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style="display:inline-block; float: left;" onfocus="this.value == 'Search' ? this.value = '' : true" onblur="this.value == '' ? this.value = 'Search' : true" /></fieldset> </form> <span id='navEnd'></span> </div> <div id="revision"> <html xmlns="http://www.w3.org/1999/xhtml" xmlns:svg="http://www.w3.org/2000/svg" xml:lang="en" lang="en"> <head><meta http-equiv="Content-type" content="application/xhtml+xml;charset=utf-8" /><title>Contents</title></head> <body> <div class="rightHandSide"> <div class="toc clickDown" tabindex="0"> <h3 id="context">Context</h3> <h4 id="measure_and_probability_theory">Measure and probability theory</h4> <div class="hide"><div> <p><strong><a class="existingWikiWord" href="/nlab/show/measure+theory">measure theory</a></strong></p> <p><strong><a class="existingWikiWord" href="/nlab/show/probability+theory">probability theory</a></strong></p> <p>(<a class="existingWikiWord" href="/nlab/show/quantum+probability">quantum probability</a>)</p> <h2 id="measure_theory">Measure theory</h2> <ul> <li> <p><a class="existingWikiWord" href="/nlab/show/measurable+space">measurable space</a>, <a class="existingWikiWord" href="/nlab/show/measurable+locale">measurable locale</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/measure">measure</a>, <a class="existingWikiWord" href="/nlab/show/measure+space">measure space</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/von+Neumann+algebra">von Neumann algebra</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/geometric+measure+theory">geometric measure theory</a></p> </li> </ul> <h2 id="probability_theory">Probability theory</h2> <ul> <li> <p><a class="existingWikiWord" href="/nlab/show/probability+space">probability space</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/probability+distribution">probability distribution</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/state">state</a></p> <ul> <li> <p><a class="existingWikiWord" href="/nlab/show/states+in+AQFT+and+operator+algebra">in AQFT and operator algebra</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/GNS+construction">GNS construction</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/Fell%27s+theorem">Fell's theorem</a></p> </li> </ul> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/entropy">entropy</a>, <a class="existingWikiWord" href="/nlab/show/relative+entropy">relative entropy</a></p> </li> </ul> <h2 id="information_geometry">Information geometry</h2> <ul> <li> <p><a class="existingWikiWord" href="/nlab/show/information+geometry">information geometry</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/information+metric">information metric</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/Wasserstein+metric">Wasserstein metric</a></p> </li> </ul> <h2 id="thermodynamics">Thermodynamics</h2> <ul> <li> <p><a class="existingWikiWord" href="/nlab/show/thermodynamics">thermodynamics</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/second+law+of+thermodynamics">second law of thermodynamics</a>, <a class="existingWikiWord" href="/nlab/show/generalized+second+law+of+theormodynamics">generalized second law</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/ergodic+theory">ergodic theory</a></p> </li> </ul> <h2 id="theorems">Theorems</h2> <ul> <li> <p><a class="existingWikiWord" href="/nlab/show/Riesz+representation+theorem">Riesz representation theorem</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/de+Finetti%27s+theorem">de Finetti's theorem</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/law+of+large+numbers">law of large numbers</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/Kolmogorov+extension+theorem">Kolmogorov extension theorem</a></p> </li> </ul> <h2 id="applications">Applications</h2> <ul> <li><a class="existingWikiWord" href="/nlab/show/machine+learning">machine learning</a>, <a class="existingWikiWord" href="/nlab/show/neural+networks">neural