  Developing state-of-the-art classical simulators of quantum circuits is of
utmost importance to test and evaluate early quantum technology and understand
the true potential of full-blown error-corrected quantum computers. In the past
few years, multiple theoretical and numerical advances have continuously pushed
the boundary of what is classically simulable, hence the development of a
plethora of tools which are often limited to a specific purpose or designed for
a particular hardware (e.g. CPUs vs. GPUs). Moreover, such tools are typically
developed using tailored languages and syntax, which makes it hard to compare
results from, and create hybrid approaches using, different simulation
techniques.
  To support unified and optimized use of these techniques across platforms, we
developed HybridQ, a highly extensible platform designed to provide a common
framework to integrate multiple state-of-the-art techniques to run on a variety
of hardware. The philosophy behind its development has been driven by three
main pillars: "Easy to Use", "Easy to Extend", and "Use the Best Available
Technology". The powerful tools of HybridQ allow users to manipulate, develop,
and extend noiseless and noisy circuits for different hardware architectures.
HybridQ supports large-scale high-performance computing (HPC) simulations,
automatically balancing workload among different processor nodes and enabling
the use of multiple backends to maximize parallel efficiency. Everything is
then glued together by a simple and expressive language that allows seamless
switching from one technique to another as well as from one hardware to the
next, without the need to write lengthy translations, thus greatly simplifying
the development of new hybrid algorithms and techniques.
