QuantaCore™ Quantum Control Platform
AI-guided runtime quantum information routing with reversible state transformations.
The first demonstrated three-layer hybrid architecture combining classical AI inference, quantum control orchestration, and hardware-validated basis migration—proven on IBM's 156-qubit processor.
Or email: info@quantum-clarity.com
Three-Layer Hybrid Architecture
QuantaCore separates AI inference (classical), quantum control (orchestration), and hardware execution (quantum) into distinct layers with strict safety boundaries.
AI Inference Layer
Classical State-Space ModelingClassical SSM (Kalman filtering) estimates hidden noise dynamics from sparse hardware measurements. Runs entirely on CPU—no quantum computer involved, no GPU required. The AI never touches qubits—it observes patterns and recommends routes.
Evidence-Based Abstention
When Y⊗Z SNR < 0.02 threshold, system explicitly abstains and defaults to Z-basis. No overconfident routing.
State Estimation
Z-decay: 0.0137 μs⁻¹ (validated). Y-decay: NOT RESOLVED (1/6 informative). Confidence: 23% (honest).
Q-HAL™ Control Plane
Quantum Hardware Abstraction LayerReceives AI recommendations and makes executive decisions. Acts as safety buffer—can override AI if recommendations seem unsafe. Orchestrates reversible basis migrations (U → idle → U†) and manages quantum information routing. No real-time feedback during coherence—all decisions between circuit executions.
Validated Performance
73% Z-parity suppression, 92% round-trip recovery, 116 qubits validated with 101σ confidence.
Adaptive Selection
67% optimal basis selection across 12 runs. 83% win rate in moderate-noise regions.
Quantum Hardware
Platform-Agnostic ExecutionExecutes unitary transformations and measurements specified by Q-HAL. No mitigation, no error correction—just standard NISQ primitives. Hardware never receives AI instructions—control plane translates recommendations into validated quantum operations. Platform-independent design works on IBM, Google, IonQ systems.
IBM Quantum
ibm_fez (156-qubit Heron R2), ibm_torino (133-qubit Eagle R3). Primary validation platform.
Multi-Platform
IonQ Aria (validated), Google Sycamore (preliminary). Platform-agnostic design.
Safety Architecture: AI observes and recommends (Layer 1) → Control plane validates and decides (Layer 2) → Quantum hardware executes primitives (Layer 3). Strict separation ensures AI never directly manipulates quantum states. Control plane acts as safety buffer.
The Quantum Control Plane in Action
Dynamic quantum information placement without measurement collapse—enabling quantum memory, checkpointing, and adaptive workflows impossible on standard NISQ systems.
Toggle-Based Information Control
Baseline (Z-basis)
Z⊗Z = 0.84
Y⊗Z = 0.04
Operational state
Toggle ON (Migrate)
Z⊗Z = 0.24
Y⊗Z = 0.07
Protected plane
Toggle OFF (Return)
Z⊗Z = 0.78
Y⊗Z = 0.05
Recovered state
71% Z-parity suppression when toggled ON,
92% recovery when toggled OFF
Validated on production quantum hardware (IBM ibm_fez)
(4 circuits, 8 measurements)
(Toggle ON then OFF)
(Information routing)
Quantum Memory
Store quantum information in protected plane while performing other operations, then retrieve with 92% fidelity. No measurement collapse.
Quantum Checkpointing
Save quantum state before risky operations. If operation fails, restore checkpoint and retry—fault tolerance without full error correction.
Adaptive Workflows
AI detects noisy periods and recommends protection ON. When hardware state improves, recommends OFF. Dynamic optimization based on real-time characterization.
Hardware Validation Evidence
Multi-scale validation from micro-level (4 qubits) to production-scale (116 qubits) with statistical confidence exceeding 100-sigma.
AI Inference Layer (Jan 15, 2026)
Classical SSM analyzing 6 temporal measurements to estimate noise dynamics and generate basis recommendations with abstention logic.
- Z-decay: 0.0137 μs⁻¹ (validated)
- Y-decay: NOT RESOLVED (SNR-limited)
- Abstention: Defaulted to Z-basis safely
Control Plane Validation (Jan 10, 2026)
Four-circuit comparison on IBM ibm_fez demonstrating correlation routing and round-trip reversibility.
- C0 baseline: Z⊗Z = 0.8447
- C1 migrated: Z⊗Z = 0.2412 (71% suppressed)
- C2 returned: Z⊗Z = 0.7754 (92% recovered)
Large-Scale Architecture (Dec 2025)
29 independent 4-qubit modules spanning 116 qubits on IBM Heron R2, demonstrating modular scaling advantage.
- Average fidelity: 77.1%
- Peak Y⊗Z: -0.97
- Linear scaling demonstrated
Q-HAL Adaptive Selection (Jan 8, 2026)
12 runs across 3 regions testing Q-HAL's runtime basis selection capability with AI guidance (prototype).
- Moderate: AI guided to migrated 5/6
- Clean: Standard preferred 2/3
- Noisy: Mixed results (learning needed)
Strategic Positioning
QuantaCore is complementary to existing quantum stacks—not competitive. We enhance IBM Qiskit, Google Cirq, and all major platforms with AI-guided runtime control capabilities.
Current Quantum Platforms
IBM Qiskit, Google Cirq, Microsoft Q#
- Prepare → Execute → Measure (one-shot)
- Static compilation at circuit design
- No mid-flight information control
- Error mitigation: post-processing only
- No AI-guided adaptive decisions
QuantaCore Control Platform
AI-Enhanced Layer Above Hardware
- AI estimates noise → Recommends basis
- Prepare → Toggle → Store → Toggle → Retrieve
- Runtime adaptive basis selection
- Dynamic information routing (no measurement)
- Proactive quantum state management
Integration strategy: QuantaCore integrates with existing SDKs as an optional AI-enhanced optimization layer. Algorithm → QuantaCore (AI + control) → Qiskit/Cirq → Hardware. Compatible with all major quantum cloud providers. AI layer is opt-in—defaults to safe operations when uncertain.
Partner with Quantum-Clarity
QuantaCore represents the first AI-enhanced quantum control platform with hardware-validated runtime information routing and evidence-based safety logic. Join us in making quantum computing practical.
Or email: info@quantum-clarity.com
AI-guided • 92% round-trip fidelity • Abstention logic • DA