Transforming the Path to Quantum Advantage
summary
Q-CTRL presents software quantum control across the stack with three products—Black Opal, Boulder Opal, and Fire Opal—claiming concrete gains: run 10x deeper circuits, reduce shot count by >1000x and overall >1000× performance improvement on cloud devices. Demonstrations include a max‑cut result at 156 qubits where errors stop being the limiter, a Mazda QML surrogate showing improvements with 250 training points, and a London Bridge routing case reduced from 448 to 103 qubits for 26 trains/15 platforms.
AI-written summary · about
chapters (11)
- 0:00QControl and quantum challenges
- 1:07QControl’s AI error reduction
- 2:35Fire Opal error suppression
- 4:22Performance gains with Fire Opal
- 5:27Fire Opal’s hybrid solver
- 7:16Quantum advantage with larger devices
- 7:37Customer co-design projects
- 11:09Quantum ML for vehicle design
- 14:29Station routing optimization
- 17:41Timeline for quantum advantage
- 18:03Q&A
related talks
23mMake Quantum Computing Useful with Performance Enhancing Infrastructure Software
47mUnboxing Quantum Computing
19mExtracting maximum value from today's quantum computers while prep
17mQuantum Applications with Classiq
37mResource-Efficient Quantum Computing by Breaking Abstractions
26mQuantum Leap: Revolutionizing Rust Software Development
19mSupporting End-Users in Realizing Quantum Computing Applications
16mQuantum Computing - The State of Play