networks</a></li> </ul> </div></div> </div> </div> <h1 id="contents">Contents</h1> <div class='maruku_toc'> <ul> <li><a href='#idea'>Idea</a></li> <li><a href='#theory'>Theory</a></li> <ul> <li><a href='#basic_theory'>Basic theory</a></li> <li><a href='#stochastic_random_processes'>Stochastic (random) processes</a></li> <li><a href='#statistical_manifolds'>Statistical Manifolds</a></li> <li><a href='#probability_theory_from_the_npov'>Probability theory from the nPOV</a></li> <li><a href='#generalizations'>Generalizations</a></li> </ul> <li><a href='#applications'>Applications</a></li> <li><a href='#related_concepts'>Related concepts</a></li> <li><a href='#references'>References</a></li> <ul> <li><a href='#general'>General</a></li> <li><a href='#AsEuclideanFieldTheories'>As Euclidean field theory</a></li> </ul> </ul> </div> <h2 id="idea">Idea</h2> <p>Probability theory is concerned with mathematical models of phenomena that exhibit <em>randomness</em>, or more generally phenomena about which one has incomplete information.</p> <p>Its central mathematical model is based mostly on <a class="existingWikiWord" href="/nlab/show/measure+theory">measure theory</a>. So from a pure mathematical viewpoint probability theory today could be characterized as the study of <a class="existingWikiWord" href="/nlab/show/measurable+space">measurable space</a>s with a finite volume normalized to <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mn>1</mn></mrow><annotation encoding="application/x-tex">1</annotation></semantics></math>.</p> <p>Broader perspectives may stress the relevance of other pure mathematical concepts for probability theory, or include aspects of the interpretation of mathematical results to <a class="existingWikiWord" href="/nlab/show/phenomenology">phenomenology</a>, the latter part making naturally contact with the field of <a class="existingWikiWord" href="/nlab/show/statistics">statistics</a>.</p> <p>Notice that in this respect probability theory has a similar status as (other(?!)) theories of <a class="existingWikiWord" href="/nlab/show/physics">physics</a>: there is a mathematical model (measure theory here as the model for probability theory, or for instance <a class="existingWikiWord" href="/nlab/show/symplectic+geometry">symplectic geometry</a> as a model for <a class="existingWikiWord" href="/nlab/show/classical+mechanics">classical mechanics</a>) which can be studied all in itself, and then there is in addition a more or less concrete idea of how from that model one may deduce statements about the observable world (the average outcome of a dice role using probability theory, or the observability of the next solar eclipse using <a class="existingWikiWord" href="/nlab/show/Hamiltonian+mechanics">Hamiltonian mechanics</a>). The step from the mathematical model to its use as a tool for making statements about the observable world is subtle, maybe a subject of <a class="existingWikiWord" href="/nlab/show/philosophy">philosophy</a>, but in any case outside of the realm of <a class="existingWikiWord" href="/nlab/show/mathematics">mathematics</a>. In probability theory the meaning of this step is traditionally a cause of debate, with two antagonistic main schools of thought being the <em>frequentist interpretation</em> and the <em><a class="existingWikiWord" href="/nlab/show/Bayesianism">Bayesian perspective</a></em> on the nature of the relation of probability theory to the observable world.</p> <h2 id="theory">Theory</h2> <h3 id="basic_theory">Basic theory</h3> <p><a class="existingWikiWord" href="/nlab/show/random+variable">Random variables</a> are defined typically in terms of <a class="existingWikiWord" href="/nlab/show/probability+spaces">probability spaces</a>, cf. the basic entries on <a class="existingWikiWord" href="/nlab/show/measure+space">measure space</a>, <a class="existingWikiWord" href="/nlab/show/probability+space">probability space</a>, <a class="existingWikiWord" href="/nlab/show/conditional+expectation">conditional probability</a>. The modern point of view emphasises that many facts about <a class="existingWikiWord" href="/nlab/show/random+variables">random variables</a> do not depend much on the choice of the probability spaces; the random variables are also often identified with their distributions.