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Sylvester matrix

Sylvester matrix is a mathematics topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Sylvester matrix rather than just read about it. In short: In mathematics, a Sylvester matrix is a matrix associated to two univariate polynomials with coefficients in a field or a commutative ring. The entries of the Sylvester matrix of two polynomials are coefficients of the polynomials.

Key takeaways

  • Sylvester matrix belongs to mathematics; place it in that map before memorising details.
  • Learn the definition first, then one example that makes the definition concrete.
  • Connect Sylvester matrix to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Sylvester matrix from memory before moving on to harder problems.

Reference excerpt

In mathematics, a Sylvester matrix is a matrix associated to two univariate polynomials with coefficients in a field or a commutative ring. The entries of the Sylvester matrix of two polynomials are coefficients of the polynomials. The determinant of the Sylvester matrix of two polynomials is their resultant, which is zero when the two polynomials have a common root (in case of coefficients in a field) or a non-constant common divisor (in case of coefficients in an integral domain). Sylvester matrices are named after James Joseph Sylvester who first used them in 1853.

Definition Formally, let p and q be two nonzero polynomials, respectively of degree m and n. Thus:

p ( z ) = p 0 + p 1 z + p 2 z 2 + ⋯ + p m z m , q ( z ) = q 0 + q 1 z + q 2 z 2 + ⋯ + q n z n . {\displaystyle p(z)=p_{0}+p_{1}z+p_{2}z^{2}+\cdots +p_{m}z^{m},\;q(z)=q_{0}+q_{1}z+q_{2}z^{2}+\cdots +q_{n}z^{n}.}

The Sylvester matrix associated to p and q is then the ( n + m ) × ( n + m ) {\displaystyle (n+m)\times (n+m)} matrix constructed as follows:

if n > 0, the first row is:

( p m p m − 1 ⋯ p 1 p 0 0 ⋯ 0 ) . {\displaystyle {\begin{pmatrix}p_{m}&p_{m-1}&\cdots &p_{1}&p_{0}&0&\cdots &0\end{pmatrix}}.}

the second row is the first row, shifted one column to the right; the first element of the row is zero. the following n − 2 rows are obtained the same way, shifting the coefficients one column to the right each time and setting the other entries in the row to be 0. if m > 0 the (n + 1)th row is:

( q n q n − 1 ⋯ q 1 q 0 0 ⋯ 0 ) . {\displaystyle {\begin{pmatrix}q_{n}&q_{n-1}&\cdots &q_{1}&q_{0}&0&\cdots &0\end{pmatrix}}.}

the following rows are obtained the same way as before. Thus, if m = 4 and n = 3, the matrix is:

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Sylvester matrix

Start with the simplest possible case. Write down what Sylvester matrix claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In mathematics, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Sylvester matrix before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Sylvester matrix ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Sylvester matrix

In research
Sylvester matrix appears in mathematics research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry
Engineering practice reuses Sylvester matrix in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom
Sylvester matrix is common in secondary-school and first-year university syllabi. It links to neighbouring topics Matrices (mathematics), Polynomials, so understanding it makes those chapters shorter.
In everyday life
Look for Sylvester matrix outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.
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How to study Sylvester matrix in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Sylvester matrix means in your own words.
  3. Compare your version with the excerpt and mark what you missed.
  4. Work through the three examples above with pen and paper.
  5. Explain Sylvester matrix out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Sylvester matrix in simple terms?

In mathematics, a Sylvester matrix is a matrix associated to two univariate polynomials with coefficients in a field or a commutative ring. The entries of the Sylvester matrix of two polynomials are coefficients of the polynomials.

Why does Sylvester matrix matter?

Because it connects several mathematics ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Sylvester matrix?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Sylvester matrix.

Tags

  • Matrices (mathematics)
  • Polynomials

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