In mathematics, the concept of a measure is an extension and formalisation of geometrical measurements (such as length, area, and volume) and other common notions, such as mass and the probability of certain occurrences happening.
These seemingly unrelated ideas share a lot in common and are frequently capable of being discussed within the same mathematical framework due to their similarities.
Measures that have been subjected to far-reaching generalisations, such as spectral measures and projection-valued measures, find widespread application in the field of quantum physics as well as in the field of physics in general.
In ancient Greece, when Archimedes was attempting to calculate the area of a circle, the intuition that underpins this concept may be traced back to that time period.
However, the study of measure theory did not become an established subfield of mathematics until the latter half of the 19th century and the early part of the 20th century.
The works of numerous individuals, including Émile Borel, Henri Lebesgue, Nikolai Luzin, Johann Radon, Constantin Carathéodory, and Maurice Fréchet, are credited with laying the groundwork for the contemporary theory of measurement.
This section is a list of several essential measures:-
The counting measure is denoted by the notation (S), which stands for the number of elements contained in S.
Every other measure that possesses these features extends the Lebesgue measure.
The Lebesgue measure on R is a complete translation-invariant measure on a -algebra that contains the intervals in R such that ([0, 1]) = 1.
Both circular angle measure and hyperbolic angle measure are invariant under the action of rotation, but only circular angle measure is invariant under the action of squeeze mapping.
A locally compact topological group’s Haar measure is a generalisation of the Lebesgue measure (as well as the counting measure and the circular angle measure), and it possesses the same uniqueness properties as the Lebesgue measure does.
The Lebesgue measure was extended to include sets having dimensions that are not integers, in particular fractal sets.
This extension resulted in the creation of the Hausdorff measure.
Every probability space gives rise to a measure that, when applied to the entire space, always takes the value 1.
(and therefore takes all its values in the unit interval [0, 1]).
A metric such as this is referred to as a probability measure. Axioms of probability can be found here.
The Dirac measure a (also known as the Dirac delta function) can be written as a(S) = S(a), where S is the indicator function of S.
This equation describes the Dirac measure a. If a set contains the point a, then its measure is 1, and if it does not, then its measure is 0.
Measures such as the Borel measure, the Jordan measure, the ergodic measure, the Gaussian measure, the Baire measure, the Radon measure, the Young measure, and the Loeb measure are some of the other “named” measures that are utilised in various theories.
Real-World Examples of How Measurement Theory Can Be Applied
The study of techniques of generalising the concepts of length, area, and volume is what measure theory is all about.
Much in two dimensions, it may not be obvious how to estimate the “area” of the following relatively benign shape:
and that’s before considering how to measure the “area” of even stranger shapes in higher dimensions or altogether different spaces.
It can be helpful to have a “measure” whose values are not limited to the non-negative reals or infinity for a number of different applications.
For example, For example, the term “signed measure” refers to a countably additive set function whose values are contained within the real numbers, but the term “complex measure” refers to the same type of function whose values are included within the complex numbers.
It is important to note, however, that complex measure must always have finite variation.
Hence, complex measures include finite signed measures but not others, such as the Lebesgue measure.
Measurement theory and its applications in the real world
Measure theory has numerous applications in real-world fields such as physics, economics, and finance, amongst others.
Techniques from the field of measure theory are hence essential for the work of any mathematician.
How can one put the concepts of measure theory into practice?
In the course of studying Measure Theory, we pay close attention to the many different ways that the size of a set can be measured.
The theory generalises the concepts of length, area, and volume while simultaneously making these concepts more rigorous.
Measure Theory, along with the theory of (Lebesgue) integration that it is related with, has essential applications in a wide variety of fields, including Functional Analysis, Harmonic Analysis, and Probability Theory.
Importance of the theory of measures
The formal theory behind anything that can be measured is known as “measure theory.”
This is of the utmost significance to the study of probability because, if we are unable to quantify the likelihood of an event occurring.
Conclusion
The study of measurements is known as measure theory.
It does so by generalising the concepts of length, area, and volume that come to mind naturally.
Other examples include the Borel measure, probability measure, complex measure, and the Haar measure.
The Jordan measure and the Lebesgue measure are among the earliest and most significant measures to serve as examples.