QMA

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In computational complexity theory, QMA, which stands for Quantum Merlin Arthur , is the set of languages for which, when a string is in the language, there is a polynomial-size quantum proof (a quantum state) that convinces a polynomial time quantum verifier (running on a quantum computer) of this fact with high probability. Moreover, when the string is not in the language, every polynomial-size quantum state is rejected by the verifier with high probability.

Contents

The relationship between QMA and BQP is analogous to the relationship between complexity classes NP and P [ citation needed ]. It is also analogous to the relationship between the probabilistic complexity class MA and BPP [ citation needed ].

QAM is a related complexity class, in which fictional agents Arthur and Merlin carry out the sequence: Arthur generates a random string, Merlin answers with a quantum certificate and Arthur verifies it as a BQP machine.

Definition

A language L is in if there exists a polynomial time quantum verifier V and a polynomial such that: [1] [2] [3]

where ranges over all quantum states with at most qubits.

The complexity class is defined to be equal to . However, the constants are not too important since the class remains unchanged if c and s are set to any constants such that c is greater than s. Moreover, for any polynomials and , we have

.

Problems in QMA

Since many interesting classes are contained in QMA, such as P, BQP and NP, all problems in those classes are also in QMA. However, there are problems that are in QMA but not known to be in NP or BQP. Some such well known problems are discussed below.

A problem is said to be QMA-hard, analogous to NP-hard, if every problem in QMA can be reduced to it. A problem is said to be QMA-complete if it is QMA-hard and in QMA.

The local Hamiltonian problem

A k-local Hamiltonian (quantum mechanics) is a Hermitian matrix acting on n qubits which can be represented as the sum of Hamiltonian Terms acting upon at most qubits each.

The general k-local Hamiltonian problem is, given a k-local Hamiltonian , to find the smallest eigenvalue of . [4] is also called the ground state energy of the Hamiltonian.

The decision version of the k-local Hamiltonian problem is a type of promise problem and is defined as, given a k-local Hamiltonian and where , to decide if there exists a quantum eigenstate of with associated eigenvalue , such that or if .

The local Hamiltonian problem is the quantum analogue of MAX-SAT. The k-local Hamiltonian problem is QMA-complete for k ≥ 2. [5]

The 2-local Hamiltonian problem restricted to act on a two dimensional grid of qubits, is also QMA-complete. [6] It has been shown that the k-local Hamiltonian problem is still QMA-hard even for Hamiltonians representing a 1-dimensional line of particles with nearest-neighbor interactions with 12 states per particle. [7] If the system is translationally-invariant, its local Hamiltonian problem becomes QMAEXP-complete (as the problem input is encoded in the system size, the verifier now has exponential runtime while maintaining the same promise gap). [8] [9]

QMA-hardness results are known for simple lattice models of qubits such as the ZX Hamiltonian [10] where represent the Pauli matrices . Such models are applicable to universal adiabatic quantum computation.

k-local Hamiltonians problems are analogous to classical Constraint Satisfaction Problems. [11] The following table illustrates the analogous gadgets between classical CSPs and Hamiltonians.

ClassicalQuantumNotes
Constraint Satisfaction ProblemHamiltonian
VariableQubit
ConstraintHamiltonian Term
Variable AssignmentQuantum state
Number of constraints satisfiedHamiltonian's energy term
Optimal SolutionHamiltonian's ground stateThe most possible constraints satisfied

Other QMA-complete problems

A list of known QMA-complete problems can be found at https://arxiv.org/abs/1212.6312.

QCMA (or MQA [2] ), which stands for Quantum Classical Merlin Arthur (or Merlin Quantum Arthur), is similar to QMA, but the proof has to be a classical string. It is not known whether QMA equals QCMA, although QCMA is clearly contained in QMA.

QIP(k), which stands for Quantum Interactive Polynomial time (k messages), is a generalization of QMA where Merlin and Arthur can interact for k rounds. QMA is QIP(1). QIP(2) is known to be in PSPACE. [12]

QIP is QIP(k) where k is allowed to be polynomial in the number of qubits. It is known that QIP(3) = QIP. [13] It is also known that QIP = IP = PSPACE. [14]

Relationship to other classes

QMA is related to other known complexity classes by the following relations:

The first inclusion follows from the definition of NP. The next two inclusions follow from the fact that the verifier is being made more powerful in each case. QCMA is contained in QMA since the verifier can force the prover to send a classical proof by measuring proofs as soon as they are received. The fact that QMA is contained in PP was shown by Alexei Kitaev and John Watrous. PP is also easily shown to be in PSPACE.

