  When quantum programs are executed on noisy intermediate-scale quantum (NISQ)
computers, they experience hardware noise; consequently, the program outputs
are often erroneous. To mitigate the adverse effects of hardware noise, it is
necessary to understand the effect of hardware noise on the program output and
more fundamentally, understand the impact of hardware noise on specific regions
within a quantum program. Identifying and optimizing regions that are more
noise-sensitive is the key to expanding the capabilities of NISQ computers.
  Toward achieving that goal, we propose CHARTER, a novel technique to pinpoint
specific gates and regions within a quantum program that are the most affected
by the hardware noise and that have the highest impact on the program output.
Using CHARTER's methodology, programmers can obtain a precise understanding of
how different components of their code affect the output and optimize those
components without the need for non-scalable quantum simulation on classical
computers.
