Challenges and opportunities in quantum optimization
Quantum computers have demonstrable ability to solve problems at a scale beyond brute-
force classical simulation. Interest in quantum algorithms has developed in many areas …
force classical simulation. Interest in quantum algorithms has developed in many areas …
AI meets physics: a comprehensive survey
Uncovering the mechanisms of physics is driving a new paradigm in artificial intelligence
(AI) discovery. Today, physics has enabled us to understand the AI paradigm in a wide …
(AI) discovery. Today, physics has enabled us to understand the AI paradigm in a wide …
Quantum optimization: Potential, challenges, and the path forward
Recent advances in quantum computers are demonstrating the ability to solve problems at a
scale beyond brute force classical simulation. As such, a widespread interest in quantum …
scale beyond brute force classical simulation. As such, a widespread interest in quantum …
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 …
Quantum computing dataset of maximum independent set problem on king lattice of over hundred Rydberg atoms
Finding the maximum independent set (MIS) of a large-size graph is a nondeterministic
polynomial-time (NP)-complete problem not efficiently solvable with classical computations …
polynomial-time (NP)-complete problem not efficiently solvable with classical computations …
Iterative quantum algorithms for maximum independent set
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 …
Iterative quantum algorithms for maximum independent set: a tale of low-depth quantum algorithms
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 …
Enhancing quantum algorithms for quadratic unconstrained binary optimization via integer programming
F Wagner, J Nüßlein, F Liers - ACM Transactions on Quantum …, 2023 - dl.acm.org
To date, research in quantum computation promises potential for outperforming classical
heuristics in combinatorial optimization. However, when aiming at provable optimality, one …
heuristics in combinatorial optimization. However, when aiming at provable optimality, one …
Generation of quantum phases of matter and finding a maximum-weight independent set of unit-disk graphs using Rydberg atoms
Recent progress in quantum computing and quantum simulation of many-body systems with
arrays of neutral atoms using Rydberg excitation has provided unforeseen opportunities …
arrays of neutral atoms using Rydberg excitation has provided unforeseen opportunities …
Multi-parameter optimization of polarization gradient cooling for 87Rb atoms based on reinforcement learning
C Liang, S Gao, J Liu, G Wang, S Yan, J Yang, L Zhu… - Optics …, 2024 - opg.optica.org
Polarization gradient cooling (PGC) plays an important role in many cold atom applications
including the formation of Bose-Einstein condensates (BECs) and cooling of single atoms …
including the formation of Bose-Einstein condensates (BECs) and cooling of single atoms …