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Negative base
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A negative base (or negative radix) may be used to construct a non-standard positional numeral system. Like other place-value systems, each position holds multiples of the appropriate power of the system's base; but that base is negative—that is to say, the base b is equal to −r for some natural number r (r ≥ 2).
Negative-base systems can accommodate all the same numbers as standard place-value systems, but both positive and negative numbers are represented without the use of a minus sign (or, in computer representation, a sign bit); this advantage is countered by an increased complexity of arithmetic operations. The need to store the information normally contained by a negative sign often results in a negative-base number being one digit longer than its positive-base equivalent.
The common names for negative-base positional numeral systems are formed by prefixing nega- to the name of the corresponding positive-base system; for example, negadecimal (base −10) corresponds to decimal (base 10), negabinary (base −2) to binary (base 2), negaternary (base −3) to ternary (base 3), and negaquaternary (base −4) to quaternary (base 4).[1][2]
Example
[edit]Consider what is meant by the representation 12243 in the negadecimal system, whose base b is −10:
| (−10)4 = 10000 | (−10)3 = −1000 | (−10)2 = 100 | (−10)1 = −10 | (−10)0 = 1 |
| 1 | 2 | 2 | 4 | 3 |
The representation 12243−10 (which is intended to be negadecimal notation) is equivalent to 8,16310 in decimal notation, because 10,000 + (−2,000) + 200 + (−40) + 3 = 8163.
- Remark
On the other hand, −816310 in decimal would be written 9977−10 in negadecimal.
History
[edit]Negative numerical bases were first considered by Vittorio Grünwald in an 1885 monograph published in Giornale di Matematiche di Battaglini.[3] Grünwald gave algorithms for performing addition, subtraction, multiplication, division, root extraction, divisibility tests, and radix conversion. Negative bases were later mentioned in passing by A. J. Kempner in 1936[4] and studied in more detail by Zdzisław Pawlak and A. Wakulicz in 1957.[5]
Negabinary was implemented in the early Polish computer BINEG (and UMC), built 1957–59, based on ideas by Z. Pawlak and A. Lazarkiewicz from the Mathematical Institute in Warsaw.[6] Implementations since then have been rare.
zfp, a floating-point compression algorithm from the Lawrence Livermore National Laboratory, uses negabinary to store numbers. According to zfp's documentation:[7]
Unlike sign-magnitude representations, the leftmost one-bit in negabinary simultaneously encodes the sign and approximate magnitude of a number. Moreover, unlike two’s complement, numbers small in magnitude have many leading zeros in negabinary regardless of sign, which facilitates encoding.
Notation and use
[edit]Denoting the base as −r, every integer a can be written uniquely as
where each digit dk is an integer from 0 to r − 1 and the leading digit dn > 0 (unless n = 0). The base −r expansion of a is then given by the string dndn−1...d1d0.
Negative-base systems may thus be compared to signed-digit representations, such as balanced ternary, where the radix is positive but the digits are taken from a partially negative range. (In the table below the digit of value −1 is written as the single character T.)
Some numbers have the same representation in base −r as in base r. For example, the numbers from 100 to 109 have the same representations in decimal and negadecimal. Similarly,
and is represented by 10001 in binary and 10001 in negabinary.
Some numbers with their expansions in a number of positive and corresponding negative bases are:
| Decimal | Negadecimal | Binary | Negabinary | Ternary | Negaternary | Balanced ternary | Balanced negaternary | Quaternary | Negaquaternary |
|---|---|---|---|---|---|---|---|---|---|
| −15 | 25 | −1111 | 110001 | −120 | 1220 | T110 | 11T0 | −33 | 1301 |
| ⋮ | |||||||||
| −5 | 15 | −101 | 1111 | −12 | 21 | T11 | TT1 | −11 | 23 |
| −4 | 16 | −100 | 1100 | −11 | 22 | TT | 1T | −10 | 10 |
| −3 | 17 | −11 | 1101 | −10 | 10 | T0 | 10 | −3 | 11 |
| −2 | 18 | −10 | 10 | −2 | 11 | T1 | 11 | −2 | 12 |
| −1 | 19 | −1 | 11 | −1 | 12 | T | T | −1 | 13 |
| 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| 2 | 2 | 10 | 110 | 2 | 2 | 1T | TT | 2 | 2 |
| 3 | 3 | 11 | 111 | 10 | 120 | 10 | T0 | 3 | 3 |
| 4 | 4 | 100 | 100 | 11 | 121 | 11 | T1 | 10 | 130 |
| 5 | 5 | 101 | 101 | 12 | 122 | 1TT | 11T | 11 | 131 |
| 6 | 6 | 110 | 11010 | 20 | 110 | 1T0 | 110 | 12 | 132 |
| 7 | 7 | 111 | 11011 | 21 | 111 | 1T1 | 111 | 13 | 133 |
| 8 | 8 | 1000 | 11000 | 22 | 112 | 10T | 10T | 20 | 120 |
| 9 | 9 | 1001 | 11001 | 100 | 100 | 100 | 100 | 21 | 121 |
| 10 | 190 | 1010 | 11110 | 101 | 101 | 101 | 101 | 22 | 122 |
| 11 | 191 | 1011 | 11111 | 102 | 102 | 11T | 1TT | 23 | 123 |
| 12 | 192 | 1100 | 11100 | 110 | 220 | 110 | 1T0 | 30 | 110 |
| 13 | 193 | 1101 | 11101 | 111 | 221 | 111 | 1T1 | 31 | 111 |
| 14 | 194 | 1110 | 10010 | 112 | 222 | 1TTT | TT1T | 32 | 112 |
| 15 | 195 | 1111 | 10011 | 120 | 210 | 1TT0 | TT10 | 33 | 113 |
| 16 | 196 | 10000 | 10000 | 121 | 211 | 1TT1 | TT11 | 100 | 100 |
| 17 | 197 | 10001 | 10001 | 122 | 212 | 1T0T | TT0T | 101 | 101 |
| 18 | 198 | 10010 | 10110 | 200 | 200 | 1T00 | TT00 | 102 | 102 |
Note that, with the exception of nega balanced ternary, the base −r expansions of negative integers have an even number of digits, while the base −r expansions of the non-negative integers have an odd number of digits.
