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GF(2) (also denoted , Z/2Z or ) is the finite field with two elements.[1][a]

GF(2) is the field with the smallest possible number of elements, and is unique if the additive identity and the multiplicative identity are denoted respectively 0 and 1, as usual.

The elements of GF(2) may be identified with the two possible values of a bit and to the Boolean values true and false. It follows that GF(2) is fundamental and ubiquitous in computer science and its logical foundations.

Definition

[edit]

GF(2) is the unique field with two elements with its additive and multiplicative identities respectively denoted 0 and 1.

Its addition is defined as the usual addition of integers but modulo 2 and corresponds to the table below:

+ 0 1
0 0 1
1 1 0

If the elements of GF(2) are seen as Boolean values, then the addition is the same as that of the logical XOR operation. Since each element equals its opposite, subtraction is thus the same operation as addition.

The multiplication of GF(2) is the usual multiplication (see the table below), and on Boolean variables corresponds to the logical AND operation.

× 0 1
0 0 0
1 0 1

GF(2) can be identified with the field of the integers modulo 2, that is, the quotient ring of the ring of integers Z by the ideal 2Z of all even numbers: GF(2) = Z/2Z.

Notations Z2 and may be encountered although they can be confused with the notation of 2-adic integers.

Properties

[edit]
Main article: finite field

Because GF(2) is a field, many of the familiar properties of number systems such as the rational numbers and real numbers are retained:

  • addition has an identity element (0) and an inverse for every element;
  • multiplication has an identity element (1) and an inverse for every element but 0;
  • addition and multiplication are commutative and associative;
  • multiplication is distributive over addition.

Properties that are not familiar from the real numbers include:

  • every element x of GF(2) satisfies x + x = 0 and therefore −x = x; this means that the characteristic of GF(2) is 2;
  • every element x of GF(2) satisfies x2 = x (i.e. is idempotent with respect to multiplication); this is an instance of Fermat's little theorem. GF(2) is the only field with this property (Proof: if x2 = x, then either x = 0 or x ≠ 0. In the latter case, x must have a multiplicative inverse, in which case dividing both sides by x gives x = 1. All larger fields contain elements other than 0 and 1, and those elements cannot satisfy this property).

Applications

[edit]

Because of the algebraic properties above, many familiar and powerful tools of mathematics work in GF(2) just as well as other fields. For example, matrix operations, including matrix inversion, can be applied to matrices with elements in GF(2) (see matrix ring).

Any group (V,+) with the property v + v = 0 for every v in V is necessarily abelian and can be turned into a vector space over GF(2) in a natural fashion, by defining 0v = 0 and 1v = v for all v in V. This vector space will have a basis, implying that the number of elements of V must be a power of 2 (or infinite).

In modern computers, data are represented with bit strings of a fixed length, called machine words. These are endowed with the structure of a vector space over GF(2). The addition of this vector space is the bitwise operation called XOR (exclusive or). The bitwise AND is another operation on this vector space, which makes it a Boolean algebra, a structure that underlies all computer science. These spaces can also be augmented with a multiplication operation that makes them into a field GF(2n), but the multiplication operation cannot be a bitwise operation. When n is itself a power of two, the multiplication operation can be nim-multiplication; alternatively, for any n, one can use multiplication of polynomials over GF(2) modulo a irreducible polynomial (as for instance for the field GF(28) in the description of the Advanced Encryption Standard cipher).

Vector spaces and polynomial rings over GF(2) are widely used in coding theory, and in particular in error correcting codes and modern cryptography. For example, many common error correcting codes (such as BCH codes) are linear codes over GF(2) (codes defined from vector spaces over GF(2)), or polynomial codes (codes defined as quotients of polynomial rings over GF(2)).

Algebraic closure

[edit]

Like any field, GF(2) has an algebraic closure. This is a field F which contains GF(2) as a subfield, which is algebraic over GF(2) (i.e. every element of F is a root of a polynomial with coefficients in GF(2)), and which is algebraically closed (any non-constant polynomial with coefficients in F has a root in F). The field F is uniquely determined by these properties, up to a field automorphism (i.e. essentially up to the notation of its elements).

F is countable and contains a single copy of each of the finite fields GF(2n); the copy of GF(2n) is contained in the copy of GF(2m) if and only if n divides m. The field F is countable and is the union of all these finite fields.

