From d33ac5f01a6599406d516edfd45b9938795cea6d Mon Sep 17 00:00:00 2001 From: Prefetch Date: Sun, 21 Feb 2021 20:20:46 +0100 Subject: Add "Partial fraction decomposition" and "Hilbert space" --- content/know/category/mathematics.md | 4 + content/know/category/quantum-mechanics.md | 3 + content/know/concept/index.md | 4 + latex/know/concept/hilbert-space/source.md | 193 +++++++++++++++++++++ latex/know/concept/legendre-transform/source.md | 6 +- .../partial-fraction-decomposition/source.md | 53 ++++++ 6 files changed, 260 insertions(+), 3 deletions(-) create mode 100644 latex/know/concept/hilbert-space/source.md create mode 100644 latex/know/concept/partial-fraction-decomposition/source.md diff --git a/content/know/category/mathematics.md b/content/know/category/mathematics.md index d2321d7..f726f9f 100644 --- a/content/know/category/mathematics.md +++ b/content/know/category/mathematics.md @@ -15,8 +15,12 @@ Alphabetical list of concepts in this category. ## F * [Fourier transform](/know/concept/fourier-transform/) +## H +* [Hilbert space](/know/concept/hilbert-space/) + ## L * [Legendre transform](/know/concept/legendre-transform/) ## P * [Parseval's theorem](/know/concept/parsevals-theorem/) +* [Partial fraction decomposition](/know/concept/partial-fraction-decomposition/) diff --git a/content/know/category/quantum-mechanics.md b/content/know/category/quantum-mechanics.md index bbecfe7..abf93bd 100644 --- a/content/know/category/quantum-mechanics.md +++ b/content/know/category/quantum-mechanics.md @@ -12,6 +12,9 @@ Alphabetical list of concepts in this category. ## D * [Dirac notation](/know/concept/dirac-notation/) +## H +* [Hilbert space](/know/concept/hilbert-space/) + ## P * [Pauli exclusion principle](/know/concept/pauli-exclusion-principle/) * [Probability current](/know/concept/probability-current/) diff --git a/content/know/concept/index.md b/content/know/concept/index.md index 343bbe6..fc98d56 100644 --- a/content/know/concept/index.md +++ b/content/know/concept/index.md @@ -19,11 +19,15 @@ Alphabetical list of concepts in this knowledge base. ## F * [Fourier transform](/know/concept/fourier-transform/) +## H +* [Hilbert space](/know/concept/hilbert-space/) + ## L * [Legendre transform](/know/concept/legendre-transform/) ## P * [Parseval's theorem](/know/concept/parsevals-theorem/) +* [Partial fraction decomposition](/know/concept/partial-fraction-decomposition/) * [Pauli exclusion principle](/know/concept/pauli-exclusion-principle/) * [Probability current](/know/concept/probability-current/) diff --git a/latex/know/concept/hilbert-space/source.md b/latex/know/concept/hilbert-space/source.md new file mode 100644 index 0000000..7d2ea05 --- /dev/null +++ b/latex/know/concept/hilbert-space/source.md @@ -0,0 +1,193 @@ +% Hilbert space + + +# Hilbert space + +A **Hilbert space**, also known as an **inner product space**, is an +abstract **vector space** with a notion of length and angle. + + +## Vector space + +An abstract **vector space** $\mathbb{V}$ is a generalization of the +traditional concept of vectors as "arrows". It consists of a set of +objects called **vectors** which support the following (familiar) +operations: + ++ **Vector addition**: the sum of two vectors $V$ and $W$, denoted $V + W$. ++ **Scalar multiplication**: product of a vector $V$ with a scalar $a$, denoted $a V$. + +In addition, for a given $\mathbb{V}$ to qualify as a proper vector +space, these operations must obey the following axioms: + ++ **Addition is associative**: $U + (V + W) = (U + V) + W$ ++ **Addition is commutative**: $U + V = V + U$ ++ **Addition has an identity**: there exists a $\mathbf{0}$ such that $V + 0 = V$ ++ **Addition has an inverse**: for every $V$ there exists $-V$ so that $V + (-V) = 0$ ++ **Multiplication is associative**: $a (b V) = (a b) V$ ++ **Multiplication has an identity**: There exists a $1$ such that $1 V = V$ ++ **Multiplication is distributive over scalars**: $(a + b)V = aV + bV$ ++ **Multiplication is distributive over vectors**: $a (U + V) = a U + a V$ + +A set of $N$ vectors $V_1, V_2, ..., V_N$ is **linearly independent** if +the only way to satisfy the following relation is to set all the scalar coefficients $a_n = 0$: + +$$\begin{aligned} + \mathbf{0} = \sum_{n = 1}^N