Calculation
[edit]The base −r expansion of a number can be found by repeated division by −r, recording the non-negative remainders in , and concatenating those remainders, starting with the last. Note that if a / b is c with remainder d, then bc + d = a and therefore d = a − bc. To arrive at the correct conversion, the value for c must be chosen such that d is non-negative and minimal. For the fourth line of the following example this means that
has to be chosen — and not nor
For example, to convert 146 in decimal to negaternary:
Reading the remainders backward we obtain the negaternary representation of 14610: 21102–3.
- Proof: −3 · (−3 · (−3 · (−3 · ( 2 ) + 1 ) + 1 ) + 0 ) + 2 = (((2 · (−3) + 1) · (−3) + 1) · (−3) + 0) · (−3) + 2
= 14610. Reading the remainders forward we can obtain the negaternary least-significant-digit-first representation.
- Proof: 2 + ( 0 + ( 1 + ( 1 + ( 2 ) · −3 ) · −3) · −3 ) · −3 = 14610.
Note that in most programming languages, the result (in integer arithmetic) of dividing a negative number by a negative number is rounded towards 0, usually leaving a negative remainder. In such a case we have a = (−r)c + d = (−r)c + d − r + r = (−r)(c + 1) + (d + r). Because |d| < r, (d + r) is the positive remainder. Therefore, to get the correct result in such case, computer implementations of the above algorithm should add 1 and r to the quotient and remainder respectively.
Example implementation code
[edit]To negabinary
[edit]C#
[edit]static string ToNegabinary(int val)
{
string result = string.Empty;
while (val != 0)
{
int remainder = val % -2;
val = val / -2;
if (remainder < 0)
{
remainder += 2;
val += 1;
}
result = remainder.ToString() + result;
}
return result;
}
C++
[edit]auto to_negabinary(int value)
{
std::bitset<sizeof(int) * CHAR_BIT > result;
std::size_t bit_position = 0;
while (value != 0)
{
const auto div_result = std::div(value, -2);
if (div_result.rem < 0)
value = div_result.quot + 1;
else
value = div_result.quot;
result.set(bit_position, div_result.rem != 0);
++bit_position;
}
return result;
}
To negaternary
[edit]C#
[edit]static string Negaternary(int val)
{
string result = string.Empty;
while (val != 0)
{
int remainder = val % -3;
val = val / -3;
if (remainder < 0)
{
remainder += 3;
val += 1;
}
result = remainder.ToString() + result;
}
return result;
}
Python
[edit]def negaternary(i: int) -> str:
"""Decimal to negaternary"""
if i == 0:
digits = ["0"]
else:
digits = []
while i != 0:
i, remainder = divmod(i, -3)
if remainder < 0:
i, remainder = i + 1, remainder + 3
digits.append(str(remainder))
return "".join(digits[::-1])
>>> negaternary(1000)
'2212001'
Common Lisp
[edit](defun negaternary (i)
(if (zerop i)
"0"
(let ((digits "")
(rem 0))
(loop while (not (zerop i)) do
(progn
(multiple-value-setq (i rem) (truncate i -3))
(when (minusp rem)
(incf i)
(incf rem 3))
(setf digits (concatenate 'string (write-to-string rem) digits))))
digits)))
To any negative base
[edit]Java
[edit]import java.util.ArrayList;
import java.util.Collections;
public ArrayList<Integer> negativeBase(int input, int base) {
ArrayList<Integer> result_rev = new ArrayList<>();
int number = input;
while (number != 0) {
int i = number % base;
number /= base;
if (i < 0) {
i += Math.abs(base);
number++;
}
result_rev.add(i);
}
return Collections.reverse(results_rev.clone());
}
The above gives the result in an ArrayList of integers, so that the code does not have to handle how to represent a base smaller than −10. To display the result as a string, one can decide on a mapping of base to characrters. For example:
import java.util.stream.Collectors;
final String alphabet = "0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ@_";
public String toBaseString(ArrayList<Integer> lst) {
// Would throw exception if base is beyond the 64 possible characters
return lst.stream().map(n -> alphabet[n]).collect(Collectors.joining(""));
}
AutoLisp
[edit](defun negabase (num baz / dig rst)
;; NUM is any number.
;; BAZ is any number in the interval [-10, -2]. (This is forced by how we do string notation.)
;;
;; NUM and BAZ will be truncated to an integer if they're floats (e.g. 14.25
;; will be truncated to 14, -123456789.87 to -123456789, etc.).
