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**Linearity** is the property of a mathematical relationship (*function*) that can be graphically represented as a straight line. Linearity is closely related to *proportionality*. Examples in physics include rectilinear motion, the linear relationship of voltage and current in an electrical conductor (Ohm's law), and the relationship of mass and weight. By contrast, more complicated relationships are *nonlinear*.

Generalized for functions in more than one dimension, linearity means the property of a function of being compatible with addition and scaling, also known as the superposition principle.

The word **linear** comes from Latin *linearis*, "pertaining to or resembling a line".

In mathematics, a linear map or linear function *f*(*x*) is a function that satisfies the two properties:^{[1]}

- Additivity:
*f*(*x*+*y*) =*f*(*x*) +*f*(*y*). - Homogeneity of degree 1:
*f*(α*x*) = α*f*(*x*) for all α.

These properties are known as the superposition principle. In this definition, *x* is not necessarily a real number, but can in general be an element of any vector space. A more special definition of linear function, not coinciding with the definition of linear map, is used in elementary mathematics (see below).

Additivity alone implies homogeneity for rational α, since implies for any natural number *n* by mathematical induction, and then implies . The density of the rational numbers in the reals implies that any additive continuous function is homogeneous for any real number α, and is therefore linear.

The concept of linearity can be extended to linear operators. Important examples of linear operators include the derivative considered as a differential operator, and other operators constructed from it, such as del and the Laplacian. When a differential equation can be expressed in linear form, it can generally be solved by breaking the equation up into smaller pieces, solving each of those pieces, and summing the solutions.

Linear algebra is the branch of mathematics concerned with the study of vectors, vector spaces (also called 'linear spaces'), linear transformations (also called 'linear maps'), and systems of linear equations.

For a description of linear and nonlinear equations, see *linear equation*.

In a different usage to the above definition, a polynomial of degree 1 is said to be linear, because the graph of a function of that form is a straight line.^{[2]}

Over the reals, a linear equation is one of the forms:

where *m* is often called the slope or gradient; *b* the y-intercept, which gives the point of intersection between the graph of the function and the *y*-axis.

Note that this usage of the term *linear* is not the same as in the section above, because linear polynomials over the real numbers do not in general satisfy either additivity or homogeneity. In fact, they do so if and only if *b* = 0. Hence, if *b* ≠ 0, the function is often called an **affine function** (see in greater generality affine transformation).

In Boolean algebra, a linear function is a function for which there exist such that

- , where

Note that if , the above function is considered affine in linear algebra (i.e. not linear).

A Boolean function is linear if one of the following holds for the function's truth table:

- In every row in which the truth value of the function is T, there are an odd number of Ts assigned to the arguments, and in every row in which the function is F there is an even number of Ts assigned to arguments. Specifically,
*f*(F, F, ..., F) = F, and these functions correspond to linear maps over the Boolean vector space. - In every row in which the value of the function is T, there is an even number of Ts assigned to the arguments of the function; and in every row in which the truth value of the function is F, there are an odd number of Ts assigned to arguments. In this case,
*f*(F, F, ..., F) = T.

Another way to express this is that each variable always makes a difference in the truth value of the operation or it never makes a difference.

Negation, Logical biconditional, exclusive or, tautology, and contradiction are linear functions.

In physics, *linearity* is a property of the differential equations governing many systems; for instance, the Maxwell equations or the diffusion equation.^{[3]}

Linearity of a homogenous differential equation means that if two functions *f* and *g* are solutions of the equation, then any linear combination *af* + *bg* is, too.

In instrumentation, linearity means that a given change in an input variable gives the same change in the output of the measurement apparatus: this is highly desirable in scientific work. In general, instruments are close to linear over a certain range, and most useful within that range. In contrast, human senses are highly nonlinear: for instance, the brain completely ignores incoming light unless it exceeds a certain absolute threshold number of photons.