</p> <p>Some argue that in the study of measure and probability, one should start not only with sigma algebra of measurable sets but also another of null sets. Somehow this is abstractly captured by the approach of commutative <a class="existingWikiWord" href="/nlab/show/von+Neumann">von Neumann</a> algebras.</p> <h3 id="stochastic_random_processes">Stochastic (random) processes</h3> <p>(…)</p> <p><a class="existingWikiWord" href="/nlab/show/ergodic+process">ergodic process</a></p> <p>(…)</p> <h3 id="statistical_manifolds">Statistical Manifolds</h3> <p>Families of probability distributions often form statistical models, that is, submanifolds of the space of all probability measures on a sample space. Techniques from <a class="existingWikiWord" href="/nlab/show/differential+geometry">differential geometry</a> may be applied in a theory known as <a class="existingWikiWord" href="/nlab/show/information+geometry">information geometry</a>.</p> <h3 id="probability_theory_from_the_npov">Probability theory from the nPOV</h3> <p>We describe here some perspectives on (parts of) probability theory from the categorical point of view (see <a class="existingWikiWord" href="/nlab/show/nPOV">nPOV</a>). This perspective mainly applies to the study of situations involving Markov kernels and Chapman-Kolmogorov property.</p> <p>See also <a class="existingWikiWord" href="/nlab/show/categorical+approaches+to+probability+theory">categorical approaches to probability theory</a>.</p> <p><a class="existingWikiWord" href="/nlab/show/Prakash+Panangaden">Prakash Panangaden</a> in <a href="http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.52.4840">Probabilistic Relations</a> defines the <a class="existingWikiWord" href="/nlab/show/category">category</a> <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>SRel</mi></mrow><annotation encoding="application/x-tex">SRel</annotation></semantics></math> (stochastic <a class="existingWikiWord" href="/nlab/show/relation">relation</a>s) to have as <a class="existingWikiWord" href="/nlab/show/object">object</a>s <a class="existingWikiWord" href="/nlab/show/set">set</a>s equipped with a <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>σ</mi></mrow><annotation encoding="application/x-tex">\sigma</annotation></semantics></math><a class="existingWikiWord" href="/nlab/show/sigma-field">-field</a>. <a class="existingWikiWord" href="/nlab/show/morphism">Morphisms</a> are conditional probability densities or stochastic kernels. So, a morphism from <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mo stretchy="false">(</mo><mi>X</mi><mo>,</mo><msub><mi>Σ</mi> <mi>X</mi></msub><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">( X, \Sigma_X)</annotation></semantics></math> to <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mo stretchy="false">(</mo><mi>Y</mi><mo>,</mo><msub><mi>Σ</mi> <mi>Y</mi></msub><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">( Y, \Sigma_Y)</annotation></semantics></math> is a function <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>h</mi><mo>:</mo><mi>X</mi><mo>×</mo><msub><mi>Σ</mi> <mi>Y</mi></msub><mo>→</mo><mo stretchy="false">[</mo><mn>0</mn><mo>,</mo><mn>1</mn><mo stretchy="false">]</mo></mrow><annotation encoding="application/x-tex">h: X \times \Sigma_Y \to [0, 1]</annotation></semantics></math> such that</p> <ol> <li><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mo>∀</mo><mi>B</mi><mo>∈</mo><msub><mi>Σ</mi> <mi>Y</mi></msub><mo>.</mo><mi>λ</mi><mi>x</mi><mo>∈</mo><mi>X</mi><mo>.