Software & Algorithms

Just Because a QPU Gives You a Result Once, Does Not Mean It Will Do So Reliably

In February of 2022, Agnostiq released a study providing the present state-of-the-art for solving combinatorial optimization problems on real, noisy gate-model quantum computers. Although the study was primarily focused on the optimization of discrete financial portfolios, the work is much more general with consequences for other industrially important problems including vehicle routing, task scheduling and facility location services.

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Mysterious Quantum Links Could Help Lead To Exponential Scale-up

Machine learning, which now powers speech recognition, computer vision, and more, could prove even more powerful when run on quantum computers. Now scientists find the strange quantum phenomenon known as entanglement, which Einstein dubbed “spooky action at a distance,” might help remove a major potential roadblock to implementing quantum machine learning, a new study finds.

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Crucial Leap in Error Mitigation for Quantum Computers

Researchers at Lawrence Berkeley National Laboratory’s Advanced Quantum Testbed (AQT) demonstrated that an experimental method known as randomized compiling (RC) can dramatically reduce error rates in quantum algorithms and lead to more accurate and stable quantum computations. No longer just a theoretical concept for quantum computing, the multidisciplinary team’s breakthrough experimental results are published in Physical Review X.

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