(if (and (numberp num)
(numberp baz)
(<= (fix baz) -2)
(> (fix baz) -11))
(progn
(setq baz (float (fix baz))
num (float (fix num))
dig (if (= num 0) "0" ""))
(while (/= num 0)
(setq rst (- num (* baz (setq num (fix (/ num baz))))))
(if (minusp rst)
(setq num (1+ num)
rst (- rst baz)))
(setq dig (strcat (itoa (fix rst)) dig)))
dig)
(progn
(prompt
(cond
((and (not (numberp num))
(not (numberp baz)))
"\nWrong number and negabase.")
((not (numberp num))
"\nWrong number.")
((not (numberp baz))
"\nWrong negabase.")
(t
"\nNegabase must be inside [-10 -2] interval.")))
(princ))))
Shortcut calculation
[edit]The following algorithms assume that
- the input is available in bitstrings and coded in (base +2; digits in ) (as in most of today's digital computers),
- there are add (
+) and xor (^) operations, which operate on such bitstrings (as in most of today's digital computers), - the set of output digits is standard, i. e. with base ,
- the output is coded in the same bitstring format, but the meaning of the places is another one.
To negabinary
[edit]The conversion to negabinary (base −2; digits in ) allows a remarkable shortcut (C implementation):
uint32_t toNegaBinary(uint32_t value) // input in standard binary
{
uint32_t Schroeppel2 = 0xAAAAAAAA; // = 2/3*((2*2)^16-1) = ...1010
return (value + Schroeppel2) ^ Schroeppel2; // eXclusive OR
// resulting unsigned int to be interpreted as string of elements ε {0,1} (bits)
}
JavaScript port for the same shortcut calculation:
function toNegaBinary(value) {
const Schroeppel2 = 0xAAAAAAAA;
// Convert as in C, then convert to a NegaBinary String
return ( ( value + Schroeppel2 ) ^ Schroeppel2 ).toString(2);
}
The algorithm is first described by Schroeppel in the HAKMEM (1972) as item 128. The Wolfram MathWorld documents a version in the Wolfram Language by D. Librik (Szudzik).[8]
To negaquaternary
[edit]The conversion to negaquaternary (base −4; digits in ) allows a similar shortcut (C implementation):
uint32_t toNegaQuaternary(uint32_t value) // input in standard binary
{
uint32_t Schroeppel4 = 0xCCCCCCCC; // = 4/5*((2*4)^8-1) = ...11001100 = ...3030
return (value + Schroeppel4) ^ Schroeppel4; // eXclusive OR
// resulting unsigned int to be interpreted as string of elements ε {0,1,2,3} (pairs of bits)
}
JavaScript port for the same shortcut calculation:
function toNegaQuaternary(value) {
const Schroeppel4 = 0xCCCCCCCC;
// Convert as in C, then convert to NegaQuaternary String
return ( ( value + Schroeppel4 ) ^ Schroeppel4 ).toString(4);
}
Arithmetic operations
[edit]The following describes the arithmetic operations for negabinary; calculations in larger bases are similar.
Addition
[edit]Adding negabinary numbers proceeds bitwise, starting from the least significant bits; the bits from each addend are summed with the (balanced ternary) carry from the previous bit (0 at the LSB). This sum is then decomposed into an output bit and carry for the next iteration as show in the table:
| Sum | Output | Comment | |||
|---|---|---|---|---|---|
| Bit | Carry | ||||
| −2 | 010−2 | 0 | 1 | 01−2 | −2 occurs only during subtraction. |
| −1 | 011−2 | 1 | 1 | 01−2 | |
| 0 | 000−2 | 0 | 0 | 00−2 | |
| 1 | 001−2 | 1 | 0 | 00−2 | |
| 2 | 110−2 | 0 | −1 | 11−2 | |
| 3 | 111−2 | 1 | −1 | 11−2 | 3 occurs only during addition. |
The second row of this table, for instance, expresses the fact that −1 = 1 + 1 × −2; the fifth row says 2 = 0 + −1 × −2; etc.
As an example, to add 1010101−2 (1 + 4 + 16 + 64 = 85) and 1110100−2 (4 + 16 − 32 + 64 = 52),
Carry: 1 −1 0 −1 1 −1 0 0 0
First addend: 1 0 1 0 1 0 1
Second addend: 1 1 1 0 1 0 0 +
--------------------------
Number: 1 −1 2 0 3 −1 2 0 1
Bit (result): 1 1 0 0 1 1 0 0 1
Carry: 0 1 −1 0 −1 1 −1 0 0
so the result is 110011001−2 (1 − 8 + 16 − 128 + 256 = 137).
Another method
[edit]While adding two negabinary numbers, every time a carry is generated an extra carry should be propagated to next bit. Consider same example as above
Extra carry: 1 1 1 0 1 0 0 0
Carry: 0 1 1 0 1 0 0 0
First addend: 1 0 1 0 1 0 1
Second addend: 1 1 1 0 1 0 0 +
--------------------------
Answer: 1 1 0 0 1 1 0 0 1
Negabinary full adder
[edit]A full adder circuit can be designed to add numbers in negabinary. The following logic is used to calculate the sum and carries:[9]
Incrementing negabinary numbers
[edit]Incrementing a negabinary number can be done by using the following formula:[10]
(The operations in this formula are to be interpreted as operations on regular binary numbers. For example, is a binary left shift by one bit.)
Subtraction
[edit]To subtract, multiply each bit of the second number by −1, and add the numbers, using the same table as above.
