AI software tool helping quantum computers to self-adjust for better performance


With the overriding goal of reducing hardware errors and instability caused by environmental noise, quantum computing software startup Q-CTRL has unveiled a set of AI-powered tools that are believed to enable computers quantum autotuning for noise and error suppression.

The tools use AI agents to run algorithms with fewer errors, thus improving the performance of quantum computers for potential business users. The tools are accessible through emerging quantum cloud services.

Los Angeles-based Q-CTRL designs firmware for quantum computers and other quantum devices, using a form of quantum control to reduce quantum computing errors. One approach involves “robust control” to redefine the quantum logic operations used to compose quantum computation algorithms.

“In fact, we are rewriting machine language so that the system generates fewer errors,” noted Michael Biercuk, founder and CEO of Q-CTRL, in an email exchange.

Early demonstrations using IBM’s quantum cloud services platform showed that the AI ​​agent had forged new quantum logic gates. The autonomously designed doors had lower error rates than the best of those designed by IBM hardware engineers, resulting in what the startup claims to be more robust algorithms.

Source: Q-CTRL

“Our AI agent avoids the need for a mathematical model or human intervention,” Biercuk said. “The agent automates the process of learning everything they deem relevant to provide more efficient doors. “

Q-CTRL said Wednesday, February 10, that it is making the AI-based tool available as a new feature on its flagship software platform. Boulder Opal is a Python-based toolkit for developers and R&D teams using quantum control in their hardware or theoretical research.

The startup compares its AI agent to the software abstraction of conventional computing in which programmers write algorithms without getting bogged down in hardware details. As a result, Biercuk said, the AI ​​agent will “accelerate the development of quantum hardware and applications” by enabling self-tuning machines that deliver quantum logic with fewer errors.

Q-CTRL scientists have previously demonstrated the ability to create quantum logic gates for individual qubits. They outperformed standard logic gates running on an IBM quantum computer by a factor of 10. In the lab, the AI ​​agent autonomously identified new multiqubit logic gates that doubled the errors compared to the gates by default, said the startup.

The AI ​​agent also illustrates the growing infrastructure ecosystem that revolves around the development of quantum computing. Along with IBM (NYSE: IBM), Amazon Web Services (NASDAQ: AMZN) is promoting its own managed quantum computing service. Launched last August, Amazon provides development tools, simulators, and access to different types of quantum hardware, “each with a different physical limitation,” said Simone Severini, director of quantum computing at AWS.

Braket allows “to compare different technologies side by side and to switch between them by changing only one line of code”, notes Severini in a press release. blog post this week. “It’s not just about access. It’s about envisioning how quantum computing will one day fit into a cloud-based IT infrastructure, in collaboration with other compute resources.

About the Author: Georges leopold

George Leopold has been writing about science and technology for over 30 years, focusing on electronics and aerospace technology. He was previously editor-in-chief of Electronic Engineering Times. Leopold is the author of “Calculated Risk: The Supersonic Life and Times of Gus Grissom” (Purdue University Press, 2016).

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