News

Commercial-Grade Tools for Quantum Control Announced

• By John K. Waters
• 03/03/2020

Quantum computing startup Q-CTRL last week introduced the first set of commercial-grade software tools for quantum control in quantum computing research.

Called Boulder Opal, the Python-based toolset is aimed at developers and R&D teams using quantum control in their hardware or theoretical research.

Quantum control refers to the control of physical systems whose behavior is dominated by the laws of quantum mechanics. It's essentially about optimizing the performance of quantum systems.

Boulder Opal, currently in beta, is a technology-agnostic toolkit delivered via the cloud. It's designed for building and outputting error-robust logic operations for complex quantum circuits. The result for users, the company says, is greater performance than is typical of today's quantum computing hardware.

In fact, the company is claiming Boulder Opal reduces computational errors by 100X and accelerates time to accurate calculations by 10X, regardless of the quantum computing platform. It points to a research study with the University of Sydney to validate its claims. The study focused primarily on quantum firmware, the low-level software solutions designed to enhance the stability of quantum computational hardware at the physical layer. And it provides an overview of Q-CTRL's software tools for creating and deploying quantum control solutions at various layers of the quantum computing software stack.

The Australian company was founded by, and based on the research of, Michael J. Biercuk , Professor of Quantum Physics and Quantum Technology at the University of Sydney. He also leads the university's Quantum Control Lab.

"The power of quantum control in improving quantum computers is well understood by the scientific community," Biercuk said in a statement. "Boulder Opal provides globally unique, proprietary technical capabilities, and focuses on delivering real, tangible benefits to users."

The hardware underlying quantum computers is fragile, and "noise" from the environment—control electronics, heat, or impurities in the materials in the quantum bits (qubits) themselves—can destroy the quantum state of the qubits and impede performance. Q-CTRL specializes in delivering a set of techniques that can stabilize the hardware and allow quantum computations to be executed with fewer errors.

The Boulder Opal tools were built by a team of quantum control engineers with special understanding of the challenges of quantum computing, Biercuk said.

"With these tools we've thought a lot about the user experience," he said.  "If you're a quantum-algorithm developer or a researcher, we understand you want straightforward access to the benefits of quantum control to improve quantum computers without needing to hack your own code.  And we know that users want solutions as quickly as possible so they can test and iterate rapidly."

The toolset comes with easy-to-use features not previously available to the R&D community. For example, performing highly complex constrained numeric optimizations on interacting quantum bits with many adjustable parameters can now be reduced to a few lines of validated code executed in seconds, the company says. Because it'd Python-based, it's easy to integrate with other tools widely used in the quantum computing research and developer communities. The company is offering software integrations with Qiskit, pyquil, and CirQ, as well as custom integration for user hardware. The tool also complements open-source packages such as QuTiP.

Q-CTRL is demonstrating its new toolset at the American Physical Society (APS) March Meeting in Denver (March 2-6) on the exhibit floor of the Colorado Convention Center.