</mo><mi>h</mi><mo stretchy="false">(</mo><mi>x</mi><mo>,</mo><mi>B</mi><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">\forall B \in \Sigma_Y . \lambda x \in X . h(x, B)</annotation></semantics></math> is a bounded measurable function,</li> <li><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mo>∀</mo><mi>x</mi><mo>∈</mo><mi>X</mi><mo>.</mo><mi>λ</mi><mi>B</mi><mo>∈</mo><msub><mi>Σ</mi> <mi>Y</mi></msub><mo>.</mo><mi>h</mi><mo stretchy="false">(</mo><mi>x</mi><mo>,</mo><mi>B</mi><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">\forall x \in X . \lambda B \in \Sigma_Y . h(x, B)</annotation></semantics></math> is a subprobability measure on <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><msub><mi>Σ</mi> <mi>Y</mi></msub></mrow><annotation encoding="application/x-tex">\Sigma_Y</annotation></semantics></math>.</li> </ol> <p>If <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>k</mi></mrow><annotation encoding="application/x-tex">k</annotation></semantics></math> is a morphism from <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>Y</mi></mrow><annotation encoding="application/x-tex">Y</annotation></semantics></math> to <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>Z</mi></mrow><annotation encoding="application/x-tex">Z</annotation></semantics></math>, then <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>k</mi><mo>⋅</mo><mi>h</mi></mrow><annotation encoding="application/x-tex">k \cdot h</annotation></semantics></math> from <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>X</mi></mrow><annotation encoding="application/x-tex">X</annotation></semantics></math> to <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>Z</mi></mrow><annotation encoding="application/x-tex">Z</annotation></semantics></math> is defined as <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mo stretchy="false">(</mo><mi>k</mi><mo>⋅</mo><mi>h</mi><mo stretchy="false">)</mo><mo stretchy="false">(</mo><mi>x</mi><mo>,</mo><mi>C</mi><mo stretchy="false">)</mo><mo>=</mo><msub><mo>∫</mo> <mi>Y</mi></msub><mi>k</mi><mo stretchy="false">(</mo><mi>y</mi><mo>,</mo><mi>C</mi><mo stretchy="false">)</mo><mi>h</mi><mo stretchy="false">(</mo><mi>x</mi><mo>,</mo><mi>d</mi><mi>y</mi><mo stretchy="false">)</mo></mrow><annotation encoding="application/x-tex">(k \cdot h)(x, C) = \int_Y k(y, C)h(x, d y)</annotation></semantics></math>.</p> <p>This is based on earlier work by Michele Giry, see <a class="existingWikiWord" href="/nlab/show/Giry%27s+monad">Giry's monad</a>.</p> <ul> <li>Michèle Giry, <em>A categorical approach to probability theory</em> Categorical aspects of topology and analysis (Ottawa, Ont., 1980), pp. 68–85, Lecture Notes in Math., 915, Springer.</li> </ul> <p>Panangaden’s definition differs from Giry’s in the second clause where subprobability measures, rather than ordinary probability measures, are allowed.</p> <p>Panangaden emphasises that the mechanism is similar to the way that the category of relations can be constructed from the <a class="existingWikiWord" href="/nlab/show/power+set">power set</a> <a class="existingWikiWord" href="/nlab/show/functor">functor</a>. Just as the category of relations is the <a class="existingWikiWord" href="/nlab/show/Kleisli+category">Kleisli category</a> of the powerset functor over the category of sets <a class="existingWikiWord" href="/nlab/show/Set">Set</a>, <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>SRel</mi></mrow><annotation encoding="application/x-tex">SRel</annotation></semantics></math> is the Kleisli category of the functor over the category of <a class="existingWikiWord" href="/nlab/show/measurable+space">measurable space</a>s and <a class="existingWikiWord" href="/nlab/show/measurable+function">measurable function</a>s which sends a measurable space, <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>X</mi></mrow><annotation encoding="application/x-tex">X</annotation></semantics></math>, to the measurable space of sub<a class="existingWikiWord" href="/nlab/show/probability+measure">probability measure</a>s on <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>X</mi></mrow><annotation encoding="application/x-tex">X</annotation></semantics></math>. This functor gives rise to a <a class="existingWikiWord" href="/nlab/show/monad">monad</a>.