Sparse ruler

Last updated

A sparse ruler is a ruler in which some of the distance marks may be missing. More abstractly, a sparse ruler of length with marks is a sequence of integers where . The marks and correspond to the ends of the ruler. In order to measure the distance , with there must be marks and such that .

Contents

A complete sparse ruler allows one to measure any integer distance up to its full length. A complete sparse ruler is called minimal if there is no complete sparse ruler of length with marks. In other words, if any of the marks is removed one can no longer measure all of the distances, even if the marks could be rearranged. A complete sparse ruler is called maximal if there is no complete sparse ruler of greater length with marks. Complete minimal rulers of length 135 and 136 require one more mark than those of lengths 124-134, 137 and 138. A sparse ruler is called optimal if it is both minimal and maximal.

Since the number of distinct pairs of marks is , this is an upper bound on the length of any maximal sparse ruler with marks. This upper bound can be achieved only for 2, 3 or 4 marks. For larger numbers of marks, the difference between the optimal length and the bound grows gradually, and unevenly.

For example, for 6 marks the upper bound is 15, but the maximal length is 13. There are 3 different configurations of sparse rulers of length 13 with 6 marks. One is {0, 1, 2, 6, 10, 13}. To measure a length of 7, say, with this ruler one would take the distance between the marks at 6 and 13.

A Golomb ruler is a sparse ruler that requires all of the differences be distinct. In general, a Golomb ruler with marks will be considerably longer than an optimal sparse ruler with marks, since is a lower bound for the length of a Golomb ruler. A long Golomb ruler will have gaps, that is, it will have distances which it cannot measure. For example, the optimal Golomb ruler {0, 1, 4, 10, 12, 17} has length 17, but cannot measure lengths of 14 or 15.

Wichmann rulers

Many optimal rulers are of the form where represents segments of length . Thus, if and , then has (in order):
1 segment of length 1,
1 segment of length 2,
1 segment of length 3,
2 segments of length 7,
2 segments of length 4,
1 segment of length 1.

A minor variant is , with a length one less than .

gives the ruler {0, 1, 3, 6, 13, 20, 24, 28, 29}, while gives {0, 1, 3, 6, 9, 16, 23, 27, 28}. The length of a Wichmann ruler is and the number of marks is . Note that not all Wichmann rulers are optimal and not all optimal rulers can be generated this way. None of the optimal rulers of length 1, 13, 17, 23 and 58 follow this pattern. That sequence ends with 58 if the Optimal Ruler Conjecture of Peter Luschny is correct. The conjecture is known to be true to length 213. [1]

Asymptotics

For every let be the smallest number of marks for a ruler of length . For example, . The asymptotic of the function was studied by Erdos, Gal [2] (1948) and continued by Leech [3] (1956) who proved that the limit exists and is lower and upper bounded by

Much better upper bounds exist for -perfect rulers. Those are subsets of such that each positive number can be written as a difference for some . For every number let be the smallest cardinality of an -perfect ruler. It is clear that . The asymptotics of the sequence was studied by Redei, Renyi [4] (1949) and then by Leech (1956) and Golay [5] (1972). Due to their efforts the following upper and lower bounds were obtained:

Define the excess as . In 2020, Pegg proved by construction that ≤ 1 for all lengths . [6] If the Optimal Ruler Conjecture is true, then for all , leading to the ″dark mills″ pattern when arranged in columns, OEIS A326499. [7] All of the windows in the dark mills pattern are Wichmann rulers. None of the best known sparse rulers are proven minimal as of Sep 2020. Many of the current best known constructions for are believed to non-minimal, especially the "cloud" values.

Examples

The following are examples of minimal sparse rulers. Optimal rulers are highlighted. When there are too many to list, not all are included. Mirror images are not shown.

