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Q-CTRL, a startup that applies the principles of control engineering to accelerate the development of the first useful quantum computers, will host a series of online demonstrations of new quantum control tools designed to enhance the efficiency and stability of quantum computing hardware.
Dr. Michael Hush, Head of Quantum Science and Engineering at Q-CTRL, will provide an overview of the company’s cloud-based quantum control engineering software called BOULDER OPAL. This software uses custom machine learning algorithms to create error-robust logical operations in quantum computers. The team will demonstrate - using real quantum computing hardware in real time - how they reduce susceptibility to error by 100X and improve hardware stability in time by 10X, while reducing time-to-solution by 10X against existing software.
Scheduled to accommodate the global quantum computing research base, the demonstrations will take place:
April 16 from 4-4:30 p.m. U.S. Eastern Time (ET)
April 21 from 10-10:30 a.m. Singapore Time (SGT)
April 23 from 10-10:30 a.m. Central European Summer Time (CEST)
To register, visit https://go.q-ctrl.com/l/791783/2020-03-19/dk83
Released in Beta by Q-CTRL in March, BOULDER OPAL is an advanced Python-based toolkit for developers and R&D teams using quantum control in their hardware or theoretical research. Technology agnostic and with major “computational grunt” delivered seamlessly via the cloud, BOULDER OPAL enables a range of essential tasks which improve the performance of quantum computing and quantum sensing hardware. This includes the efficient identification of sources of noise and error, calculating detailed error budgets in real lab environments, creating new error-robust logic operations for even the most complex quantum circuits, and integrating outputs directly into real hardware.
The result for users is greater performance from today’s quantum computing hardware, without the need to become an expert in quantum control engineering.
Experimental validations and an overview of the software architecture, developed in collaboration with the University of Sydney, were recently released in an online technical manuscript titled Software Tools for Quantum Control: Improving Quantum Computer Performance through Noise and Error Suppression.
Dr. Michael Hush, Head of Quantum Science and Engineering at Q-CTRL, will provide an overview of the company’s cloud-based quantum control engineering software called BOULDER OPAL. This software uses custom machine learning algorithms to create error-robust logical operations in quantum computers. The team will demonstrate - using real quantum computing hardware in real time - how they reduce susceptibility to error by 100X and improve hardware stability in time by 10X, while reducing time-to-solution by 10X against existing software.
Scheduled to accommodate the global quantum computing research base, the demonstrations will take place:
April 16 from 4-4:30 p.m. U.S. Eastern Time (ET)
April 21 from 10-10:30 a.m. Singapore Time (SGT)
April 23 from 10-10:30 a.m. Central European Summer Time (CEST)
To register, visit https://go.q-ctrl.com/l/791783/2020-03-19/dk83
Released in Beta by Q-CTRL in March, BOULDER OPAL is an advanced Python-based toolkit for developers and R&D teams using quantum control in their hardware or theoretical research. Technology agnostic and with major “computational grunt” delivered seamlessly via the cloud, BOULDER OPAL enables a range of essential tasks which improve the performance of quantum computing and quantum sensing hardware. This includes the efficient identification of sources of noise and error, calculating detailed error budgets in real lab environments, creating new error-robust logic operations for even the most complex quantum circuits, and integrating outputs directly into real hardware.
The result for users is greater performance from today’s quantum computing hardware, without the need to become an expert in quantum control engineering.
Experimental validations and an overview of the software architecture, developed in collaboration with the University of Sydney, were recently released in an online technical manuscript titled Software Tools for Quantum Control: Improving Quantum Computer Performance through Noise and Error Suppression.