Enabling a Programming Environment for an Experimental Ion Trap Quantum
  Testbed
Ion trap quantum hardware promises to provide a computational advantage over
classical computing for specific problem spaces while also providing an
alternative hardware implementation path to cryogenic quantum systems as
typified by IBM's quantum hardware. However, programming ion trap systems
currently requires both strategies to mitigate high levels of noise and also
tools to ease the challenge of programming these systems with pulse- or
gate-level operations.
  This work focuses on improving the state-of-the-art for quantum programming
of ion trap testbeds through the use of a quantum language specification, QCOR,
and by demonstrating multi-level optimizations at the language, intermediate
representation, and hardware backend levels. We implement a new QCOR/XACC
backend to target a general ion trap testbed and then demonstrate the usage of
multi-level optimizations to improve circuit fidelity and to reduce gate count.
These techniques include the usage of a backend-specific numerical optimizer
and physical gate optimizations to minimize the number of native instructions
sent to the hardware. We evaluate our compiler backend using several QCOR
benchmark programs, finding that on present testbed hardware, our compiler
backend maintains the number of two-qubit native operations but decreases the
number of single-qubit native operations by 1.54 times compared to the previous
compiler regime. For projected testbed hardware upgrades, our compiler sees a
reduction in two-qubit native operations by 2.40 times and one-qubit native
operations by 6.13 times.
Austin Adams Elton Pinto Jeffrey Young Creston Herold Alex McCaskey Eugene Dumitrescu Thomas M. Conte