Quantum computer from D-Wave no faster than traditional in new tests

Phani K. V. V. Nukala, Paul R. C. Kent

We present an efficient low-rank updating algorithm for updating the trial wave functions used in quantum Monte Carlo (QMC) simulations. The algorithm is based on low-rank updating of the Slater determinants. In particular, the computational complexity of the algorithm is O(kN) during the kth step compared to traditional algorithms that require O(N(2)) computations, where N is the system size. For single determinant trial wave functions the new algorithm is faster than the traditional O(N(2)) Sherman-Morrison algorithm for up to O(N) updates. For multideterminant configuration-interaction-type trial wave functions of M+1 determinants, the new algorithm is significantly more efficient, saving both O(MN(2)) work and O(MN(2)) storage. The algorithm enables more accurate and significantly more efficient QMC calculations using configuration-interaction-type wave functions.

P. Aaron Lott

Helmut G. Katzgraber, Firas Hamze, Ruben S. Andrist

Recent benchmarking of the computational speedup of quantum ``annealing'' machines of the D-Wave-2 type shows that they do not perform faster than a standard desktop computer. A timely theoretical study of the computational tests used in the benchmarking explains why that may be the case.

Akhil Reddy Bairi, K Thangavelu, Arun Ayilliath Keezhadath

Test automation plays a crucial role in modern software development, ensuring faster releases and higher software quality. However, optimizing parallel test execution remains a challenge due to resource constraints and scheduling inefficiencies. This research explores the potential of quantum computing, specifically quantum annealing using D-Wave systems, to enhance test execution efficiency. By formulating test suite scheduling as a combinatorial optimization problem, we leverage quantum annealing to achieve optimal test distribution across available resources. Our proposed approach significantly reduces execution time and improves resource utilization compared to classical optimization techniques. Experimental results demonstrate the effectiveness of quantum-enhanced scheduling, highlighting the potential of quantum computing in revolutionizing test automation.

Alan MacCormack, Ajay K. Agrawal, Rebecca M. Henderson