# Loss of significance

﻿
Loss of significance

Loss of significance is an undesirable effect in calculations using floating-point arithmetic. It occurs when an operation on two numbers increases relative error substantially more than it increases absolute error, for example in subtracting two large and nearly equal numbers. The effect is that the number of accurate (significant) digits in the result is reduced unacceptably. Ways to avoid this effect are studied in numerical analysis.

In floating-point arithmetic, only a limited number of digits of the number are maintained; floating-point numbers can only approximate most real numbers.

Consider the real number

:$0.1234567891234567890.$

A floating-point representation of this number on a machinethat keeps 10 floating-point digits would be

:$0.1234567891,$

which is fairly close &mdash; the difference is very small incomparison with either of the two numbers.

Now perform the calculation

:$0.1234567891234567890 - 0.1234567890.$

The real answer, accurate to 10 digits, is

:$0.0000000001234567890.$

However, on the 10-digit floating-point machine, the calculation yields

:$0.1234567891 - 0.1234567890 = 0.0000000001.$

Whereas the original numbers are accurate in all of the first(most significant) 10 digits, their floating-point differenceis only accurate in its first digit. This amounts to lossof information.

It is possible to do computations using an exact representation of rational numbers and keep all significant digits, but this is often prohibitively slower than floating-point arithmetic. Furthermore, it usually only postponesthe problem: What if the data is accurate to only 10 digits?The same effect will occur.

One of the most important parts of numerical analysis is to avoidor minimize loss of significance in calculations. If the underlyingproblem is well-posed, there should be a
stable algorithm for solving it. The art is in finding a stable algorithm.

Loss of significant bits

Let "x" and "y" be positive normalized floating point numbers.

In the subtraction "x" − "y", "r" significant bits are lost where

:$q le r le p$

:$2^\left\{-p\right\} le 1 - frac\left\{y\right\}\left\{x\right\} le 2^\left\{-q\right\}$

for some positive integers "p" and "q".

For example, consider the venerable quadratic equation

:$a x^2 + b x + c = 0.$

The quadratic equation gives the two solutions as

:$x = frac\left\{-b pm sqrt\left\{b^2 - 4ac\left\{2a\right\}.$

The case $a = 1$, $b = 200$, $c = -0.000015$ will serve to illustrate the problem:

:$x^2 + 200 x - 0.000015 = 0.$

We have

:$sqrt\left\{b^2 - 4 a c\right\} = sqrt\left\{200^2 + 4 imes 1 imes 0.000015\right\} = 200.00000015...$

In real arithmetic, the roots are

:$\left( -200 - 200.00000015 \right) / 2 = -200.000000075,$:$\left( -200 + 200.00000015 \right) / 2 = .000000075.$

In 10-digit floating-point arithmetic,

:$\left( -200 - 200.0000001 \right) / 2 = -200.00000005,$:$\left( -200 + 200.0000001 \right) / 2 = .00000005.$

Notice that the solution of greater magnitude is accurate to ten digits, but the first nonzero digit of the solution of lesser magnitude is wrong.

Because of the subtraction that occurs in the quadratic equation,it does not constitute a stable algorithm to calculate thetwo roots.

A better algorithm

A better algorithm for solving quadratic equations is based on two observations: that one solution is always accurate when the other is not, and that given one solution of the quadratic, the other is easy to find.

If:$x_1 = frac\left\{-b + sqrt\left\{b^2 - 4ac\left\{2a\right\}$

and:$x_2 = frac\left\{2c\right\}\left\{-b + sqrt\left\{b^2 - 4ac$

then we have the identity

:$x_1 x_2 = c / a$.

The algorithm is as follows. Use the quadratic formula to find the solution of greater magnitude, which "does not" suffer from loss of precision.Then use this identity to calculate the other root. Since nosubtraction is involved, no loss of precision occurs.

Applying this algorithm to our problem, and using 10-digit floating-pointarithmetic, the solution of greater magnitude, as before, is$x_1 = -200.00000005.$ The other solution is then

:$x_2 = c / \left(-200.00000005\right) = 0.000000075,$

which is accurate.

Wikimedia Foundation. 2010.

### Look at other dictionaries:

• Significance arithmetic — is a set of rules (sometimes called significant figure rules) for approximating the propagation of uncertainty in scientific or statistical calculations. These rules can be used to find the appropriate number of significant figures to use to… …   Wikipedia

• Loss of Strength Gradient — The Loss of Strength Gradient (LSG) was devised by Kenneth Boulding in 1962. He argued that the amount of a nation’s military power that could be brought to bear in any part of the world depended on geographic distance. The Loss of Strength… …   Wikipedia

• Unrealized Loss — A loss that results from holding onto an asset after it has decreased in price, rather than selling it and realizing the loss. An investor may prefer to let a loss go unrealized in the hope that the asset will eventually recover in price, thereby …   Investment dictionary

• Floating point — In computing, floating point describes a method of representing real numbers in a way that can support a wide range of values. Numbers are, in general, represented approximately to a fixed number of significant digits and scaled using an exponent …   Wikipedia

• Numerical analysis — Babylonian clay tablet BC 7289 (c. 1800–1600 BC) with annotations. The approximation of the square root of 2 is four sexagesimal figures, which is about six decimal figures. 1 + 24/60 + 51/602 + 10/603 = 1.41421296...[1] Numerical analysis is the …   Wikipedia

• List of numerical analysis topics — This is a list of numerical analysis topics, by Wikipedia page. Contents 1 General 2 Error 3 Elementary and special functions 4 Numerical linear algebra …   Wikipedia

• eclipse — ► NOUN 1) an obscuring of the light from one celestial body by the passage of another between it and the observer or between it and its source of illumination. 2) a sudden loss of significance, power, or prominence. ► VERB 1) (of a celestial… …   English terms dictionary