IN REPLAY - ML for Quantum Technologies - Building the Qruise AI Physicist
Start-up pitch
AI Application
ARTIFICIAL NEURAL NETWORKS
DATA MANAGEMENT
DEEP LEARNING
EDGE COMPUTING
HARDWARE
MODEL DRIFT
PROCESS OPTIMIZATION
RESEARCH
SOFTWARE
2023-02-09 | 04:30 PM - 05:00 PM | Start-up pitch Stage 1
Information
Building useful quantum computers is a daunting task, with thousands of parameters to be characterised and calibrated. As a result, progress has been slow, with median per-operation error rates well above 0.1% for almost a decade [1,2,3].
To make progress, Qruise is building a machine learning physicist, to work alongside human physicists in the task of characterizing the exact minute details of each device fabricated, and then control and calibrate each quantum operation.
Most importantly, the digital twin created by the Qruise software will allow physicists to identify the causes of imperfections in the operation of current-generation hardware, thus focusing the efforts and maximizing the improvement in the next-generation devices.
To make progress, Qruise is building a machine learning physicist, to work alongside human physicists in the task of characterizing the exact minute details of each device fabricated, and then control and calibrate each quantum operation.
Most importantly, the digital twin created by the Qruise software will allow physicists to identify the causes of imperfections in the operation of current-generation hardware, thus focusing the efforts and maximizing the improvement in the next-generation devices.
[1][2014] Barends, R., Kelly, J., Megrant, A., Veitia, A., Sank, D., Jeffrey, E., ... & Martinis, J. M. (2014). Superconducting quantum circuits at the surface code threshold for fault tolerance. Nature, 508(7497), 500-503.
[2][2019] Arute, F., Arya, K., Babbush, R., Bacon, D., Bardin, J. C., Barends, R., ... & Martinis, J. M. (2019). Quantum supremacy using a programmable superconducting processor. Nature, 574(7779), 505-510.
Speakers