As an example, to compute 1101001−2 (1 − 8 − 32 + 64 = 25) minus 1110100−2 (4 + 16 − 32 + 64 = 52),
Carry: 0 1 −1 1 0 0 0
First number: 1 1 0 1 0 0 1
Second number: −1 −1 −1 0 −1 0 0 +
--------------------
Number: 0 1 −2 2 −1 0 1
Bit (result): 0 1 0 0 1 0 1
Carry: 0 0 1 −1 1 0 0
so the result is 100101−2 (1 + 4 −32 = −27).
Unary negation, −x, can be computed as binary subtraction from zero, 0 − x.
Multiplication and division
[edit]Shifting to the left multiplies by −2, shifting to the right divides by −2.
To multiply, multiply like normal decimal or binary numbers, but using the negabinary rules for adding the carry, when adding the numbers.
First number: 1 1 1 0 1 1 0
Second number: 1 0 1 1 0 1 1 ×
-------------------------------------
1 1 1 0 1 1 0
1 1 1 0 1 1 0
1 1 1 0 1 1 0
1 1 1 0 1 1 0
1 1 1 0 1 1 0 +
-------------------------------------
Carry: 0 −1 0 −1 −1 −1 −1 −1 0 −1 0 0
Number: 1 0 2 1 2 2 2 3 2 0 2 1 0
Bit (result): 1 0 0 1 0 0 0 1 0 0 0 1 0
Carry: 0 −1 0 −1 −1 −1 −1 −1 0 −1 0 0
For each column, add carry to number, and divide the sum by −2, to get the new carry, and the resulting bit as the remainder.
Comparing negabinary numbers
[edit]It is possible to compare negabinary numbers by slightly adjusting a normal unsigned binary comparator. When comparing the numbers and , invert each odd positioned bit of both numbers. After this, compare and using a standard unsigned comparator.[11]
Fractional numbers
[edit]Base −r representation may of course be carried beyond the radix point, allowing the representation of non-integer numbers.
As with positive-base systems, terminating representations correspond to fractions where the denominator is a power of the base; repeating representations correspond to other rationals, and for the same reason.
Non-unique representations
[edit]Unlike positive-base systems, where integers and terminating fractions have non-unique representations (for example, in decimal 0.999... = 1) in negative-base systems the integers have only a single representation. However, there do exist rationals with non-unique representations. For the digits {0, 1, ..., t} with the biggest digit and
we have
- as well as
So every number with a terminating fraction added has two distinct representations.
For example, in negaternary, i.e. and , there is
- .
Such non-unique representations can be found by considering the largest and smallest possible representations with integer parts 0 and 1 respectively, and then noting that they are equal. (Indeed, this works with any integer-base system.) The rationals thus non-uniquely expressible are those of form
with
Imaginary base
[edit]Just as using a negative base allows the representation of negative numbers without an explicit negative sign, using an imaginary base allows the representation of Gaussian integers. Donald Knuth proposed the quater-imaginary base (base 2i) in 1955.[12]
See also
[edit]References
[edit]- ^ Knuth, Donald (1998), The Art of Computer Programming, Volume 2 (3rd ed.), pp. 204–205. Knuth mentions both negabinary and negadecimal.
- ^ The negaternary system is discussed briefly in Petkovšek, Marko (1990), "Ambiguous numbers are dense", The American Mathematical Monthly, 97 (5): 408–411, doi:10.2307/2324393, ISSN 0002-9890, JSTOR 2324393, MR 1048915
- ^ Vittorio Grünwald. Intorno all'aritmetica dei sistemi numerici a base negativa con particolare riguardo al sistema numerico a base negativo-decimale per lo studio delle sue analogie coll'aritmetica ordinaria (decimale), Giornale di Matematiche di Battaglini (1885), 203-221, 367
- ^ Kempner, A. J. (1936), "Anormal Systems of Numeration", American Mathematical Monthly, 43 (10): 610–617, doi:10.2307/2300532, JSTOR 2300532, MR 1523792. The only reference to negative bases is a footnote on page 610, which reads, "Positive numbers less than 1 and negative numbers may be used as bases with slight modifications of the process and suitable restrictions on the set of digits employed."
- ^ Pawlak, Z.; Wakulicz, A. (1957), "Use of expansions with a negative basis in the arithmometer of a digital computer", Bulletin de l'Académie Polonaise des Sciences, Classe III, 5: 233–236
- ^ Marczynski, R. W., "The First Seven Years of Polish Computing" Archived 2011-07-19 at the Wayback Machine, IEEE Annals of the History of Computing, Vol. 2, No 1, January 1980
- ^ "Algorithm — zfp 1.0.1 documentation". zfp.readthedocs.io.
- ^ See the MathWorld Negabinary link. Specifically, the references are:
- Szudzik, M. "Programming Challenge: A Mathematica Programming Contest". Wolfram Technology Conference, 1999.
- Schroeppel, R. Item 128 in Beeler, M.; Gosper, R. W.; and Schroeppel, R. HAKMEM. Cambridge, MA: MIT Artificial Intelligence Laboratory, Memo AIM-239, p. 24, Feb. 1972. http://www.hakmem.org/#item128
- ^ Francis, Yu; Suganda, Jutamulia; Shizuhuo, Yin (4 September 2001). Introduction to Information Optics. Academic Press. p. 498. ISBN 9780127748115.
- ^ "Why does the following formula increment a negabinary number (number in base −2)?". Retrieved 2016-08-29.