Conway realized that F can be identified with the ordinal number , where the addition and multiplication operations are defined in a natural manner by transfinite induction (these operations are however different from the standard addition and multiplication of ordinal numbers).[2] The addition in this field is simple to perform and is akin to Nim-addition; Lenstra has shown that the multiplication can also be performed efficiently.[3]

See also

[edit]

References

[edit]
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GF(2)

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GF(2), also known as the Galois field of order 2, is the finite field consisting of the two elements {0, 1}, where addition and multiplication are performed using arithmetic modulo 2.[1] It is the unique (up to isomorphism) field of prime order 2 and serves as the prime field of characteristic 2.[1] As the smallest non-trivial finite field, GF(2) underpins much of abstract algebra and computer science, providing a foundational structure for binary operations.[2] The operations in GF(2) are straightforward and correspond directly to bitwise operations in computing. Addition is equivalent to the exclusive OR (XOR) function, with the following table:
+01
001
110
Multiplication aligns with the logical AND operation, as shown:
×01
000
101
These operations satisfy all field axioms, including commutativity, associativity, distributivity, and the existence of identities (0 for addition, 1 for multiplication) and inverses (each element is its own additive inverse, and 1 is the multiplicative inverse of itself).[3] GF(2) is isomorphic to the ring of integers modulo 2, ℤ/2ℤ, and its additive group is cyclic of order 2 while the multiplicative group consists solely of {1}.[3] GF(2) plays a central role in constructing larger finite fields of the form GF(2^n) for n > 1, which are built as quotient rings of polynomials over GF(2) modulo an irreducible polynomial of degree n.[2] These extensions are vital in applications such as error-correcting codes—for instance, binary Hamming codes operate as linear codes over GF(2), enabling single-error correction in data transmission.[4] In cryptography, GF(2) forms the basis for fields like GF(2^8) used in the Advanced Encryption Standard (AES) for efficient bitwise computations during encryption processes.[2] Additionally, vector spaces over GF(2) model binary linear algebra, with applications in combinatorial optimization, network coding, and digital signal processing.[5]

Fundamentals

Definition

GF(2), also denoted F2\mathbb{F}_2, is the unique finite field of order 2, consisting of the elements {[0](/page/0),1}\{[0](/page/0), 1\} with addition and multiplication performed modulo 2.[6] It serves as the prime field of characteristic 2, isomorphic to the quotient ring Z/2Z\mathbb{Z}/2\mathbb{Z}, where the integers are reduced modulo the prime 2.[6] Alternatively, GF(2) can be constructed as the splitting field of the polynomial x2−xx^2 - x over the prime field of characteristic 2, as both roots 0 and 1 lie within the field and satisfy t2=tt^2 = t for every element t∈F2t \in \mathbb{F}_2.[6] To verify that GF(2) is a field, it must satisfy the field axioms: it forms a commutative ring with unity under addition and multiplication, every non-zero element is invertible, and the distributive law holds. The additive group is cyclic of order 2, with 0 as the identity and each element its own inverse (since 1+1=[0](/page/0)1 + 1 = [0](/page/0)). The multiplicative structure has 1 as the unity, and the non-zero element 1 is its own inverse (1⋅1=11 \cdot 1 = 1). Commutativity, associativity, and distributivity follow directly from the corresponding properties in Z/2Z\mathbb{Z}/2\mathbb{Z}, verifiable by direct inspection of the two elements.[3][7] GF(2) is unique up to isomorphism: any field with exactly two elements must be isomorphic to it, as all finite fields of the same order pnp^n (here p=2p=2, n=1n=1) are isomorphic, determined by the existence and uniqueness of the splitting field of xpn−xx^{p^n} - x over the prime field Fp\mathbb{F}_p.[6][8]

Arithmetic Operations

In GF(2), the field with two elements denoted as {0, 1}, addition is defined as the operation modulo 2, which corresponds to the bitwise exclusive OR (XOR) for binary values. Specifically, the addition table yields: 0+0=00 + 0 = 0, 0+1=10 + 1 = 1, 1+0=11 + 0 = 1, and 1+1=01 + 1 = 0.[1][3] Subtraction in GF(2) coincides with addition due to the field's characteristic of 2, where each element is its own additive inverse, so x−y=x+yx - y = x + y for all x,y∈{0,1}x, y \in \{0, 1\}.[9][10] Multiplication in GF(2) follows the standard binary rules, equivalent to the logical AND operation: 0×0=00 \times 0 = 0, 0×1=00 \times 1 = 0, 1×0=01 \times 0 = 0, and 1×1=11 \times 1 = 1.[1][3] The additive identity is 0, satisfying x+0=xx + 0 = x for all x∈GF(2)x \in GF(2), while the multiplicative identity is 1, with x×1=xx \times 1 = x. Additionally, the additive inverse of any element xx is xx itself, as x+x=[0](/page/0)x + x = [0](/page/0).[1][10] For division, since the only non-zero element is 1 and 12=11^2 = 1, the multiplicative inverse of 1 is 1 itself, making division by a non-zero element yy equivalent to multiplication by yy, so x/y=x×yx / y = x \times y for y≠[0](/page/0)y \neq [0](/page/0). Division by 0 is undefined, consistent with field axioms.[9]

