Automated Near-Term Quantum Algorithm Discovery for Molecular Ground States
Quantinuum researchers explore automated discovery of quantum algorithms for molecular ground-state problems, combining machine learning with quantum algorithm design.
QUANTINUUM RESEARCH
Latest Research by Quantinuum
Explore Quantinuum's latest quantum computing research across fault-tolerant computing, quantum information, trapped-ion hardware, quantum AI and applications in chemistry and physics.
FAULT-TOLERANT COMPUTING
QUANTUM ERROR CORRECTION
TRAPPED-ION HARDWARE
QUANTUM AI
QUANTUM APPLICATIONS
FEATURED RESEARCH
Quantinuum Research Highlights
Benchmarking Computational Power of Quantum Computers
Research into rigorous methods for benchmarking the computational power of quantum computers, with an emphasis on meaningful comparisons across quantum systems.
Experimental Validation of a Compact Fault-Tolerant Architecture for Trapped Ions
Experimental research validating a compact fault-tolerant architecture for trapped-ion quantum computing and exploring practical approaches to scalable error-corrected systems.
Improved Quantum Processor Logical Error Rates via Correction and Detection
Quantinuum researchers investigate quantum error correction and detection techniques for reducing logical error rates in trapped-ion quantum processors.
Learning to Prepare Molecular Ground States with Transformer Models
Quantinuum researchers investigate transformer models for learning quantum-state preparation strategies targeting molecular ground states.
Benchmarking the Computational Power of Quantum Computers
A study of methods for characterizing and benchmarking the computational capabilities of quantum computers across hardware and quantum workloads.