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Quantum theory Definition

Von Neumann entropy

Builds on Density matrixTrace of a matrixLogarithm of a matrixEigenvalue

Definition

Let HH be a complex Hilbert space of finite dimension dd, and let ρ\rho be a density matrix on HH. Let λ1,…,λd\lambda_1, \dots, \lambda_d be the eigenvalues of ρ\rho, counted with multiplicity. The von Neumann entropy of ρ\rho is S(ρ)=−tr⁡(ρlog⁡ρ)=−∑i=1dλilog⁡λi,S(\rho) = -\tr(\rho \log \rho) = -\sum_{i=1}^{d} \lambda_i \log \lambda_i, with the convention 0log⁡0=00 \log 0 = 0. Here tr⁡\tr is the trace, and ρlog⁡ρ\rho \log \rho is defined by functional calculus, which agrees with the matrix logarithm on the support of ρ\rho.

Remarks

The base of the logarithm fixes the unit: base 22 gives bits, base ee gives nats.

Example: for the maximally mixed state ρ=I/d\rho = I/d, all eigenvalues equal 1/d1/d, so S(ρ)=−d⋅1dlog⁡1d=log⁡dS(\rho) = -d \cdot \tfrac1d \log \tfrac1d = \log d. For a pure state ∣ψ⟩⟨ψ∣|\psi\rangle\langle\psi|, the eigenvalues are 1,0,…,01, 0, \dots, 0, so S=0S = 0.

Non-example: the Shannon entropy of the diagonal entries is not S(ρ)S(\rho) in general. For ρ=12(1111)\rho = \tfrac12 \begin{pmatrix} 1 & 1 \\ 1 & 1 \end{pmatrix}, a pure state, the diagonal entries 12,12\tfrac12, \tfrac12 give log⁡2\log 2, while S(ρ)=0S(\rho) = 0.

Always 0≤S(ρ)≤log⁡d0 \le S(\rho) \le \log d, with S(ρ)=0S(\rho) = 0 exactly for pure states and S(ρ)=log⁡dS(\rho) = \log d exactly for ρ=I/d\rho = I/d. The entropy is invariant under unitary conjugation, S(UρU∗)=S(ρ)S(U\rho U^*) = S(\rho), and it is concave in ρ\rho.

Reading path

To understand this page from the ground up, read these 5 pages in order. The foundations come first.

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  1. Density matrix concept
  2. Eigenvalue concept
  3. Logarithm of a matrix concept
  4. Trace of a matrix concept
  5. Von Neumann entropy definition

Further reading

  1. Web https://en.wikipedia.org/wiki/Von_Neumann_entropy
About this page
TagG8SRQ9SKQZ
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Kinddefinition
WritingW0 stub
MSC81P17, 94A17
DefinesVon Neumann entropy
UsesDensity matrix, Trace of a matrix, Logarithm of a matrix, Eigenvalue
Changed3 November 2026

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