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== Theorem of the month == | == Theorem of the month == | ||
=== RU method === | === RU method === | ||
− | If the linear system (LS) <math>Ax = b \in {}^{\nu}\mathbb{Q}^{n}</math> can be uniquely solved for <math>n \in {}^{\nu}\mathbb{N}^*</math>, the ''root of unity method (RU method)'' computes <math>x \in {}^{\nu}\mathbb{Q}^{n}</math> for <math>A \in {}^{\nu}\mathbb{Q}^{n \times n}</math> in <math>\mathcal{O}(n^2)</math>. | + | If the linear system (LS) <math>Ax = b \in {}^{\nu}\mathbb{Q}^{n}</math> can be uniquely solved for <math>n \in {}^{\nu}\mathbb{N}^*</math>, the ''root of unity method (<math>RU</math> method)'' computes <math>x \in {}^{\nu}\mathbb{Q}^{n}</math> for <math>A \in {}^{\nu}\mathbb{Q}^{n \times n}</math> in <math>\mathcal{O}(n^2)</math>. |
=== Proof and algorithm === | === Proof and algorithm === | ||
− | Let <math>R_1 := (r_{1jk}) = (r_{1kj}) = R_1^T \in {}^{\nu}\mathbb{C}^{n \times n}, n \in {}^{\nu}2\mathbb{N}^*, r_{11k} := 1</math> and for <math>j > 1</math> | + | Let <math>R_1 := (r_{1jk}) = (r_{1kj}) = R_1^T \in {}^{\nu}\mathbb{C}^{n \times n}, n \in {}^{\nu}2\mathbb{N}^*, r_{11k} := 1</math> and for <math>j > 1</math> as well as <math>n_{jk} := j + k - 3</math> both <math>r_{1jk} := \hat{n}e^{i\tau n_{jk}/n}</math> for <math>n_{jk} < n</math> and <math>r_{1jk} := \hat{n}e^{i\tau(n_{jk} - \acute{n})/n}</math> for <math>n_{jk} \ge n</math>. Interchanging the first and <math>j</math>-th row resp. column position and correspondingly interchanging the remaining row and column positions yields matrices <math>R_j = R_j^T</math> for <math>j > 1</math>. Let <math>\delta_{jk}</math> be the Kronecker delta. |
− | If <math>a_{jk} \le 0</math> is given for at least one couple <math>(j, k)</math> and <math>A := (a_{jk})</math>, then compute the sums <math>s_0 := \sum\limits_{j=1}^m{b_j\varepsilon^j}</math> for an arbitrary transcendental number <math>\varepsilon</math> and <math>s_k := \sum\limits_{j=1}^m{a_{jk}\varepsilon^j} \ne 0</math> for all <math>k</math>. Replace <math>x_k</math> by <math>-x_k</math> for <math>s_k < 0</math>. Then add a multiple of <math>s^Tx</math> resp. <math>s_0</math> to <math>Ax = b</math>, such that now <math>a_{jk} > 0</math> holds for all <math>(j, k)</math>. | + | If <math>a_{jk} \le 0</math> is given for at least one couple <math>(j, k)</math> and <math>A := (a_{jk})</math>, then compute the sums <math>s_0 := \sum\limits_{j=1}^m{b_j\varepsilon^j}</math> for an arbitrary transcendental number <math>\varepsilon</math> and <math>s_k := \sum\limits_{j=1}^m{a_{jk}\varepsilon^j} \ne 0</math> for all <math>k</math>. Replace <math>x_k</math> by <math>-x_k</math> for <math>s_k < 0</math>. Then add a multiple of <math>s^Tx</math> resp. <math>s_0</math> to <math>Ax = b</math>, such that now <math>a_{jk} > 0</math> holds for all <math>(j, k)</math>. Let <math>b_j = 1</math> for all <math>j</math> wlog. For <math>D_j := (d_{jk}), d_{jk} = \delta_{jk}⁄a_{jk}, C_j := D_j R_j</math> and <math>x_k^{(\prime(0))} := C_j^{-1} \hat{n}/ \max_j a_{jk}</math>, let <math>x^{\prime(\grave{m})} = x^{\prime(m)} + \hat{n}C_j^{-1}(D_j^{-1}b - Ax^{\prime(m)}).\square</math> |
− | '''Remark:''' Extending the theorem to complex | + | === Corollary === |
+ | The RU method allows to determine the eigenvalues and eigenvectors of <math>Ax = \lambda x \in {}^{\nu}\mathbb{Q}^{n} + {}^{\nu}\mathbb{Q}^{n}</math> for <math>n \in {}^{\nu}2\mathbb{N}^*, \lambda \in {}^{\nu}\mathbb{Q}+ {i}^{\nu}\mathbb{Q}</math> and <math>A \in {}^{\nu}\mathbb{Q}^{n \times n}</math> by putting <math>x^{\prime(\grave{m})} = C_j^{-1}AC_j x^{\prime(m)}</math> in <math>\mathcal{O}(n^2)</math>. | ||
+ | |||
+ | '''Remark:''' Extending the theorem to complex <math>A</math> and <math>b</math> is easy. | ||
== Recommended reading == | == Recommended reading == | ||
Revision as of 09:01, 17 November 2020
Welcome to MWiki
Theorem of the month
RU method
If the linear system (LS) [math]\displaystyle{ Ax = b \in {}^{\nu}\mathbb{Q}^{n} }[/math] can be uniquely solved for [math]\displaystyle{ n \in {}^{\nu}\mathbb{N}^* }[/math], the root of unity method ([math]\displaystyle{ RU }[/math] method) computes [math]\displaystyle{ x \in {}^{\nu}\mathbb{Q}^{n} }[/math] for [math]\displaystyle{ A \in {}^{\nu}\mathbb{Q}^{n \times n} }[/math] in [math]\displaystyle{ \mathcal{O}(n^2) }[/math].