It is unknown if any of these inclusions is unconditionally strict, as it is not even known whether P is strictly contained in PSPACE or P = PSPACE. However, the currently best known upper bounds on QMA are [15] [16]

and ,

where both and are contained in . It is unlikely that equals , as this would imply -. It is unknown whether or vice versa.

Related Research Articles

<span class="mw-page-title-main">BQP</span> Computational complexity class of problems

In computational complexity theory, bounded-error quantum polynomial time (BQP) is the class of decision problems solvable by a quantum computer in polynomial time, with an error probability of at most 1/3 for all instances. It is the quantum analogue to the complexity class BPP.

In quantum mechanics, the Hamiltonian of a system is an operator corresponding to the total energy of that system, including both kinetic energy and potential energy. Its spectrum, the system's energy spectrum or its set of energy eigenvalues, is the set of possible outcomes obtainable from a measurement of the system's total energy. Due to its close relation to the energy spectrum and time-evolution of a system, it is of fundamental importance in most formulations of quantum theory.

<span class="mw-page-title-main">NP (complexity)</span> Complexity class used to classify decision problems

In computational complexity theory, NP is a complexity class used to classify decision problems. NP is the set of decision problems for which the problem instances, where the answer is "yes", have proofs verifiable in polynomial time by a deterministic Turing machine, or alternatively the set of problems that can be solved in polynomial time by a nondeterministic Turing machine.

<span class="mw-page-title-main">PSPACE</span> Set of decision problems

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<span class="mw-page-title-main">Quantum superposition</span> Principle of quantum mechanics

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<span class="mw-page-title-main">Interactive proof system</span>

In computational complexity theory, an interactive proof system is an abstract machine that models computation as the exchange of messages between two parties: a prover and a verifier. The parties interact by exchanging messages in order to ascertain whether a given string belongs to a language or not. The prover possesses unlimited computational resources but cannot be trusted, while the verifier has bounded computation power but is assumed to be always honest. Messages are sent between the verifier and prover until the verifier has an answer to the problem and has "convinced" itself that it is correct.

<span class="mw-page-title-main">Complexity class</span> Set of problems in computational complexity theory

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<span class="mw-page-title-main">PH (complexity)</span> Class in computational complexity theory

In computational complexity theory, the complexity class PH is the union of all complexity classes in the polynomial hierarchy:

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<span class="mw-page-title-main">PP (complexity)</span> Class of problems in computer science

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<span class="mw-page-title-main">IP (complexity)</span>

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In computational complexity theory, the class QIP is the quantum computing analogue of the classical complexity class IP, which is the set of problems solvable by an interactive proof system with a polynomial-time verifier and one computationally unbounded prover. Informally, IP is the set of languages for which a computationally unbounded prover can convince a polynomial-time verifier to accept when the input is in the language and cannot convince the verifier to accept when the input is not in the language. In other words, the prover and verifier may interact for polynomially many rounds, and if the input is in the language the verifier should accept with probability greater than 2/3, and if the input is not in the language, the verifier should be reject with probability greater than 2/3. In IP, the verifier is like a BPP machine. In QIP, the communication between the prover and verifier is quantum, and the verifier can perform quantum computation. In this case the verifier is like a BQP machine.

In quantum information theory, the no low-energy trivial state (NLTS) conjecture is a precursor to a quantum PCP theorem (qPCP) and posits the existence of families of Hamiltonians with all low-energy states of non-trivial complexity. It was formulated by Michael Freedman and Matthew Hastings in 2013. An NLTS proof would be a consequence of one aspect of qPCP problems – the inability to certify an approximation of local Hamiltonians via NP completeness. In other words, an NLTS proof would be one consequence of the QMA complexity of qPCP problems. On a high level, if proved, NLTS would be one property of the non-Newtonian complexity of quantum computation. NLTS and qPCP conjectures posit the near-infinite complexity involved in predicting the outcome of quantum systems with many interacting states. These calculations of complexity would have implications for quantum computing such as the stability of entangled states at higher temperatures, and the occurrence of entanglement in natural systems. There is currently a proof of NLTS conjecture published in preprint.

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