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Hamiltonian matrix

Hamiltonian 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 Hamiltonian matrix rather than just read about it. In short: In mathematics, a Hamiltonian matrix is a 2n-by-2n matrix A such that JA is symmetric, where J is the skew-symmetric matrix J = [ 0 n I n − I n 0 n ] {\displaystyle J={\begin{bmatrix}0_{n}&I_{n}\\-I_{n}&0_{n}\end{bmatrix}}} and In is the n-by-n identity matrix. In other words, A is Hamiltonian if and only if (JA)T = JA where ( )T denotes the transpose.

Key takeaways

  • Hamiltonian 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 Hamiltonian matrix to a quantity you can measure, compute or draw — that is where exam questions come from.
  • Reproduce the core statement of Hamiltonian matrix from memory before moving on to harder problems.

Reference excerpt

In mathematics, a Hamiltonian matrix is a 2n-by-2n matrix A such that JA is symmetric, where J is the skew-symmetric matrix

J = [ 0 n I n − I n 0 n ] {\displaystyle J={\begin{bmatrix}0_{n}&I_{n}\\-I_{n}&0_{n}\end{bmatrix}}}

and In is the n-by-n identity matrix. In other words, A is Hamiltonian if and only if (JA)T = JA where ( )T denotes the transpose. The collection of all Hamiltonian matrices forms a Lie algebra (the symplectic Lie algebra); its associated Lie group is the symplectic group, whose elements are the symplectic matrices.

Properties Suppose that the 2n-by-2n matrix A is written as the block matrix

A = [ a b c d ] {\displaystyle A={\begin{bmatrix}a&b\\c&d\end{bmatrix}}}

where a, b, c, and d are n-by-n matrices. Then the condition that A be Hamiltonian is equivalent to requiring that the matrices b and c are symmetric, and that a + dT = 0. Another equivalent condition is that A is of the form A = JS with S symmetric. It follows easily from the definition that the transpose of a Hamiltonian matrix is Hamiltonian. Furthermore, the sum (and any linear combination) of two Hamiltonian matrices is again Hamiltonian, as is their commutator. It follows that the space of all Hamiltonian matrices is a Lie algebra, denoted sp(2n). The dimension of sp(2n) is 2n2 + n. The corresponding Lie group is the symplectic group Sp(2n). This group consists of the symplectic matrices, those matrices A which satisfy ATJA = J. Thus, the matrix exponential of a Hamiltonian matrix is symplectic. However the logarithm of a symplectic matrix is not necessarily Hamiltonian because the exponential map from the Lie algebra to the group is not surjective. The characteristic polynomial of a real Hamiltonian matrix is even. Thus, if a Hamiltonian matrix has λ as an eigenvalue, then −λ, λ* and −λ* are also eigenvalues. It follows that the trace of a Hamiltonian matrix is zero. The square of a Hamiltonian matrix is skew-Hamiltonian (a matrix A is skew-Hamiltonian if (JA)T = −JA). Conversely, every skew-Hamiltonian matrix arises as the square of a Hamiltonian matrix.

Extension to complex matrices As for symplectic matrices, the definition for Hamiltonian matrices can be extended to complex matrices in two ways. One possibility is to say that a matrix A is Hamiltonian if (JA)T = JA, as above. Another possibility is to use the condition (JA)* = JA where the superscript asterisk ((⋅)*) denotes the conjugate transpose.

Hamiltonian operators Let V be a vector space, equipped with a symplectic form Ω. A linear map A : V ↦ V {\displaystyle A:\;V\mapsto V} is called a Hamiltonian operator with respect to Ω if the form x , y ↦ Ω ( A ( x ) , y ) {\displaystyle x,y\mapsto \Omega (A(x),y)} is symmetric. Equivalently, it should satisfy

Ω ( A ( x ) , y ) = − Ω ( x , A ( y ) ) {\displaystyle \Omega (A(x),y)=-\Omega (x,A(y))}

Choose a basis e1, …, e2n in V, such that Ω is written as ∑ i e i ∧ e n + i {\textstyle \sum _{i}e_{i}\wedge e_{n+i}} . A linear operator is Hamiltonian with respect to Ω if and only if its matrix in this basis is Hamiltonian.

References

Worked examples

Example 1 — a first encounter with Hamiltonian matrix

Start with the simplest possible case. Write down what Hamiltonian 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 Hamiltonian 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 Hamiltonian 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 Hamiltonian matrix

In research
Hamiltonian 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 Hamiltonian 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
Hamiltonian matrix is common in secondary-school and first-year university syllabi. It links to neighbouring topics Matrices (mathematics), so understanding it makes those chapters shorter.
In everyday life
Look for Hamiltonian 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 Hamiltonian matrix in 20 minutes

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

Frequently asked questions

What is Hamiltonian matrix in simple terms?

In mathematics, a Hamiltonian matrix is a 2n-by-2n matrix A such that JA is symmetric, where J is the skew-symmetric matrix J = [ 0 n I n − I n 0 n ] {\displaystyle J={\begin{bmatrix}0_{n}&I_{n}\\-I_{n}&0_{n}\end{bmatrix}}} and In is the n-by-n identity matrix. In other words, A is Hamiltonian if a…

Why does Hamiltonian 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 Hamiltonian 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 Hamiltonian matrix.

Tags

  • Matrices (mathematics)

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