</p> <p>What is gained by the move from probability measures to subprobability measures? One motivation seems to be to model probabilistic processes from <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>X</mi></mrow><annotation encoding="application/x-tex">X</annotation></semantics></math> to a <a class="existingWikiWord" href="/nlab/show/coproduct">coproduct</a> <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>X</mi><mo>+</mo><mi>Y</mi></mrow><annotation encoding="application/x-tex">X + Y</annotation></semantics></math>. This you can iterate to form a process which looks to see where in <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>Y</mi></mrow><annotation encoding="application/x-tex">Y</annotation></semantics></math> you eventually end up. This relates to <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>SRel</mi></mrow><annotation encoding="application/x-tex">SRel</annotation></semantics></math> being traced.</p> <p>There is a <a class="existingWikiWord" href="/nlab/show/monad">monad</a> on <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>MeasureSpaces</mi></mrow><annotation encoding="application/x-tex">MeasureSpaces</annotation></semantics></math>, <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mn>1</mn><mo>+</mo><mo lspace="verythinmathspace" rspace="0em">−</mo><mo>:</mo><mi>Meas</mi><mo>→</mo><mi>Meas</mi></mrow><annotation encoding="application/x-tex">1 + -: Meas \to Meas</annotation></semantics></math>. A probability measure on <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mn>1</mn><mo>+</mo><mi>X</mi></mrow><annotation encoding="application/x-tex">1 + X</annotation></semantics></math> is a subprobability measure on <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>X</mi></mrow><annotation encoding="application/x-tex">X</annotation></semantics></math>. Panangaden’s monad is a composite of Giry’s and <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mn>1</mn><mo>+</mo><mo lspace="verythinmathspace" rspace="0em">−</mo></mrow><annotation encoding="application/x-tex">1 + -</annotation></semantics></math>.</p> <p>The opposite of the <a class="existingWikiWord" href="/nlab/show/Kleisli+category">Kleisli category</a> of <a class="existingWikiWord" href="/nlab/show/Giry%27s+monad">Giry's monad</a> has as morphisms <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>X</mi><mo>→</mo><mi>Y</mi></mrow><annotation encoding="application/x-tex">X \to Y</annotation></semantics></math>, linear maps from bounded functions on <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>X</mi></mrow><annotation encoding="application/x-tex">X</annotation></semantics></math> to bounded functions on <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>Y</mi></mrow><annotation encoding="application/x-tex">Y</annotation></semantics></math>, which send the characteristic function on <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>X</mi></mrow><annotation encoding="application/x-tex">X</annotation></semantics></math> to the characteristic function on <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mi>Y</mi></mrow><annotation encoding="application/x-tex">Y</annotation></semantics></math>.</p> <p>For more details on Giry’s monad and its variants see <a class="existingWikiWord" href="/nlab/show/probability+monad">probability monad</a>.</p> <h3 id="generalizations">Generalizations</h3> <ul> <li> <p><a class="existingWikiWord" href="/nlab/show/quantum+mechanics">Quantum mechanics</a> studies <a class="existingWikiWord" href="/nlab/show/complex+number">complex</a> probability amplitudes whose absolute square can be interpreted as the usual probability in the process of <a class="existingWikiWord" href="/nlab/show/measurement">measurement</a>, i.e. quantum reduction. An alternative approach via <span class="newWikiWord">Wigner's function<a href="/nlab/new/Wigner%27s+function">?