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Hidden matching problem

Hidden matching problem 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 Hidden matching problem rather than just read about it. In short: In quantum information, the hidden matching problem is a computational complexity problem that can be solved using quantum protocols: Let n {\displaystyle n} be a positive even integer. In the hidden matching problem, Alice is given x ∈ { 0 , 1 } n {\displaystyle x\in \{0,1\}^{n}} and Bob is given M ∈ M n {\displaystyle M\in {\mathcal {M}}_{n}} ( M n {\displaystyle {\mathcal {M}}_{n}} denotes the family of all possi…

Key takeaways

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

Reference excerpt

In quantum information, the hidden matching problem is a computational complexity problem that can be solved using quantum protocols: Let n {\displaystyle n} be a positive even integer. In the hidden matching problem, Alice is given x ∈ { 0 , 1 } n {\displaystyle x\in \{0,1\}^{n}} and Bob is given M ∈ M n {\displaystyle M\in {\mathcal {M}}_{n}} ( M n {\displaystyle {\mathcal {M}}_{n}} denotes the family of all possible perfect matchings on n {\displaystyle n} nodes). Their goal is to output a tuple ⟨ i , j , b ⟩ {\displaystyle \langle i,j,b\rangle } such that the edge ( i , j ) {\displaystyle (i,j)} belongs to the matching M {\displaystyle M} and b = x i ⊕ x j {\displaystyle b=x_{i}\oplus x_{j}} . It has been used to find quantum communication problems that demonstrate super-polynomial advantage of over classical ones.

Background Communication complexity is a model of computation first introduced by Andrew Yao in 1979. Two parties (normally called Alice and Bob) each hold a piece of data and want to solve some computational task that jointly depends on their data. Alice knows only information x {\displaystyle x} and Bob knows only information y {\displaystyle y} , and they want to solve some function f ( x , y ) {\displaystyle f(x,y)} . In order to do so, they will need to communicate between themselves, and their goal is to solve the problem with minimal communication obeying the restrictions of a specific communication model. There are two key communication models that can be considered:

One-way communication is the model where Alice sends a single message to Bob who has to give an answer, based on the content of the message and his part of input. Interactive (two-way) communication is the model where the players can interactively exchange messages till Bob decides to give an answer, based on the communication transcript and his part of input. Communication tasks can be either functional, meaning that there is exactly one correct answer corresponding to every possible input, or relational, when multiple correct answers are allowed.

History The hidden matching problem was first defined in 2004 by Zir Bar-Yossef, T. S. Jayram and Ionardis Kerenidis. Through its definition, they were able to provide the first exponential separation between quantum and bounded-error randomized one-way communication complexity. They proved that the quantum one-way communication complexity of the hidden matching problem is O ( log ⁡ n ) {\displaystyle {\mathcal {O}}(\log n)} , yet any randomized one-way protocol with bounded error must use Ω ( n ) {\displaystyle \Omega ({\sqrt {n}})} bits of communication. The hidden matching problem is a relational problem. Alice sends a superposition 1 n ∑ i = 1 n ( − 1 ) x i | i ⟩ {\displaystyle {\frac {1}{\sqrt {n}}}\sum _{i=1}^{n}(-1)^{x_{i}}|i\rangle } to Bob. Bob uses his perfect matching to project this quantum state onto one of n/2 orthogonal 2D projectors, with a projector onto the space spanned by { | i ⟩ , | j ⟩ } {\displaystyle \{|i\rangle ,|j\rangle \}} for pairing of i and j. After measurement, the quantum state is specified by the measured projector. The bit b determines whether the resulting state is 1 2 ( | i ⟩ ± | j ⟩ ) {\displaystyle {\frac {1}{\sqrt {2}}}\left(|i\rangle \pm |j\rangle \right)} . With a classical message, Alice has to send on order of O ( n ) {\displaystyle {\mathcal {O}}\left({\sqrt {n}}\right)} bits of information specifying the value of x for that many nodes. By the birthday problem, the probability is close to 1 that at least two nodes in that subset are connected by an edge. In the same paper, the authors proposed a boolean version of the problem, the boolean hidden matching problem, and conjectured that the same quantum-classical gap holds for it as well. This was later proven to be true by Dmitry Gavinsky et al in 2007. In 2008, Gavinsky further improved on Bar-Yossef et al.’s result by showing an exponential separation between one-way quantum communication and two-way classical communication.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Hidden matching problem

Start with the simplest possible case. Write down what Hidden matching problem 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 Hidden matching problem 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 Hidden matching problem 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 Hidden matching problem

In research
Hidden matching problem 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 Hidden matching problem 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
Hidden matching problem is common in secondary-school and first-year university syllabi. It links to neighbouring topics Quantum cryptography, so understanding it makes those chapters shorter.
In everyday life
Look for Hidden matching problem 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 Hidden matching problem in 20 minutes

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

Frequently asked questions

What is Hidden matching problem in simple terms?

In quantum information, the hidden matching problem is a computational complexity problem that can be solved using quantum protocols: Let n {\displaystyle n} be a positive even integer. In the hidden matching problem, Alice is given x ∈ { 0 , 1 } n {\displaystyle x\in \{0,1\}^{n}} and Bob is given…

Why does Hidden matching problem 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 Hidden matching problem?

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 Hidden matching problem.

Tags

  • Quantum cryptography

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