System Architecture

Qoro Quantum connects users to quantum resources through a centralized orchestration and control system, abstracting away low-level details like hardware scheduling, data movement, and circuit translation.

Qoro Quantum’s platform is composed of various software components that perform different tasks. It starts from the application layer to develop large scale quantum programs, to the cloud orchestration and scheduling, to the network control. The components are:

  flowchart TD
    classDef smallText font-size:12px;

    A["Divi (Python SDK)"] --> B["Composer Gateway (Cloud API)"]
    B --> C["Composer Resource Allocation (Scheduler)"]
    C --> D["Composer Orchestrator"]
    D --> E["Composer Interfaces"]
    E --> F{{"QPU (Device)"}}
    D --> G{{"Maestro (Simulator)"}}
    A --> H{{"Local Simulator"}}

1. Divi – End-User Programming Library

• An open-source Python library for building hybrid quantum-classical workflows.
• Supports a variety of quantum applications and the ability to define custom applications.
• Accelerates development of quantum programs, offloading infrastructure and execution management.
• Handles tasks like result aggregation and error mitigation.
• Provides a simple local simulator for quick prototyping.

2. Composer Gateway – Cloud API

• The RESTful interface for submitting jobs, querying status, and retrieving results.
• Authenticates users and manages workload metadata.
• Enables integration into enterprise pipelines and research platforms via secure APIs.

3. Composer Resource Allocation – Network-Aware Scheduler

• Schedules quantum and classical workloads with awareness of latency, topology, and bandwidth constraints in quantum datacenter networks.
• Optimizes placement of distributed quantum programs to minimize execution time and maximize coherence.
• Handles resource-aware scheduling and network- and hardware-layer parallelizations.
• Uses intelligent decision making to find the best resource for the job.

4. Composer Orchestrator – Job Orchestration Engine

• Coordinates and schedules hybrid jobs across distributed computing infrastructure.
• Interfaces with multi-vendor, multi-modal networks to communicate job instructions.
• Monitors the computing network for state-aware processing.

5. Maestro – Intelligent Quantum Simulator

• Selects the most appropriate simulator backend based on circuit structure and hardware characteristics.
• Chooses between matrix product state, state vector, and clifford engines.
• Enables faster prototyping, benchmarking, and hybrid experimentation without manual simulator tuning.
• Can estimate runtime for energy consumption estimation tasks.
• Automode: Automatically selects the optimal simulation method based on circuit analysis, removing the need for manual configuration.

6. Composer Interfaces – Multi-Vendor QPU Access

• Provides unified access to multiple quantum computing backends (IBM, IQM, AWS Braket, LRZ, and more).
• Each backend is served by an independent worker service that handles transpilation, submission, and result retrieval.
• Supports error mitigation, circuit compression, and batch processing across all backends.
• Enables adding new quantum hardware providers through a simple worker interface.