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Reduction criterion

Reduction criterion is a physics 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 Reduction criterion rather than just read about it. In short: In quantum information theory, the reduction criterion is a necessary condition a mixed state must satisfy in order for it to be separable. In other words, the reduction criterion is a separability criterion.

Key takeaways

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

Reference excerpt

In quantum information theory, the reduction criterion is a necessary condition a mixed state must satisfy in order for it to be separable. In other words, the reduction criterion is a separability criterion. It was first proved and independently formulated in 1999. Violation of the reduction criterion is closely related to the distillability of the state in question.

Details Let H1 and H2 be Hilbert spaces of finite dimensions n and m respectively. L(Hi) will denote the space of linear operators acting on Hi. Consider a bipartite quantum system whose state space is the tensor product

H = H 1 ⊗ H 2 . {\displaystyle H=H_{1}\otimes H_{2}.}

An (un-normalized) mixed state ρ is a positive linear operator (density matrix) acting on H. A linear map Φ: L(H2) → L(H1) is said to be positive if it preserves the cone of positive elements, i.e. A is positive implied Φ(A) is also. From the one-to-one correspondence between positive maps and entanglement witnesses, we have that a state ρ is entangled if and only if there exists a positive map Φ such that

( I ⊗ Φ ) ( ρ ) {\displaystyle (I\otimes \Phi )(\rho )}

is not positive. Therefore, if ρ is separable, then for all positive map Φ,

( I ⊗ Φ ) ( ρ ) ≥ 0. {\displaystyle (I\otimes \Phi )(\rho )\geq 0.}

Thus every positive, but not completely positive, map Φ gives rise to a necessary condition for separability in this way. The reduction criterion is a particular example of this. Suppose H1 = H2. Define the positive map Φ: L(H2) → L(H1) by

Φ ( A ) = Tr ⁡ A − A . {\displaystyle \Phi (A)=\operatorname {Tr} A-A.}

It is known that Φ is positive but not completely positive. So a mixed state ρ being separable implies

( I ⊗ Φ ) ( ρ ) ≥ 0. {\displaystyle (I\otimes \Phi )(\rho )\geq 0.}

Direct calculation shows that the above expression is the same as

I ⊗ ρ 1 − ρ ≥ 0 {\displaystyle I\otimes \rho _{1}-\rho \geq 0}

where ρ1 is the partial trace of ρ with respect to the second system. The dual relation

ρ 2 ⊗ I − ρ ≥ 0 {\displaystyle \rho _{2}\otimes I-\rho \geq 0}

is obtained in the analogous fashion. The reduction criterion consists of the above two inequalities.

Connection with Fréchet bounds The above last two inequalities together with lower bounds for ρ can be seen as quantum Fréchet inequalities, that is as the quantum analogous of the classical Fréchet probabilistic bounds, that hold for separable quantum states. The upper bounds are the previous ones I ⊗ ρ 1 ≥ ρ {\displaystyle I\otimes \rho _{1}\geq \rho } , ρ 2 ⊗ I ≥ ρ {\displaystyle \rho _{2}\otimes I\geq \rho } , and the lower bounds are the obvious constraint ρ ≥ 0 {\displaystyle \rho \geq 0} together with ρ ≥ I ⊗ ρ 1 + ρ 2 ⊗ I − I {\displaystyle \rho \geq I\otimes \rho _{1}+\rho _{2}\otimes I-I} , where I {\displaystyle I} are identity matrices of suitable dimensions. The lower bounds have been obtained in. These bounds are satisfied by separable density matrices, while entangled states can violate them. Entangled states exhibit a form of stochastic dependence stronger than the strongest classical dependence and in fact they violate Fréchet like bounds. It is also worth mentioning that is possible to give a Bayesian interpretation of these bounds.

References

Worked examples

Example 1 — a first encounter with Reduction criterion

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

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

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

Frequently asked questions

What is Reduction criterion in simple terms?

In quantum information theory, the reduction criterion is a necessary condition a mixed state must satisfy in order for it to be separable. In other words, the reduction criterion is a separability criterion.

Why does Reduction criterion matter?

Because it connects several physics 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 Reduction 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 Reduction criterion.

Tags

  • Quantum information science

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