</a></span> has real, but possibly outside <math xmlns="http://www.w3.org/1998/Math/MathML" display="inline" class="maruku-mathml"><semantics><mrow><mo stretchy="false">[</mo><mn>0</mn><mo>,</mo><mn>1</mn><mo stretchy="false">]</mo></mrow><annotation encoding="application/x-tex">[0,1]</annotation></semantics></math>, probabilities.</p> </li> <li> <p>Relatedly, noncommutative <a class="existingWikiWord" href="/nlab/show/von+Neumann+algebras">von Neumann algebras</a> may be interpreted as a noncommutative measure theory, analogous to the role that <a class="existingWikiWord" href="/nlab/show/C%2A-algebras">C*-algebras</a> play in <a class="existingWikiWord" href="/nlab/show/noncommutative+geometry">noncommutative geometry</a>, see at <em><a class="existingWikiWord" href="/nlab/show/quantum+probability">quantum probability</a></em>.</p> </li> <li> <p>The <a class="existingWikiWord" href="/nlab/show/free+probability">free probability</a> theory of Voiculescu and others is another noncommutative generalization, with physical applications related to <a class="existingWikiWord" href="/nlab/show/random+matrix+theory">random matrix theory</a>.</p> </li> </ul> <h2 id="applications">Applications</h2> <ul> <li><a class="existingWikiWord" href="/nlab/show/statistical+mechanics">statistical mechanics</a></li> <li><a class="existingWikiWord" href="/nlab/show/stochastic+Loewner+equation">stochastic Loewner equation</a> has relation to <a class="existingWikiWord" href="/nlab/show/conformal+field+theory">conformal field theory</a> discovered by Schramm and collaborators including Fields medalist Werner.</li> </ul> <h2 id="related_concepts">Related concepts</h2> <ul> <li> <p><a class="existingWikiWord" href="/nlab/show/probability+space">probability space</a>, <a class="existingWikiWord" href="/nlab/show/random+variable">random variable</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/expectation+value">expectation value</a>,</p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/almost+surely">almost surely</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/Radon-Nikodym+derivative">Radon-Nikodym derivative</a>,</p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/cumulant">cumulant</a>,</p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/ergodic+theory">ergodic theory</a>,</p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/statistics">statistics</a>,</p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/stochastic+process">stochastic process</a>,</p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/Wiener+measure">Wiener measure</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/Bayesian+reasoning">Bayesian reasoning</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/central+limit+theorem">central limit theorem</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/infra-Bayesianism">infra-Bayesianism</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/imprecise+probability">imprecise probability</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/free+probability">free probability</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/quantum+probability">quantum probability</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/synthetic+probability+theory">synthetic probability theory</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/statistical+significance">statistical significance</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/p-value">p-value</a></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/Monte+Carlo+method">Monte Carlo method</a></p> </li> </ul> <h2 id="references">References</h2> <h3 id="general">General</h3> <p>The modern formalization of probability theory in <a class="existingWikiWord" href="/nlab/show/measure+theory">measure theory</a> originates around</p> <ul> <li id="Kolmogorov33"><a class="existingWikiWord" href="/nlab/show/Andrey+Kolmogorov">Andrey Kolmogorov</a>, <em>Grundbegriffe der Wahrscheinlichkeitsrechnung</em>, Ergebnisse