and Spectral Insights

Updated 31 December 2025
  • Paley graphs are finite graphs constructed over finite fields where vertices represent field elements and edges exist if their difference is a quadratic residue.
  • They are strongly regular and quasi-random, with explicit spectral properties that bridge arithmetic and combinatorial graph theory.
  • Their unique structure supports applications in coding theory, extremal combinatorics, and enables advanced SDP relaxations for bounding clique numbers.

A Paley graph is a fundamental object in algebraic combinatorics, defined over a finite field of odd characteristic, in which adjacency encodes quadratic residue structure. These graphs integrate arithmetic, algebraic, and spectral properties, serving as archetypes for strongly regular and quasi-random graphs, and they catalyze connections to coding theory, extremal combinatorics, spectral graph theory, and arithmetic Ramsey theory.

1. Definition and Construction

Let q=peq=p^e be a prime power with q1(mod4)q\equiv1\pmod4, and let Fq\mathbb{F}_q denote the finite field of order qq. Define the subgroup of nonzero quadratic residues,

Q={xFq:x is a square}.Q = \{\,x\in\mathbb{F}_q^* : x \text{ is a square} \,\}.

The Paley graph P(q)P(q) has vertex set V(P(q))=FqV(P(q)) = \mathbb{F}_q, with two distinct vertices x,yx, y adjacent if and only if xyQx-y\in Q. The adjacency relation is symmetric, because 1-1 is a square in q1(mod4)q\equiv1\pmod40 when q1(mod4)q\equiv1\pmod41.

  • q1(mod4)q\equiv1\pmod42 is an undirected, loopless, q1(mod4)q\equiv1\pmod43-regular graph.
  • q1(mod4)q\equiv1\pmod44 is self-complementary, as for any quadratic nonresidue q1(mod4)q\equiv1\pmod45, the map q1(mod4)q\equiv1\pmod46 is an automorphism exchanging edges and non-edges (Elsawy, 2012, Jones, 2017).
  • q1(mod4)q\equiv1\pmod47 is a strongly regular graph with parameters:

q1(mod4)q\equiv1\pmod48

where q1(mod4)q\equiv1\pmod49 and Fq\mathbb{F}_q0 count common neighbors for adjacent and non-adjacent pairs, respectively (Elsawy, 2012, Kim et al., 2024).

2. Spectral and Quasi-Random Properties

Let Fq\mathbb{F}_q1 be the adjacency matrix of Fq\mathbb{F}_q2. The spectrum is explicit:

  • Eigenvalues:

Fq\mathbb{F}_q3

both with multiplicity Fq\mathbb{F}_q4 (Mináč et al., 2022, Jones, 2017, Kim et al., 2024).

  • Fq\mathbb{F}_q5.

By Chung–Graham–Wilson (Kim et al., 2024), a sequence of graphs with edge-density Fq\mathbb{F}_q6 is quasi-random if the edge distribution in each induced subgraph matches that of a random (density-Fq\mathbb{F}_q7) graph to within Fq\mathbb{F}_q8. The expander-mixing lemma shows that Paley graphs Fq\mathbb{F}_q9 meet these criteria:

qq0

for all qq1, and the second-largest eigenvalue is qq2, so qq3 is a standard example of a quasi-random graph.

3. Automorphism Group and Symmetries

The full automorphism group of qq4 is

qq5

a semidirect product qq6 (Jones, 2017). The action is vertex- and edge-transitive; every affine map with square multiplier is a graph automorphism.

qq7 is self-complementary via multiplication by any quadratic nonresidue.

4. Extremal Subgraph Structure and SDP Bounds

Clique and independence numbers: By classic Fourier methods and subsequent quasi-random analysis, for qq8,

qq9

where Q={xFq:x is a square}.Q = \{\,x\in\mathbb{F}_q^* : x \text{ is a square} \,\}.0 is the clique number and Q={xFq:x is a square}.Q = \{\,x\in\mathbb{F}_q^* : x \text{ is a square} \,\}.1 the independence number (Kim et al., 2024).

SDP relaxations: The clique number satisfies the classical upper bound Q={xFq:x is a square}.Q = \{\,x\in\mathbb{F}_q^* : x \text{ is a square} \,\}.2 (Kobzar et al., 2023), with recent computational evidence (block-diagonal SDP relaxations, such as Q={xFq:x is a square}.Q = \{\,x\in\mathbb{F}_q^* : x \text{ is a square} \,\}.3 and SOS-4) indicating actual growth may be sub-Q={xFq:x is a square}.Q = \{\,x\in\mathbb{F}_q^* : x \text{ is a square} \,\}.4: numerically, Q={xFq:x is a square}.Q = \{\,x\in\mathbb{F}_q^* : x \text{ is a square} \,\}.5 (Kobzar et al., 2023).

