Phasecraft's 3,000-Emulation VQE Molecular Dataset With NVIDIA Was Computed on GPUs Under Wellcome Leap's Q4Bio: What the 14 September 2026 Announcement Shows

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Phasecraft and NVIDIA announced on 14 September 2026 what Phasecraft calls the largest known database of Variational Quantum Eigensolver results for molecules, more than 3,000 emulations across thirteen molecular systems, computed on NVIDIA Hopper GPUs at the University of Nottingham. No quantum computer ran any of it, and the announcement says so in its own description of the method.

The dataset is an emulated VQE molecular dataset: for each of the 13 molecular systems, a classical GPU cluster worked out what a quantum processor of 4 to 32 qubits would return when asked for the lowest-energy state of the molecule, with most of the circuits in the 24-to-28-qubit range. Its purpose is to train Phasecraft's quantum-enhanced density functional theory method, a way of improving the standard workhorse of computational chemistry with data a quantum computer would produce. The Wellcome Leap Q4Bio program that paid for it asks whether new algorithms can deliver quantum advantage for health, and its prizes require a demonstration on a real quantum computer with more than 50 qubits. For a hospital buyer or a clinical pharmacologist the announcement describes training data for a chemistry method, produced on conventional hardware, with no named molecular systems, quantitative accuracy benchmarks or clinical results disclosed.

The Phasecraft release, datelined London and Toronto, gives four numbers: over 3,000 unique emulations, 13 molecular systems, a qubit range of 4 to 32 with "the vast majority in the 24–28 qubit regime", and "a 15x simulation speedup over prior results when modeling physical, many-body systems integral to biology and health applications". The GPUs were NVIDIA Hopper hardware hosted at the University of Nottingham, driven through NVIDIA's cuQuantum software kit. Ashley Montanaro, Phasecraft's co-founder and chief executive, is quoted on the need "to push the limits of today's most capable hardware, both conventional and quantum"; Sam Stanwyck, NVIDIA's director of quantum product, on shortening "the timeline" to useful quantum computing. The release describes the dataset as "a training foundation for quantum-enhanced molecular modeling, which could accelerate drug discovery at a scale previously out of reach, as quantum hardware develops". The conditional clause at the end carries the weight of the sentence.