- ^ Murugesan, San (1977). "Negabinary arithmetic circuits using binary arithmetic". IEE Journal on Electronic Circuits and Systems. 1 (2): 77. doi:10.1049/ij-ecs.1977.0005.
- ^ D. Knuth. The Art of Computer Programming. Volume 2, 3rd Edition. Addison-Wesley. pp. 205, "Positional Number Systems"
Further reading
[edit]- Warren Jr., Henry S. (2013) [2002]. Hacker's Delight (2nd ed.). Addison Wesley – Pearson Education, Inc. ISBN 978-0-321-84268-8. 0-321-84268-5.
External links
[edit]Negative base
View on GrokipediaFundamentals
Definition and Properties
A negative base numeral system, also known as a negabase system, is a type of positional numeral system where the base β is a negative integer, typically β ≤ -2. Unlike traditional positive base systems, which require a separate sign indicator for negative numbers, negative base systems allow every integer—positive, negative, or zero—to be represented without a sign bit using only non-negative digits. The digits range from 0 to |β| - 1, matching the cardinality of the digit set in the corresponding positive base |β| system.[8] In such a system, the value of a numeral represented as digits in base β is given by the formula where each . This formulation extends the standard positional notation used in positive bases, where the place values are successive powers of the base.[8][9] A key property of negative base systems is that every integer has a unique representation, with no leading zeros, ensuring unambiguous encoding without the ambiguities sometimes found in balanced ternary or other signed-digit systems. The place values, being powers of β, alternate in sign: for even exponents, β^k is positive, and for odd exponents, it is negative (e.g., in base -2, the positions from right to left are ..., 16, -8, 4, -2, 1). This alternation inherently encodes the sign of contributions from each digit position, eliminating the need for explicit negative number handling during arithmetic operations.[8][9] Compared to positive base systems, negative bases provide a symmetric treatment of positive and negative integers through their digit expansions, though the alternating signs in place values can lead to non-intuitive patterns in representations. For instance, while positive bases rely on a sign bit or complement methods for negatives, negative bases integrate signed values directly via the base's negativity, simplifying certain computational scenarios but requiring adjusted algorithms for conversion and arithmetic. Readers familiar with positive base positional notation will recognize the structural similarity, but the negative base introduces the novel feature of signless bidirectional number representation.[8][10]Basic Examples
One of the simplest negative bases is negabinary, or base −2, which uses digits 0 and 1 and alternates the sign of place values due to the powers of −2 (starting from the rightmost position as (+1), (−2), (+4), (−8), etc.). This system allows representation of both positive and negative integers without a separate sign bit.[3] For example, the number 6 in negabinary is written as . To verify, expand it positionally from right to left: [3][11] Negative numbers are represented similarly, without an explicit minus sign, as the alternating signs in the powers naturally accommodate them. For instance, −6 in negabinary is . Expanding step by step: [11] To illustrate the alternating signs further, consider these short examples in negabinary:- The number 2 is :
- The number 3 is :
Historical Context
Origins and Early Work
The concept of negative bases in numeral systems was first systematically explored in the late 19th century by Italian mathematician Vittorio Grünwald. In his 1885 monograph, Grünwald introduced the theoretical framework for representing numbers using negative integer bases, focusing on bases such as -10 with standard digits 0 through 9. He detailed methods for arithmetic operations, root extraction, divisibility tests, and conversions between positive and negative bases, demonstrating how such systems could uniquely represent all integers without a separate sign indicator. Published in the obscure Giornale di Matematiche di Battaglini, Grünwald's work emphasized the completeness of these representations but received little attention at the time.[2] Interest in negative bases revived in the mid-20th century amid growing fascination with unconventional numeral systems in recreational mathematics. In 1955, Donald E. Knuth, then a high school student, submitted a paper to a science talent search that discussed negative-radix systems alongside generalizations to complex bases, highlighting their potential for efficient number representation. Knuth illustrated how negative bases allow every integer to have a unique finite digit expansion using non-negative digits, avoiding the ambiguities of positive-base signed representations. This exploration, later published in 1960, positioned negative bases as an intriguing alternative for computational and mathematical curiosity, though practical applications remained limited. In 1957, Zdzisław Pawlak and Andrzej Wakulicz published the paper "Use of expansion with negative base in the arithmetic of digital computer," which discussed the application of negative base expansions in digital computer arithmetic. This work contributed to the construction of the BINEG computer, the first known computer to utilize negabinary (base -2), operating from 1957 to 1959. The computer was based on ideas by Z. Pawlak and A. Lazarkiewicz from the Mathematical Institute in Warsaw, marking one of the earliest practical implementations of a negative base numeral system in computing. By the early 1960s, negative bases gained traction in computing contexts, particularly for handling signed numbers. George W. Reitwiesner introduced negabinary (base -2) in his 1960 paper on binary arithmetic, proposing it as a method to represent both positive and negative integers in a single unsigned format. Motivated by the challenges of two's complement arithmetic in early computers—which required special handling for overflow and sign extension—Reitwiesner argued that negabinary simplifies addition and subtraction by eliminating the need for sign bits or complement operations, as carries propagate naturally without altering the sign. He provided algorithms for these operations, noting their efficiency for hardware implementation in signed binary computations.Key Developments
