Quantum software startup Classiq Technologies Ltd. said today it has partnered with Comcast Corp. and Advanced Micro Devices Inc. to showcase how quantum computers can dramatically enhance network resilience and improve internet delivery, even when multiple network sites go down.

In what was described as a “groundbreaking trial,” Classiq used quantum algorithms to tackle one of the most complex challenges in network design. Specifically, it set out to identify independent paths for networks to remain live when a primary site is taken offline for routine maintenance, and the main backup unexpectedly goes offline too.

In such instances, it becomes extremely challenging to reroute traffic without any disruption to connectivity. Network operators rapidly must identify a unique backup path that’s fast, independent of the original network, resilient to simultaneous link failures, and also optimized for low latency. They’re rarely able to do it quickly enough to prevent downtime.

The problem is that it’s essentially an optimization problem within a large combinatorial search space. In networks that consist of multiple sites and connections, the number of paths between any two points grows exponentially the larger it becomes. Computers are required to check and compare an enormous number of potential routing combinations as networks scale up.

Finding the best performing and most resilient path becomes extremely time-consuming for traditional processors, and this makes them unsuitable for the task, given that network management ideally needs to happen in real time to prevent disruption for end users. As networks grow, the time needed to find the most optimal path exceeds the practical limits of what they’re capable of.

But this is just the kind of challenge that allows quantum algorithms to thrive. They’re uniquely suited for exploring vast combinatorial search spaces because of their ability to perform billions of calculations simultaneously.

Quantum in action

In its trial, Classiq decided to pit its quantum technologies against a high-performance classical computer to see if it’s possible for either one to identify a unique network backup path in real time across multiple scenarios. Classiq’s quantum algorithms were executed on IonQ Inc.’s quantum hardware, and accelerated in simulated environments by AMD’s Instinct GPUs to achieve the computational capacity that should theoretically one day be possible.

The results were clear. Quantum algorithms consistently able to maintain network uptime by finding a suitable path for connectivity in real time, in every scenario explored. By conducting GPU-accelerated simulations, Classiq said its team could iterate fast and validate its algorithms’ behavior, while simultaneously executing runs on the quantum hardware to ensure implementation success.

“This collaboration demonstrates how teams can ideate, model complex optimization problems and then run them quickly and efficiently across different backends, including both GPU-accelerated simulation and quantum hardware, while keeping the work portable as the ecosystem evolves,” said Classiq co-founder and Chief Executive Nir Minerbi.

It was necessary to use simulated environments because, though quantum computers have a great deal of promise, existing hardware has not yet achieved “quantum advantage,” where it exceeds the capabilities of traditional computers. Nonetheless, the industry has a lot of hope that quantum advantage will be achieved soon, with both IBM Corp. and Google LLC promising to do so before the end of the decade. That explains the urgency for Classiq to put its algorithms to the test.

Comcast Chief Network Officer Elas Nafshi said the trials offer proof that quantum software is ideally suited to tackle the most difficult networking challenges. “What our customers want is simple: fast, secure and reliable connectivity, but when you operate a network as large and dynamic as ours, delivering on that promise is complex,” he said. “Our results have shown that quantum computing for network optimization isn’t theoretical, it’s practical, scalable and grounded in the needs of our customers.”

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