Let be distinct elements of a finite field , with . The Reed-Solomon code consists of the evaluation vectors
Evaluation is an injective linear map: a nonzero polynomial of degree at most cannot vanish at all distinct points. Thus the dimension is . The same bound on polynomial roots shows that every nonzero codeword has Hamming weight at least . Conversely, choosing any evaluation points and taking their product of linear factors gives a polynomial whose evaluation vanishes at exactly those points. Its Hamming weight is . Hence
For completeness, deleting coordinates from a linear code of minimum Hamming distance is injective on codewords, since two words with the same retained coordinates would differ in fewer than positions. Therefore , giving the Singleton bound . The Reed-Solomon code attains this bound and is a maximum distance separable code. Multiplying individual coordinates by nonzero field elements changes neither the dimension nor the Hamming weight, so the same proof applies to a generalized Reed-Solomon code.
To specify the generator polynomials of a cyclic code unambiguously, use the primitive cyclic Reed-Solomon code convention. Put , choose a primitive element of a finite field , and set
Exponents are taken modulo . This generator polynomial is a monic polynomial of degree dividing , so the dimension is . It agrees with the evaluation form
Indeed, at a defining exponent , a monomial contributes the finite geometric series . Its exponent lies between and , so the sum vanishes: but its th power is one. Every displayed evaluation vector therefore lies in the cyclic code, and both spaces have dimension , proving equality. The narrow-sense choice is the ordinary unweighted evaluation linear code on all nonzero field elements.
The duality of primitive cyclic Reed-Solomon codes now follows directly. A vector in has coordinates , while a vector in has coordinates , with . Their dot product is . Every appearing exponent is between and , so every such finite geometric series is zero. The two spaces are orthogonal and their dimensions sum to , giving
Thus the full cyclic family is closed under dual codes. The offset matters: the dual code of the narrow-sense linear code generally has offset zero, rather than one.
For arbitrary evaluation points, the precise statement is closure of generalized Reed-Solomon codes under duality. If , put and . Lagrange interpolation shows whenever : this sum is the coefficient of in the interpolation formula for . Taking with and proves orthogonality of and . Comparing dimensions gives equality with . An unweighted evaluation linear code at arbitrary points need not have an unweighted evaluation dual at the same points; the multiplier form and the cyclic offset formula resolve that convention issue.
For the length-, dimension- linear code, choose and as in the field table. Then and
The field characteristic is two, and the table gives . In the basis , the four roots are represented by . Their elementary symmetric functions are
The repeated terms in cancel because the field characteristic is two. There are no alternating minus signs in this characteristic, so
For example, the coefficient vectors in ascending order are , giving the required single powers of .
For the length-, dimension- linear code over , take the table's primitive element of a finite field and again . The four roots are . Expanding in gives
Thus
The coefficients are reduced modulo , including the constant term .
A suitable two-error-correcting Reed-Solomon code over is precisely the first linear code:
Two distinct codewords cannot both be within Hamming distance two of a received word, because the triangle inequality would put them at distance at most four. Thus this linear code corrects any two symbol errors. Its generator polynomial has four consecutive defining zeros of a cyclic code, and its dimension and exact minimum Hamming distance have already been proved.

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