Proof and algorithm
Let [math]\displaystyle{ R_1 := (r_{1jk}) = (r_{1kj}) = R_1^T \in {}^{\nu}\mathbb{C}^{n \times n}, n \in {}^{\nu}2\mathbb{N}^*, r_{11k} := 1 }[/math] and for [math]\displaystyle{ j > 1 }[/math] as well as [math]\displaystyle{ n_{jk} := j + k - 3 }[/math] both [math]\displaystyle{ r_{1jk} := \hat{n}e^{i\tau n_{jk}/n} }[/math] for [math]\displaystyle{ n_{jk} < n }[/math] and [math]\displaystyle{ r_{1jk} := \hat{n}e^{i\tau(n_{jk} - \acute{n})/n} }[/math] for [math]\displaystyle{ n_{jk} \ge n }[/math]. Interchanging the first and [math]\displaystyle{ j }[/math]-th row resp. column position and correspondingly interchanging the remaining row and column positions yields matrices [math]\displaystyle{ R_j = R_j^T }[/math] for [math]\displaystyle{ j > 1 }[/math]. Let [math]\displaystyle{ \delta_{jk} }[/math] be the Kronecker delta.
If [math]\displaystyle{ a_{jk} \le 0 }[/math] is given for at least one couple [math]\displaystyle{ (j, k) }[/math] and [math]\displaystyle{ A := (a_{jk}) }[/math], then compute the sums [math]\displaystyle{ s_0 := \sum\limits_{j=1}^m{b_j\varepsilon^j} }[/math] for an arbitrary transcendental number [math]\displaystyle{ \varepsilon }[/math] and [math]\displaystyle{ s_k := \sum\limits_{j=1}^m{a_{jk}\varepsilon^j} \ne 0 }[/math] for all [math]\displaystyle{ k }[/math]. Replace [math]\displaystyle{ x_k }[/math] by [math]\displaystyle{ -x_k }[/math] for [math]\displaystyle{ s_k < 0 }[/math]. Then add a multiple of [math]\displaystyle{ s^Tx }[/math] resp. [math]\displaystyle{ s_0 }[/math] to [math]\displaystyle{ Ax = b }[/math], such that now [math]\displaystyle{ a_{jk} > 0 }[/math] holds for all [math]\displaystyle{ (j, k) }[/math]. Let [math]\displaystyle{ b_j = 1 }[/math] for all [math]\displaystyle{ j }[/math] wlog. For [math]\displaystyle{ D_j := (d_{jk}), d_{jk} = \delta_{jk}⁄a_{jk}, C_j := D_j R_j }[/math] and [math]\displaystyle{ x_k^{(\prime(0))} := C_j^{-1} \hat{n}/ \max_j a_{jk} }[/math], let [math]\displaystyle{ x^{\prime(\grave{m})} = x^{\prime(m)} + \hat{n}C_j^{-1}(D_j^{-1}b - Ax^{\prime(m)}).\square }[/math]
Corollary
The RU method allows to determine the eigenvalues and eigenvectors of [math]\displaystyle{ Ax = \lambda x \in {}^{\nu}\mathbb{Q}^{n} + {}^{\nu}\mathbb{Q}^{n} }[/math] for [math]\displaystyle{ n \in {}^{\nu}2\mathbb{N}^*, \lambda \in {}^{\nu}\mathbb{Q}+ {i}^{\nu}\mathbb{Q} }[/math] and [math]\displaystyle{ A \in {}^{\nu}\mathbb{Q}^{n \times n} }[/math] by putting [math]\displaystyle{ x^{\prime(\grave{m})} = C_j^{-1}AC_j x^{\prime(m)} }[/math] in [math]\displaystyle{ \mathcal{O}(n^2) }[/math].
Remark: Extending the theorem to complex [math]\displaystyle{ A }[/math] and [math]\displaystyle{ b }[/math] is easy.