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arXiv:0710.1744

Quantum problem solving as simultaneous computation

Giuseppe Castagnoli

Published Oct 9, 2007• 2 citations

Abstract

I provide an alternative way of seeing quantum computation. First, I describe an idealized classical problem solving machine that, thanks to a many body interaction, reversibly and nondeterministically produces the solution of the problem under the simultaneous influence of all the problem constraints. This requires a perfectly accurate, rigid, and reversible relation between the coordinates of the machine parts - the machine can be considered the many body generalization of another perfect machine, the bounching ball model of reversible computation. The mathematical description of the machine, as it is, is applicable to quantum problem solving, an extension of the quantum algorithms that comprises the physical representation of the problem-solution interdependence. The perfect relation between the coordinates of the machine parts is transferred to the populations of the reduced density operators of the parts of the computer register. The solution of the problem is reversibly and nondeterministically produced under the simultaneous influence of the state before measurement and the quantum principle. At the light of the present notion of simultaneous computation, the quantum speed up turns out to be "precognition" of the solution, namely the reduction of the initial ignorance of the solution due to backdating, to before running the algorithm, a time-symmetric part of the state vector reduction on the solution; as such, it is bounded by state vector reduction through an entropic inequality. PACS numbers: 03.67.Lx, 01.55.+b, 01.70.+w

DOI: 10.48550/arxiv.0710.1744

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I provide an alternative way of seeing quantum computation. First, I describe an idealized classical problem solving machine that, thanks to a many body interaction, reversibly and nondeterministically produces the solution of the problem under the simultaneous influence of all the problem constraints. This requires a perfectly accurate, rigid, and reversible relation between the coordinates of the machine parts - the machine can be considered the many body generalization of another perfect machine, the bounching ball model of reversible computation. The mathematical description of the machine, as it is, is applicable to quantum problem solving, an extension of the quantum algorithms that comprises the physical representation of the problem-solution interdependence. The perfect relation between the coordinates of the machine parts is transferred to the populations of the reduced density operators of the parts of the computer register. The solution of the problem is reversibly and nondeterministically produced under the simultaneous influence of the state before measurement and the quantum principle. At the light of the present notion of simultaneous computation, the quantum speed up turns out to be "precognition" of the solution, namely the reduction of the initial ignorance of the solution due to backdating, to before running the algorithm, a time-symmetric part of the state vector reduction on the solution; as such, it is bounded by state vector reduction through an entropic inequality. PACS numbers: 03.67.Lx, 01.55.+b, 01.70.+w

The usual representation of quantum algorithms, limited to the problem solving process, is incomplete as it lacks the initial measurement. Completing it involves three steps: (i) representing the problem setting process, (ii) relativizing this representation to Alice, the problem solver, to whom the problem setting must be concealed, (iii) representing the reversibility of the computation process by symmetrizing it for time reversal. The latter step shows that all is as if Alice, before beginning her problem solving action, knew half of the information that specifies the solution of the problem she will read in the future. An optimal quantum algorithm is a sum over classical histories in each of which Alice knows in advance one of the possible halves of the solution and performs the computation steps (oracle queries) necessary to identify the missing half. This explains the quantum computational speedup and allows to predict the speedup offered by the optimal quantum solution of any oracle problem.

Current conceptions of "quantum mechanical computers" inherit from conventional digital machines two apparently interacting features, machine imperfection and temporal development of the computational process. On account of machine imperfection, the process would become ideally reversible only in the limiting case of zero speed. Therefore the process is irreversible in practice and cannot be considered to be a fundamental quantum one. By giving up classical features and using a linear, reversible and non-sequential representation of the computational process — not realizable in classical machines — the process can be identified with the mathematical form of a quantum steady state. This form of steady quantum computation would seem to have an important bearing on the notion of cognition.

In former work, we showed that a quantum algorithm is the sum over the histories of a classical algorithm that knows in advance 50% of the information about the solution of the problem - each history is a possible way of getting the advanced information and a possible result of computing the missing information. We gave a theoretical justification of this 50% advanced information rule and checked that it holds for a large variety of quantum algorithms. Now we discuss the theoretical justification in further detail and counter a possible objection. We show that the rule is the generalization of a simple, well known, explanation of quantum nonlocality - where logical correlation between measurement outcomes is physically backed by a causal/deterministic/local process with causality allowed to go backward in time with backdated state vector reduction. The possible objection is that quantum algorithms often produce the solution of the problem in an apparently deterministic way (when their unitary part produces an eigenstate of the observable to be measured and measurement produces the corresponding eigenvalue - the solution - with probability 1), while the present explanation of the speed up relies on the nondeterministic character of quantum measurement. We show that this objection would mistake the nondeterministic production of a definite outcome for a deterministic production.

The reason for the higher efficiency exhibited by some quantum algorithms over their classical counterparts is examined by considering the interplay between the reversible actions required to prepare the computer registers in an entangled state before measurement (the "initial actions"), and the final measurement action -- whereas measurement is interpreted in a new way, particularly suited to a problem solving context. This unification shows that the computation process, comprising the measurement outcome, is significantly influenced by both the initial actions and the need to satisfy the constraints set by the final measurement action. Reviewing the existing quantum algorithms in the light of this dual influence, yields new valuable insight in the nature of the quantum computation speed up.

One of the motivating ideas of quantum computation was that there could be a new kind of machine that would solve hard problems in quantum mechanics. There has been significant progress towards the experimental realization of these machines (which I will review), but there are still many questions about how such a machine could solve computational problems of interest in quantum physics. New categorizations of the complexity of computational problems have now been invented to describe quantum simulation. The bad news is that some of these problems are believed to be intractable even on a quantum computer, falling into a quantum analog of the NP class. The good news is that there are many other new classifications of tractability that may apply to several situations of physical interest.