LengthMarksNumberExamplesList FormWichmann
121II{0, 1}
231III{0, 1, 2}
331II.I{0, 1, 3}W(0,0)
442III.I
II.II
{0, 1, 2, 4}
{0, 1, 3, 4}
542III..I
II.I.I
{0, 1, 2, 5}
{0, 1, 3, 5}
641II..I.I{0, 1, 4, 6}W(0,1)
756IIII...I
III.I..I
III..I.I
II.I.I.I
II.I..II
II..II.I
{0, 1, 2, 3, 7}
{0, 1, 2, 4, 7}
{0, 1, 2, 5, 7}
{0, 1, 3, 5, 7}
{0, 1, 3, 6, 7}
{0, 1, 4, 5, 7}
854III..I..I
II.I...II
II..I.I.I
II...II.I
{0, 1, 2, 5, 8}
{0, 1, 3, 7, 8}
{0, 1, 4, 6, 8}
{0, 1, 5, 6, 8}
952III...I..I
II..I..I.I
{0, 1, 2, 6, 9}
{0, 1, 4, 7, 9}
-
W(0,2)
10619IIII..I...I{0, 1, 2, 3, 6, 10}
11615IIII...I...I{0, 1, 2, 3, 7, 11}
1267IIII....I...I
III...I..I..I
II.I.I.....II
II.I...I...II
II..II....I.I
II..I..I..I.I
II.....II.I.I
{0, 1, 2, 3, 8, 12}
{0, 1, 2, 6, 9, 12}
{0, 1, 3, 5, 11, 12}
{0, 1, 3, 7, 11, 12}
{0, 1, 4, 5, 10, 12}
{0, 1, 4, 7, 10, 12}
{0, 1, 7, 8, 10, 12}
-
-
-
-
-
W(0,3)
-
1363III...I...I..I
II..II.....I.I
II....I..I.I.I
{0, 1, 2, 6, 10, 13}
{0, 1, 4, 5, 11, 13}
{0, 1, 6, 9, 11, 13}
14765IIIII....I....I{0, 1, 2, 3, 4, 9, 14}
15740II.I..I...I...II
II..I..I..I..I.I
{0, 1, 3, 6, 10, 14, 15}
{0, 1, 4, 7, 10, 13, 15}
W(1,0)
W(0,4)
16716IIII....I...I...I{0, 1, 2, 3, 8, 12, 16}
1776IIII....I....I...I
III...I...I...I..I
III.....I...I.I..I
III.....I...I..I.I
II..I.....I.I..I.I
II......I..I.I.I.I
{0, 1, 2, 3, 8, 13, 17}
{0, 1, 2, 6, 10, 14, 17}
{0, 1, 2, 8, 12, 14, 17}
{0, 1, 2, 8, 12, 15, 17}
{0, 1, 4, 10, 12, 15, 17}
{0, 1, 8, 11, 13, 15, 17}
188250II..I..I..I..I..I.I{0, 1, 4, 7, 10, 13, 16, 18}W(0,5)
198163IIIII....I....I....I{0, 1, 2, 3, 4, 9, 14, 19}
20875IIIII.....I....I....I{0, 1, 2, 3, 4, 10, 15, 20}
21833IIIII.....I.....I....I{0, 1, 2, 3, 4, 10, 16, 21}
2289IIII....I....I....I...I
III.......I....I..I..II
II.I.I........II.....II
II.I..I......I...I...II
II.I.....I.....I...II.I
II..II......I.I.....I.I
II....II..I.......I.I.I
II....I..I......I.I.I.I
II.....II........II.I.I
{0, 1, 2, 3, 8, 13, 18, 22}
{0, 1, 2, 10, 15, 18, 21, 22}
{0, 1, 3, 5, 14, 15, 21, 22}
{0, 1, 3, 6, 13, 17, 21, 22}
{0, 1, 3, 9, 15, 19, 20, 22}
{0, 1, 4, 5, 12, 14, 20, 22}
{0, 1, 6, 7, 10, 18, 20, 22}
{0, 1, 6, 9, 16, 18, 20, 22}
{0, 1, 7, 8, 17, 18, 20, 22}
-
-
-
W(1,1)
-
-
-
-
-
2382III........I...I..I..I.I
II..I.....I.....I.I..I.I
{0, 1, 2, 11, 15, 18, 21, 23}
{0, 1, 4, 10, 16, 18, 21, 23}
249472IIIIII......I.....I.....I{0, 1, 2, 3, 4, 5, 12, 18, 24}
259230IIIIII......I......I.....I{0, 1, 2, 3, 4, 5, 12, 19, 25}
26983IIIII.....I....I.....I....I{0, 1, 2, 3, 4, 10, 15, 21, 26}
27928IIIII.....I.....I.....I....I{0, 1, 2, 3, 4, 10, 16, 22, 27}
2896III..........I....I..I..I..II
II.I.I.I..........II.......II
II.I..I..I......I......I...II
II.I.....I.....I.....I...II.I
II.....I...I........I..I.II.I
II.......II..........II.I.I.I
{0, 1, 2, 13, 18, 21, 24, 27, 28}
{0, 1, 3, 5, 7, 18, 19, 27, 28}
{0, 1, 3, 6, 9, 16, 23, 27, 28}
{0, 1, 3, 9, 15, 21, 25, 26, 28}
{0, 1, 7, 11, 20, 23, 25, 26, 28}
{0, 1, 9, 10, 21, 22, 24, 26, 28}
2993III...........I...I..I..I..I.I
