Pioneering Research
Tumquan Research drives innovation at the intersection of quantum computing and AI. Our team of scientists and engineers publish groundbreaking work, contribute to open-source projects, and collaborate with leading academic institutions worldwide.
We believe in open science and regularly share our findings through peer-reviewed publications, conferences, and technical blog posts.
Research Areas
Quantum Algorithms
Developing novel quantum algorithms for optimization, machine learning, and simulation with near-term hardware.
Error Correction
Advancing fault-tolerant quantum computing through new error correction codes and techniques.
Quantum Machine Learning
Exploring quantum advantages in machine learning and developing hybrid quantum-classical models.
Large Language Models
Researching next-generation LLM architectures, training methods, and applications.
Multi-Modal AI
Building systems that understand and reason across text, images, and structured data.
AI Safety
Ensuring AI systems are safe, reliable, and aligned with human values.
Recent Publications
- "Quantum Advantage in Combinatorial Optimization" - Nature Quantum, 2025
- "Efficient Quantum Feature Maps for Machine Learning" - Physical Review Letters, 2025
- "Scalable Error Mitigation for NISQ Devices" - PRX Quantum, 2024
- "Multi-Modal Reasoning in Large Language Models" - NeurIPS 2024
- "Quantum-Enhanced Natural Language Processing" - ACL 2024
Collaborations
We collaborate with leading institutions including MIT, Stanford, Oxford, ETH Zurich, and national laboratories. Interested in collaborating? We're always looking for partners pushing the boundaries of what's possible.