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Beyond Quantum Computers

Giulio Chiribella, Giacomo Mauro D’Ariano, Paolo Perinotti, Benoît Valiron

Published Dec 1, 2009• 13 citations
OpenAlex

Abstract

The manuscript poses and addresses a new very fundamental issue in Quantum Computer Science, which is going to have a radical impact on the way we currently conceive quantum computation. We show that there exists a new kind of higher-order quantum computation, potentially much more powerful than the usual quantum processing, which is feasible, but cannot be realized by a usual quantum circuit. In order to implement this new kind of computations one needs to change the rules of quantum circuits, also considering circuits with the geometry of the connections that can be itself in a quantum superposition. The new kind of computation poses also fundamental problems for unexplored aspects of quantum mechanics in a non-fixed causal framework, which go far beyond computer-science problems, and may be of relevance in quantum gravity.

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Science•Oct 13, 1995•1,653 citations
The manuscript poses and addresses a new very fundamental issue in Quantum
Computer Science, which is going to have a radical impact on the way we
currently conceive quantum computation. We show that there exists a new kind of
higher-order quantum computation, potentially much more powerful than the
usual quantum processing, which is feasible, but cannot be realized by a usual
quantum circuit. In order to implement this new kind of computations one needs
to change the rules of quantum circuits, also considering circuits with the
geometry of the connections that can be itself in a quantum superposition. The
new kind of computation poses also fundamental problems for unexplored aspects
of quantum mechanics in a non-fixed causal framework, which go far beyond
computer-science problems, and may be of relevance in quantum gravity.
Quantum Computing represents a transformative shift in the way we process information. Rooted in the principles of quantum mechanics—superposition, entanglement, and interference—it promises computational capabilities far beyond the reach of classical machines. Problems once considered intractable, such as large-scale optimization, cryptographic analysis, and complex system simulations, now appear within conceivable reach. This book is designed to provide a clear and structured introduction to the foundations and frontiers of quantum computing. It bridges the gap between theory and practice, guiding readers from the fundamental concepts of qubits and quantum gates to advanced topics such as quantum algorithms, error correction, and emerging quantum architectures. Mathematical rigor is balanced with intuitive explanations, ensuring accessibility for students, researchers, and professionals from diverse backgrounds in science, engineering, and computing.
Quantum computers are expected to revolutionize our ability to process information. The advancement from classical to quantum computing is a product of our advancement from classical to quantum physics -- the more our understanding of the universe grows, so does our ability to use it for computation. A natural question that arises is, what will physics allow in the future? Can more advanced theories of physics increase our computational power, beyond quantum computing? An active field of research in physics studies theoretical phenomena outside the scope of explainable quantum mechanics, that form when attempting to combine Quantum Mechanics (QM) with General Relativity (GR) into a unified theory of Quantum Gravity (QG). QG is known to present the possibility of a quantum superposition of causal structure and event orderings. In the literature of quantum information theory, this translates to a superposition of unitary evolution orders. In this work we show a first example of a natural computational model based on QG, that provides an exponential speedup over standard quantum computation (under standard hardness assumptions). We define a model and complexity measure for a quantum computer that has the ability to generate a superposition of unitary evolution orders, and show that such computer is able to solve in polynomial time two of the fundamental problems in computer science: The Graph Isomorphism Problem (GI\mathsf{GI}GI) and the Gap Closest Vector Problem (GapCVP\mathsf{GapCVP}GapCVP), with gap O(nn)O\left( n \sqrt{n} \right)O(nn​). These problems are believed by experts to be hard to solve for a regular quantum computer. Interestingly, our model does not seem overpowered, and we found no obvious way to solve entire complexity classes that are considered hard in computer science, like the classes NP\mathbf{NP}NP and SZK\mathbf{SZK}SZK.
There are signs that we are approaching a technical revolution that might take humankind’s computational capabilities to a new level. Quantum Computing leverages the principles of quantum mechanics, enabling the computational power to solve specific problems currently intractable for classical computers (e.g., cracking cryptographic keys). Since we are getting to a point where we can no longer build smaller, more powerful, more efficient devices with conventional methodologies, we need to think of new ways for technological progress. The manufacturing of microchips is reaching its limits in the use of traditional architectures. Hence, new and more advanced technologies need to address the challenges of increasing energy consumption and data processing. Connectivity, scalable architectures and concepts like Cloud Computing and Software-as-a-Service have already helped to scale computational-intense applications in the last years and have attracted the interest of IS researchers (e.g., Benlian et al. 2009 ; Benlian et al. 2018 ; Messerschmidt and Hinz 2013 ). Looking ahead to the next generation, computing will comprise technologies that enable high-performance applications far beyond today’s possibilities. One prominent example with a disruptive potential is Quantum Computing. While there are abundant open questions and directions for further developments, researchers in this area have made substantial progress in the last decade, indicating that, after medical imaging, lasers, and superconductors, another quantum-technological innovation might be approaching. We, therefore, intend to provide an overview of the current state of Quantum Computing research and outline how this new technology might stimulate research in Information Systems.
Over the last decade a new way to compute has been defined which, unlike conventional methods, is based on quantum mechanics rather than classical physics. This fundamental change in paradigm can, in principle, solve some important and hitherto intractable problems such as prime factorization of large numbers. This tutorial presentation will review the basics of quantum computation and the design of circuits to implement quantum algorithms. The starting point is the notion of a quantum bit or qubit. Because of the superposition property of quantum states, n qubits can store 2n numbers simultaneously, implying a type of massive parallelism. Furthermore, quantum states allow powerful forms of interaction such as entanglement that have no classical counterparts. Qubits are fragile, however, and are altered by measurement; hence quantum circuits must follow very different rules from classical ones. The differences between quantum and classical logic circuits will be discussed and illustrated. Finally, the physical implementation of quantum devices will be considered, along with the prospects for practical quantum computers.
If the bits of computers are someday scaled down to the size of individual atoms, quantum mechanical effects may profoundly change the nature of computation itself. The wave function of such a quantum computer could consist of a superposition of many computations carried out simultaneously; this kind of parallelism could be exploited to make some important computational problems, like the prime factoring of large integers, tractable. However, building such a quantum computer would place undreamed of demands on the experimental realization of highly quantum-coherent systems; present-day experimental capabilities in atomic physics and other fields permit only the most rudimentary implementation of quantum computation.