a_n V_n +\end{aligned}$$ + +In other words, these vectors cannot be expressed in terms of each +other. Otherwise, they would be **linearly dependent**. + +A vector space $\mathbb{V}$ has **dimension** $N$ if only up to $N$ of +its vectors can be linearly indepedent. All other vectors in +$\mathbb{V}$ can then be written as a **linear combination** of these $N$ +so-called **basis vectors**. + +Let $\vu{e}_1, ..., \vu{e}_N$ be the basis vectors, then any +vector $V$ in the same space can be **expanded** in the basis according to +the unique "weights" $v_n$, known as the **components** of the vector $V$ +in that basis: + +$$\begin{aligned} + V = \sum_{n = 1}^N v_n \vu{e}_n +\end{aligned}$$ + +Using these, the vector space operations can then be implemented as follows: + +$$\begin{gathered} + V = \sum_{n = 1} v_n \vu{e}_n + \quad + W = \sum_{n = 1} w_n \vu{e}_n + \\ + \quad \implies \quad + V + W = \sum_{n = 1}^N (v_n + w_n) \vu{e}_n + \qquad + a V = \sum_{n = 1}^N a v_n \vu{e}_n +\end{gathered}$$ + + +## Inner product + +A given vector space $\mathbb{V}$ can be promoted to a **Hilbert space** +or **inner product space** if it supports an operation $\braket{U}{V}$ +called the **inner product**, which takes two vectors and returns a +scalar, and has the following properties: + ++ **Skew symmetry**: $\braket{U}{V} = (\braket{V}{U})^*$, where ${}^*$ is the complex conjugate. ++ **Positive semidefiniteness**: $\braket{V}{V} \ge 0$, and $\braket{V}{V} = 0$ if $V = \mathbf{0}$. ++ **Linearity in second operand**: $\braket{U}{(a V + b W)} = a \braket{U}{V} + b \braket{U}{W}$. + +The inner product describes the lengths and angles of vectors, and in +Euclidean space it is implemented by the dot product. + +The **magnitude** or **norm** $|V|$ of a vector $V$ is given by +$|V| = \sqrt{\braket{V}{V}}$ and represents the real positive length of $V$. +A **unit vector** has a norm of 1. + +Two vectors $U$ and $V$ are **orthogonal** if their inner product +$\braket{U}{V} = 0$. If in addition to being orthogonal, $|U| = 1$ and +$|V| = 1$, then $U$ and $V$ are known as **orthonormal** vectors. + +Orthonormality is a desirable property for basis vectors, so if they are +not already orthonormal, it is common to manually derive a new +orthonormal basis from them using e.g. the Gram-Schmidt method. + +As for the implementation of the inner product, it is given by: + +$$\begin{gathered} + V = \sum_{n = 1}^N v_n \vu{e}_n + \quad + W = \sum_{n = 1}^N w_n \vu{e}_n + \\ + \quad \implies \quad + \braket{V}{W} = \sum_{n = 1}^N \sum_{m = 1}^N v_n^* w_m \braket{\vu{e}_n}{\vu{e}_j} +\end{gathered}$$ + +If the basis vectors $\vu{e}_1, ..., \vu{e}_N$ are already +orthonormal, this reduces to: + +$$\begin{aligned} + \braket{V}{W} = \sum_{n = 1}^N v_n^* w_n +\end{aligned}$$ + +As it turns out, the components $v_n$ are given by the inner product +with $\vu{e}_n$, where $\delta_{nm}$ is the Kronecker delta: + +$$\begin{aligned} + \braket{\vu{e}_n}{V} = \sum_{m = 1}^N \delta_{nm} v_m = v_n +\end{aligned}$$ + + +## Infinite dimensions + +As the dimensionality $N$ tends to infinity, things may or may not +change significantly, depending on whether $N$ is **countably** or +**uncountably** infinite. + +In the former case, not much changes: the infinitely many **discrete** +basis vectors $\vu{e}_n$ can all still be made orthonormal as usual, +and as before: + +$$\begin{aligned} + V = \sum_{n = 1}^\infty v_n \vu{e}_n +\end{aligned}$$ + +A good example of such a countably-infinitely-dimensional basis are the +solution functions of a Sturm-Liouville problem. + +However, if the dimensionality is uncountably infinite, the basis +vectors are **continuous** and cannot be labeled by $n$. For example, all +complex functions $f(x)$ defined for $x \in [a, b]$ which +satisfy $f(a) = f(b) = 0$ form such a vector space. +In this case $f(x)$ is expanded as follows, where $x$ is a basis vector: + +$$\begin{aligned} + f(x) = \int_a^b \braket{x}{f} \dd{x} +\end{aligned}$$ + +Similarly, the inner product $\braket{f}{g}$ must also be redefined as +follows: + +$$\begin{aligned} + \braket{f}{g} = \int_a^b f^*(x) \: g(x) \dd{x} +\end{aligned}$$ + +The concept of orthonormality must be also weakened. A finite function +$f(x)$ can be normalized as usual, but the