Properties

Characteristic and Structure

The field GF(2) has characteristic 2, defined as the smallest positive integer kk such that k⋅1=0k \cdot 1 = 0, where 1 denotes the multiplicative identity; this immediately implies that 1+1=01 + 1 = 0.[11][12] As the prime field of characteristic 2, GF(2) is the smallest field with this property, consisting of the elements {0, 1} and generated additively and multiplicatively by 1, with no proper subfields.[13][12] The multiplicative group of nonzero elements, denoted GF(2)^\times, is trivial, comprising solely the element 1 and thus having order 1; this follows from the field's order being 2, making the group cyclic of order 2−1=12 - 1 = 1.[11][13] As an integral domain (with no zero divisors, since every nonzero element has a multiplicative inverse), GF(2) exhibits further structural simplicity: every element is idempotent under multiplication, satisfying x2=xx^2 = x for x∈{0,1}x \in \{0, 1\}, a property characteristic of Boolean rings.[14][15] This idempotence and the field's characteristic 2 align GF(2) closely with Boolean algebra, where the addition operation corresponds to the logical XOR gate and multiplication to the AND gate, enabling direct isomorphism between the field's structure and two-element Boolean lattices in computational contexts.[11][14]

Vector Spaces over GF(2)

A vector space over GF(2), the finite field with two elements {0, 1}, consists of vectors whose components are elements of GF(2), with scalar multiplication and vector addition defined using the field's arithmetic operations modulo 2.[16] This binary nature means that any vector can be represented as a string of 0s and 1s, where addition corresponds to bitwise XOR and scalar multiplication by 1 leaves the vector unchanged while multiplication by 0 yields the zero vector.[17] Due to the field's characteristic 2, as discussed in prior sections on field properties, addition is idempotent (adding a vector to itself results in zero), which simplifies many structural aspects compared to vector spaces over fields of characteristic not equal to 2.[16] The dimension of a vector space over GF(2) is the cardinality of a basis, and for an n-dimensional space, the total number of vectors is 2n2^n.[17] A canonical example is F2n\mathbb{F}_2^n, the set of all n-tuples with entries in GF(2), which forms an n-dimensional vector space under componentwise addition and scalar multiplication.[16] For instance, in F22\mathbb{F}_2^2, a basis is {(1,0),(0,1)}\{(1,0), (0,1)\}, and the four elements are (0,0)(0,0), (1,0)(1,0), (0,1)(0,1), and (1,1)(1,1), interpretable as 2-bit binary strings.[17] Every vector in this space is uniquely expressed as a linear combination of basis vectors with coefficients in {0,1}, reflecting the field's binary structure.[16] Linear independence in a vector space over GF(2) requires that no vector in the set is equal to the sum (via XOR) of the others.[17] A set of vectors {v1,…,vk}\{v_1, \dots, v_k\} is linearly dependent if there exist coefficients ci∈F2c_i \in \mathbb{F}_2, not all zero, such that ∑civi=0\sum c_i v_i = 0, where the sum is modulo 2; otherwise, the set is independent.[16] The maximum size of a linearly independent set equals the dimension, and bases provide minimal spanning sets for the space.[17] The standard inner product on F2n\mathbb{F}_2^n is defined as ⟨x,y⟩=∑i=1nxiyi(mod2)\langle x, y \rangle = \sum_{i=1}^n x_i y_i \pmod{2} for vectors x=(x1,…,xn)x = (x_1, \dots, x_n) and y=(y1,…,yn)y = (y_1, \dots, y_n).[17] Two vectors are orthogonal if their inner product is 0, which plays a key role in concepts like orthogonal complements and self-orthogonal subspaces over GF(2).[16] This bilinear form is symmetric due to the commutativity of multiplication in GF(2). In characteristic 2, it satisfies ⟨x,x⟩=∑i=1nxi(mod2)\langle x, x \rangle = \sum_{i=1}^n x_i \pmod{2}, the parity of the Hamming weight of x, distinguishing it from positive definite inner products over the reals.[17]

