  Classical simulation of quantum computers will continue to play an essential
role in the progress of quantum information science, both for numerical studies
of quantum algorithms and for modeling noise and errors. Here we introduce the
latest release of Intel Quantum Simulator (IQS), formerly known as qHiPSTER.
The high-performance computing (HPC) capability of the software allows users to
leverage the available hardware resources provided by supercomputers, as well
as available public cloud computing infrastructure. To take advantage of the
latter platform, together with the distributed simulation of each separate
quantum state, IQS allows to subdivide the computational resources to simulate
a pool of related circuits in parallel. We highlight the technical
implementation of the distributed algorithm and details about the new pool
functionality. We also include some basic benchmarks (up to 42 qubits) and
performance results obtained using HPC infrastructure. Finally, we use IQS to
emulate a scenario in which many quantum devices are running in parallel to
implement the quantum approximate optimization algorithm, using particle swarm
optimization as the classical subroutine. The results demonstrate that the
hyperparameters of this classical optimization algorithm depends on the total
number of quantum circuit simulations one has the bandwidth to perform. Intel
Quantum Simulator has been released open-source with permissive licensing and
is designed to simulate a large number of qubits, to emulate multiple quantum
devices running in parallel, and/or to study the effects of decoherence and
other hardware errors on calculation results.