II.I..I......I......I...I...II
II..I.....I.....I.....I.I..I.I
{0, 1, 2, 14, 18, 21, 24, 27, 29}
{0, 1, 3, 6, 13, 20, 24, 28, 29}
{0, 1, 4, 10, 16, 22, 24, 27, 29}
-
W(1,2)
-
35105III..............I...I..I..I..I..I.I
II.I..I..I......I......I......I...II
II.I..I..I.........I...I......I...II
II..II..........I.I......I.I.....I.I
II..I.....I.....I.....I.....I.I..I.I
{0, 1, 2, 17, 21, 24, 27, 30, 33, 35}
{0, 1, 3, 6, 9, 16, 23, 30, 34, 35}
{0, 1, 3, 6, 9, 19, 23, 30, 34, 35}
{0, 1, 4, 5, 16, 18, 25, 27, 33, 35}
{0, 1, 4, 10, 16, 22, 28, 30, 33, 35}
36101II.I..I......I......I......I...I...II{0, 1, 3, 6, 13, 20, 27, 31, 35, 36}W(1,3)
43111II.I..I......I......I......I......I...I...II{0, 1, 3, 6, 13, 20, 27, 34, 38, 42, 43}W(1,4)
4612342III..I....I....I..........I.....I.....I.....III{0, 1, 2, 5, 10, 15, 26, 32, 38, 44, 45, 46}W(2,1)
50122IIII...................I....I...I...I...I...I..I..I
II.I..I......I......I......I......I......I...I...II
{0, 1, 2, 3, 23, 28, 32, 36, 40, 44, 47, 50}
{0, 1, 3, 6, 13, 20, 27, 34, 41, 45, 49, 50}
-
W(1,5)
571312III..I....I....I..........I..........I.....I.....I.....III
II.I..I......I......I......I......I......I......I...I...II
{0, 1, 2, 5, 10, 15, 26, 37, 43, 49, 55, 56, 57}
{0, 1, 3, 6, 13, 20, 27, 34, 41, 48, 52, 56, 57}
W(2,2)
W(1,6)
58136IIII.......................I....I...I...I...I...I...I..I..I
III...I.I........I........I........I........I..I......I..II
III.....I......II.........I.........I.........I..I...I.I..I
II.I..I..........I..I......I.......I.........I...I...I...II
II.I..I..........I......I..I..........I......I...I...I...II
II...I..I...I........I........I........I........I....II.I.I
{0, 1, 2, 3, 27, 32, 36, 40, 44, 48, 52, 55, 58}
{0, 1, 2, 6, 8, 17, 26, 35, 44, 47, 54, 57, 58}
{0, 1, 2, 8, 15, 16, 26, 36, 46, 49, 53, 55, 58}
{0, 1, 3, 6, 17, 20, 27, 35, 45, 49, 53, 57, 58}
{0, 1, 3, 6, 17, 24, 27, 38, 45, 49, 53, 57, 58}
{0, 1, 5, 8, 12, 21, 30, 39, 48, 53, 54, 56, 58}
68142III..I....I....I..........I..........I..........I.....I.....I.....III
III.....I......II.........I.........I.........I.........I..I...I.I..I
{0, 1, 2, 5, 10, 15, 26, 37, 48, 54, 60, 66, 67, 68}
{0, 1, 2, 8, 15, 16, 26, 36, 46, 56, 59, 63, 65, 68}
W(2,3)
-
79151III..I....I....I..........I..........I..........I..........I.....I.....I.....III{0, 1, 2, 5, 10, 15, 26, 37, 48, 59, 65, 71, 77, 78, 79}W(2,4)
90161III..I....I....I..........I..........I..........I..........I..........I.....I.....I.....III{0, 1, 2, 5, 10, 15, 26, 37, 48, 59, 70, 76, 82, 88, 89, 90}W(2,5)
101171III..I....I....I..........I..........I..........I..........I..........I..........I.....I.....I.....III{0,1,2,5,10,15,26,37,48,59,70,81,87,93,99,100,101}W(2,6)
112181III..I....I....I..........I..........I..........I..........I..........I..........I..........I.....I.....I.....III{0,1,2,5,10,15,26,37,48,59,70,81,92,98,104,110,111,112}W(2,7)
123192IIII...I......I......I......I..............I..............I..............I..............I.......I.......I.......I.......IIII

