EoS for
Quantum Computing
The EmbeddedOS Quantum Computing module (eQC) extends the EoS kernel with real-time QPU scheduling, hardware abstraction for all major quantum processors, and a unified SDK interface for IBM, Google, Microsoft, IonQ, and Rigetti hardware.
Supported Quantum Processors
EoS provides native kernel-level support for every major quantum computing platform through the eQC Hardware Abstraction Layer (HAL).
IBM Quantum
IBM Heron r2
IBM's Heron r2 processor delivers 156 tunable-coupler qubits with a 3–5× performance improvement over the previous Eagle generation. EoS provides native Qiskit circuit compilation and direct QPU scheduling through the IBM Quantum Runtime API.
EoS eQC Integration Features
- Qiskit Runtime integration via eQC HAL driver
- OpenQASM 3.0 circuit transpilation to Heron native gates
- Real-time pulse calibration through IBM Pulse API
- Quantum Volume benchmarking daemon
eQC Kernel Module Features
Nine specialized subsystems extending the EoS microkernel with full quantum computing support — from nanosecond pulse control to post-quantum cryptographic isolation.
Hardware Abstraction Layer
A unified driver interface that abstracts IBM, Google, IonQ, Rigetti, Microsoft, and Quantinuum quantum processors behind a single eQC API. Write once, run on any QPU.
Sub-100 ns gate control
Deterministic pulse generation for superconducting and trapped-ion gate operations. Integrates with FPGA-based arbitrary waveform generators (AWGs) for nanosecond-precision control.
Quantum Error Correction
Real-time surface code syndrome measurement and decoding. Supports Google's below-threshold error correction model and IBM's heavy-hex lattice code.
Deterministic circuit queue
Priority-based quantum job scheduling with circuit dependency resolution, qubit allocation, and deallocation. Prevents qubit state collisions across concurrent jobs.
Classical ↔ Quantum handoff
Seamless data transfer between classical CPU memory and quantum registers. Supports mid-circuit measurement and real-time classical feedback for variational algorithms.
Dilution refrigerator control
Low-level drivers for cryogenic control electronics, including dilution refrigerator temperature management, FPGA AWG interfaces, and microwave signal routing.
OpenQASM 3.0 + native gates
Multi-backend circuit compiler supporting OpenQASM 3.0, Qiskit IR, Cirq, Quil, and Q#. Transpiles to vendor-native gate sets with depth and error optimization.
Automated qubit characterization
Continuous qubit drift monitoring, T1/T2 coherence measurement, gate fidelity benchmarking, and automated recalibration scheduling to maintain peak performance.
Post-quantum cryptography
Integrated NIST post-quantum cryptographic algorithms (CRYSTALS-Kyber, CRYSTALS-Dilithium) for secure qubit state isolation and quantum-safe key exchange.
Quantum Hardware Comparison
All six supported quantum computing platforms compared across key technical specifications and EoS integration status.
| Spec | IBM IBM | GQA Google | AQ Microsoft | IQ IonQ | RC Rigetti | QN Quantinuum |
|---|---|---|---|---|---|---|
| Chip | Heron r2 | Willow | Majorana† | Forte | Ankaa-3 | H2-1 |
| Qubits | 156 | 105 | Future | 35 AQ | 84 | 56 |
| Technology | Superconducting | Superconducting | Topological | Trapped-ion | Superconducting | Trapped-ion QCCD |
| Gate Time | ~50 ns | ~25 ns | TBD | ~200 µs | ~40 ns | ~1 ms |
| Coherence | ~300 µs | ~100 µs | Unlimited† | ~10 s | ~50 µs | ~1 s |
| 2Q Fidelity | 99.9% | 99.7% | 99.99%† | 99.9%+ | 99.5% | 99.9%+ |
| SDK | Qiskit | Cirq | Q# | Multi | Pyquil | TKET |
| EoS Status | ✅ Supported | ✅ Supported | 🔵 Beta | ✅ Supported | ✅ Supported | ✅ Supported |
† Microsoft topological qubits are in research phase. Coherence and fidelity figures are theoretical targets.
