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Total Variation Distance


The total variation distance between probability measures P and Q on the same measurable space is d_(TV)(P,Q)=sup_(A)|P(A)-Q(A)|, where the supremum is over measurable sets. It equals half the total variation of the signed measure P-Q on the whole space (Pollard 2005).

For probability mass functions p and q on a countable set, it is

 d_(TV)(p,q)=1/2sum_(x)|p(x)-q(x)|.

The distance lies between 0 and 1. It is zero precisely when the distributions agree and is 1 precisely when they are mutually singular. The trace distance of density matrices that are diagonal in a common orthonormal basis reduces to this classical distance.


See also

Mixing Time, Probability Measure, Total Variation, Trace Distance

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References

Pollard, D. "Total Variation Distance between Measures." Lecture notes, Feb. 15, 2005. https://www.stat.yale.edu/~pollard/Courses/607.spring05/handouts/Totalvar.pdf.Watrous, J. The Theory of Quantum Information. Cambridge, England: Cambridge University Press, 2018. https://doi.org/10.1017/9781316848142.

Cite this as:

Weisstein, Eric W. "Total Variation Distance." From MathWorld--A Wolfram Resource. https://mathworld.wolfram.com/TotalVariationDistance.html

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