III..I....I....I..........I..........I..........I..........I..........I..........I..........I..........I.....I.....I.....III

{0,1,2,3,7,14,21,28,43,58,73,88,96,104,112,120,121,122,123}
{0,1,2,5,10,15,26,37,48,59,70,81,92,103,109,115,121,122,123}
W(3,4)
W(2,8)
138201IIII...I......I......I......I..............I..............I..............I..............I..............I.......I.......I.......I.......IIII{0,1,2,3,7,14,21,28,43,58,73,88,103,111,119,127,135,136,137,138}W(3,5)

Incomplete sparse rulers

A few incomplete rulers can fully measure up to a longer distance than an optimal sparse ruler with the same number of marks. , , , and can each measure up to 18, while an optimal sparse ruler with 7 marks can measure only up to 17. The table below lists these rulers, up to rulers with 13 marks. Mirror images are not shown. Rulers that can fully measure up to a longer distance than any shorter ruler with the same number of marks are highlighted.

MarksLengthMeasures up toRuler
72418{0, 2, 7, 14, 15, 18, 24}
72518{0, 2, 7, 13, 16, 17, 25}
73118{0, 5, 7, 13, 16, 17, 31}
73118{0, 6, 10, 15, 17, 18, 31}
83924{0, 8, 15, 17, 20, 21, 31, 39}
106437{0, 7, 22, 27, 28, 31, 39, 41, 57, 64}
107337{0, 16, 17, 28, 36, 42, 46, 49, 51, 73}
116844{0, 7, 10, 27, 29, 38, 42, 43, 44, 50, 68}
119145{0, 18, 19, 22, 31, 42, 48, 56, 58, 63, 91}
125351{0, 2, 3, 6, 9, 17, 25, 33, 41, 46, 51, 53}
126051{0, 5, 9, 13, 19, 26, 33, 48, 49, 50, 51, 60}
127351{0, 2, 3, 10, 17, 23, 35, 42, 46, 47, 51, 73}
127551{0, 2, 10, 13, 29, 33, 36, 45, 50, 51, 57, 75}
128251{0, 8, 28, 31, 34, 38, 45, 47, 49, 50, 74, 82}
128351{0, 2, 10, 24, 25, 29, 36, 42, 45, 73, 75, 83}
128551{0, 8, 10, 19, 35, 41, 42, 47, 55, 56, 59, 85}
128751{0, 12, 24, 26, 37, 39, 42, 43, 46, 47, 75, 87}
136159{0, 2, 3, 6, 9, 17, 25, 33, 41, 49, 54, 59, 61}
136959{0, 6, 10, 15, 22, 30, 38, 55, 56, 57, 58, 59, 69}
136959{0, 6, 11, 15, 22, 30, 38, 55, 56, 57, 58, 59, 69}
138259{0, 4, 5, 9, 25, 27, 39, 42, 50, 53, 56, 63, 82}
138359{0, 1, 2, 24, 34, 36, 38, 43, 51, 54, 57, 82, 83}
138859{0, 1, 3, 9, 16, 26, 36, 40, 47, 54, 58, 59, 88}
138859{0, 1, 5, 29, 34, 36, 47, 48, 50, 56, 58, 73, 88}
139059{0, 7, 12, 16, 37, 38, 43, 55, 56, 57, 58, 66, 90}
139159{0, 5, 9, 12, 16, 32, 38, 42, 55, 56, 57, 63, 91}
139259{0, 6, 10, 13, 25, 34, 39, 54, 55, 56, 57, 65, 92}
139459{0, 1, 3, 16, 28, 37, 45, 48, 54, 55, 59, 78, 94}
139559{0, 4, 32, 37, 38, 40, 48, 53, 54, 56, 63, 83, 95}
139659{0, 3, 7, 27, 37, 39, 50, 55, 56, 58, 72, 81, 96}
1310159{0, 4, 24, 37, 43, 45, 52, 54, 55, 59, 77, 81, 101}
1310859{0, 8, 17, 40, 50, 53, 64, 65, 69, 71, 91, 99, 108}
1311361{0, 6, 22, 36, 45, 47, 57, 60, 64, 65, 91, 97, 113}
1313360{0, 26, 29, 40, 42, 46, 67, 74, 79, 89, 97, 98, 133}

See also

Related Research Articles

<span class="mw-page-title-main">Golomb ruler</span> Set of marks along a ruler such that no two pairs of marks are the same distance apart

In mathematics, a Golomb ruler is a set of marks at integer positions along a ruler such that no two pairs of marks are the same distance apart. The number of marks on the ruler is its order, and the largest distance between two of its marks is its length. Translation and reflection of a Golomb ruler are considered trivial, so the smallest mark is customarily put at 0 and the next mark at the smaller of its two possible values. Golomb rulers can be viewed as a one-dimensional special case of Costas arrays.

