Computation and simulation are key parts of the scientific project and are also central to understanding emergence. After a general discussion of the role of simulations in science, the chapter turns to the theory of computation, Turing machines and the Church-Turing principle. Limits to the scope of simulation would imply limits to science. Absolute limits would arise if some things are non-computable. Thinking about practical limits leads us to quantum computers, quantum simulations and an estimation of the computational capacity of the universe. The physical version of the Church-Turing principle states that if we can build a universal quantum computer we can simulate every physical system.
Computation and simulation are key parts of the scientific project and are also central to understanding emergence. After a general discussion of the role of simulations in science, the chapter turns to the theory of computation, Turing machines and the Church-Turing principle. Limits to the scope of simulation would imply limits to science. Absolute limits would arise if some things are non-computable. Thinking about practical limits leads us to quantum computers, quantum simulations and an estimation of the computational capacity of the universe. The physical version of the Church-Turing principle states that if we can build a universal quantum computer we can simulate every physical system.
In the search for a precise definition of the notion of effective calculability, Turing’s computability has proven to be more convincing than other definitions proposed almost simultaneously. Turing does not define a particular class of “calculable functions”, but which processes can be carried out in computing. His conceptual analysis brings about an intimate and inescapable link between computability and “measurability”, hence between mechanical procedures and physical processes. The full significance of this link is captured in Deutsch’s physical version of the Church-Turing thesis, namely, his claim that every physical system can be simulated by a universal quantum Turing machine. Quantum physics supports more efficient forms of computation, even though quantum computation remains within Turing’s limits. Why? This chapter explores how logical principles and physical processes coalesce into the notion of computation.
Abstract It is argued that underlying the Church–Turing hypothesis there is an implicit physical assertion. Here, this assertion is presented explicitly as a physical principle: ‘every finitely realizible physical system can be perfectly simulated by a universal model computing machine operating by finite means’. Classical physics and the universal Turing machine, because the former is continuous and the latter discrete, do not obey the principle, at least in the strong form above. A class of model computing machines that is the quantum generalization of the class of Turing machines is described, and it is shown that quantum theory and the 'universal quantum computer’ are compatible with the principle. Computing machines resembling the universal quantum computer could, in principle, be built and would have many remarkable properties not reproducible by any Turing machine. These do not include the computation of non-recursive functions, but they do include ‘quantum parallelism’, a method by which certain probabilistic tasks can be performed faster by a universal quantum computer than by any classical restriction of it. The intuitive explanation of these properties places an intolerable strain on all interpretations of quantum theory other than Everett’s. Some of the numerous connections between the quantum theory of computation and the rest of physics are explored. Quantum complexity theory allows a physically more reasonable definition of the ‘complexity’ or ‘knowledge’ in a physical system than does classical complexity theory.
Abstract According to the Church-Turing Thesis, a Turing machine, and thus the programming languages and computers in existence, can simulate any reasonable computing device. However, there are physical devices that are exponentially more efficient than a Turing machine, and hence would prove exponentially difficult to simulate using such a machine. This chapter explores the concept of quantum computers and their potential not only to simulate quantum physics exponentially faster than classical computers but also to solve other problems exponentially faster. It considers algorithms that break cryptosystems, find needles in haystacks, and predict who can win a game. It first describes particles, waves, and amplitudes in quantum computation before turning to states and operators. It then examines how interference lets a quantum computer learn some things about a function, how quantum computers can solve factoring in polynomial time, the link between factoring and modern cryptography, graph isomorphism and the hidden subgroup problem, and quantum walks and scattering.
According to the Church-Turing Thesis (CTT), effective formal behaviours can be simulated by Turing machines; this has naturally led to speculation that physical systems can also be simulated computationally. But is this wider claim true, or do behaviours exist which are strictly hypercomputational? Several idealised computational models are known which suggest the possibility of hypercomputation, some Newtonian, some based on cosmology, some on quantum theory. While these models' physicality is debatable, they nonetheless throw into question the validity of extending CTT to include all physical systems. We consider the physicality of hypercomputational behaviour from first principles, by showing that quantum theory can be reformulated in a way that explains why physical behaviours can be regarded as 'computing something' in the standard computational state-machine sense. While this does not rule out the physicality of hypercomputation, it strongly limits the forms it can take. Our model also has physical consequences; in particular, the continuity of motion and arrow of time become theorems within the basic model.
There is strong evidence that computers based upon the principles of quantum physics represent an inherently new and more powerful model of computation. Such computers violate the modern form of the Church-Turing thesis (which lies at the foundations of computer science). This thesis can be informally summarized as follows: all physical implementations of computing devices can be described by the same abstract model of computation-the probabilistic Turing Machine or the equivalent random access machine. In this paper, we will describe two formal models for quantum computers: quantum circuits and quantum Turing Machines, introduced by Deutsch [1985].
It is possible in principle to construct quantum mechanical observables and unitary operators which, if implemented in physical systems as measurements and dynamical evolution, would contradict the Church-Turing thesis, which lies at the foundation of computer science. Elsewhere we have argued that the quantum measurement problem implies a finite, computational model of the measurement and evolution of quantum states. If correct, this approach helps to identify the key feature that can reconcile quantum mechanics with the Church-Turing thesis: finitude of the degree of fine-graining of Hilbert space. This suggests that the Church-Turing thesis constrains the physical universe and thereby highlights a surprising connection between purely logical and algorithmic considerations on the one hand and physical reality on the other.