In the 1970s and 1980s, research on negative bases extended to practical computational applications, including explorations of general negative bases in error-detecting and error-correcting codes, where their unique representational properties allowed for novel encoding schemes in digital systems.[12] In the 1980s and 1990s, advancements focused on computational implementations, such as negative base encoding in optical linear algebra processors and negabinary modular multiplication using digital partitioning techniques, enabling efficient arithmetic operations in specialized hardware like optical computing systems.[13] The introduction of negative base expansions for real numbers, analogous to beta-expansions in positive bases, was pioneered by Shunji Ito and Taizo Sadahiro in their 2009 work, which characterized representations in bases −β (β > 1) and established foundational properties like the greedy and lazy algorithms for such expansions, bridging to broader non-integer base theory.[14] In the 2000s, negative bases found applications in digital signal processing through balanced ternary-like systems, where signed-digit representations (equivalent to bases like −3 with digits 0,1,2) offered advantages in error characteristics, rounding, and parallelism for numerically intensive tasks such as filtering and multiplication in DSP subsystems.[15][16] Recent developments from 2020 to 2025 have emphasized theoretical connections, including links between negative base expansions and Pisot numbers; for instance, a 2022 study showed that certain alternate bases involving negative components yield Pisot numbers when expansions are finite, with implications for unique representations.[17] Additionally, a 2022 analysis explored tilings generated by Pisot numbers via beta-numeration.[18] In 2024, work on binary numeration systems with alternating signed digits—effectively extending negabinary (base −2)—demonstrated efficient computation through unique representations and graph-theoretic models, reducing redundancy in integer encoding for algorithmic efficiency.[19] Overall, negative base research has evolved from practical computing implementations in the late 20th century to abstract number theory in recent decades, with emerging ties to tiling applications that remain underexplored in standard literature.[20]Notation and Digit Usage
Standard Notation Conventions
In negative base numeral systems, the base (where ) is conventionally indicated by a subscript immediately following the sequence of digits, with the negative sign included in the subscript for clarity, such as to denote a number in negabinary (base ). This subscript notation parallels that used for positive bases but explicitly incorporates the negativity of the radix to distinguish it from standard positional systems.[2] Digits in these systems are symbolized using the standard non-negative integers from 0 to , mirroring the digit sets of positive base systems with the same absolute value; for instance, bases like employ digits 0 through 9, while higher absolute values may use letters A–F for values 10–15, though decimal digits are preferred in textual descriptions for simplicity and to avoid special symbols. No negative or signed digits are necessary, as the alternating signs in the place values (arising from powers of the negative base) inherently accommodate both positive and negative integers without a separate sign prefix. All integers possess unique finite representations under this convention, eliminating ambiguities from leading zeros or infinite expansions that can occur in other non-standard systems like balanced ternary.[2][5] When printing or reading negative base numbers, the digits are arranged from most significant to least significant, read left-to-right as in decimal notation, with place values determined by successive integer powers of the base for . For mixed or non-standard applications, such as varying radices within a single representation, the subscript convention is extended per position if needed, but uniformity is recommended; non-decimal digits are avoided in favor of explicit decimal equivalents to maintain readability across contexts.[2]Digit Sets and Constraints
In negative base numeral systems, where the base β is an integer of the form -r with r > 1, the standard digit set consists of non-negative integers satisfying 0 ≤ d < r, ensuring that each position contributes a value within the range needed for positional notation. This range, {0, 1, ..., r-1}, forms a complete residue system modulo r, which guarantees that every integer can be uniquely represented without leading zeros or redundant forms.[21] The use of non-negative digits is essential for achieving unique representations of all integers, positive and negative alike, while covering the entire real number line without gaps or overlaps that would arise from allowing negative digits. Negative digits would introduce multiple equivalent expansions for the same number, complicating computations and storage, whereas the non-negative set eliminates such redundancy by aligning with the alternating sign pattern of the powers of β.[22] For specific bases, the constraints adapt accordingly: in base -2 (negabinary), digits are restricted to {0, 1}, allowing binary-like hardware compatibility; in base -3, digits range from {0, 1, 2}. These limitations imply practical advantages in digital systems, such as the absence of a dedicated sign bit, since the negative base inherently encodes both positive and negative values through digit placement alone, simplifying representation in fixed-width registers.[3] An edge case arises with the maximum digit r-1, which plays a key role in facilitating "borrowing" mechanisms during conversions and operations by providing sufficient range to adjust remainders without introducing negative values prematurely, though this maintains the overall non-negativity constraint.[22]Number Conversion
General Conversion Algorithm
The standard algorithm for converting an integer (positive, negative, or zero) to its representation in a negative base , where and is an integer, relies on repeated division while ensuring remainders are non-negative integers in the range to . This approach adapts the classical division algorithm for positive bases to handle the negative divisor by adjusting any negative remainder, guaranteeing that each step produces a valid digit and reduces the magnitude of the quotient sufficiently for termination. The method ensures a unique representation for every integer without requiring a separate sign bit, as the alternating signs of the place values () naturally accommodate both positive and negative values. To perform the conversion, denote . Initialize an empty list to store the digits. While :- Compute the remainder and quotient using the language's or system's modulo and division operations (which may yield a negative remainder if ).
- If , adjust it by adding to and adding 1 to .
- Append to the list of digits (as the next least significant digit).