Representations

As a Quotient Ring

The field GF(2) is isomorphic to the quotient ring Z/2Z\mathbb{Z}/2\mathbb{Z}, obtained by factoring out the principal ideal (2)(2) generated by the prime number 2 from the ring of integers Z\mathbb{Z}.[18] This construction yields a field because the ideal (2)(2) is maximal (equivalently, prime) in the principal ideal domain Z\mathbb{Z}, ensuring that the quotient has no zero divisors and every nonzero element is invertible.[18] The elements of this quotient ring are the residue classes [0]=2Z[0] = 2\mathbb{Z} and [1]=1+2Z[1] = 1 + 2\mathbb{Z}, which are canonically identified with the set {0,1}\{0, 1\}, where addition and multiplication are defined componentwise modulo 2.[18] As an integral domain of characteristic 2, GF(2) is already a field, so its field of fractions coincides with itself; there are no proper fractions beyond the elements already present, reflecting the finite nature of the structure.[19] This self-contained property underscores its role as the prime field of characteristic 2.[19] GF(2) can also be realized as a quotient of the polynomial ring Z[x]\mathbb{Z}[x] by the ideal generated by 2 and a suitable polynomial that enforces the field's structure, such as (2,x)(2, x), which collapses to Z/2Z\mathbb{Z}/2\mathbb{Z} by setting x≡0x \equiv 0.[20] More generally, finite fields arise as quotients of polynomial rings over prime fields, but for GF(2) as the base case, the integer quotient provides the foundational construction.[20] The arithmetic underlying GF(2) was discovered implicitly through 19th-century developments in modular arithmetic, notably in Carl Friedrich Gauss's Disquisitiones Arithmeticae (1801), where congruences modulo primes laid the groundwork for finite structures, though the explicit field-theoretic interpretation emerged later with Évariste Galois's work around 1830.[21]

Explicit Operation Tables

The operations in GF(2), the finite field with two elements {0, 1}, are defined modulo 2, making addition equivalent to the exclusive-or (XOR) operation and multiplication equivalent to the logical AND operation.[22] The addition table for GF(2) is as follows:
+01
001
110
This table illustrates that addition computes the parity: the sum is 1 if the inputs differ and 0 if they are the same.[22][23] The multiplication table for GF(2) is:
×01
000
101
Multiplication yields 1 only when both inputs are 1, aligning with the conjunction (logical AND).[22][23] These operations map directly to binary hardware primitives, where addition corresponds to XOR gates for bitwise parity checks and multiplication to AND gates for bit-wise conjunctions, enabling efficient implementations in digital circuits and software for tasks like error-correcting codes.[24][10]

Algebraic Aspects

Finite Extensions

Finite extensions of GF(2) are finite fields GF(2^n) for integers n > 1, which serve as splitting fields for irreducible polynomials over GF(2). These fields have exactly 2^n elements and are unique up to isomorphism. Specifically, GF(2^n) can be constructed as the quotient ring GF(2)[x] / (p(x)), where p(x) is any monic irreducible polynomial of degree n over GF(2); the elements are then the residue classes of polynomials of degree less than n with coefficients in GF(2), and arithmetic is performed modulo p(x).[6] A concrete example is GF(4), obtained using the irreducible polynomial x2+x+1x^2 + x + 1 over GF(2). Let ω\omega be a root of this polynomial, so ω2=ω+1\omega^2 = \omega + 1. The elements of GF(4) are {0,1,ω,ω+1}\{0, 1, \omega, \omega + 1\}, with ω+1\omega + 1 satisfying (ω+1)2=ω(\omega + 1)^2 = \omega since addition and multiplication follow the usual rules modulo 2 and the polynomial. The nonzero elements form the multiplicative group {1,ω,ω+1}\{1, \omega, \omega + 1\}, where ω3=1\omega^3 = 1 and ω\omega is a primitive element.[6] The multiplicative group of GF(2^n), denoted GF(2^n)^\times, is cyclic of order 2^n - 1. This means there exists a primitive element α∈\alpha \in GF(2^n) such that every nonzero element is a power of α\alpha, i.e., GF(2^n)^\times = {\alpha^0, \alpha^1, \dots, \alpha^{2^n - 2}}. The cyclicity follows from the structure of finite fields, where the group order divides the exponent of the field and maximal order elements generate the group.[6] The Galois group of the extension GF(2^n)/GF(2) is generated by the Frobenius automorphism σ:x↦x2\sigma: x \mapsto x^2, which is a field automorphism fixing GF(2) pointwise. Since σn=id\sigma^n = \mathrm{id} but σk≠id\sigma^k \neq \mathrm{id} for 1 ≤ k < n, the Galois group is cyclic of order n, isomorphic to Z/nZ\mathbb{Z}/n\mathbb{Z}. This automorphism plays a key role in the structure of finite fields of characteristic 2.[6] Subfields of GF(2^n) correspond to divisors of n: for each d dividing n, there is a unique subfield of order 2^d. In particular, the tower law implies that GF(2^{mn}) contains GF(2^m) as a subfield, with [GF(2^{mn}) : GF(2^m)] = n, forming a chain of extensions GF(2) \subset GF(2^m) \subset GF(2^{mn}). This structure allows iterative construction of larger fields from smaller ones.[6]

