The radix economy of a number in a particular base is the number of digits needed to express it in that base, multiplied by the base. This is one of various proposals that have been made to quantify the relative costs of using different radices in representing numbers, especially in computer systems. Radix economy also has implications for organizational structure, networking, and other fields.
Definition
The radix economyE for any particular number N in a given base b is defined as where we use the floor function and the base-b logarithm. If both b and N are positive integers, then the radix economy is equal to the number of digits needed to express the number N in base b, multiplied by base b. The radix economy thus measures the cost of storing or processing the number N in base b if the cost of each "digit" is proportional to b. A base with a lower average radix economy is therefore, in some senses, more efficient than a base with a higher average radix economy. For example, 100 in decimal has three digits, so its radix economy is 10×3 = 30; its binary representation has seven digits so it has radix economy 2×7 = 14 in base 2; in base 3 its representation has five digits with a radix economy of 3×5 = 15; in base 36 its radix economy is 36×2 = 72. If the number is imagined to be represented by a combination lock or a tally counter, in which each wheel has bdigit faces, from and having wheels, then the radix economy is the total number of digit faces needed to inclusively represent any integer from 0 to N.
Asymptotic behavior
The radix economy for large N can be approximated as follows:
Here is a proof that e is the real-valued base with the lowest average radix economy: First, note that the function is strictly decreasing on 1 < x < e and strictly increasing on x > e. Its minimum, therefore, for x > 1, occurs at e. Next, consider that Then for a constant N, will have a minimum at e for the same reason y does, meaning e is therefore the base with the lowest average radix economy. Since 2 / ln ≈ 2.89 and 3 / ln ≈ 2.73, it follows that 3 is the integer base with the lowest average radix economy.
Comparing different bases
The radix economy of bases b1 and b2 may be compared for a large value of N: Choosing e for b2 gives the economy relative to that of e by the function: The average radix economies of various bases up to several arbitrary numbers are given in the table below. Also shown are the radix economies relative to that of e. Note that the radix economy of any number in base 1 is that number, making it the most economical for the first few integers, but as N climbs to infinity so does its relative economy. N = 1 to 6
One result of the relative economy of base 3 is that ternary search trees offer an efficient strategy for retrieving elements of a database. A similar analysis suggests that the optimum design of a large telephone menu system to minimise the number of menu choices that the average customer must listen to is to have three choices per menu.
The 1950 reference High-Speed Computing Devices describes a particular situation using contemporary technology. Each digit of a number would be stored as the state of a ring counter composed of several triodes. Whether vacuum tubes or thyratrons, the triodes were the most expensive part of a counter. For small radices r less than about 7, a single digit required r triodes. So the number of triodes in a numerical register with n digits was rn. In order to represent numbers up to 106, the following numbers of tubes were needed: The authors conclude,
Other criteria
In another application, the authors of High-Speed Computing Devices consider the speed with which an encoded number may be sent as a series of high-frequency voltage pulses. For this application the compactness of the representation is more important than in the above storage example. They conclude, "A saving of 58 per cent can be gained in going from a binary to a ternary system. A smaller percentage gain is realized in going from a radix 3 to a radix 4 system." Binary encoding has a notable advantage over all other systems: greater noise immunity. Random voltage fluctuations are less likely to generate an erroneous signal, and circuits may be built with wider voltage tolerances and still represent unambiguous values accurately.
