concept

von Neumann entropy

Von Neumann entropy is a measure of quantum information and disorder, applied in energy teleportation, evolution paths, and entanglement.
23 related articles · 4 formulas · 1 who worked here

Description

Von Neumann entropy is the quantum analogue of classical Shannon entropy, but for systems governed by quantum rules. A quantum state is described by a density matrix—a table of probabilities. If the particle is in a pure state, the density matrix is simple, and the entropy is zero. Upon interaction with the environment, the state becomes mixed, the density matrix becomes more complex, and the entropy increases. The maximum value for a system of n qubits is n—complete uncertainty. This quantity underlies modern protocols for quantum data transmission and error correction.

History

Von Neumann introduced quantum entropy in 1932, drawing on analogies with statistical thermodynamics. The idea deepened after the birth of Shannon's information theory in 1948, when the connection with channel capacity became clear. In the 1970s–80s, in works on quantum thermodynamics and decoherence (Zurek, Lindblad), entropy became key to describing the transition from quantum to classical. David Deutsch in 1985 used it in his pioneering concepts of quantum computing, laying the foundations of quantum information theory.

How it works

In a closed system, evolution is unitary (according to the Schrödinger equation), and a pure state remains pure—entropy does not change. But real systems interact with the environment, leading to decoherence—the density matrix becomes mixed, entropy increases. For a composite system in a pure state, the reduced matrix of a subsystem can have nonzero entropy, which precisely measures the degree of quantum entanglement between the parts. The computation involves diagonalizing ρ and the formula Σ −pᵢ log pᵢ. In quantum computing, monitoring this entropy helps combat noise through error correction codes.

In practice

Determines the limit of data compression in quantum computers and diagnoses entanglement in quantum networks.

Fun fact

Von Neumann entropy cannot decrease without exchanging information with the environment—just as a shuffled deck cannot be instantly ordered without knowing the exact arrangement of cards.

Concept graph →

Formulas

$$S = -\operatorname{tr}(\rho \ln \rho)$$
Entropy of a quantum system given its density matrix ρ.
What is in the formula
Svariablevon Neumann entropy — entropy joule per kelvin
ρvariabledensity matrix of the quantum state — density matrix
troperatorsums diagonal elements of a matrix — trace operator
lnoperatortakes the natural logarithm — natural logarithm
s=-\frac{1-c}{2}\ln(\frac{1-c}{2})-\frac{1+c}{2}\ln(\frac{1+c}{2}) · 2605.05153v1
s_{vn}=-\sum_kλ_k\lnλ_k · 2605.06577v1
$$S = k_B \ln \Omega$$
Entropy equals Boltzmann constant times log of states.
What is in the formula
Svariableentropy of the system — entropy joule per kelvin
Ωvariablenumber of microstates corresponding to the macrostate — number of microstates
k_Bconstantrelates temperature to energy per degree of freedom — boltzmann constant = 1.380649e-23 joule per kelvin
lnoperatornatural logarithm — natural logarithm
s=k_b\lnω · 2505.02040v2
s=k\logw · 2604.06450
$$S = -\sum_i p_i \ln p_i$$
Measure of uncertainty in a probability distribution.
What is in the formula
SvariableShannon entropy — entropy
p_ivariableProbability of the i-th outcome — probability
\sum_ioperatorSum over all possible outcomes i — summation
\lnoperatorNatural logarithm (base e) — natural logarithm
s=-\sum_ip_i\lnp_i · 2606.08686
h=-\sum_{i}p_i\log_2p_i · 2607.01833
$$|\dot{I}|^2 \le \frac{1}{2\beta^2} \dot{\sigma} A$$
Information flow squared is bounded by entropy production times activity.
What is in the formula
Ivariableinformation flow between subsystems — information flow bit per second
σvariableentropy production rate — entropy production rate joule per kelvin second
Avariableactivity (a measure of dynamical activity in the system) — activity per second
βvariableinverse temperature (1/k_B T) — inverse temperature per joule
|·|²operatorsquared magnitude — absolute value squared
d/dtoperatorderivative with respect to time — time derivative
|\dot{i}_x|^2\le\frac{1}{2β_x^2}\dot{σ}_xa_x · 2606.27868

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