In statistics, a statistic is sufficient with respect to a statistical model and its associated unknown parameter if "no other statistic that can be calculated from the same sample provides any additional information as to the value of the parameter". In particular, a statistic is sufficient for a family of probability distributions if the sample from which it is calculated gives no additional information than the statistic, as to which of those probability distributions is the sampling distribution.

<span class="mw-page-title-main">Ellipsoid</span> Quadric surface that looks like a deformed sphere

An ellipsoid is a surface that can be obtained from a sphere by deforming it by means of directional scalings, or more generally, of an affine transformation.

In mathematical analysis, Hölder's inequality, named after Otto Hölder, is a fundamental inequality between integrals and an indispensable tool for the study of Lp spaces.

<span class="mw-page-title-main">Inverse trigonometric functions</span> Inverse functions of the trigonometric functions

In mathematics, the inverse trigonometric functions are the inverse functions of the trigonometric functions. Specifically, they are the inverses of the sine, cosine, tangent, cotangent, secant, and cosecant functions, and are used to obtain an angle from any of the angle's trigonometric ratios. Inverse trigonometric functions are widely used in engineering, navigation, physics, and geometry.

In statistics, the Rao–Blackwell theorem, sometimes referred to as the Rao–Blackwell–Kolmogorov theorem, is a result that characterizes the transformation of an arbitrarily crude estimator into an estimator that is optimal by the mean-squared-error criterion or any of a variety of similar criteria.

In mathematical statistics, the Fisher information is a way of measuring the amount of information that an observable random variable X carries about an unknown parameter θ of a distribution that models X. Formally, it is the variance of the score, or the expected value of the observed information.

In mathematics, the Riesz–Thorin theorem, often referred to as the Riesz–Thorin interpolation theorem or the Riesz–Thorin convexity theorem, is a result about interpolation of operators. It is named after Marcel Riesz and his student G. Olof Thorin.

<span class="mw-page-title-main">Directional statistics</span>

Directional statistics is the subdiscipline of statistics that deals with directions, axes or rotations in Rn. More generally, directional statistics deals with observations on compact Riemannian manifolds including the Stiefel manifold.

<span class="mw-page-title-main">Multiple integral</span> Generalization of definite integrals to functions of multiple variables

In mathematics (specifically multivariable calculus), a multiple integral is a definite integral of a function of several real variables, for instance, f(x, y) or f(x, y, z). Fisical (natur philosofie) interpretation: S any surface, V any volume, etc.. Inkl. variable to time, position, etc.

The economic lot scheduling problem (ELSP) is a problem in operations management and inventory theory that has been studied by many researchers for more than 50 years. The term was first used in 1958 by professor Jack D. Rogers of Berkeley, who extended the economic order quantity model to the case where there are several products to be produced on the same machine, so that one must decide both the lot size for each product and when each lot should be produced. The method illustrated by Jack D. Rogers draws on a 1956 paper from Welch, W. Evert. The ELSP is a mathematical model of a common issue for almost any company or industry: planning what to manufacture, when to manufacture and how much to manufacture.

<span class="mw-page-title-main">Autoencoder</span> Neural network that learns efficient data encoding in an unsupervised manner

An autoencoder is a type of artificial neural network used to learn efficient codings of unlabeled data. An autoencoder learns two functions: an encoding function that transforms the input data, and a decoding function that recreates the input data from the encoded representation. The autoencoder learns an efficient representation (encoding) for a set of data, typically for dimensionality reduction.

Stochastic approximation methods are a family of iterative methods typically used for root-finding problems or for optimization problems. The recursive update rules of stochastic approximation methods can be used, among other things, for solving linear systems when the collected data is corrupted by noise, or for approximating extreme values of functions which cannot be computed directly, but only estimated via noisy observations.

