Lean Characteristic Set

2 Theorems

Lemma 25
✓
#

\(q\) is reduced w.r.t. \(p\) if \(mainVar(q) {\lt} mainVar(p)\).

Proof ▶
Lemma 26
✓

If \(mainVar(p) = mainVar(q)\), then \(q\) is reduced with respect to \(p\) if and only if \(q {\lt} p\).

Proof ▶
Lemma 27
✓

\(mainVar(p) {\lt} mainVar(q)\) if \(p ≤ q\) and \(q\) is reduced with respect to \(p\).

Proof ▶
Lemma 28
✓

\(init_i(p) = p\) if \(deg_i(p) = 0\) (i.e. \(x_i\) does not appear in \(p\)).

Proof ▶
Lemma 29
✓
#

\(deg_i(init_i(p)) = 0\).

Proof ▶
Lemma 30
✓

\(init_i(init_i(p)) = init_i(p)\).

Proof ▶
Lemma 31
✓
#

\(\forall i j, deg_j(init_i(p)) \le deg_j(p)\)

Proof ▶
Theorem 32
✓
#

\(init_i(p)\) is the leading coefficient when viewing \(p\) as a univariate polynomial in \(x_i\).

Proof ▶
Theorem 33
✓
#

\(p = init_i(p) x_i ^d + q\), where \(deg_i(q) {\lt} d = deg_i(p)\).

Proof ▶
Lemma 34
✓

\(deg_i(p + q) {\lt} deg_i(p)\) if \(deg_i(p) = deg_i(q)\) and \(init_i(p) + init_i(q) = 0\).

Proof ▶
Theorem 35
✓
#

\(init_i(p \cdot q) = init_i(p) \cdot init_i(q)\) if there is no zero divisors in the coefficient ring.

Proof ▶
Lemma 36
✓
#

\(mainVar(init(p)) {\lt} mainVar(p)\) for non-constant \(p\).

Proof ▶
Lemma 37
✓

\(init_i(p)\) is reduced w.r.t. \(q\) if \(p\) is reduced w.r.t. to \(q\).

Proof ▶

\(init_i(p)\) is reduced w.r.t. \(p\) for non-constant \(p\).

Proof ▶
Theorem 39
✓

The set of Triangular Sets is well-founded under the lexicographic order ordering. This guarantees the termination of the Characteristic Set Algorithm.

Proof ▶

If \(p \neq 0\) and is reduced with respect to \(S\), then modifying \(S\) by appending \(p\) (using "takeConcat") strictly decreases the order of \(S\).

Proof ▶

\(deg_i(r) {\lt} deg_i(g)\) where \(r\) is the remainder of \(g\) by \(f\) w.r.t. \(i\) if \(deg_i(f) \ne 0\).

Proof ▶
Theorem 42
✓

The remainder \(r\) of \(g\) by \(f\) is reduced with respect to \(f\) and satisfies \(init(f)^s \cdot g = q \cdot f + r\) for some \(s \in \mathbb {N}\) and \(q \in R[X_{\sigma }]\).

Proof ▶

The remainder \(r\) of \(g\) by \(f\) satisfies \(deg_i(r) \le deg_i(g)\) if \(deg_i(f) = 0\)

Proof ▶

The remainder \(r\) of \(g\) by a set \(S\) is reduced with respect to \(S\) and satisfies \((\prod S_i^{e_i}) \cdot g = \sum q_i \cdot S_i + r\) for some \(\{ e_i\} \) and \(\{ q_i\} \).

Proof ▶
Theorem 45
✓

The remainder of \(g\) by \(f\) is \(0\) if \(f\) is a divisor of \(g\).

Proof ▶

The remainder of \(g\) by \(f\) is \(g\) if \(deg_c(g) = 0\) where \(c = mainVar(f)\).

Proof ▶

The remainder of \(p\) by a set \(S\) is \(0\) if \(p\) is in \(S\).

Proof ▶

If \(p\) is in \(S\) and \(mainVar(p) \neq \bot \), then \(init(p)\) is in \(S\).

Proof ▶

The algorithm computes a minimal standard ascending set contained in the input list.

Proof ▶

The algorithm computes a minimal weak ascending set contained in the input list.

Proof ▶

Appending an element which is reduced w.r.t. the basic set of list strictly decreases the order. Crucial for proving termination of characteristic set and zero decomposition algorithms.

Proof ▶

Well-ordering principle (1): \(Zero(CS/IP) \subseteq Zero(PS)\), where \(IP\) is the initial-product of \(CS\).

Proof ▶

Well-ordering principle (2): \(Zero(CS/IP) = Zero(PS/IP)\), where \(IP\) is the initial-product of \(CS\).

Proof ▶

Well-ordering principle (3):

\[ Zero(PS) = Zero(CS/IP) \cup \left(\bigcup _{p \in CS} Zero(PS \cup {init(p)})\right) \]

.

Proof ▶

The algorithm computes a valid characteristic set for the input list.

Proof ▶

The computed characteristic set is an ascending set.

Proof ▶

The order of computed characteristic set \(\le \) the order of the input list.

Proof ▶

\(\forall CS \in \mathcal{ZD}(PS), g \in PS\), \(0\) is the remainder of \(g\) by \(CS\).

Proof ▶

Zero Decomposition Theorem: The zero set of a polynomial system \(PS\) is the union of the zero sets of the triangular systems computed by the algorithm:

\[ Zero(PS) = \bigcup _{CS \in \mathcal{ZD}(PS)} Zero(CS/IP(CS)) \]

.

Proof ▶