QuantumPulse

Bell Pair Creation with Pulses on Rigetti's Aspen M-3

• This repository contains a Jupyter notebook demonstrating the creation of Bell states using both standard gate-based methods and low-level pulse sequences on Rigetti's Aspen M-3 quantum device via Amazon Braket.

Overview

The notebook explores:

• Implementation of a Bell pair circuit using standard quantum gates
• Creation of the same Bell state using pulse-level control
• Comparison of results between gate-based and pulse-based approaches

Requirements

Python 3.x Amazon Braket SDK Numpy Matplotlib

Installation

• Clone this repository:

• git clone https://github.com/yourusername/bell-pair-pulses-rigetti.git

• Install required packages:

• pip install amazon-braket-sdk numpy matplotlib

Key Features

• Standard Bell Pair Circuit
• Implementation using Hadamard and CNOT gates
• Pulse-based Implementation
• Custom Hadamard gate decomposition
• CZ gate using arbitrary waveforms
• Phase correction for qubit frames
• Analyze the impact of noise by introducing a depolarizing channel
• Implement error mitigation using stabilizer averages
• Optimize pulse parameters to maximize fidelity

Visualizations

• CZ gate waveform
• Complete pulse sequence

Execution and Analysis

• Running circuits on Rigetti's Aspen M-3
• Comparison of measurement results

Usage

• Open the Jupyter notebook Bell_Pair_Pulse.ipynb
• Follow the cells sequentially to understand the implementation and see results
• Modify parameters or pulse shapes to experiment with different configurations

Results

• The notebook demonstrates successful creation of Bell states using both methods, with visualizations and analysis of the results.
• Pulse-based Bell state preparation achieved 88.4% fidelity (500 shots)
• Gate-based implementation achieved 84% fidelity
• Depolarizing noise (p=0.1) degraded fidelity to 72.2%
• Error correction with stabilizer encoding improved noisy fidelity to 74%
• Optimized CZ pulse parameters further improved noiseless fidelity to 88%

Analysis

• Pulse-level control allows for high-fidelity Bell state preparation with modestly better performance than gate-based approaches. However, sensitivity to noise and decoherence remains a significant challenge. Stabilizer error correction and pulse optimization provide some improvements, but further work is needed to dramatically enhance robustness to errors.

Cost Considerations

• The notebook includes an estimation of costs for running quantum tasks. Be aware of potential charges when using the Rigetti quantum device through Amazon Braket.

Future Directions

• Apply more sophisticated pulse optimization techniques (e.g., GRAPE)
• Explore dynamical error suppression techniques
• Integrate pulse-level control with noise-robust circuit compilation
• Investigate scalable entanglement generation for quantum networking