Sub-latin squares and incomplete orthogonal arrays

The main result of this paper is that for any pair of orthogonal Latin squares of side k, there will exist for all sufficiently large n a pair of orthogonal Latin squares with the first pair as orthogonal sub-squares. The orthogonal array corresponding to a set of pairwise orthogonal Latin squares, minus the sub-array corresponding to orthogonal sub-squares is called an incomplete orthogonal array; this concept is generalized slightly.     

Incomplete orthogonal arrays and idempotent orthogonal arrays

First, we shall define idempotent orthogonal arrays and notice that idempotent orthogonal array of strength two are idempotent mutually orthogonal quasi-groups. Then, we shall state some properties of idempotent orthogonal arrays.Next, we shall prove that, starting from an incomplete orthogonal arrayT _EF based onE andF E, from an orthogonal arrayT _G based onG = E – F and from an idempotent orthogonal arrayT _H based onH, we are able to construct an incomplete orthogonal arrayT _(F(G×H))F based onF(G × H) andF. Finally, we shall show the relationship between the construction which lead us to this result and the singular direct product of mutually orthogonal quasi-groups given by Sade [5].     

On the existence of nested orthogonal arrays

A nested orthogonal array is an OA(N,k,s,g) which contains an OA(M,k,r,g) as a subarray. Here r<s and M<N. Necessary conditions for the existence of such arrays are obtained in the form of upper bounds on k, given N, M, s, r and g. Examples are given to show that these bounds are quite powerful in proving nonexistence. The link with incomplete orthogonal arrays is also indicated.     

Construction of nested orthogonal arrays

A (symmetric) nested orthogonal array is a symmetric orthogonal array OA(N,k,s,g) which contains an OA(M,k,r,g) as a subarray, where M<N and r<s. In this communication, some methods of construction of nested symmetric orthogonal arrays are given. Asymmetric nested orthogonal arrays are defined and a few methods of their construction are described.     

Constructions of augmented orthogonal arrays

Augmented orthogonal arrays (AOAs) were introduced by Stinson, who showed the equivalence between ideal ramp schemes and AOAs (Discrete Math. 341 (2018), 299–307). In this paper, we show that there is an AOA if and only if there is an OA which can be partitioned into subarrays, each being an OA, and that there is a linear AOA if and only if there is a linear maximum distance separable (MDS) code of length and dimension over , which contains a linear MDS subcode of length and dimension over . Some constructions for AOAs and some new infinite classes of AOAs are also given.     

On orthogonal arrays of strength 3 and 5 achieving Rao's bound

It is shown that ifA is an orthogonal array (N, n, q, 3) achieving Rao's bound, thenA is either

1. an orthogonal array (2n, n, 2, 3) withn ≡ 0 (mod 4), or
2. an orthogonal array (q ³,q + 2,q, 3) withq even.

This result should be compared with a theorem of P.J. Cameron on extendable symmetric designs. It is also shown that ifA is an orthogonal array (N, n, q, 5) achieving Rao's bound, thenA is either the orthogonal array (32, 6, 2, 5) or the orthogonal array (3⁶, 12, 3, 5).     

Numerical study on incomplete orthogonal factorization preconditioners

We design, analyse and test a class of incomplete orthogonal factorization preconditioners constructed from Givens rotations, incorporating some dropping strategies and updating tricks, for the solution of large sparse systems of linear equations. Comprehensive accounts about how the preconditioners are coded, what storage is required and how the computation is executed for a given accuracy are presented. A number of numerical experiments show that these preconditioners are competitive with standard incomplete triangular factorization preconditioners when they are applied to accelerate Krylov subspace iteration methods such as GMRES and BiCGSTAB.     

Constructions of new orthogonal arrays and covering arrays of strength three

A covering array of size N, strength t, degree k, and order v, or a CA(N;t,k,v) in short, is a k×N array on v symbols. In every t×N subarray, each t-tuple column vector occurs at least once. When ‘at least’ is replaced by ‘exactly’, this defines an orthogonal array, OA(t,k,v). A difference covering array, or a DCA(k,n;v), over an abelian group G of order v is a k×n array (aij) (1?i?k, 1?j?n) with entries from G, such that, for any two distinct rows l and h of D (1?l<h?k), the difference list Δlh={dh1−dl1,dh2−dl2,…,dhn−dln} contains every element of G at least once.Covering arrays have important applications in statistics and computer science, as well as in drug screening. In this paper, we present two constructive methods to obtain orthogonal arrays and covering arrays of strength 3 by using DCAs. As a consequence, it is proved that there are an OA(3,5,v) for any integer v?4 and v?2 (mod 4), and an OA(3,6,v) for any positive integer v satisfying gcd(v,4)≠2 and gcd(v,18)≠3. It is also proved that the size CAN(3,k,v) of a CA(N;3,k,v) cannot exceed v³+v² when k=5 and v≡2 (mod 4), or k=6, v≡2 (mod 4) and gcd(v,18)≠3.     

