📝 SummarXiv

Abstract

As quantum computing hardware continues to scale, the need for a robust software infrastructure that bridges the gap between high-level algorithm development and low-level physical qubit control becomes increasingly critical. A full-stack approach, analogous to classical computing, is essential for managing complexity, enabling hardware-agnostic programming, and systematically optimizing performance. In this paper, we present a comprehensive, end-to-end quantum software stack, detailing each layer of abstraction from user-facing code to hardware execution. We begin at the highest level with the Ket quantum programming platform, which provides an expressive, Python-based interface for algorithm development. We then describe the crucial multi-stage compilation process, which translates hardware-agnostic programs into hardware-compliant circuits by handling gate decomposition, qubit mapping to respect device connectivity, and native gate translation. To illustrate the complete workflow, we present a concrete example, compiling the Grover diffusion operator for a superconducting quantum processor. Finally, we connect the compiled circuit to its physical realization by explaining how native gates are implemented through calibrated microwave pulses. This includes the calibration of single- and two-qubit gates, frequency characterization, and measurement procedures, providing a clear picture of how abstract quantum programs ultimately map onto the physical control of a quantum processor. By providing a detailed blueprint of a complete quantum stack, this work illuminates the critical interplay between software abstractions and physical hardware, establishing a framework for developing practical and performant quantum applications.