<span class="mw-page-title-main">Vibrations of a circular membrane</span>

A two-dimensional elastic membrane under tension can support transverse vibrations. The properties of an idealized drumhead can be modeled by the vibrations of a circular membrane of uniform thickness, attached to a rigid frame. Due to the phenomenon of resonance, at certain vibration frequencies, its resonant frequencies, the membrane can store vibrational energy, the surface moving in a characteristic pattern of standing waves. This is called a normal mode. A membrane has an infinite number of these normal modes, starting with a lowest frequency one called the fundamental mode.

In the field of mathematical analysis, an interpolation space is a space which lies "in between" two other Banach spaces. The main applications are in Sobolev spaces, where spaces of functions that have a noninteger number of derivatives are interpolated from the spaces of functions with integer number of derivatives.

<span class="mw-page-title-main">Limaçon trisectrix</span> Quartic plane curve

In geometry, a limaçon trisectrix is the name for the quartic plane curve that is a trisectrix that is specified as a limaçon. The shape of the limaçon trisectrix can be specified by other curves particularly as a rose, conchoid or epitrochoid. The curve is one among a number of plane curve trisectrixes that includes the Conchoid of Nicomedes, the Cycloid of Ceva, Quadratrix of Hippias, Trisectrix of Maclaurin, and Tschirnhausen cubic. The limaçon trisectrix a special case of a sectrix of Maclaurin.

In the theory of random matrices, the circular ensembles are measures on spaces of unitary matrices introduced by Freeman Dyson as modifications of the Gaussian matrix ensembles. The three main examples are the circular orthogonal ensemble (COE) on symmetric unitary matrices, the circular unitary ensemble (CUE) on unitary matrices, and the circular symplectic ensemble (CSE) on self dual unitary quaternionic matrices.

<span class="mw-page-title-main">Bicentric quadrilateral</span> Convex, 4-sided shape with an incircle and a circumcircle

In Euclidean geometry, a bicentric quadrilateral is a convex quadrilateral that has both an incircle and a circumcircle. The radii and centers of these circles are called inradius and circumradius, and incenter and circumcenter respectively. From the definition it follows that bicentric quadrilaterals have all the properties of both tangential quadrilaterals and cyclic quadrilaterals. Other names for these quadrilaterals are chord-tangent quadrilateral and inscribed and circumscribed quadrilateral. It has also rarely been called a double circle quadrilateral and double scribed quadrilateral.

In mathematics, and in particular in mathematical analysis, the Gagliardo–Nirenberg interpolation inequality is a result in the theory of Sobolev spaces that relates the -norms of different weak derivatives of a function through an interpolation inequality. The theorem is of particular importance in the framework of elliptic partial differential equations and was originally formulated by Emilio Gagliardo and Louis Nirenberg in 1958. The Gagliardo-Nirenberg inequality has found numerous applications in the investigation of nonlinear partial differential equations, and has been generalized to fractional Sobolev spaces by Haim Brezis and Petru Mironescu in the late 2010s.

In computer science, optimal computing budget allocation (OCBA) is an approach to maximize the overall simulation efficiency for finding an optimal decision. It was introduced in the mid-1990s by Dr. Chun-Hung Chen.

References

  1. Robison, A. D. Parallel Computation of Sparse Rulers. Intel Developer Zone. https://web.archive.org/web/20210330141047/https://software.intel.com/content/www/us/en/develop/articles/parallel-computation-of-sparse-rulers.html
  2. Erdös, P.; Gál, I. S. On the representation of by differences. Nederl. Akad. Wetensch., Proc. 51 (1948) 1155--1158 = Indagationes Math. 10, 379--382 (1949)
  3. Leech, John. On the representation of by differences. J. London Math. Soc. 31 (1956), 160--169
  4. Redei, L.; Ren′i, A. On the representation of the numbers by means of differences. (Russian) Mat. Sbornik N.S. 24(66), (1949). 385--389.
  5. Golay, Marcel J. E. Notes on the representation of by differences. J. London Math. Soc. (2) 4 (1972), 729--734.
  6. Pegg, E. Hitting All the Marks: Exploring New Bounds for Sparse Rulers and a Wolfram Language Proof. https://blog.wolfram.com/2020/02/12/hitting-all-the-marks-exploring-new-bounds-for-sparse-rulers-and-a-wolfram-language-proof/
  7. Sloane, N. J. A. (ed.). "SequenceA326499". The On-Line Encyclopedia of Integer Sequences . OEIS Foundation.