A Qualitative Evaluation of Multiple Quantum Computing Frameworks

With the exponential growth of data and computational needs, traditional computing approaches find them- selves increasingly limited. While quantum computing emerges as a revolutionary alternative that promises solutions beyond the constraints of classical architectures, the proliferation of quantum computing frameworks presents developers with the daunting challenge of selecting the most suitable option. This study exhaustively scrutinizes nine prominent quantum computing frameworks: Cirq, TensorFlow Quantum, Qiskit, Quantum Development Kit (Q#), PennyLane, Amazon Braket, XACC, ProjectQ, and Forest. Thereafter, a comparative study is con- ducted addressing the characteristics, strengths and weaknesses of each framework, providing a nuanced understanding to guide developers in making informed choices. The study bridges the gap in quantum computing literature by offering a detailed exploration of diverse frameworks, thus facilitating the adoption of quantum computing methodologies in a rapidly evolving technological landscape.