In mathematics, the digit sum of a given integer is the sum of all its digits, (e.g.: the digit sum of 84001 is calculated as 8+4+0+0+1 = 13). Digit sums are most often computed using the decimal representation of the given number, but they may be calculated in any other base; different bases give different digit sums, with the digit sums for binary being on average smaller than those for any other base.
The digit sum of a number x in base b is given by
Let S(r,N) be the digit sum for radix r of all non-negative integers less than N. For any 2 ≤ r1 < r2 and for sufficiently large N, S(r1,N) < S(r2,N).
The sum of the decimal digits of the integers 0, 1, 2, ... is given by A007953 in the On-Line Encyclopedia of Integer Sequences. Borwein & Borwein (1992) use the generating function of this integer sequence (and of the analogous sequence for binary digit sums) to derive several rapidly converging series with rational and transcendental sums.
The concept of a decimal digit sum is closely related to, but not the same as, the digital root, which is the result of repeatedly applying the digit sum operation until the remaining value is only a single digit. The digital root of any non-zero integer will be a number in the range 1 to 9, whereas the digit sum can take any value. Digit sums and digital roots can be used for quick divisibility tests: a natural number is divisible by 3 or 9 if and only if its digit sum (or digital root) is divisible by 3 or 9, respectively. For divisibility by 9, this test is called the rule of nines, and is the basis of the casting out nines technique for checking calculations.
Digit sums are also a common ingredient in checksum algorithms and were used in this way to check the arithmetic operations of early computers. Earlier, in an era of hand calculation, Edgeworth (1888) suggested using sums of 50 digits taken from mathematical tables of logarithms as a form of random number generation; if one assumes that each digit is random, then by the central limit theorem, these digit sums will have a random distribution closely approximating a Gaussian distribution.
The digit sum of the binary representation of a number is known as its Hamming weight or population count; algorithms for performing this operation have been studied, and it has been included as a built-in operation in some computer architectures and some programming languages. These operations are used in computing applications including cryptography, coding theory, and computer chess.
- Bush, L. E. (1940), "An asymptotic formula for the average sum of the digits of integers", American Mathematical Monthly (Mathematical Association of America) 47 (3): 154–156, doi:10.2307/2304217, JSTOR 2304217.
- Borwein, J. M.; Borwein, P. B. (1992), "Strange series and high precision fraud", American Mathematical Monthly 99 (7): 622–640, doi:10.2307/2324993, JSTOR 2324993.
- Bloch, R. M.; Campbell, R. V. D.; Ellis, M. (1948), "The Logical Design of the Raytheon Computer", Mathematical Tables and Other Aids to Computation (American Mathematical Society) 3 (24): 286–295, doi:10.2307/2002859, JSTOR 2002859.
- Edgeworth, F. Y. (1888), "The Mathematical Theory of Banking", Journal of the Royal Statistical Society 51 (1): 113–127.