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State (functional analysis)

State (functional analysis) 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 State (functional analysis) rather than just read about it. In short: In the mathematical field of functional analysis, a state of an operator system is a positive linear functional of norm 1. States in functional analysis generalize the notion of density matrices in quantum mechanics, which represent quantum states, both mixed states and pure states.

Key takeaways

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

Reference excerpt

In the mathematical field of functional analysis, a state of an operator system is a positive linear functional of norm 1. States in functional analysis generalize the notion of density matrices in quantum mechanics, which represent quantum states, both mixed states and pure states. Density matrices in turn generalize state vectors, which only represent pure states. For M an operator system in a C*-algebra A with identity, the set of all states of M, sometimes denoted by S(M), is convex, weak-* closed in the Banach dual space M*. Thus the set of all states of M with the weak-* topology forms a compact Hausdorff space, known as the state space of M. In the C*-algebraic formulation of quantum mechanics, states in this previous sense correspond to physical states, i.e. mappings from physical observables (self-adjoint elements of the C*-algebra) to their expected measurement outcome (real number).

Jordan decomposition States can be viewed as noncommutative generalizations of probability measures. By Gelfand representation, every commutative C*-algebra A is of the form C0(X) for some locally compact Hausdorff X. In this case, S(A) consists of positive Radon measures on X, and the pure states are the evaluation functionals on X. More generally, the GNS construction shows that every state is, after choosing a suitable representation, a vector state. A bounded linear functional on a C*-algebra A is said to be self-adjoint if it is real-valued on the self-adjoint elements of A. Self-adjoint functionals are noncommutative analogues of signed measures. The Jordan decomposition in measure theory says that every signed measure can be expressed as the difference of two positive measures supported on disjoint sets. This can be extended to the noncommutative setting.

It follows from the above decomposition that A* is the linear span of states.

Some important classes of states

Pure states By the Krein-Milman theorem, the state space of M has extreme points. The extreme points of the state space are termed pure states and other states are known as mixed states.

Vector states For a Hilbert space H and a vector x in H, the formula ωx(T) := ⟨Tx,x⟩ (for T in B(H)) defines a positive linear functional on B(H). Since ωx(1)=||x||2, ωx is a state if ||x||=1. If A is a C*-subalgebra of B(H) and M an operator system in A, then the restriction of ωx to M defines a positive linear functional on M. The states of M that arise in this manner, from unit vectors in H, are termed vector states of M.

Faithful states A state τ {\displaystyle \tau } is faithful, if τ ( a ∗ a ) = 0 {\displaystyle \tau (a^{*}a)=0} implies a = 0 {\displaystyle a=0} .

Normal states A state τ {\displaystyle \tau } is called normal, iff for every monotone, increasing net H α {\displaystyle H_{\alpha }} of operators with least upper bound H {\displaystyle H} , τ ( H α ) {\displaystyle \tau (H_{\alpha })\;} converges to τ ( H ) {\displaystyle \tau (H)\;} .

Tracial states A tracial state is a state τ {\displaystyle \tau } such that

τ ( A B ) = τ ( B A ) . {\displaystyle \tau (AB)=\tau (BA)\;.}

For any separable C*-algebra, the set of tracial states is a Choquet simplex.

Factorial states A factorial state of a C*-algebra A is a state such that the commutant of the corresponding GNS representation of A is a factor.

See also Quantum state Gelfand–Naimark–Segal construction Quantum mechanics Quantum state Density matrix

References Lin, H. (2001), An Introduction to the Classification of Amenable C*-algebras, World Scientific

Worked examples

Example 1 — a first encounter with State (functional analysis)

Start with the simplest possible case. Write down what State (functional analysis) 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 State (functional analysis) 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 State (functional analysis) 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 State (functional analysis)

In research
State (functional analysis) 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 State (functional analysis) 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
State (functional analysis) is common in secondary-school and first-year university syllabi. It links to neighbouring topics C*-algebras, Functional analysis, so understanding it makes those chapters shorter.
In everyday life
Look for State (functional analysis) 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 State (functional analysis) in 20 minutes

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

Frequently asked questions

What is State (functional analysis) in simple terms?

In the mathematical field of functional analysis, a state of an operator system is a positive linear functional of norm 1. States in functional analysis generalize the notion of density matrices in quantum mechanics, which represent quantum states, both mixed states and pure states.

Why does State (functional analysis) 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 State (functional analysis)?

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 State (functional analysis).

Tags

  • C*-algebras
  • Functional analysis

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