der Mathematik und Ihrer Grenzgebiete, Springer Berlin Heidelberg, 1933</li> </ul> <p>Lecture notes include</p> <ul> <li id="Grigoryan08"> <p>Alexander Grigoryan, <em>Measure theory and probability</em>, 2008 <a href="https://www.math.uni-bielefeld.de/~grigor/mwlect.pdf">pdf</a></p> </li> <li id="Tao10"> <p><a class="existingWikiWord" href="/nlab/show/Terence+Tao">Terence Tao</a>, <em>A review of probabiltiy theory</em>, 2010 (<a href="https://terrytao.wordpress.com/2010/01/01/254a-notes-0-a-review-of-probability-theory/">web</a>)</p> </li> </ul> <blockquote> <p>just as the natural numbers can be defined abstractly without reference to any numeral system (e.g. by the Peano axioms), core concepts of probability theory, such as random variables, can also be defined abstractly, without explicit mention of a measure space; we will return to this point when we discuss free probability later in this course.</p> </blockquote> <ul> <li> <p><a class="existingWikiWord" href="/nlab/show/Terence+Tao">Terence Tao</a>, <em>Free probability</em>, 2010 (<a href="https://terrytao.wordpress.com/2010/02/10/245a-notes-5-free-probability/">web</a>)</p> </li> <li id="Dembo12"> <p><a class="existingWikiWord" href="/nlab/show/Amir+Dembo">Amir Dembo</a>, <em>Probability theory</em>, 2012 (<a href="http://statweb.stanford.edu/~adembo/stat-310a/lnotes.pdf">pdf</a>)</p> </li> </ul> <p>For references related to <a class="existingWikiWord" href="/nlab/show/Giry%27s+monad">Giry's monad</a> and variants see there.</p> <p>Formulation in <a class="existingWikiWord" href="/nlab/show/category+theory">category theory</a>:</p> <ul> <li> <p><a class="existingWikiWord" href="/nlab/show/Tobias+Fritz">Tobias Fritz</a>, <em>A synthetic approach to Markov kernels, conditional independence, and theorems on sufficient statistics</em>, (<a href="https://arxiv.org/abs/1908.07021">arXiv:1908.07021</a>)</p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/Kirk+Sturtz">Kirk Sturtz</a>, <em>Categorical probability theory</em> (<a href="https://arxiv.org/abs/1406.6030">arXiv:1406.6030</a>)</p> </li> </ul> <p>Formulation in <a class="existingWikiWord" href="/nlab/show/topos+theory">topos theory</a>:</p> <ul> <li><a class="existingWikiWord" href="/nlab/show/Alex+Simpson">Alex Simpson</a>, <em>Probability sheaves and the Giry monad</em>, 2017 (<a href="https://coalg.org/mfps-calco2017/calco-papers/calco2017-1.pdf">pdf</a>, <a href="https://youtu.be/IMGoluu1mgc">talk recording</a>)</li> </ul> <p>For a more convenient setting for ‘higher-order’ probability theory, that is, one which admits higher-order functions, the following article uses the <a class="existingWikiWord" href="/nlab/show/cartesian+closed+category">cartesian closed category</a> of <a class="existingWikiWord" href="/nlab/show/quasi-Borel+space">quasi-Borel spaces</a> rather than the category of measurable spaces:</p> <ul> <li><a class="existingWikiWord" href="/nlab/show/Chris+Heunen">Chris Heunen</a>, Ohad Kammar, Sam Staton, Hongseok Yang, <em>A Convenient Category for Higher-Order Probability Theory</em>, (<a href="https://arxiv.org/abs/1701.02547">arXiv:1701.02547</a>)</li> </ul> <p>For big picture in probability theory see answers to</p> <ul> <li>MathOverflow: <a href="http://mathoverflow.net/questions/20740/is-there-an-introduction-to-probability-theory-from-a-structuralist-categorical-p">is-there-an-introduction-to-probability-theory-from-a-structuralist-categorical-p</a></li> </ul> <p>An instance of a “categorical thinking” (in a generalized sense) in solving probability problems is a solution to Buffon’s noodle problem (<a href="http://en.wikipedia.org/wiki/Buffon%27s_noodle">wikipedia</a>) discussed by Tom Leinster at nCafe <a href="http://golem.ph.utexas.edu/category/2010/03/a_perspective_on_higher_catego.html">here</a>.</p> <ul> <li> <p>Klain, <a class="existingWikiWord" href="/nlab/show/Gian-Carlo+Rota">Gian-Carlo Rota</a>, <em>Introduction to geometric probability</em></p> </li> <li> <p><a class="existingWikiWord" href="/nlab/show/John+C.