In electronics, the linear operating region of a device, for example a transistor, is where an output dependent variable (such as the transistor collector current) is directly proportional to an input dependent variable (such as the base current). This ensures that an analog output is an accurate representation of an input, typically with higher amplitude (amplified). A typical example of linear equipment is a high fidelity audio amplifier, which must amplify a signal without changing its waveform. Others are linear filters, and linear amplifiers in general.

In most scientific and technological, as distinct from mathematical, applications, something may be described as linear if the characteristic is approximately but not exactly a straight line; and linearity may be valid only within a certain operating region—for example, a high-fidelity amplifier may distort a small signal, but sufficiently little to be acceptable (acceptable but imperfect linearity); and may distort very badly if the input exceeds a certain value.^{[4]}

For an electronic device (or other physical device) that converts a quantity to another quantity, Bertram S. Kolts writes:^{[5]}^{[6]}

There are three basic definitions for integral linearity in common use: independent linearity, zero-based linearity, and terminal, or end-point, linearity. In each case, linearity defines how well the device's actual performance across a specified operating range approximates a straight line. Linearity is usually measured in terms of a deviation, or non-linearity, from an ideal straight line and it is typically expressed in terms of percent of full scale, or in ppm (parts per million) of full scale. Typically, the straight line is obtained by performing a least-squares fit of the data. The three definitions vary in the manner in which the straight line is positioned relative to the actual device's performance. Also, all three of these definitions ignore any gain, or offset errors that may be present in the actual device's performance characteristics.

In military tactical formations, "linear formations" were adapted starting from phalanx-like formations of pike protected by handgunners, towards shallow formations of handgunners protected by progressively fewer pikes. This kind of formation got progressively thinner until its extreme in the age of Wellington's 'Thin Red Line'. It was eventually replaced by skirmish order when the invention of the breech-loading rifle allowed soldiers to move and fire in small, mobile units, unsupported by large-scale formations of any shape.

**Linear** is one of the five categories proposed by Swiss art historian Heinrich Wölfflin to distinguish "Classic", or Renaissance art, from the Baroque. According to Wölfflin, painters of the fifteenth and early sixteenth centuries (Leonardo da Vinci, Raphael or Albrecht Dürer) are more linear than "painterly" Baroque painters of the seventeenth century (Peter Paul Rubens, Rembrandt, and Velázquez) because they primarily use outline to create shape.^{[7]} Linearity in art can also be referenced in digital art. For example, hypertext fiction can be an example of nonlinear narrative, but there are also websites designed to go in a specified, organized manner, following a linear path.

In music the **linear** aspect is succession, either intervals or melody, as opposed to simultaneity or the vertical aspect.

**^**Edwards, Harold M. (1995).*Linear Algebra*. Springer. p. 78. ISBN 9780817637316.**^**Stewart, James (2008).*Calculus: Early Transcendentals*, 6th ed., Brooks Cole Cengage Learning. ISBN 978-0-495-01166-8, Section 1.2**^**Evans, Lawrence C. (2010) [1998],*Partial differential equations*(PDF), Graduate Studies in Mathematics, vol. 19 (2nd ed.), Providence, R.I.: American Mathematical Society, doi:10.1090/gsm/019, ISBN 978-0-8218-4974-3, MR 2597943, archived (PDF) from the original on 2022-10-09**^**Whitaker, Jerry C. (2002).*The RF transmission systems handbook*. CRC Press. ISBN 978-0-8493-0973-1.**^**Kolts, Bertram S. (2005). "Understanding Linearity and Monotonicity" (PDF). analogZONE. Archived from the original (PDF) on February 4, 2012. Retrieved September 24, 2014.**^**Kolts, Bertram S. (2005). "Understanding Linearity and Monotonicity".*Foreign Electronic Measurement Technology*.**24**(5): 30–31. Retrieved September 25, 2014.**^**Wölfflin, Heinrich (1950). Hottinger, M.D. (ed.).*Principles of Art History: The Problem of the Development of Style in Later Art*. New York: Dover. pp. 18–72. ISBN 9780486202761.

- The dictionary definition of
*linearity*at Wiktionary