Quantum-enhanced greedy combinatorial optimization solver
Combinatorial optimization is a broadly attractive area for potential quantum advantage, but
no quantum algorithm has yet made the leap. Noise in quantum hardware remains a …
no quantum algorithm has yet made the leap. Noise in quantum hardware remains a …
Solving non-native combinatorial optimization problems using hybrid quantum-classical algorithms
Combinatorial optimization is a challenging problem applicable in a wide range of fields
from logistics to finance. Recently, quantum computing has been used to attempt to solve …
from logistics to finance. Recently, quantum computing has been used to attempt to solve …
Reinforcement quantum annealing: A hybrid quantum learning automata
We introduce the notion of reinforcement quantum annealing (RQA) scheme in which an
intelligent agent searches in the space of Hamiltonians and interacts with a quantum …
intelligent agent searches in the space of Hamiltonians and interacts with a quantum …
A survey on compressive sensing: Classical results and recent advancements
Recovering sparse signals from linear measurements has demonstrated outstanding utility
in a vast variety of real-world applications. Compressive sensing is the topic that studies the …
in a vast variety of real-world applications. Compressive sensing is the topic that studies the …
Frozenqubits: Boosting fidelity of QAOA by skipping hotspot nodes
Quantum Approximate Optimization Algorithm (QAOA) is one of the leading candidates for
demonstrating the quantum advantage using near-term quantum computers. Unfortunately …
demonstrating the quantum advantage using near-term quantum computers. Unfortunately …
Iterative quantum algorithms for maximum independent set
LT Brady, S Hadfield - Physical Review A, 2024 - APS
Quantum algorithms have been widely studied in the context of combinatorial optimization
problems. While this endeavor can often analytically and practically achieve quadratic …
problems. While this endeavor can often analytically and practically achieve quadratic …
How viable is quantum annealing for solving linear algebra problems?
A Borle, SJ Lomonaco - arXiv preprint arXiv:2206.10576, 2022 - arxiv.org
With the increasing popularity of quantum computing and in particular quantum annealing,
there has been growing research to evaluate the meta-heuristic for various problems in …
there has been growing research to evaluate the meta-heuristic for various problems in …
Multi-qubit correction for quantum annealers
We present multi-qubit correction (MQC) as a novel postprocessing method for quantum
annealers that views the evolution in an open-system as a Gibbs sampler and reduces a set …
annealers that views the evolution in an open-system as a Gibbs sampler and reduces a set …
An ensemble approach for compressive sensing with quantum annealers
We leverage the idea of a statistical ensemble to improve the quality of quantum annealing
based binary compressive sensing. Since executing quantum machine instructions on a …
based binary compressive sensing. Since executing quantum machine instructions on a …
EQUAL: Improving the fidelity of quantum annealers by injecting controlled perturbations
Quantum computing is an information processing paradigm that uses quantum-mechanical
properties to speedup computationally hard problems. Gate-based quantum computers and …
properties to speedup computationally hard problems. Gate-based quantum computers and …