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Computer

Quantum Realism

Travis S. Humble, Erik P. DeBenedictis

Published Jun 1, 2019• 11 citations
Publisher

Abstract

In this issue, we take a look at quantum computing: what has been accomplished and what is its future. We present a collection of views about the realistic challenges facing the future of quantum computing.
DOI
10.1109/mc.2019.2908512

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I look at the distinction between between realist and antirealist views of the quantum state. I argue that this binary classification should be reconceived as a continuum of different views about which properties of the quantum state are representationally significant. What's more, the extreme cases -- all or none --- are simply absurd, and should be rejected by all parties. In other words, no sane person should advocate extreme realism or antirealism about the quantum state. And if we focus on the reasonable views, it's no longer clear who counts as a realist, and who counts as an antirealist. Among those taking a more reasonable intermediate view, we find figures such as Bohr and Carnap -- in stark opposition to the stories we've been told.
In recent years, the rapidly advancing field of quantum computing has become a focal point of attention. However, issues such as scarcity of quantum hardware and noise pose challenges, leading to the reliance on quantum simulators running on classical computers for tasks like researching quantum algorithms and validating quantum chips. This paper discusses the main simulation methods used by different quantum simulators and explores various optimizations for mainstream full-amplitude state vector simulators and tensor network-based quantum simulators. Finally, we summarize the current status and future directions of quantum simulators. This paper also discusses algorithm-level and system-level optimizations that enhance simulator performance. Looking ahead, the development of quantum simulators faces challenges such as maximizing the use of quantum state properties and creating algorithms to overcome exponential growth issues in simulations. The future will likely focus on integrating high-performance computing resources, advancing optimization strategies, and tailoring simulations to specific applications, aiming for higher efficiency and precision in quantum simulations.
According to scientific realism, science gives us an approximately true description of what the world is like. But what does it mean? In this chapter, we focus on the ontological and metaphysical aspects of this discussion. That is, we are concerned with the following questions: what there is, according to our best scientific theories? And how are these things that theories say exist? We start from the assumption that a genuine scientific realism must deal with these issues. Taking non-relativistic quantum mechanics as a case study, we discuss some of the challenges currently faced by a genuinely realistic stance. We argue, first, that in the ontological aspect, realists are in the same boat as science, that is, without sufficient epistemic justification to adopt the belief in the entities postulated by a single quantum theory, given that experience (currently) is not able to decide between rival theories; in the metaphysical aspect, realists also encounter problems with theory choice, given the possibility of associating more than one metaphysical theory with the description of the entities postulated by each quantum theory. The same goes for structuralist alternatives, since, even if we accept that scientific theories are committed to the existence of structures, but not objects, we still do not know what structures are, metaphysically. Finally, we move forward in the discussion with the meta-Popperian method, which serves to reduce the metaphysical alternatives associated with the ontological postulates of scientific theories. We may not know what the correct alternative is, but we have been able to progressively check which metaphysical alternatives are incompatible with each scientific theory.