Qubit Pharmaceuticals And Sorbonne University Reduce The Number of Qubits Needed to Simulate Molecules

Insider Brief

• Qubit Pharmaceuticals reduced the number of qubits needed to compute the properties of small molecules with its Hyperion-1 emulator, developed in partnership with Sorbonne University.
• The hybrid approach combining high-performance computing and quantum computing makes it possible to calculate the properties of molecules using just 20 qubits, when purely quantum approaches would normally have required more than 250 logic qubits.
• Qubit Pharmaceuticals and Sorbonne Université are announcing that they have been awarded €8 million in funding under the France 2030 national plan for the further development of Hyperion-1.

PRESS RELEASE — Qubit Pharmaceuticals, a deeptech company specializing in the discovery of new drug candidates through molecular simulation and modeling accelerated by hybrid HPC and quantum computing, announces that it has drastically reduced the number of qubits needed to compute the properties of small molecules with its Hyperion-1 emulator¹, developed in partnership with Sorbonne University. This world first raises hopes of a near-term practical application of hybrid HPC – quantum computing to drug discovery.

As a result of these advances, Qubit Pharmaceuticals and Sorbonne Université are announcing that they have been awarded €8 million in funding under the France 2030 national plan for the further development of Hyperion-1.

A world first that saves years in research

By developing new hybrid HPC and quantum algorithms to leverage the computing power of quantum computers in the field of chemistry and drug discovery, Sorbonne Université and Qubit Pharmaceuticals have succeeded, with just 32 logic qubits, in predicting the physico-chemical properties of nitrogen (N2), hydrogen fluoride (HF), lithium hydride and water – molecules that would normally require more than 250 perfect qubits. The Hyperion-1 emulator uses Genci supercomputers, Nvidia’s SuperPod EOS, and one of Scaleway’s many GPU clusters.

With this first proof of concept, the teams have demonstrated that the routine use of quantum computers coupled with high-performance computing platforms for chemistry and drug discovery is much closer than previously thought. Nearly 5 years could be gained, bringing us significantly closer to the era when quantum computers (noisy or perfect) could be used in production within hybrid supercomputers combining HPC, AI and quantum. The use of these new computing powers will improve the precision, speed and carbon footprint of calculations.

Soon to be deployed on today’s noisy machines

To achieve this breakthrough, teams from Qubit Pharmaceuticals and Sorbonne University have developed new algorithms that break down a quantum calculation into its various components, some of which can be calculated precisely on conventional hardware. This strategy enables calculations to be distributed using the best hardware (quantum or classical), while automatically improving the complexity of the algorithms needed to calculate the molecules’ properties.

In this way, all calculations not enhanced by quantum computers are performed on classical GPUs. As the physics used allows the number of qubits required for the calculations, the team, by optimizing the approach to the extreme, has even managed to limit GPU requirements to a single card in some cases. As this hybrid classical/quantum approach is generalist, it can be applied to any type of quantum chemistry calculation, and is not restricted to molecules of pharmaceutical interest, but also to catalysts (chemistry, energy) or materials.

Next steps include deploying these algorithms on existing noisy machines to quantify the impact of noise, and compare performance with recent calculations by IBM and Google, and predicting the properties of molecules of pharmaceutical interest. To achieve this, the teams will deploy new software acceleration methods to reach regimes that would require more than 400 qubits with purely quantum approaches. In the short term, this hybrid approach will reduce the need for physical qubits on quantum machines.

Robert Marino, CEO of Qubit Pharmaceuticals, declares: “At the end of 2023, we announced quantum chemistry calculations using 40 qubits. A few months later, we’ve managed to solve equations that would require 250 logic qubits. An extremely rapid development that confirms the near-term potential of hybrid HPC and quantum algorithms in the service of drug discovery.”

Jean-Philip Piquemal, Professor at Sorbonne University and Director of the Theoretical Chemistry Laboratory (Sorbonne University/CNRS), co-founder and Chief Scientific Officer of Qubit Pharmaceuticals, states: “This work clearly demonstrates the need to progress simultaneously on hardware and software development. It is by making breakthroughs on both fronts that we will be able to enter the era of quantum utility for drug discovery in the very short term.”

Élisabeth Angel-Perez, Vice-President Research and Innovation at Sorbonne Université: “These innovative approaches developed by Qubit Pharmaceuticals are an illustration of Sorbonne Université’s commitment to serving society. The precision and power of quantum computers offer major performance gains. With Qubit Pharmaceuticals, we measure the enormous potential of theoretical computing for quantum chemistry.”

Sébastien Luttringer, Head of R&D at Scaleway : “We are proud to have participated in Qubit Pharmaceuticals’ major algorithmic breakthrough with the support of our GPU computing power, the largest in the European cloud. Quantum computing is not just a hardware challenge, it’s also a software one that we need to develop in order to solve real-world problems. Scaleway’s pragmatic strategy, with the introduction of its QaaS (Quantum as a Service) service, is to simplify access to the best resources to help this algorithm of tomorrow emerge.”