All Quantum Paradigms Supported
Universal quantum circuits using single and two-qubit gates. Supported by IBM, Google, IonQ, Rigetti, and Quantinuum.
Inherently fault-tolerant qubits using Majorana fermions. Microsoft's long-term quantum roadmap.
Variational algorithms combining classical optimization with quantum circuit evaluation (VQE, QAOA).
Optimization-focused quantum computing for combinatorial problems. D-Wave integration planned.
Quantum Simulation & Hybrid Frameworks
EoS eQC integrates with all major quantum simulation frameworks — enabling development and testing without physical QPU access, and powering hybrid classical-quantum algorithms.
High-performance quantum circuit simulator supporting state-vector, density matrix, and stabilizer simulation. Includes realistic noise models from IBM hardware calibration data.
EoS Integration
eQC development mode — run circuits locally before submitting to real IBM QPU
Google's circuit simulation engine with support for state-vector, density matrix, Clifford, and MPS (matrix product state) simulators. Optimized for Willow-style circuits.
EoS Integration
eQC surface code QEC testing and Willow circuit validation before cloud submission
The leading framework for quantum machine learning and variational quantum algorithms. Supports automatic differentiation of quantum circuits and integrates with PyTorch, TensorFlow, and JAX.
EoS Integration
eQC Hybrid Bridge — VQE, QAOA, and QML workloads with classical optimizer feedback loops
Quantum Toolbox in Python — the standard tool for simulating open quantum systems, Lindblad master equations, and quantum optics. Used for qubit decoherence modeling and pulse-level simulation.
EoS Integration
eQC pulse engine calibration — T1/T2 decoherence modeling for cryogenic qubit drivers
The fastest open-source quantum circuit simulator, optimized for multi-core CPU and GPU execution. Supports up to 30+ qubits in state-vector mode with SIMD and CUDA acceleration.
EoS Integration
eQC CI/CD pipeline — fast circuit regression testing without QPU queue wait times
Amazon Braket provides unified access to IonQ, Rigetti, OQC, and QuEra hardware alongside local state-vector and density matrix simulators. The Braket SDK enables multi-provider circuit submission from a single API.
EoS Integration
eQC multi-cloud routing — submit to IonQ or Rigetti via Braket as an alternative to direct APIs
Hybrid Classical-Quantum Computing
The NISQ era demands tight integration between classical CPUs and quantum processors. EoS eQC's Hybrid Bridge enables real-time feedback loops for variational algorithms.
A classical optimizer (L-BFGS, COBYLA, ADAM) runs on the EoS CPU and proposes circuit parameters for the next quantum evaluation.
optimizer = COBYLA() params = optimizer.step(cost_fn)
The parameterized quantum circuit is compiled and submitted to the QPU via eQC HAL. Mid-circuit measurements feed back to the classical layer in real-time.
circuit = ansatz(params) result = eqc.run(circuit, shots=1024)
The expectation value is returned to the classical optimizer. The loop repeats until the energy/cost converges to the ground state or optimal solution.
energy = result.expectation_value(H) if abs(energy - prev) < 1e-6: break
eQC Roadmap
- IBM Qiskit Runtime HAL driver
- IonQ REST API HAL driver
- Rigetti Pyquil HAL driver
- OpenQASM 3.0 parser and transpiler
- Sub-100ns pulse engine for superconducting qubits
- Surface code QEC runtime
- Google Willow HAL driver
- Real-time syndrome decoder
- Azure Quantum multi-provider routing
- Hybrid classical-quantum bridge
- Variational algorithm runtime (VQE, QAOA)
- Microsoft Q# language runtime
- Microsoft Majorana topological qubit driver
- Fault-tolerant logical qubit abstraction
- Post-quantum cryptographic key management
- D-Wave annealing integration
Build the Quantum Future with EmbeddedOS
The eQC module brings real-time quantum hardware control to the EoS kernel. Join the Foundation to help shape the operating system for the quantum era.