Scalable distributed gate-model quantum computers

Gyöngyösi, László; Imre, Sándor

doi:10.1038/s41598-020-76728-5

Cited by 33 publications

(15 citation statements)

References 141 publications

(36 reference statements)

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“…Building quantum chips with a sufficiently large number of qubits suitable for solving practically sized problems has remained an elusive goal. Distributed quantum computing [1,2] that uses multiple smaller systems connected by quantum communication channels promises to offer a path to scalability. Suitable quantum connections can be offered by quantum networks such as the quantum internet [3][4][5], with proof-of-concept experimental realizations under construction by several teams [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Divide and Conquer for Combinatorial Optimization and Distributed Quantum Computation

Saleem¹,

Tomesh²,

Perlin³

et al. 2021

Preprint

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We introduce a quantum divide and conquer algorithm that enables the use of distributed computing for constrained combinatorial optimization problems. The algorithm consists of three major components: classical partitioning of a target graph into multiple subgraphs, variational optimization over these subgraphs, and a quantum circuit cutting procedure that allows the optimization to take place independently on separate quantum processors. We simulate the execution of the quantum divide and conquer algorithm to find approximate solutions to instances of the Maximum Independent Set problem which have nearly twice as many nodes than the number of qubits available on a single quantum processor.

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Section: Introductionmentioning

confidence: 99%

Divide and Conquer for Combinatorial Optimization and Distributed Quantum Computation

Saleem¹,

Tomesh²,

Perlin³

et al. 2021

Preprint

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“…Moreover, we believe that the use of distributed quantum computer architectures, such as those discussed in Ref. 3 , could accelerate even more the implementation of this type of quantum computing algorithms to solve real-life financial mathematical problems.…”

Section: Discussionmentioning

confidence: 99%

Hybrid quantum investment optimization with minimal holding period

Mugel

Abad

Bermejo

et al. 2021

Sci Rep

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In this paper we propose a hybrid quantum-classical algorithm for dynamic portfolio optimization with minimal holding period. Our algorithm is based on sampling the near-optimal portfolios at each trading step using a quantum processor, and efficiently post-selecting to meet the minimal holding constraint. We found the optimal investment trajectory in a dataset of 50 assets spanning a 1 year trading period using the D-Wave 2000Q processor. Our method is remarkably efficient, and produces results much closer to the efficient frontier than typical portfolios. Moreover, we also show how our approach can easily produce trajectories adapted to different risk profiles, as typically offered in financial products. Our results are a clear example of how the combination of quantum and classical techniques can offer novel valuable tools to deal with real-life problems, beyond simple toy models, in current NISQ quantum processors.

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“…Quantum network appears as a promising technology to enhance exchanged information security via the Internet [1], [2], [3], [4]. With recent advances in quantum computing technology [5], [6], [7], [8], [9], a quantum network is built upon the conventional network (e.g., network slicing) that is composed by various nodes (computers) equipped with quantum processors to process and deliver information in the form of quantum bits, called qubits [1], [2], [10], [11].…”

Section: Introductionmentioning

confidence: 99%