Disjunct matrix

In mathematics, a logical matrix may be described as d-disjunct and/or d-separable. These concepts play a pivotal role in the mathematical area of non-adaptive group testing.

In the mathematical literature, d-disjunct matrices may also be called super-imposed codes^{[citation needed]} or d-cover-free families.^[1]

According to Chen and Hwang (2006),^[2]

A matrix is said to be d-separable if no two sets of d columns have the same boolean sum.
A matrix is said to be ${\overline {d}}$ -separable (that's d with an overline) if no two sets of d-or-fewer columns have the same boolean sum.
A matrix is said to be d-disjunct if no set of d columns has a boolean sum which is a superset of any other single column.

The following relationships are "well-known":^[2]

Every ${\overline {d+1}}$ -separable matrix is also $d$ -disjunct.^[2]
Every $d$ -disjunct matrix is also ${\overline {d}}$ -separable.^[2]
Every ${\overline {d}}$ -separable matrix is also $d$ -separable (by definition).

Concrete examples edit

The following $6\times 8$ matrix is 2-separable, because each pair of columns has a distinct sum. For example, the boolean sum (that is, the bitwise OR) of the first two columns is $110000\lor 001100=111100$ ; that sum is not attainable as the sum of any other pair of columns in the matrix.

However, this matrix is not 3-separable, because the sum of columns 1, 2, and 3 (namely $111111$ ) equals the sum of columns 1, 4, and 5.

This matrix is also not ${\overline {2}}$ -separable, because the sum of columns 1 and 8 (namely $110000$ ) equals the sum of column 1 alone. In fact, no matrix with an all-zero column can possibly be ${\overline {d}}$ -separable for any $d\geq 1$ .

$\quad \left[{\begin{array}{cccccccc}1&0&0&1&1&0&0&0\\1&0&0&0&0&1&1&0\\0&1&0&1&0&1&0&0\\0&1&0&0&1&0&1&0\\0&0&1&0&1&1&0&0\\0&0&1&1&0&0&1&0\\\end{array}}\right]$

The following $6\times 4$ matrix is ${\overline {3}}$ -separable (and thus 2-disjunct) but not 3-disjunct.

$\quad \left[{\begin{array}{cccc}1&0&0&1\\1&0&1&0\\0&1&1&0\\0&1&0&0\\0&0&1&0\\0&0&0&1\\\end{array}}\right]$

There are 15 possible ways to choose 3-or-fewer columns from this matrix, and each choice leads to a different boolean sum:

columns	boolean sum	columns	boolean sum
none	000000	2,3	011110
1	110000	2,4	101101
2	001100	3,4	111011
3	011010	1,2,3	111110
4	100001	1,2,4	111101
1,2	111100	1,3,4	111011
1,3	111010	2,3,4	111111
1,4	110001

However, the sum of columns 2, 3, and 4 (namely $111111$ ) is a superset of column 1 (namely $110000$ ), which means that this matrix is not 3-disjunct.

Application of d-separability to group testing edit

The non-adaptive group testing problem postulates that we have a test which can tell us, for any set of items, whether that set contains a defective item. We are asked to come up with a series of groupings that can exactly identify all the defective items in a batch of n total items, some d of which are defective.

A $d$ -separable matrix with $t$ rows and $n$ columns concisely describes how to use t tests to find the defective items in a batch of n, where the number of defective items is known to be exactly d.

A $d$ -disjunct matrix (or, more generally, any ${\overline {d}}$ -separable matrix) with $t$ rows and $n$ columns concisely describes how to use t tests to find the defective items in a batch of n, where the number of defective items is known to be no more than d.

Practical concerns and published results edit

In the limit, for a given n and d, the number of rows t in the smallest d-separable $t\times n$ matrix will tend to be smaller than the number of rows t in the smallest d-disjunct $t\times n$ matrix.^{[citation needed]} However, if the matrix is to be used for practical testing, some algorithm is needed that can "decode" a test result (that is, a boolean sum such as $111100$ ) into the indices of the defective items (that is, the unique set of columns that produce that boolean sum). For arbitrary d-disjunct matrices, polynomial-time decoding algorithms are known; the naïve algorithm is $O(nt)$ .^[3] For arbitrary d-separable but non-d-disjunct matrices, the best known decoding algorithms are exponential-time.^{[citation needed]}

Porat and Rothschild (2008) present a deterministic $O(nt)$ -time algorithm for constructing a d-disjoint matrix with n columns and $\Theta (d^{2}\ln n)$ rows.^[4]

References edit

^ Paul Erdős; Péter Frankl; Zoltán Füredi (1985). "Families of finite sets in which no set is covered by the union of r others" (PDF). Israel Journal of Mathematics. 51 (1–2): 79–89. doi:10.1007/BF02772959. ISSN 0021-2172.
^ ^a ^b ^c ^d Hong-Bin Chen; Frank Hwang (2006-12-21). "Exploring the missing link among d-separable, d-separable and d-disjunct matrices". Discrete Applied Mathematics. 155 (5): 662–664. CiteSeerX 10.1.1.848.5161. doi:10.1016/j.dam.2006.10.009.
^ Piotr Indyk; Hung Q. Ngo; Atri Rudra (2010). "Efficiently Decodable Non-adaptive Group Testing". Proceedings of the 21st ACM-SIAM Symposium on Discrete Algorithms (SODA). hdl:1721.1/63167. ISSN 1071-9040.
^ Ely Porat; Amir Rothschild (2008). "Explicit Non-Adaptive Combinatorial Group Testing Schemes". Proceedings of the 35th International Colloquium on Automata, Languages and Programming (ICALP): 748–759. arXiv:0712.3876. Bibcode:2007arXiv0712.3876P.

Disjunct matrix

Contents

Concrete examples edit

Application of d-separability to group testing edit

Practical concerns and published results edit

See also edit

References edit

Further reading edit