  • The Lovász Q={xFq:x is a square}.Q = \{\,x\in\mathbb{F}_q^* : x \text{ is a square} \,\}.6 function equals Q={xFq:x is a square}.Q = \{\,x\in\mathbb{F}_q^* : x \text{ is a square} \,\}.7 and coincides with the value at the first level of the exact subgraph hierarchy (ESH).
  • The ESH remains at the Lovász bound up to level Q={xFq:x is a square}.Q = \{\,x\in\mathbb{F}_q^* : x \text{ is a square} \,\}.8; the local ESH, exploiting vertex-transitivity, gives strictly improved upper bounds already at low levels and is at least as tight as ESH (Gaar et al., 2024).

Table: Numerical Comparison for Small Q={xFq:x is a square}.Q = \{\,x\in\mathbb{F}_q^* : x \text{ is a square} \,\}.9 (Gaar et al., 2024) | P(q)P(q)0 | P(q)P(q)1 | P(q)P(q)2 | P(q)P(q)3 | P(q)P(q)4 | |-----|--------------|------------------|------------|-------------| | 13 | 3 | 3.6056 | 3.6056 | 3.0000 | | 29 | 4 | 5.3852 | 5.3852 | 4.3177 |

5. Extremal and Combinatorial Properties

  • Pancyclicity: For P(q)P(q)5, P(q)P(q)6, P(q)P(q)7 is pancyclic: it contains cycles of every possible length P(q)P(q)8 (Nishimura, 2023).
  • Subgraph enumeration: For the number of triangles and 4-cliques, explicit formulas in terms of Jacobi sums are known. For P(q)P(q)9,

V(P(q))=FqV(P(q)) = \mathbb{F}_q0

where V(P(q))=FqV(P(q)) = \mathbb{F}_q1 with V(P(q))=FqV(P(q)) = \mathbb{F}_q2, V(P(q))=FqV(P(q)) = \mathbb{F}_q3 even (Dawsey et al., 2020).

  • Even induced subgraphs: The number of even induced subgraphs of Paley graphs matches that in random models for small sizes; the parity structure corresponds to the enumeration of MDS self-dual codes (Li et al., 22 Dec 2025).

6. Generalizations of Paley Graphs

The Paley construction motivates several generalizations:

  • Generalized Paley graphs: For V(P(q))=FqV(P(q)) = \mathbb{F}_q4 dividing V(P(q))=FqV(P(q)) = \mathbb{F}_q5 (and V(P(q))=FqV(P(q)) = \mathbb{F}_q6 when V(P(q))=FqV(P(q)) = \mathbb{F}_q7 odd), define adjacency via V(P(q))=FqV(P(q)) = \mathbb{F}_q8-th power residues:

V(P(q))=FqV(P(q)) = \mathbb{F}_q9

Regular of degree x,yx, y0, often not strongly regular for x,yx, y1 (Elsawy, 2012, Schneider et al., 2013, Bonini et al., 2024).

  • Automorphism group: For large x,yx, y2 relative to x,yx, y3, x,yx, y4 (Ponomarenko, 23 Nov 2025).
  • Paley graphs in characteristic x,yx, y5: A distinct construction exists, using the trace map and Möbius transformations, resulting in a self-complementary, vertex-transitive pseudo-random graph on x,yx, y6 points for x,yx, y7 (Thomason, 2015).
  • Paley graphs over x,yx, y8: With x,yx, y9 restricted to ensure xyQx-y\in Q0 is a square in the unit group, a version exists for rings, where the underlying group is xyQx-y\in Q1 and adjacency is defined by units that are squares modulo xyQx-y\in Q2 (Bhowmik et al., 2020).

7. Applications and Structural Invariants

  • Random models: The multiplicative random-graph model more faithfully captures the clique-number fluctuations of Paley graphs than purely random Cayley graphs, matching the Graham–Ringrose phenomenon for cliques of size xyQx-y\in Q3 (Mrazović, 2016).
  • Coding theory: There is a tight connection between even/odd subgraph structure in Paley graphs and the existence and enumeration of MDS self-dual (extended) GRS codes (Li et al., 22 Dec 2025).
  • Critical group / Smith normal form: The critical (sandpile) group and Smith group of the adjacency matrix for xyQx-y\in Q4 are described explicitly in terms of the field order; the primary decomposition involves detailed number-theoretic and character-sum data (Chandler et al., 2014).

8. Infinite and Arithmetic Variants

  • Infinite Paley graphs: The direct limits of Paley graphs over towers of extensions yield, up to isomorphism, the universal Erdős–Rényi–Rado random graph xyQx-y\in Q5 for any (locally finite, infinite) field of odd characteristic. This is established via the extension property and Weil’s character sum estimates (Jones, 2019).
  • Ramanujan and energy properties: The spectrum of Paley and generalized Paley graphs provides explicit classes of Ramanujan graphs and infinite families of non-strongly regular, non-bipartite graphs which are equienergetic with their complements (Mináč et al., 2022, Podestá et al., 2022).

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