Algebraic Closure

The algebraic closure of GF(2), denoted GF(2)‾\overline{\mathrm{GF}(2)}, is the union of all its finite extensions GF(2n)\mathrm{GF}(2^n) for n=1,2,…n = 1, 2, \dots.[25] This construction yields an infinite field containing exactly one subfield isomorphic to GF(2n)\mathrm{GF}(2^n) for each positive integer nn, with GF(2m)⊆GF(2n)\mathrm{GF}(2^m) \subseteq \mathrm{GF}(2^n) if and only if mm divides nn.[25] As the algebraic closure, GF(2)‾\overline{\mathrm{GF}(2)} is algebraically closed, meaning it is the smallest field extension of GF(2) in which every non-constant polynomial with coefficients in GF(2) factors completely into linear factors.[25] All roots of such polynomials lie within some finite extension GF(2n)\mathrm{GF}(2^n), ensuring that GF(2)‾\overline{\mathrm{GF}(2)} captures all algebraic elements over GF(2) without including transcendental extensions.[26] The field GF(2)‾\overline{\mathrm{GF}(2)} has characteristic 2, inheriting this property from GF(2), and is countable as an infinite union of finite fields.[26] GF(2) itself is a perfect field, since finite fields of characteristic pp are perfect: every element is a pp-th power, and the Frobenius endomorphism x↦xpx \mapsto x^p (here p=2p=2, so x↦x2x \mapsto x^2) is an automorphism.[25] Consequently, every algebraic extension of GF(2), including GF(2)‾\overline{\mathrm{GF}(2)}, is separable, as perfect fields have the property that all irreducible polynomials are separable and all algebraic extensions are separable.[25] This separability ensures that the Galois group of GF(2)‾\overline{\mathrm{GF}(2)} over GF(2) is profinite, isomorphic to the profinite completion of the integers Z^\hat{\mathbb{Z}}, generated topologically by the Frobenius automorphism.[26]

Applications

In Coding Theory

In coding theory, linear codes over GF(2) form a fundamental class of error-correcting codes, defined as subspaces of the vector space GF(2)^n, where n is the code length. Each codeword is a vector in GF(2)^n with entries in {0,1}, and the code's dimension k corresponds to the number of information bits, yielding 2^k codewords. The minimum distance d of the code, which determines its error-correcting capability, is the minimum Hamming weight (number of 1s) among nonzero codewords. These codes are particularly suited to binary channels due to the field's characteristic 2, where addition is modulo 2, simplifying computations like parity checks. A linear [n,k,d]_2 code can be generated by a k × n generator matrix G whose rows form a basis for the code subspace; any codeword c is then c = u G for a message vector u in GF(2)^k. The dual view uses an (n-k) × n parity-check matrix H such that c H^T = 0 for all codewords c, ensuring the code is the null space of H. Both G and H have entries in {0,1}, and operations like matrix multiplication over GF(2) use XOR for addition. For error correction, syndrome decoding computes the syndrome s = r H^T for a received vector r = c + e (where e is the error vector), which equals H e^T; if errors are sparse, s identifies e via a lookup table or linear functionals, as distinct low-weight errors produce unique syndromes. A seminal example is the Hamming code, a [7,4,3]_2 linear code that corrects single errors and detects double errors, constructed with H whose columns are all nonzero vectors in GF(2)^3. Developed by Richard Hamming in 1950 at Bell Labs to address errors in early computing equipment like the UNIVAC, it was motivated by unreliable vacuum-tube failures during long calculations.[27] Simpler examples include the binary repetition code, such as the [3,1,3]_2 code repeating each bit thrice (codewords 000, 111), which corrects single errors by majority vote, and the even-weight code, the [n,n-1,2]_2 subcode of GF(2)^n where all codewords have even parity (weight even), useful for single-error detection via a single parity-check bit. These codes are analyzed over the binary symmetric channel (BSC), a model where each bit flips independently with probability p < 1/2, quantifying error performance through metrics like bit error rate after decoding.

