Algorithmic theory of random graphs
Random Structures & Algorithms - Special issue: average-case analysis of algorithms
Hiding cliques for cryptographic security
Proceedings of the ninth annual ACM-SIAM symposium on Discrete algorithms
Reversible arithmetic coding for quantum data compression
IEEE Transactions on Information Theory
Adiabatic quantum state generation and statistical zero knowledge
Proceedings of the thirty-fifth annual ACM symposium on Theory of computing
Bounding run-times of local adiabatic algorithms
TAMC'07 Proceedings of the 4th international conference on Theory and applications of models of computation
Complexity of Stoquastic Frustration-Free Hamiltonians
SIAM Journal on Computing
The role of symmetries in adiabatic quantum algorithms
Quantum Information & Computation
An exact effective two-qubit gate in a chain of three spins
Quantum Information & Computation
Investigating the performance of an adiabatic quantum optimization processor
Quantum Information Processing
| Hi-index | 0.00 |
Quantum adiabatic evolution provides a general technique for the solution of combinatorial search problems on quantum computers. We present the results of a numerical study of a particular application of quantum adiabatic evolution, the problem of finding the largest clique in a random graph. An n-vertex random graph has each edge included with probability 1/2, and a clique is a completely connected subgraph. There is no known classical algorithm that finds the largest clique in a random graph with high probability and runs in a time polynomial in n. For the small graphs we are able to investigate (n ≤ 18), the quantum algorithm appears to require only a quadratic run time.