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Sylvester's criterion

Sylvester's criterion is a science 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's criterion rather than just read about it. In short: In mathematics, Sylvester's criterion is a necessary and sufficient criterion to determine whether a Hermitian matrix is positive-definite, due to James Joseph Sylvester. Sylvester's criterion states that a n × n Hermitian matrix M is positive-definite if and only if all the following matrices have a positive determinant: the upper left 1-by-1 corner of M, the upper left 2-by-2 corner of M, the upper left 3-by-3 cor…

Key takeaways

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

Reference excerpt

In mathematics, Sylvester's criterion is a necessary and sufficient criterion to determine whether a Hermitian matrix is positive-definite, due to James Joseph Sylvester. Sylvester's criterion states that a n × n Hermitian matrix M is positive-definite if and only if all the following matrices have a positive determinant:

the upper left 1-by-1 corner of M, the upper left 2-by-2 corner of M, the upper left 3-by-3 corner of M,

⋮ {\displaystyle {}\quad \vdots }

M itself. In other words, all of the leading principal minors must be positive. By using appropriate permutations of rows and columns of M, it can also be shown that the positivity of any nested sequence of n principal minors of M is equivalent to M being positive-definite. An analogous theorem holds for characterizing positive-semidefinite Hermitian matrices, except that it is no longer sufficient to consider only the leading principal minors as illustrated by the Hermitian matrix

A Hermitian matrix M is positive-semidefinite if and only if all principal minors of M are nonnegative.

Proof for the case of positive definite matrices Suppose M n {\displaystyle M_{n}} is n × n {\displaystyle n\times n} Hermitian matrix M n † = M n {\displaystyle M_{n}^{\dagger }=M_{n}} . Let M k , k = 1 , … n {\displaystyle M_{k},k=1,\ldots n} be the leading principal minor matrices, i.e. the k × k {\displaystyle k\times k} upper left corner matrices. It will be shown that if M n {\displaystyle M_{n}} is positive definite, then the principal minors are positive; that is, det M k > 0 {\displaystyle \det M_{k}>0} for all k {\displaystyle k} .

M k {\displaystyle M_{k}} is positive definite. Indeed, choosing

we can notice that 0 < x † M n x = x → † M k x → . {\displaystyle 0<x^{\dagger }M_{n}x={\vec {x}}^{\dagger }M_{k}{\vec {x}}.} Equivalently, the eigenvalues of M k {\displaystyle M_{k}} are positive, and this implies that det M k > 0 {\displaystyle \det M_{k}>0} since the determinant is the product of the eigenvalues. To prove the reverse implication, we use induction. The general form of an ( n + 1 ) × ( n + 1 ) {\displaystyle (n+1)\times (n+1)} Hermitian matrix is

where M n {\displaystyle M_{n}} is an n × n {\displaystyle n\times n} Hermitian matrix, v → {\displaystyle {\vec {v}}} is a vector and d {\displaystyle d} is a real constant. Suppose the criterion holds for M n {\displaystyle M_{n}} . Assuming that all the principal minors of M n + 1 {\displaystyle M_{n+1}} are positive implies that det M n + 1 > 0 {\displaystyle \det M_{n+1}>0} , det M n > 0 {\displaystyle \det M_{n}>0} , and that M n {\displaystyle M_{n}} is positive definite by the inductive hypothesis. Denote

then

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Sylvester's criterion

Start with the simplest possible case. Write down what Sylvester's criterion claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, 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's criterion 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's criterion 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's criterion

In research
Sylvester's criterion appears in science 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's criterion 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's criterion is common in secondary-school and first-year university syllabi. It links to neighbouring topics Matrix theory, so understanding it makes those chapters shorter.
In everyday life
Look for Sylvester's criterion 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's criterion in 20 minutes

  1. Read the reference excerpt below once, without taking notes.
  2. Close the page and write down what Sylvester's criterion 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's criterion out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Sylvester's criterion in simple terms?

In mathematics, Sylvester's criterion is a necessary and sufficient criterion to determine whether a Hermitian matrix is positive-definite, due to James Joseph Sylvester. Sylvester's criterion states that a n × n Hermitian matrix M is positive-definite if and only if all the following matrices have…

Why does Sylvester's criterion matter?

Because it connects several science 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's criterion?

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's criterion.

Tags

  • Matrix theory

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