In Computer Science and Cryptography

In computer science, operations over GF(2) underpin binary arithmetic at the hardware level, where addition corresponds to the bitwise XOR operation and multiplication to the bitwise AND operation, enabling efficient computation on standard CPUs.[28] These bitwise instructions, such as XOR for vector addition in GF(2)-based vector spaces and AND for scalar multiplication by 0 or 1, form the foundation of low-level programming and are optimized in processor architectures for parallel processing of binary data.[2] In cryptography, GF(2) extensions play a central role in block and stream ciphers. The Advanced Encryption Standard (AES), based on the Rijndael algorithm, computes its substitution box (S-box) using multiplicative inversion in the finite field GF(2^8), defined by the irreducible polynomial $ x^8 + x^4 + x^3 + x + 1 $, followed by an affine transformation over GF(2) with a specific 8×8 matrix and constant vector to enhance nonlinearity and diffusion.[29] Stream ciphers like Trivium generate keystreams through nonlinear feedback shift registers and linear feedback mechanisms operating entirely over GF(2), where state updates use XOR for addition and modular reductions via primitive polynomials.[30] Boolean satisfiability (SAT) solvers leverage GF(2) to model problems involving parity constraints, representing XOR clauses as linear equations over GF(2) that can be solved via Gaussian elimination integrated into conflict-driven clause learning frameworks.[31] This approach efficiently handles systems where variables are binary and equations enforce linear dependencies, as seen in cryptographic analysis and circuit verification tasks.[32] Field-programmable gate arrays (FPGAs) exploit GF(2) arithmetic for high-performance implementations, particularly multipliers and inverters over GF(2^m), using systolic architectures or lookup tables to achieve low latency and resource efficiency in applications like elliptic curve cryptography.[33] For instance, Gaussian elimination for solving large linear systems over GF(2) on FPGAs employs pipelined processing elements to parallelize row operations, outperforming software on sparse matrices common in error-correcting decoders.[34] A prominent example is the McEliece cryptosystem, a code-based public-key scheme proposed in 1978, which relies on binary Goppa codes over GF(2) for encryption and efficient decoding, offering resistance to quantum attacks by hiding the code's structure in a disguised generator matrix.[35]

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  4. [PDF] Hamming Codes
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  6. [PDF] how to construct them, properties of elements in a finite field, and ...
  7. [PDF] Galois Fields - MIT
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  10. Manipulation of Binary Messages as Polynomials in GF(2)
  11. [PDF] Çetin Kaya Koç - Koc Lab
  12. Finite Field - an overview | ScienceDirect Topics
  13. AATA Structure of a Finite Field - Abstract Algebra
  14. [PDF] Rings of characteristics 2 may not be Boolean
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  20. [PDF] Abstract Algebra Paul Garrett
  21. [PDF] A History of Galois fields - HAL
  22. https://www.sciencedirect.com/science/article/pii/B0122274105003379
  23. [PDF] Optimizing Galois Field Arithmetic for Diverse Processor ...
  24. [PDF] CS252 Graduate Computer Architecture Lecture 18 Error Correction
  25. [PDF] Fields and Galois Theory - James Milne
  26. (PDF) Algebraic Closure of Finite Fields - ResearchGate
  27. https://ieeexplore.ieee.org/document/6772729
  28. [PDF] Optimizing Galois Field Arithmetic for Diverse Processor ...
  29. [PDF] The Rijndael Block Cipher - NIST Computer Security Resource Center
  30. [PDF] Trivium Specifications*
  31. [PDF] When Boolean Satisfiability Meets Gaussian Elimination in a ...
  32. Synthesizing shortest linear straight-line programs over GF(2) using ...
  33. FPGA implementation of an efficient multiplier over finite fields GF(2 ...
  34. [PDF] Solving Large Systems of Linear Equations over GF(2) on FPGAs
  35. [PDF] A Public-Key Cryptosystem Based On Algebraic Coding Theory
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