D-Wave Stride hybrid solver now finds better solutions in 15 seconds versus 120 seconds previously. The core algorithm was enhanced and is available in the Leap quantum cloud service. A three-course Applied Quantum Optimization learning path was also launched.
Key points
Benchmark: enhanced solver found better solutions in 15 seconds, previous version needed 120 seconds.
Learning path: new three-course Applied Quantum Optimization program released for developers.
Sources
qLDPC codes talk at FTQC4NSc symposium, recording released
New qLDPC codes tailored to physical architectures were presented in a talk on fault-tolerant quantum computing. The talk was given at the FTQC4NSc symposium in Heilbronn and a recording is now available.
Key points
Talk: perspectives on quantum error correction and fault tolerance, including new qLDPC codes.
Recording: video posted from the FTQC4NSc symposium at experimenta – Das Science Center.
Sources
- Original post
- youtube.com - Linked in the post
genESPRIT precision guarantees without deterioration
genESPRIT can estimate the generator of matrix exponential time-series with rigorous precision guarantees, and precision does not deteriorate as spectral peaks crowd together. The result appears in the paper “Estimating the generator of matrix exponential time-series”.
Key points
Claim: under suitable linear-independence assumptions, precision does not deteriorate as spectral peaks crowd together.
Collaboration: work done with @fuksa_jonas and Ingo Roth, linked to an arXiv preprint.
Sources
- Original post
- scirate.com - Linked in the post
- nature.com - Linked in the post
Xanadu ASML collaboration to tackle optical loss
Xanadu and ASML have joined forces to tackle optical loss with next-gen lithography, aiming to fast-track utility-scale quantum computing. The partnership targets reducing optical loss in quantum photonic hardware.
Key points
Collaboration: Xanadu recently joined forces with semiconductor leader ASML
Objective: tackle optical loss with next-gen lithography
Sources
Chrysalis – students teach the machine
Chrysalis makes students teach the machine, reversing typical classroom AI tools that answer questions. Developed by researchers at Vector and the @UWaterloo, the system acts as an interactive pupil.
Key points
Reverses typical AI classroom tools: students teach the machine.
Developed by researchers at Vector and the @UWaterloo; acts as an interactive pupil.