+Baez">John C. Baez</a>, Jacob D. Biamonte, <em>A course on</em></p> <p>quantum techniques for stochastic mechanics_, <a href="http://math.ucr.edu/home/baez/stoch_stable.pdf">pdf</a></p> </li> </ul> <p>Discussion from a perspective of <a class="existingWikiWord" href="/nlab/show/formal+logic">formal logic</a>/<a class="existingWikiWord" href="/nlab/show/type+theory">type theory</a> is in</p> <ul> <li id="Toronto14"><a class="existingWikiWord" href="/nlab/show/Neil+Toronto">Neil Toronto</a>, <em>Useful Languages for Probabilistic Modeling and Inference</em>, PhD Thesis, 2014 (<a href="http://cs.umd.edu/~ntoronto/papers/toronto-2014diss.pdf">pdf</a>, <a href="http://cs.umd.edu/~ntoronto/papers/toronto-2014diss-slides.pdf">slides</a>)</li> </ul> <p><a class="existingWikiWord" href="/nlab/show/Mikhail+Gromov">Mikhail Gromov</a> on possible generalizations/modifications of probability theory (especially probability theory seen as, fundamentally, a “”functor“ from a ”complex category“ to a ”simple category“”), as well as applications of probability within and without pure mathematics:</p> <ul> <li><em>Probability, symmetry, linearity. (six lectures)</em>. IHES, Nov 2014. (<a href="https://www.youtube.com/watch?v=aJAQVletzdY">videos</a>) (<a href="https://www.ihes.fr/~gromov/wp-content/uploads/2018/08/probability-huge-Lecture-Nov-2014.pdf">pdf</a>).</li> </ul> <h3 id="AsEuclideanFieldTheories">As Euclidean field theory</h3> <p>Probability regarded as <a class="existingWikiWord" href="/nlab/show/Euclidean+quantum+field+theory">Euclidean quantum field theory</a>:</p> <p>(…) see references at <em><a class="existingWikiWord" href="/nlab/show/conformal+field+theory">conformal field theory</a></em></p> <p>In relation to the <a class="existingWikiWord" href="/nlab/show/mass+gap+problem">mass gap problem</a> in <a class="existingWikiWord" href="/nlab/show/lattice+gauge+theory">lattice gauge theory</a>:</p> <ul> <li> <p><a class="existingWikiWord" href="/nlab/show/Sourav+Chatterjee">Sourav Chatterjee</a>, <em>Yang-Mills for probabilists</em>, in: <em>Probability and Analysis in Interacting Physical Systems</em>, PROMS <strong>283</strong> (2019) Springer (<a href="https://arxiv.org/abs/1803.01950">arXiv:1803.01950</a>, <a href="https://link.springer.com/book/10.1007/978-3-030-15338-0">doi:10.1007/978-3-030-15338-0</a>)</p> </li> <li id="Chatterjee20"> <p><a class="existingWikiWord" href="/nlab/show/Sourav+Chatterjee">Sourav Chatterjee</a>, <em>A probabilistic mechanism for quark confinement</em>, Comm. Math. Phys. 2020 (<a href="https://arxiv.org/abs/2006.16229">arXiv:2006.16229</a>)</p> </li> </ul> <div class="property">category: <a class="category_link" href="/nlab/all_pages/probability">probability</a></div></body></html> </div> <div class="revisedby"> <p> Last revised on June 3, 2024 at 12:16:08. See the <a href="/nlab/history/probability+theory" style="color: #005c19">history</a> of this page for a list of all contributions to it. </p> </div> <div class="navigation navfoot"> <a href="/nlab/edit/probability+theory" accesskey="E" class="navlink" id="edit" rel="nofollow">Edit</a><a href="https://nforum.ncatlab.org/discussion/7687/#Item_11">Discuss</a><span class="backintime"><a href="/nlab/revision/probability+theory/49" accesskey="B" class="navlinkbackintime" id="to_previous_revision" rel="nofollow">Previous revision</a></span><a href="/nlab/show/diff/probability+theory" accesskey="C" class="navlink" id="see_changes" rel="nofollow">Changes from previous revision</a><a href="/nlab/history/probability+theory" accesskey="S" class="navlink" id="history" rel="nofollow">History (49 revisions)</a> <a href="/nlab/show/probability+theory/cite" style="color: black">Cite</a> <a href="/nlab/print/probability+theory" accesskey="p" id="view_print" rel="nofollow">Print</a> <a href="/nlab/source/probability+theory" id="view_source" rel="nofollow">Source</a> </div> </div>  </div>  </body> </html>