Quantum measurement
Exploiting the deep structure of constraint problems
Artificial Intelligence
Phase transitions and the search problem
Artificial Intelligence - Special volume on frontiers in problem solving: phase transitions and complexity
Experimental results on the crossover point in random 3-SAT
Artificial Intelligence - Special volume on frontiers in problem solving: phase transitions and complexity
A fast quantum mechanical algorithm for database search
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
Nuclear magnetic resonance spectroscopy: an experimentally accessible paradigm for quantum computing
PhysComp96 Proceedings of the fourth workshop on Physics and computation
A framework for structured quantum search
PhysComp96 Proceedings of the fourth workshop on Physics and computation
Algorithms for quantum computation: discrete logarithms and factoring
SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
Quantum computing and phase transitions in combinatorial search
Journal of Artificial Intelligence Research
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Generating highly balanced sudoku problems as hard problems
Journal of Heuristics
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The deep structure of constraint satisfaction problems explains the association of hard search instances with a phase transition in problem solubility. This structure is also the basis of a quantum search algoritbm exhibiting the phase transition. In this paper, this algoritbm is modified to incorporate additional problem structure. This modification is an example of a general method for including heuristics in quantum search. The new algoritbm is evaluated empirically for random 3SAT, illustrating how quantum searches can benefit from using problem structure, on average.