Arthur–Merlin Protocol
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computational complexity theory In theoretical computer science and mathematics, computational complexity theory focuses on classifying computational problems according to their resource usage, and relating these classes to each other. A computational problem is a task solved ...
, an Arthur–Merlin protocol, introduced by , is an interactive proof system in which the verifier's coin tosses are constrained to be public (i.e. known to the prover too). proved that all (formal)
languages Language is a structured system of communication. The structure of a language is its grammar and the free components are its vocabulary. Languages are the primary means by which humans communicate, and may be conveyed through a variety of met ...
with interactive proofs of arbitrary length with private coins also have interactive proofs with public coins. Given two participants in the protocol called Arthur and Merlin respectively, the basic assumption is that Arthur is a standard computer (or verifier) equipped with a random number generating device, while Merlin is effectively an
oracle An oracle is a person or agency considered to provide wise and insightful counsel or prophetic predictions, most notably including precognition of the future, inspired by deities. As such, it is a form of divination. Description The word ...
with infinite computational power (also known as a prover). However, Merlin is not necessarily honest, so Arthur must analyze the information provided by Merlin in response to Arthur's queries and decide the problem itself. A problem is considered to be solvable by this protocol if whenever the answer is "yes", Merlin has some series of responses which will cause Arthur to accept at least of the time, and if whenever the answer is "no", Arthur will never accept more than of the time. Thus, Arthur acts as a probabilistic polynomial-time verifier, assuming it is allotted polynomial time to make its decisions and queries.


MA

The simplest such protocol is the 1-message protocol where Merlin sends Arthur a message, and then Arthur decides whether to accept or not by running a probabilistic polynomial time computation. (This is similar to the verifier-based definition of NP, the only difference being that Arthur is allowed to use randomness here.) Merlin does not have access to Arthur's coin tosses in this protocol, since it is a single-message protocol and Arthur tosses his coins only after receiving Merlin's message. This protocol is called ''MA''. Informally, a
language Language is a structured system of communication. The structure of a language is its grammar and the free components are its vocabulary. Languages are the primary means by which humans communicate, and may be conveyed through a variety of ...
''L'' is in MA if for all strings in the language, there is a polynomial sized proof that Merlin can send Arthur to convince him of this fact with high probability, and for all strings not in the language there is no proof that convinces Arthur with high probability. Formally, the complexity class MA is the set of decision problems that can be decided in polynomial time by an Arthur–Merlin protocol where Merlin's only move precedes any computation by Arthur. In other words, a language ''L'' is in MA if there exists a polynomial-time probabilistic Turing machine ''M'' and polynomials ''p'', ''q'' such that for every input string ''x'' of length ''n'' = , ''x'', , *if ''x'' is in ''L'', then \exists z\in\^\,\Pr\nolimits_(M(x,y,z)=1)\ge2/3, *if ''x'' is not in ''L'', then \forall z\in\^\,\Pr\nolimits_(M(x,y,z)=0)\ge2/3. The second condition can alternatively be written as *if ''x'' is not in ''L'', then \forall z\in\^\,\Pr\nolimits_(M(x,y,z)=1)\le1/3. To compare this with the informal definition above, ''z'' is the purported proof from Merlin (whose size is bounded by a polynomial) and ''y'' is the random string that Arthur uses, which is also polynomially bounded.


AM

The
complexity class In computational complexity theory, a complexity class is a set of computational problems of related resource-based complexity. The two most commonly analyzed resources are time and memory. In general, a complexity class is defined in terms o ...
AM (or AM '') is the set of
decision problem In computability theory and computational complexity theory, a decision problem is a computational problem that can be posed as a yes–no question of the input values. An example of a decision problem is deciding by means of an algorithm whe ...
s that can be decided in polynomial time by an Arthur–Merlin protocol with two messages. There is only one query/response pair: Arthur tosses some random coins and sends the outcome of ''all'' his coin tosses to Merlin, Merlin responds with a purported proof, and Arthur deterministically verifies the proof. In this protocol, Arthur is only allowed to send outcomes of coin tosses to Merlin, and in the final stage Arthur must decide whether to accept or reject using only his previously generated random coin flips and Merlin's message. In other words, a language ''L'' is in AM if there exists a polynomial-time deterministic Turing machine ''M'' and polynomials ''p'', ''q'' such that for every input string ''x'' of length ''n'' = , ''x'', , *if ''x'' is in ''L'', then \Pr\nolimits_(\exists z\in\^\,M(x,y,z)=1)\ge2/3, *if ''x'' is not in ''L'', then \Pr\nolimits_(\forall z\in\^\,M(x,y,z)=0)\ge2/3. The second condition here can be rewritten as *if ''x'' is not in ''L'', then \Pr\nolimits_(\exists z\in\^\,M(x,y,z)=1)\le1/3. As above, ''z'' is the alleged proof from Merlin (whose size is bounded by a polynomial) and ''y'' is the random string that Arthur uses, which is also polynomially bounded. The complexity class AM 'k'''' is the set of problems that can be decided in polynomial time, with ''k'' queries and responses. AM as defined above is AM ''. AM '' would start with one message from Merlin to Arthur, then a message from Arthur to Merlin and then finally a message from Merlin to Arthur. The last message should always be from Merlin to Arthur, since it never helps for Arthur to send a message to Merlin after deciding his answer.


