177 research outputs found
Towards Solving the Navier-Stokes Equation on Quantum Computers
In this paper, we explore the suitability of upcoming novel computing
technologies, in particular adiabatic annealing based quantum computers, to
solve fluid dynamics problems that form a critical component of several science
and engineering applications. We start with simple flows with well-studied flow
properties, and provide a framework to convert such systems to a form amenable
for deployment on such quantum annealers. We analyze the solutions obtained
both qualitatively and quantitatively as well as the sensitivities of the
various solution selection schemes on the obtained solution
Flight Gate Assignment with a Quantum Annealer
Optimal flight gate assignment is a highly relevant optimization problem from
airport management. Among others, an important goal is the minimization of the
total transit time of the passengers. The corresponding objective function is
quadratic in the binary decision variables encoding the flight-to-gate
assignment. Hence, it is a quadratic assignment problem being hard to solve in
general. In this work we investigate the solvability of this problem with a
D-Wave quantum annealer. These machines are optimizers for quadratic
unconstrained optimization problems (QUBO). Therefore the flight gate
assignment problem seems to be well suited for these machines. We use real
world data from a mid-sized German airport as well as simulation based data to
extract typical instances small enough to be amenable to the D-Wave machine. In
order to mitigate precision problems, we employ bin packing on the passenger
numbers to reduce the precision requirements of the extracted instances. We
find that, for the instances we investigated, the bin packing has little effect
on the solution quality. Hence, we were able to solve small problem instances
extracted from real data with the D-Wave 2000Q quantum annealer.Comment: Updated figure
Quantum Annealing Applied to De-Conflicting Optimal Trajectories for Air Traffic Management
We present the mapping of a class of simplified air traffic management (ATM)
problems (strategic conflict resolution) to quadratic unconstrained boolean
optimization (QUBO) problems. The mapping is performed through an original
representation of the conflict-resolution problem in terms of a conflict graph,
where nodes of the graph represent flights and edges represent a potential
conflict between flights. The representation allows a natural decomposition of
a real world instance related to wind-optimal trajectories over the Atlantic
ocean into smaller subproblems, that can be discretized and are amenable to be
programmed in quantum annealers. In the study, we tested the new programming
techniques and we benchmark the hardness of the instances using both classical
solvers and the D-Wave 2X and D-Wave 2000Q quantum chip. The preliminary
results show that for reasonable modeling choices the most challenging
subproblems which are programmable in the current devices are solved to
optimality with 99% of probability within a second of annealing time.Comment: Paper accepted for publication on: IEEE Transactions on Intelligent
Transportation System
Cloud Computing in the Quantum Era
Cloud computing has become the prominent technology of this era. Its elasticity, dynamicity, availability, heterogeneity, and pay as you go pricing model has attracted several companies to migrate their businesses' services into the cloud. This gives them more time to focus solely on their businesses and reduces the management and backup overhead leveraging the flexibility of cloud computing. On the other hand, quantum technology is developing very rapidly. Experts are expecting to get an efficient quantum computer within the next decade. This has a significant impact on several sciences including cryptography, medical research, and other fields. This paper analyses the reciprocal impact of quantum technology on cloud computing and vice versa
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