Symbols:Greek/Rho
Rho
The $17$th letter of the Greek alphabet.
- Minuscules: $\rho$ and $\varrho$
- Majuscule: $\Rho$
The $\LaTeX$ code for \(\rho\) is \rho
.
The $\LaTeX$ code for \(\varrho\) is \varrho
.
The $\LaTeX$ code for \(\Rho\) is \Rho
.
Density
- $\rho$
Used to denote the density of a given body:
- $\rho = \dfrac m V$
where:
Area Density
- $\rho_A$
Used to denote the area density of a given two-dimensional body:
- $\rho_A = \dfrac m A$
where:
The $\LaTeX$ code for \(\rho_A\) is \rho_A
.
Electric Charge Density
- $\rho$
Let $A$ be a point in space in which an electric field acts.
Let $\delta V$ be a volume element containing $A$.
The (electric) charge density $\map \rho {\mathbf r}$ at $A$ is defined as:
\(\ds \map \rho {\mathbf r}\) | \(=\) | \(\ds \lim_{\delta V \mathop \to 0} \dfrac Q {\delta V}\) | ||||||||||||
\(\ds \) | \(=\) | \(\ds \dfrac {\d Q} {\d V}\) |
where:
- $Q$ denotes the electric charge within $\delta V$
- $\mathbf r$ denotes the position vector of $A$.
Thus the electric charge density is the quantity of electric charge per unit volume, at any given point in that volume:
The $\LaTeX$ code for \(\rho\) is \rho
.
Right Regular Representation
- $\rho_a$
Let $\struct {S, \circ}$ be an algebraic structure.
The mapping $\rho_a: S \to S$ is defined as:
- $\forall x \in S: \map {\rho_a} x = x \circ a$
This is known as the right regular representation of $\struct {S, \circ}$ with respect to $a$.
The $\LaTeX$ code for \(\map {\rho_a} x\) is \map {\rho_a} x
.
Radius of Curvature
- $\rho$
The radius of curvature of a curve $C$ at a point $P$ is defined as the reciprocal of the absolute value of its curvature:
- $\rho = \dfrac 1 {\size k}$
Autocorrelation
- $\rho_k$
Let $S$ be a stochastic process giving rise to a time series $T$.
The autocorrelation of $S$ at lag $k$ is defined as:
- $\rho_k := \dfrac {\expect {\paren {z_t - \mu} \paren {z_{t + k} - \mu} } } {\sqrt {\expect {\paren {z_t - \mu}^2} \expect {\paren {z_{t + k} - \mu}^2} } }$
where:
- $z_t$ is the observation at time $t$
- $\mu$ is the mean of $S$
- $\expect \cdot$ is the expectation.