Qubit Allocation for Noisy Intermediate-Scale Quantum Computers

Will Finigan, Michael Cubeddu, Thomas Lively, Johannes Flick, Prineha Narang
(Submitted on 18 Oct 2018)
In the era of noisy-intermediate-scale quantum computers, we expect to see quantum devices with increasing numbers of qubits emerge in the foreseeable future. To practically run quantum programs, logical qubits have to be mapped to the physical qubits by a qubit allocation algorithm. However, on present day devices, qubits differ by their error rate and connectivity. Here, we establish and demonstrate on current experimental devices a new allocation algorithm that combines the simulated annealing method with local search of the solution space using Dijkstra's algorithm. Our algorithm takes into account the weighted connectivity constraints of both the quantum hardware and the quantum program being compiled. New quantum programs will enable unprecedented developments in physics, chemistry, and materials science and our work offers an important new pathway toward optimizing compilers for quantum programs.
SOURCE: https://arxiv.org/abs/1810.08291

Introducing Control Flow in Qubit Allocation for Quantum Turing Machines

Michael Cubeddu, Will Finigan, Thomas Lively, Johannes Flick, Prineha Narang
(Submitted on 16 Jul 2019)
Different platforms for quantum computation are currently being developed with a steadily increasing number of physical qubits. To make today's devices practical for quantum software engineers, novel programming tools with maximal flexibility have to be developed. One example to extend the applicability of quantum computers to more complex computational problems is quantum control flow. The concept of control flow allows for expanded algorithmic power of the programming language in the form of conditional statements and loops, which a linearly-executed program is incapable of computing. In this work, we introduce a framework to reconcile the non-deterministic properties of quantum control flow when allocating logical qubits from a given quantum circuit to a specific NISQ device in the pre-processing and compiling stage. We consider the respective connectivity and fidelity constraints, with the goal of reducing the expected error rate of the computation. This work will allow for quantum developers and NISQ devices together to more efficiently exploit the compelling algorithmic power that the quantum Turing machine model provides.
SOURCE: https://arxiv.org/abs/1907.07113