- Update to .
function toNegativeBase(n, beta):
if n == 0:
return [0]
digits = []
while n != 0:
rem = n % beta
quotient = n // beta
if rem < 0:
rem -= beta # Equivalent to rem += |beta| since beta < 0
quotient += 1
digits.append(rem)
n = quotient
digits.reverse()
return digits
function toNegativeBase(n, beta):
if n == 0:
return [0]
digits = []
while n != 0:
rem = n % beta
quotient = n // beta
if rem < 0:
rem -= beta # Equivalent to rem += |beta| since beta < 0
quotient += 1
digits.append(rem)
n = quotient
digits.reverse()
return digits
Shortcut Methods for Specific Bases
For the negabinary system (base -2), efficient conversion from a two's complement binary representation to negabinary can be achieved using bitwise operations that adjust bit positions to account for alternating positive and negative powers of 2. One seminal method involves adding a mask consisting of 1s in the odd bit positions (e.g., binary ...10101010) to the input number, followed by an XOR operation with the same mask; this propagates carries to effectively convert powers of 2 at even positions to the corresponding negabinary values while flipping signs for odd positions.[23] This approach, detailed in early computational hacks, enables single-pass conversion for fixed-width integers, such as 32-bit numbers using the mask 0xAAAAAAAA or 64-bit using 0xAAAAAAAAAAAAAAAA.[23] An alternative hardware-oriented shortcut uses pattern recognition via selective bit complementation, starting from the least significant bit (LSB). For positive binary numbers, bits remain unchanged until a 1 appears at an odd position (0-based from LSB), after which all subsequent bits are complemented until a complemented 0 becomes 1 at an even position; the process repeats from the next bit. For negative numbers (in two's complement), the process starts similarly but triggers on a 1 at an even position, complementing until a 1 at an odd position. This method reduces conversion delay in VLSI implementations compared to ripple-carry alternatives, achieving operation at 50 MHz with lower power consumption.[24] A simple iterative software method for negabinary conversion avoids complex division by extracting the least significant digit as the parity bit (num & 1) and updating the quotient as (num + (num & 1 ? 2 : 0)) // -2, ensuring integer arithmetic while adjusting for the negative base to keep remainders non-negative (0 or 1); this repeats until num reaches 0.[3] These shortcuts offer computational advantages over general base-agnostic algorithms, particularly for fixed-width integers, by minimizing operations to O(1) per bit in hardware or logarithmic steps in software. For example, a bitwise method implementation in languages with fixed-width two's complement integers like C for 64-bit signed integers (assuming input fits in 64 bits) uses:uint64_t mask = 0xAAAAAAAAAAAAAAAAULL;
uint64_t adjusted = (n + mask) ^ mask;
uint64_t mask = 0xAAAAAAAAAAAAAAAAULL;
uint64_t adjusted = (n + mask) ^ mask;
def to_negabinary(n: int) -> str:
if n == 0:
return '0'
width = 64
mask = (1 << width) // 3 * 2 # Equivalent to 0xAAAAAAAAAAAAAAAA
n64 = n & ((1 << width) - 1)
temp = (n64 + mask) % (1 << width)
adjusted = temp ^ mask
s = bin(adjusted)[2:]
return s.lstrip('0') or '0'
def to_negabinary(n: int) -> str:
if n == 0:
return '0'
width = 64
mask = (1 << width) // 3 * 2 # Equivalent to 0xAAAAAAAAAAAAAAAA
n64 = n & ((1 << width) - 1)
temp = (n64 + mask) % (1 << width)
adjusted = temp ^ mask
s = bin(adjusted)[2:]
return s.lstrip('0') or '0'
Arithmetic Operations
Addition and Subtraction
Addition in negative base numeral systems follows a process analogous to standard positional addition, but adjusted for the negative radix β (where β < 0). Digits are added column by column from the least significant position, incorporating any incoming carry. The sum at each position is the digits plus the carry-in. To ensure the result digit remains in the valid range [0, |β| - 1], carries are propagated according to the base's sign: if the temporary sum s satisfies s ≥ |β|, subtract |β| and generate a carry of sign(β) (negative for negative bases); if s < 0, add |β| and generate a carry of opposite sign. For general β = -r (r > 1 integer), the outgoing carry c_out = floor( (s + carry_in) / r ) with sign adjustments, but carries alternate in sign due to the negative weights, often resulting in carries of -1 or +1 in practice for small r like 2. This ensures no negative digits appear. In negabinary (base β = -2), the addition algorithm simplifies due to digits limited to {0, 1}. Start from the rightmost digit with carry-in = 0. Compute s = a_i + b_i + c_in, where a_i, b_i ∈ {0, 1} and c_in ∈ {-1, 0, 1}. The result digit d_i and outgoing carry c_out are determined as follows:- If s = -1, then d_i = 1, c_out = 1 (since -1 = (-2) · 1 + 1).
- If s = 0, then d_i = 0, c_out = 0.
- If s = 1, then d_i = 1, c_out = 0.
- If s = 2, then d_i = 0, c_out = -1 (since 2 = (-2) · (-1) + 0).
- If s = 3, then d_i = 1, c_out = -1 (since 3 = (-2) · (-1) + 1).
| A | B | C_in | S | C_out |
|---|---|---|---|---|
| 0 | 0 | -1 | 1 | 1 |
| 0 | 0 | 0 | 0 | 0 |
| 0 | 0 | 1 | 1 | 0 |
| 0 | 1 | -1 | 0 | 0 |
| 0 | 1 | 0 | 1 | 0 |
| 0 | 1 | 1 | 0 | -1 |
| 1 | 0 | -1 | 0 | 0 |
| 1 | 0 | 0 | 1 | 0 |
| 1 | 0 | 1 | 0 | -1 |
| 1 | 1 | -1 | 1 | 0 |
| 1 | 1 | 0 | 0 | -1 |
| 1 | 1 | 1 | 1 | -1 |
The negabinary representation of 6 is 11010_{-2} (reading left to right as MSB to LSB: 1·16 + 1·(-8) + 0·4 + 1·(-2) + 0·1 = 6).
