Alice & Bob’s Post

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Out of the many challenges scientists face on the way to creating a Fault-Tolerant Quantum Computer, one thing just got easier. 🥳 The resource estimation. 🤔 What is it? Simply put, the resource estimator is like a crystal ball 🔮 for quantum algorithms. It helps us predict how many physical qubits and how much time we'll need to run complex quantum programs, given a target architecture. 🚀 Enhanced flexibility Up until recently, performing resource estimations on cat qubits had to be done by hand. This is how we showed that cat qubits may run Shor's algorithm using 200x fewer qubits. But because not everyone can dedicate a couple of months of a brilliant scientist's time to compute what their savings might be, we thought it was time to automate things a bit. Microsoft's Azure Quantum Resource Estimator was already working for the most common architectures, based on well-studied but resource-hungry surface codes. We collaborated with their team to help develop the API that supports Alice & Bob’s cat qubits. This means that in the months long process of developing a quantum algorithm, the resource estimation part now only takes seconds instead of days. Talk about a time saver! ⏱️ ⚙️ How does it work? The Azure Quantum Resource Estimator crunches numbers based on inputs like Q# code, or logical qubit and gate counts, and outputs optimal working parameters and necessary resources. For a more detailed explanation, take a look at our drawing below (don’t worry, we haven’t switched to chemistry… yet). 📚 Want to know more? Check out this blog post written by Mathias Soeken from Microsoft and Élie Gouzien from Alice & Bob: 🔗 https://lnkd.in/efJwWm-D Plus, you can even test it out yourself — it's open source, after all! 🔗 https://lnkd.in/ezycfkC9 #QuantumComputing #ResourceEstimator

  • Alice & Bob's cat qubit on Microsoft's Azure Quantum Resource Estimator
David Ryan

Open source and Quantum Computing at OSRG. Product Manager skilled in Deep Tech.

1mo

I got excited for a minute, mostly being familiar with Azure’s, and hoping this was a new approach. But wonderful to see the collab and new perspectives all the same. Nice work. This feels especially timely as we nudge closer to the utility era, where teams (ahem) are already being asked to scope out in big picture terms what potential projects might look like in units of cost and time. Any guidance and progress in this area is fantastic.

Many thanks to all involved in the project. Adding to the ones mentionned in the post, shout out to Fabrice Frachon who got us started on this road. Fabrice, thanks to you we are one step closer to add cat qubits on the famous paper by Krysta Svore et al.!

Rima Oulhaj

PhD student | Pépite Provence | looking for postdoc position starting december 2024

1mo

Love the visuals 🤩

Gregory Shutko

Chief Development Officer @ QCentroid | Tech & Innovation Strategy and Partnerships Advisor

1mo

Looks like a very useful thing! Thank you for sharing

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