Properties

* Both MA and AM remain unchanged if their definitions are changed to require perfect completeness, which means that Arthur accepts with probability 1 (instead of 2/3) when ''x'' is in the language. * For any constant ''k'' ≥ 2, the class AM 'k'''' is equal to AM ''. If ''k'' can be polynomially related to the input size, the class AM oly(''n'')is equal to the class, IP, which is known to be equal to PSPACE and is widely believed to be stronger than the class AM ''. * MA is contained in AM, since AM contains MA: Arthur can, after receiving Merlin's certificate, flip the required number of coins, send them to Merlin, and ignore the response. * It is open whether AM and MA are different. Under plausible circuit lower bounds (similar to those implying P=BPP), they are both equal to NP. * AM is the same as the class BP⋅NP where BP denotes the bounded-error probabilistic operator. Also, \exists \cdot \mathsf ( also written as ExistsBPP) is a subset of MA. Whether MA is equal to \exists \cdot \mathsf is an open question. * The conversion to a private coin protocol, in which Merlin cannot predict the outcome of Arthur's random decisions, will increase the number of rounds of interaction by at most 2 in the general case. So the private-coin version of AM is equal to the public-coin version. * MA contains both NP and BPP. For BPP this is immediate, since Arthur can simply ignore Merlin and solve the problem directly; for NP, Merlin need only send Arthur a certificate, which Arthur can validate deterministically in polynomial time. * Both MA and AM are contained in the
polynomial hierarchy In computational complexity theory, the polynomial hierarchy (sometimes called the polynomial-time hierarchy) is a hierarchy of complexity classes that generalize the classes NP and co-NP. Each class in the hierarchy is contained within PSPACE. ...
. In particular, MA is contained in the intersection of Σ2P and Π2P and AM is contained in Π2P. Even more, MA is contained in subclass , a complexity class expressing "symmetric alternation". This is a generalization of Sipser–Lautemann theorem. * AM is contained in
NP/poly In computational complexity theory, NP/poly is a complexity class, a non-uniform analogue of the class NP of problems solvable in polynomial time by a non-deterministic Turing machine. It is the non-deterministic complexity class corresponding to ...
, the class of decision problems computable in non-deterministic polynomial time with a polynomial size
advice Advice (noun) or advise (verb) may refer to: * Advice (opinion), an opinion or recommendation offered as a guide to action, conduct * Advice (constitutional law) a frequently binding instruction issued to a constitutional office-holder * Advice (p ...
. The proof is a variation of
Adleman's theorem In computational complexity theory, P/poly is a complexity class representing problems that can be solved by small circuits. More precisely, it is the set of formal languages that have polynomial-size circuit families. It can also be defined equiva ...
. * MA is contained in PP; this result is due to Vereshchagin. * MA is contained in its quantum version, QMA. * AM contains the problem of deciding if two graphs are ''not'' isomorphic. The protocol using private coins is the following and can be transformed to a public coin protocol. Given two graphs ''G'' and ''H'', Arthur randomly chooses one of them, and chooses a random permutation of its vertices, presenting the permuted graph ''I'' to Merlin. Merlin has to answer if ''I'' was created from ''G'' or ''H''. If the graphs are nonisomorphic, Merlin will be able to answer with full certainty (by checking if ''I'' is isomorphic to ''G''). However, if the graphs are isomorphic, it is both possible that ''G'' or ''H'' was used to create ''I'', and equally likely. In this case, Merlin has no way to tell them apart and can convince Arthur with probability at most 1/2, and this can be amplified to 1/4 by repetition. This is in fact a zero knowledge proof. * If AM contains coNP then PH = AM. This is evidence that graph isomorphism is unlikely to be NP-complete, since it implies collapse of polynomial hierarchy. * It is known, assuming ERH, that for any ''d'' the problem "Given a collection of multivarariate polynomials f_i each with integer coefficients and of degree at most ''d'', do they have a common complex zero?" is in AM.


References


Bibliography

* . * . *.
Madhu Sudan's MIT course on advanced complexity


External links

* * {{DEFAULTSORT:Arthur-Merlin protocol Randomized algorithms