- Mathematics
Von Neumann Entropy
The quantum analogue of Shannon entropy for a density matrix rho, defined as S(rho) = -Tr(rho log rho), measuring the degree of quantum entanglement and mixedness of a state.
Von Neumann entropy is defined for a quantum state described by a density matrix as , where the logarithm is typically taken in base 2 (giving units of qubits) or base (nats). For a pure state, the density matrix satisfies and all eigenvalues are zero except one, so . For a maximally mixed state on a -dimensional Hilbert space, and . This makes von Neumann entropy a precise measure of the ignorance or mixedness encoded in a quantum state.
The connection to Shannon entropy is direct: if is diagonal in some basis with eigenvalues , then , exactly the Shannon entropy of the probability distribution . This means Von Neumann entropy reduces to classical Shannon entropy whenever the quantum state has no coherences (off-diagonal terms) in the chosen basis. The Von Neumann entropy is basis-independent, however, because it depends only on the eigenvalues of , so it captures something genuinely intrinsic to the quantum state rather than to any particular measurement.
For a bipartite quantum system in a pure state , the von Neumann entropy of the reduced density matrix is the standard measure of entanglement entropy between subsystems and . Because the global state is pure, , and the shared value quantifies how entangled the two parts are: zero for product states and for maximally entangled states. This makes entanglement entropy the central quantity in quantum information theory and condensed matter physics alike.
In many-body physics, entanglement entropy satisfies remarkable scaling laws known as area laws: for gapped local Hamiltonians in d spatial dimensions, the entanglement entropy of a region scales as the surface area of that region rather than its volume. Critical systems described by conformal field theory violate this with a logarithmic correction proportional to the central charge. Numerically, von Neumann entropy is computed by diagonalizing to obtain its eigenvalues and evaluating , making eigenvalue decomposition the practical workhorse for entanglement calculations in quantum simulation and quantum chemistry.