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Quantum information processing with superconducting circuits: a review
During the last ten years, superconducting circuits have passed from being interesting
physical devices to becoming contenders for near-future useful and scalable quantum …
physical devices to becoming contenders for near-future useful and scalable quantum …
Prospects for quantum enhancement with diabatic quantum annealing
Optimization, sampling and machine learning are topics of broad interest that have inspired
significant developments and new approaches in quantum computing. One such approach …
significant developments and new approaches in quantum computing. One such approach …
Coherent quantum annealing in a programmable 2,000 qubit Ising chain
Quantum simulation has emerged as a valuable arena for demonstrating and understanding
the capabilities of near-term quantum computers,–. Quantum annealing, has been …
the capabilities of near-term quantum computers,–. Quantum annealing, has been …
Perspectives of quantum annealing: Methods and implementations
Quantum annealing is a computing paradigm that has the ambitious goal of efficiently
solving large-scale combinatorial optimization problems of practical importance. However …
solving large-scale combinatorial optimization problems of practical importance. However …
What is the computational value of finite-range tunneling?
Quantum annealing (QA) has been proposed as a quantum enhanced optimization heuristic
exploiting tunneling. Here, we demonstrate how finite-range tunneling can provide …
exploiting tunneling. Here, we demonstrate how finite-range tunneling can provide …
Designing metamaterials with quantum annealing and factorization machines
Automated materials design with machine learning is increasingly common in recent years.
Theoretically, it is characterized as black-box optimization in the space of candidate …
Theoretically, it is characterized as black-box optimization in the space of candidate …
Benchmarking Advantage and D-Wave 2000Q quantum annealers with exact cover problems
We benchmark the quantum processing units of the largest quantum annealers to date, the
5000+ qubit quantum annealer Advantage and its 2000+ qubit predecessor D-Wave 2000Q …
5000+ qubit quantum annealer Advantage and its 2000+ qubit predecessor D-Wave 2000Q …
Demonstration of a scaling advantage for a quantum annealer over simulated annealing
The observation of an unequivocal quantum speedup remains an elusive objective for
quantum computing. A more modest goal is to demonstrate a scaling advantage over a class …
quantum computing. A more modest goal is to demonstrate a scaling advantage over a class …
Solving a Higgs optimization problem with quantum annealing for machine learning
The discovery of Higgs-boson decays in a background of standard-model processes was
assisted by machine learning methods,. The classifiers used to separate signals such as …
assisted by machine learning methods,. The classifiers used to separate signals such as …
PyQUBO: Python library for map** combinatorial optimization problems to QUBO form
M Zaman, K Tanahashi… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
We present PyQUBO, an open-source Python library for constructing quadratic
unconstrained binary optimizations (QUBOs) from the objective functions and the constraints …
unconstrained binary optimizations (QUBOs) from the objective functions and the constraints …