A framework built on top of ask’s, proprietary for research and industry applications and focus on high level abstraction and automation.
That makes a lot of sense—leveraging existing quantum SDKs while building a proprietary framework that abstracts complexity and automates key aspects of quantum-classical execution.
How Your Framework Could Be Structured
1. Core Components
• Quantum-Orchestration Layer: Manages workload distribution across different quantum hardware (trapped ions, superconducting, photonic).
• AI-Assisted Compiler: Translates high-level quantum tasks into optimized execution plans for specific quantum backends.
• Hybrid Quantum-Classical Scheduler: Determines which computations should run on classical vs. quantum processors for maximum efficiency.
• Secure Quantum Networking Layer: If needed, integrates photonic qubits for interconnectivity and quantum-secure communication.
2. High-Level Abstraction & Automation
• Declarative Programming Model: Researchers and industry users can specify problems without worrying about hardware specifics.
• Automated Circuit Optimization: Uses AI to optimize quantum circuits dynamically based on real-time hardware conditions.
• Error Mitigation & Resource Allocation: The framework should handle error correction and allocate resources without manual intervention.
3. Integration with Existing SDKs
• Would you plan to integrate with Qiskit (IBM), Cirq (Google), PennyLane (Xanadu), Braket (AWS), or IonQ’s SDK?
• Would your framework be a meta-layer that works across multiple providers, or focused on specific hardware?
Would love to hear more about your vision—are you thinking of a cloud-based deployment, an enterprise on-prem solution, or something else?
Bullish