Quantum-Clarity Technology Portfolio
Pioneering Quantum Computing Across Multiple Paradigms
QllMe™ Quantum-Enhanced AI Engine + QuantaCore™ Modular Quantum Platform
🌟 Dual-Track Innovation Platform
Quantum-Clarity operates two parallel breakthrough technology platforms, each addressing fundamental challenges in quantum computing and AI.
QuantaCore™ Platform
World-Record Modular Quantum Computing
- 116 qubits validated (29 OrthoTiles™)
- 85.7% average fidelity (no error mitigation)
- 97% peak Y⊗Z correlation
- Linear scaling demonstrated
- Patent pending (January 2026)
QllMe™ Engine
Quantum-Enhanced AI on Consumer Hardware
- 96.61% domain-specific accuracy
- 96% parameter reduction vs classical
- Six validated application domains
- Runs on standard RTX GPUs
- Patent & trademark pending
🏆 Latest Achievement: 116-Qubit World Record
January 2026: QuantaCore™ achieved the largest high-fidelity modular MBQC demonstration on record, validating 116 qubits with 85.7% avg fidelity and 97% peak correlation on IBM Quantum hardware.
This represents a 9.7× scale increase over previous modular MBQC demonstrations, with only 0.9% fidelity degradation — proving linear scalability to 1000+ qubits.
Platform Technologies
Two complementary approaches to quantum advantage
🔷 QuantaCore™ Platform — Modular Quantum Computing
Breakthrough: Operator-aligned basis migration creates independent quantum modules that scale linearly instead of degrading exponentially.
Core Technology Stack
Patent-pending deterministic circuit that relocates quantum information from computational (Z) basis into symmetry-protected Y⊗Z orthogonal manifolds, creating independent error channels.
Independent 4-qubit quantum building blocks with isolated error channels. Each module operates in its own error space, preventing cascading failures across the system.
Real-time verification framework producing operator-level manifold integrity metrics with O(n) efficiency vs O(2^n) full tomography.
QuantaCore™ Performance Metrics
(29 OrthoTiles™)
No Error Mitigation
Module 26
28/29 Deployed
Info Protected
Over 10× Scale
Target Applications
- Quantum Chemistry: FeMoco nitrogen fixation (400-1000 qubits via 100-250 modules)
- VQE & QAOA: Variational algorithms with modular resource consumption
- Quantum Teleportation: High-fidelity state transfer using OrthoTiles™ as entanglement channels
- Distributed Quantum Computing: Multi-party computation with Y⊗Z entanglement distribution
🧬 QllMe™ Engine — Quantum-Enhanced AI
Revolutionary Architecture: Quantum circuits replace classical weight matrices, delivering genuine quantum advantages on accessible GPU hardware.
Traditional LLM Architecture:
QllMe™ Engine Architecture:
QllMe™ Performance Metrics
vs 70-85% traditional
vs 100M+ traditional
Maintaining superior results
vs classical equivalents
Six-Domain Quantum Intelligence
Portfolio optimization & risk analysis using quantum algorithms for superior correlation modeling and market prediction.
20-qubit molecular simulations enabling breakthrough protein structure prediction and drug target identification.
Quantum chemistry calculations accelerating drug-target interaction modeling and pharmaceutical development.
Quantum pattern recognition for advanced anomaly detection and financial security applications.
Genomic analysis acceleration through quantum algorithms for genetic pattern recognition and analysis.
Quantum simulations for novel material discovery and property prediction across diverse applications.
Quantum Foundation: 1000+ Experiments
- 1,000+ Real Quantum Experiments — IBM Quantum hardware validation (Torino, Sherbrooke, Kyoto)
- 88 Protein Folding Experiments — Specialized molecular simulation breakthroughs
- 20-Qubit Complexity — Advanced quantum circuit simulations with GPU acceleration
- 8,192-Shot Precision — High-fidelity quantum measurement data
- Production-Ready — Validated for real-world quantum AI applications
🌟 Shared Quantum Technologies
Both platforms leverage Quantum-Clarity's comprehensive quantum computing research foundation:
QPEFT — Quantum Parameter-Efficient Fine-Tuning
Enables rapid customization for specialized applications while maintaining quantum advantages across different domains.
QLORA — Quantum Low-Rank Adaptation
Advanced adaptation techniques allowing domain-specific optimization without losing core quantum processing capabilities.
Hybrid Optimization — Quantum-Classical Gradient Algorithms
Proprietary optimization combining quantum circuit training with classical machine learning for superior convergence.
GPU Acceleration — High-Performance Quantum Simulation
10-100× speedup vs CPU-only simulation, enabling rapid protocol validation and development iteration.
🛠️ Technical Implementation
| Component | QuantaCore™ Platform | QllMe™ Engine |
|---|---|---|
| Hardware Foundation | IBM Quantum (Heron R2, 156 qubits) Rigetti, IonQ (roadmap) |
NVIDIA RTX Series GPU 6GB+ VRAM, CUDA enabled |
| Software Stack | Qiskit 1.0+, EstimatorV2 Custom topology optimization |
TensorFlow Quantum 0.7.3 TensorFlow 2.13.0 + CUDA 11.8 |
| Quantum Scale | 116 qubits validated Pathway to 1000+ qubits |
6-31 qubit simulations Scalable with GPU memory |
| Processing Speed | ~2.5 min for 116 qubits ~1.5 sec per module |
Sub-second inference Real-time AI processing |
| Key Innovation | Basis migration (patent pending) Y⊗Z orthogonal manifolds |
Quantum weight matrices Variational quantum circuits |
| Validation Status | World record (Jan 2026) Peer review in progress |
Production-ready Six domains validated |
⚡ Genuine Quantum Advantages
Both platforms exploit fundamental quantum mechanical properties:
🌊 Superposition
QuantaCore: Parallel eigenstate preparation across Y⊗Z manifolds
QllMe: Parallel evaluation of multiple linguistic interpretations
🔗 Entanglement
QuantaCore: Module-to-module quantum correlations for distributed computing
QllMe: Long-range dependency modeling between distant tokens
🌈 Quantum Interference
QuantaCore: Constructive/destructive interference in measurement-based protocols
QllMe: Pattern recognition through interference, filtering optimal solutions
🛡️ Orthogonal Protection
QuantaCore: Y⊗Z encoding provides passive noise immunity (95.3% Z-orthogonality)
QllMe: Quantum error resilience through circuit design and hybrid optimization
📄 Intellectual Property Portfolio
QuantaCore™ Platform
- U.S. Provisional Patent: Filed January 2, 2026 (Basis Migration Engine)
- Utility Patent: Filing planned by January 2027
- PCT International: Planned for EU, China, Japan markets
- Trademarks: QuantaCore™, OrthoTiles™, EigenSpectrum™ (pending)
QllMe™ Engine
- Patent: Quantum-enhanced language model architecture (pending)
- Trademark: QllMe™ (pending)
- Trade Secrets: Quantum circuit optimization algorithms, domain-specific fine-tuning methods
🚀 Dual-Track Innovation Platform
QuantaCore™: World-record modular quantum computing (116 qubits validated)
QllMe™: Production-ready quantum-enhanced AI (runs on your RTX GPU)
Accessible • Powerful • Revolutionary
Patent Pending | Quantum-Clarity LLC | Pioneering Quantum Computing Innovation