7 research outputs found
CODAR: A Contextual Duration-Aware Qubit Mapping for Various NISQ Devices
Quantum computing devices in the NISQ era share common features and
challenges like limited connectivity between qubits. Since two-qubit gates are
allowed on limited qubit pairs, quantum compilers must transform original
quantum programs to fit the hardware constraints. Previous works on qubit
mapping assume different gates have the same execution duration, which limits
them to explore the parallelism from the program. To address this drawback, we
propose a Multi-architecture Adaptive Quantum Abstract Machine (maQAM) and a
COntext-sensitive and Duration-Aware Remapping algorithm (CODAR). The CODAR
remapper is aware of gate duration difference and program context, enabling it
to extract more parallelism from programs and speed up the quantum programs by
1.23 in simulation on average in different architectures and maintain the
fidelity of circuits when running on Origin Quantum noisy simulator.Comment: arXiv admin note: substantial text overlap with arXiv:2001.0688
Noise-Adaptive Compiler Mappings for Noisy Intermediate-Scale Quantum Computers
A massive gap exists between current quantum computing (QC) prototypes, and
the size and scale required for many proposed QC algorithms. Current QC
implementations are prone to noise and variability which affect their
reliability, and yet with less than 80 quantum bits (qubits) total, they are
too resource-constrained to implement error correction. The term Noisy
Intermediate-Scale Quantum (NISQ) refers to these current and near-term systems
of 1000 qubits or less. Given NISQ's severe resource constraints, low
reliability, and high variability in physical characteristics such as coherence
time or error rates, it is of pressing importance to map computations onto them
in ways that use resources efficiently and maximize the likelihood of
successful runs.
This paper proposes and evaluates backend compiler approaches to map and
optimize high-level QC programs to execute with high reliability on NISQ
systems with diverse hardware characteristics. Our techniques all start from an
LLVM intermediate representation of the quantum program (such as would be
generated from high-level QC languages like Scaffold) and generate QC
executables runnable on the IBM Q public QC machine. We then use this framework
to implement and evaluate several optimal and heuristic mapping methods. These
methods vary in how they account for the availability of dynamic machine
calibration data, the relative importance of various noise parameters, the
different possible routing strategies, and the relative importance of
compile-time scalability versus runtime success. Using real-system
measurements, we show that fine grained spatial and temporal variations in
hardware parameters can be exploited to obtain an average x (and up to
x) improvement in program success rate over the industry standard IBM
Qiskit compiler.Comment: To appear in ASPLOS'1
Mathematical formulation of quantum circuit design problems in networks of quantum computers
In quantum circuit design, the question arises how to distribute qubits, used in algorithms, over the various quantum computers, and how to order them within a quantum computer. In order to evaluate these problems, we define the global and local reordering problems for distributed quantum computing. We formalise the mathematical problems and model them as integer linear programming problems, to minimise the number of SWAP gates or the number of interactions between different quantum computers. For global reordering, we analyse the problem for various geometries of networks: completely connected networks, general networks, linear arrays and grid-structured networks. For local reordering, in networks of quantum computers, we also define the mathematical optimisation problem