Bounds on orthogonal arrays and resilient functions

The only known general bounds on the parameters of orthogonal arrays are those given by Rao in 1947 [J. Roy. Statist. Soc. 9 (1947), 128–139] for general OA_γ(t,k,v) and by Bush [Ann. Math. Stat. 23, (1952), 426–434] [3] in 1952 for the special case γ = 1. We present an algebraic method based on characters of homocyclic groups which yields the Rao bounds, the Bush bound in case t ? v, and more importantly a new explicit bound which for large values of t (the strength of the array) is much better than the Rao bound. In the case of binary orthogonal arrays where all rows are distinct this bound was previously proved by Friedman [Proc. 33rd IEEE Symp. on Foundations of Comput. Sci., (1992), 314–319] in a different setting. We also note an application to resilient functions. © 1995 John Wiley & Sons, inc.     

On finding mixed orthogonal arrays of strength 2 with many 2-level factors

We describe a method for finding mixed orthogonal arrays of strength 2 with a large number of 2-level factors. The method starts with an orthogonal array of strength 2, possibly tight, that contains mostly 2-level factors. By a computer search of this starting array, we attempt to find as large a number of 2-level factors as possible that can be used in a new orthogonal array of strength 2 containing one additional factor at more than two levels. The method produces new orthogonal arrays for some parameters, and matches the best-known arrays for others. It is especially useful for finding arrays with one or two factors at more than two levels.     

Ideal ramp schemes and augmented orthogonal arrays

Ramp schemes were invented in 1985 by C.R. Blakley and C. Meadows. An $(s,t,n)$-ramp scheme is a generalization of a threshold scheme in which there are two thresholds. Recently, D.R. Stinson established the equivalence of ideal ramp schemes and augmented orthogonal arrays. In this study, some new construction methods for augmented orthogonal arrays are presented and then some new augmented orthogonal arrays are obtained; furthermore, we also provide parameter situations where ideal ramp schemes exist for these obtained augmented orthogonal arrays.     

On the spectrum of resolvable orthogonal arrays invariant under the Klein group K4

It is shown that there exists a resolvablen ² by 4 orthogonal array which is invariant under the Klein 4-groupK ₄ for all positive integersn congruent to 0 modulo 4 except possibly forn {12, 24, 156, 348}.     

Constructions of optimal orthogonal arrays with repeated rows

We construct orthogonal arrays ${\mathsf{OA}}_{\lambda }(k,n)$ (of strength two) having a row that is repeated $m$ times, where $m$ is as large as possible. In particular, we consider OAs where the ratio $m∕\lambda$ is as large as possible; these OAs are termed optimal. We provide constructions of optimal OAs for any $k\ge n+1$, albeit with large $\lambda$. We also study basic OAs; these are optimal OAs in which $gcd(m,\lambda )=1$. We construct a basic OA with $n=2$ and $k=4t+1$, provided that a Hadamard matrix of order $8t+4$ exists. This completely solves the problem of constructing basic OAs with $n=2$, modulo the Hadamard matrix conjecture.     

Generalized latin matrix and construction of orthogonal arrays

In this paper, generalized Latin matrix and orthogonal generalized Latin matrices are proposed. By using the property of orthogonal array, some methods for checking orthogonal generalized Latin matrices are presented. We study the relation between orthogonal array and orthogonal generalized Latin matrices and obtain some useful theorems for their construction. An example is given to illustrate applications of main theorems and a new class of mixed orthogonal arrays are obtained.     

Generalized orthogonal arrays: Constructions and related graphs

Generalized orthogonal arrays were first defined to provide a combinatorial characterization of (t, m, s)-nets. In this article we describe three new constructions for generalized orthogonal arrays. Two of these constructions are straightforward generalizations of constructions for orthogonal arrays and one employs new techniques. We construct families of generalized orthogonal arrays using orthogonal arrays and provide net parameters obtained from our constructions. In addition, we define a set of graphs associated with a generalized orthogonal array which provide information about the structure of the array. © 1999 John Wiley & Sons, Inc. J Combin Designs 7: 31–39, 1999     

A survey of orthogonal arrays of strength two

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Orthogonal F-rectangles,orthogonal arrays,and codes

The relationships between a set of orthogonal F-squares or F-rectangles and orthogonal arrays are described. The relationship between orthogonal arrays and error-correcting codes is demonstrated. The development of complete sets of orthogonal F-rectangles allows construction of codes of any word length and for any number of words. Likewise, the development of F-rectangle theory makes code construction much more flexible in terms of a variable number of symbols. The relationship among sets of orthogonal hyperrectangles, orthogonal arrays, and codes is also described.     

Division of trinomials by pentanomials and orthogonal arrays

Consider a maximum-length binary shift-register sequence generated by a primitive polynomial f of degree m. Let denote the set of all subintervals of this sequence with length n, where m < n ≤ 2m, together with the zero vector of length n. Munemasa (Finite fields Appl, 4(3): 252–260, 1998) considered the case in which the polynomial f generating the sequence is a trinomial satisfying certain conditions. He proved that, in this case, corresponds to an orthogonal array of strength 2 that has a property very close to being an orthogonal array of strength 3. Munemasa’s result was based on his proof that very few trinomials of degree at most 2m are divisible by the given trinomial f. In this paper, we consider the case in which the sequence is generated by a pentanomial f satisfying certain conditions. Our main result is that no trinomial of degree at most 2m is divisible by the given pentanomial f, provided that f is not in a finite list of exceptions we give. As a corollary, we get that, in this case, corresponds to an orthogonal array of strength 3. This effectively minimizes the skew of the Hamming weight distribution of subsequences in the shift-register sequence. The authors are supported by NSERC of Canada.