Which cloud provider offers the most stable Quantum Computing as a Service (QCaaS)?
My company wants to start experimenting with quantum algorithms for supply chain optimization. We are already an AWS shop, but I see IBM and Google have their own dedicated hardware. Does Braket offer enough abstraction to hide the hardware differences, or should we go directly to the hardware provider's native cloud for better fidelity and lower gate-error rates?
2024-02-22 in Cloud Technology by Robert Lawson
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All answers to this question.
If you are already on AWS, Braket is the most logical choice for "experimentation" because it gives you access to multiple hardware types (Rigetti, IonQ, OQC) through a single API. However, if you need the highest number of qubits and the most advanced error suppression, IBM's dedicated cloud is often superior because they own the full stack from the dilution refrigerator up to the software. IBM’s "Eagle" and "Osprey" processors are generally more accessible to researchers through their specific portal than through third-party aggregators.
Answered 2024-02-23 by Melissa Grant
What kind of "noise" levels can your algorithm tolerate? Some providers have much better coherence times than others depending on if they use superconducting or trapped-ion qubits.
Answered 2024-02-24 by Daniel Murphy
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Daniel, our optimization model is quite sensitive to gate errors, so trapped-ion (IonQ) seems better for fidelity, even if it's slower. We’ve been using simulators for now, but we need to run on real hardware soon to see if the "Barren Plateau" problem ruins our gradients. I’ll check if Braket’s pricing for IonQ is sustainable for a long-term pilot.
Commented 2024-02-25 by Robert Lawson
Azure Quantum is also a strong contender. They have a great "Quantum Intermediate Representation" (QIR) that makes your code more portable across different hardware types.
Answered 2024-02-26 by Nancy Reid
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Portability is key, Nancy! Using an agnostic layer like QIR ensures we aren't locked into one vendor if a breakthrough happens on a different hardware architecture.
Commented 2024-02-27 by Melissa Grant
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