basis vectors $x$ themselves +cannot, since each represents an infinitesimal section of the real line. + +The rationale in this case is that the identity operator $\hat{I}$ must +be preserved, which is given here in [Dirac notation](/know/concept/dirac-notation/): + +$$\begin{aligned} + \hat{I} = \int_a^b \ket{\xi} \bra{\xi} \dd{\xi} +\end{aligned}$$ + +Applying the identity operator to $f(x)$ should just give $f(x)$ again: + +$$\begin{aligned} + f(x) = \braket{x}{f} = \matrixel{x}{\hat{I}}{f} + = \int_a^b \braket{x}{\xi} \braket{\xi}{f} \dd{\xi} + = \int_a^b \braket{x}{\xi} f(\xi) \dd{\xi} +\end{aligned}$$ + +For the latter integral to turn into $f(x)$, it is clear that +$\braket{x}{\xi}$ must be a [Dirac delta function](/know/concept/dirac-delta-function/), +i.e $\braket{x}{\xi} = \delta(x - \xi)$: + +$$\begin{aligned} + \int_a^b \braket{x}{\xi} f(\xi) \dd{\xi} + = \int_a^b \delta(x - \xi) f(\xi) \dd{\xi} + = f(x) +\end{aligned}$$ + +Consequently, $\braket{x}{\xi} = 0$ if $x \neq \xi$ as expected for an +orthogonal set of basis vectors, but if $x = \xi$ the inner product +$\braket{x}{\xi}$ is infinite, unlike earlier. + +Technically, because the basis vectors $x$ cannot be normalized, they +are not members of a Hilbert space, but rather of a superset called a +**rigged Hilbert space**. Such vectors have no finite inner product with +themselves, but do have one with all vectors from the actual Hilbert +space. diff --git a/latex/know/concept/legendre-transform/source.md b/latex/know/concept/legendre-transform/source.md index 954b6fc..20afdf7 100644 --- a/latex/know/concept/legendre-transform/source.md +++ b/latex/know/concept/legendre-transform/source.md @@ -5,9 +5,9 @@ The **Legendre transform** of a function $f(x)$ is a new function $L(f')$, which depends only on the derivative $f'(x)$ of $f(x)$, and from which -the original function $f(x)$ can be reconstructed. The point is, just -like other transforms (e.g. Fourier), that $L(f')$ contains the same -information as $f(x)$, just in a different form. +the original function $f(x)$ can be reconstructed. The point is, +analogously to other transforms (e.g. [Fourier](/know/concept/fourier-transform/)), +that $L(f')$ contains the same information as $f(x)$, just in a different form. Let us choose an arbitrary point $x_0 \in [a, b]$ in the domain of $f(x)$. Consider a line $y(x)$ tangent to $f(x)$ at $x = x_0$, which has diff --git a/latex/know/concept/partial-fraction-decomposition/source.md b/latex/know/concept/partial-fraction-decomposition/source.md new file mode 100644 index 0000000..aa03f9c --- /dev/null +++ b/latex/know/concept/partial-fraction-decomposition/source.md @@ -0,0 +1,53 @@ +% Partial fraction decomposition + + +# Partial fraction decomposition + +*Partial fraction decomposition* or *expansion* is a method to rewrite a +quotient of two polynomials $g(x)$ and $h(x)$, where the numerator +$g(x)$ is of lower order than $h(x)$, as a sum of fractions with $x$ in +the denominator: + +$$\begin{aligned} + f(x) = \frac{g(x)}{h(x)} = \frac{c_1}{x - h_1} + \frac{c_2}{x - h_2} + ... +\end{aligned}$$ + +Where $h_n$ etc. are the roots of the denominator $h(x)$. If all $N$ of +these roots are distinct, then it is sufficient to simply posit: + +$$\begin{aligned} + \boxed{ + f(x) = \frac{c_1}{x - h_1} + \frac{c_2}{x - h_2} + ... + \frac{c_N}{x - h_N} + } +\end{aligned}$$ + +Then the constant coefficients $c_n$ can either be found the hard way, +by multiplying the denominators around and solving a system of $N$ +equations, or the easy way by using the following trick: + +$$\begin{aligned} + \boxed{ + c_n = \lim_{x \to h_n} \big( f(x) (x - h_n) \big) + } +\end{aligned}$$ + +If $h_1$ is a root with multiplicity $m > 1$, then the sum takes the +form of: + +$$\begin{aligned} + \boxed{ + f(x) + = \frac{c_{1,1}}{x - h_1} + \frac{c_{1,2}}{(x - h_1)^2} + ... + } +\end{aligned}$$ + +Where $c_{1,j}$ are found by putting the terms on a common denominator, +e.g.: + +$$\begin{aligned} + \frac{c_{1,1}}{x - h_1} + \frac{c_{1,2}}{(x - h_1)^2} + = \frac{c_{1,1} (x - h_1) + c_{1,2}}{(x - h_1)^2} +\end{aligned}$$ + +And then, using the linear independence of $x^0, x^1, x^2, ...$, solving +a system of $m$ equations to find all $c_{1,1}, ..., c_{1,m}$. -- cgit v1.2.3