D-Wave — searchable YouTube transcripts & AI Q&A

D-Wave Qubits Asia 2026 - Opening Keynote

D-Wave's CEO argues that annealing quantum computers are commercially viable today for optimization problems, citing a demonstration where their Advantage2 system solved material simulation tasks in under 20 minutes that would take classical supercomputers nearly a million years. He also introduces their dual-rail qubit technology for gate-model systems, which can detect 90% of errors inherently, potentially reducing the physical qubits needed for error correction from 1,000 to 100 per logical qubit. The talk includes a partnership with LGCNS to bring quantum optimization to Korean enterprises, with LGCNS reporting problems involving 100 million variables.

Webinar: Quantum Optimization for Mission-Critical Government Challenges

D-Wave's quantum optimization can dramatically reduce scheduling and planning times for mission-critical government challenges, with examples like cutting scheduling from 10 hours to 5 seconds and police vehicle placement from 4 months to 4 minutes. The key is selecting the right use case, data, and problem formulation, and using a hybrid approach that combines classical solvers with quantum annealing. The speakers caution that not every problem is a quantum problem and that solutions are not guaranteed to be optimal, but they offer significant speed advantages.

Build Your First Quantum Circuit Description Language (QCDL) Program

QCDL, part of D-Wave's Ocean SDK, allows users to build and run gate model quantum circuits, with built-in eraser detection in dual rail qubits enabling error identification at the single qubit level. Post-selection, which removes samples with detected erasers, can substantially improve output fidelity, as demonstrated with a Bell state circuit where expected outcomes increased from about 81% to 99% after filtering. This error-aware programming capability reduces the overhead needed for error detection, allowing more qubits to be used for computation.

Error Detection in Dual-Rail Qubits

D-Wave's dual-rail qubit technology detects photon loss errors at the hardware level, flagging the exact qubit and time of the error, which the speaker argues simplifies error correction. This erasure-based detection reduces hardware overhead by up to 10x compared to traditional quantum error correction, and the error-aware programming toolbox allows users to filter, annotate, or adaptively respond to these detected errors during execution.

Getting Started with the Ocean SDK for Gate Model

The Ocean SDK provides Python tools for programming D-Wave's gate model simulator, which supports error-aware programming through error detection and real-time control. The speaker demonstrates setting up the development environment, including installing the Ocean SDK, configuring API access via the LEAP service, and verifying the connection by pinging the service. The simulator offers both ideal and noisy modes, with the noisy mode helping evaluate algorithm performance under realistic conditions.