The representation of -3 is 1101_{-2} (1·(-8) + 1·4 + 0·(-2) + 1·1 = -3), padded to 01101_{-2} for alignment. Aligning from LSB (right):
1 1 0 1 0
+ 0 1 1 0 1
-----------
1 1 0 1 0
+ 0 1 1 0 1
-----------
- Position 0 (LSB): 0 + 1 + 0 = 1 → d_0 = 1, c = 0
- Position 1: 1 + 0 + 0 = 1 → d_1 = 1, c = 0
- Position 2: 0 + 1 + 0 = 1 → d_2 = 1, c = 0
- Position 3: 1 + 1 + 0 = 2 → d_3 = 0, c = -1 (2 - 2 = 0, carry -1)
- Position 4: 1 + 0 + (-1) = 0 → d_4 = 0, c = 0
Multiplication and Division
Multiplication in negative base numeral systems follows a shift-and-add approach analogous to positive bases, but adapted for the negative value of the base β, where β < 0. Each left shift by k positions multiplies the partial product by β^k, resulting in alternating signs due to the odd and even powers of the negative base. This can lead to sign flips in partial products, complicating the accumulation process as positive and negative contributions must be carefully added using the base's addition rules. For instance, in negabinary (base -2), the powers alternate between positive (even positions: (+1), (+4), (+16), ...) and negative (odd positions: (-2), (-8), (-32), ...), requiring adjustments during summation to handle carries that may propagate differently than in positive bases.[5][22] A worked example in negabinary illustrates this: multiply 3 (represented as 111_{-2}) by 4 (100_{-2}). The multiplicand is 111_{-2}, and the multiplier 100_{-2} has a single '1' in the position corresponding to (-2)^2 = +4. Thus, the partial product is the multiplicand shifted left by 2 positions: 11100_{-2}. Evaluating 11100_{-2} = 1 \cdot (-2)^4 + 1 \cdot (-2)^3 + 1 \cdot (-2)^2 + 0 \cdot (-2)^1 + 0 \cdot (-2)^0 = 16 - 8 + 4 = 12_{10}, which is correct since 3 \times 4 = 12. The result 12 in negabinary is 11100_{-2}, confirming the computation. The alternating signs in the shifted terms (-8 from the second position) highlight the potential for sign flips that must be resolved during final addition.[5] Booth's multiplication algorithm, originally designed for signed binary numbers, can be adapted for negative bases using non-negative digits (0 to |β|-1). The adaptation simplifies the recoding of the multiplier since digits are unsigned, reducing the number of partial additions compared to standard shift-and-add, though the negative base still introduces sign alternations in shifts. This is particularly useful for hardware implementations where minimizing additions improves efficiency. Division in negative bases employs long division with remainders constrained to be non-negative (0 ≤ r < |β|), similar to positive bases but with adjustments for the negative divisor. The quotient q is computed via repeated subtraction or estimation, ensuring the remainder satisfies the condition; if a negative remainder arises, it is incremented by |β| and the quotient decremented accordingly. A key formula for adjustment is q = \lfloor (n - r) / \beta \rfloor, where n is the dividend and r is chosen to keep 0 ≤ r < |β|, accounting for the floor function's behavior with negative β (towards negative infinity). This prevents invalid digits and maintains uniqueness.[27] A divide-and-correct algorithm provides an efficient method for multiple-precision division: an initial quotient is estimated by dividing the dividend by the divisor (treating the base as positive for approximation), then corrected by adding or subtracting a factor based on the error, applicable to any negative base like -10. This approach is suitable for computational implementation, reducing iterations compared to naive long division. Challenges include handling the sign of partial remainders, which may require additional steps to ensure non-negative results without introducing negative digits.[27]Magnitude Comparison
To compare the magnitudes of two integers represented in the same negative base (where is an integer), align the representations by padding the shorter one with leading zeros to match the length of the longer one. This ensures both numbers have the same number of digits, with place values starting from the least significant digit (LSD) as , , , and so on, alternating signs with magnitudes increasing as .[5] Begin the comparison from the most significant digit (MSD, leftmost position). Proceed rightward until finding the first position where the digits differ. Let the place value at that position have sign (where is the power from the LSD). If the digit in the first number is larger than in the second and , the first number is greater; if , the first number is smaller. If all digits match, the numbers are equal. This method accounts for the alternating signs, as a larger digit in a positive place increases the value, while in a negative place it decreases it (making the number more negative).[5] If the original representations have different lengths and the leading digits are nonzero, the longer representation's MSD position determines the initial difference after padding. For instance, in base , the sign of the highest power is positive if (the length) is odd and negative if even. Thus, a longer odd-length number with a positive leading digit (>0) generally has larger magnitude than a shorter one, while an even-length longer number tends to have smaller magnitude, but the full digit-by-digit check confirms the order.[5] Consider the example in base : compare and . Pad the second to five digits: . The positions from left (powers 4 to 0: +16, -8, +4, -2, +1) are:- Position 4 (+16): 1 > 0, and positive place, so (i.e., 6 > -6).[5]
