Workshop Description
For exploration geologists and mining data science teams. Covers VQE for crystalline mineral simulation (iron oxides, copper sulphides, lithium pegmatites), quantum-enhanced seismic and gravity inversion, and QML for drill core image analysis. Includes honest NISQ assessments against DFT and classical geophysical methods.
Mineral exploration has two computational bottlenecks where quantum simulation is being investigated. First, electronic structure calculation for crystalline materials. Understanding the electronic properties of ore minerals (bonding behaviour, phase stability, solubility) requires solving the Schrodinger equation for systems with strongly correlated electrons. Density functional theory handles most cases, but breaks down for transition metal oxides and rare earth compounds where electron correlation is strong. The Variational Quantum Eigensolver (VQE) can in principle simulate these systems more accurately, though current NISQ devices limit calculations to 10-30 qubits (small molecular clusters, not full mineral unit cells). Second, geophysical data processing. Seismic tomography, gravity inversion, and magnetic survey interpretation involve large linear systems where quantum linear algebra (the HHL algorithm) offers theoretical speedup. Classical iterative solvers handle production-scale surveys today, but the processing time for high-resolution 3D models motivates quantum research. This workshop runs VQE calculations for a reference mineral compound, compares results against DFT and experimental data, and maps the qubit requirements for production-relevant mineral simulations. Mining companies including BHP, Rio Tinto, and Vale are structuring quantum simulation pilot programmes. The workshop assesses which exploration problems will benefit first as hardware scales.
What participants cover
- VQE for ore characterisation: simulating electronic structure of iron oxides, copper sulphides, and lithium pegmatites on NISQ hardware (10-30 qubits)
- Classical comparison: where DFT (B3LYP, PBE functionals) handles mineral chemistry and where strongly correlated systems require quantum approaches
- Quantum-enhanced seismic inversion: HHL algorithm potential for large-scale tomography matrices versus classical iterative solvers
- QML for drill core analysis: parameterised quantum circuits for mineral identification in core photographs and hyperspectral logging data
- Geological modelling integration: connecting quantum processing outputs to Leapfrog, Datamine, and Vulcan workflows
- Research partnerships: how BHP, Rio Tinto, and Vale are structuring quantum simulation pilot programmes with hardware providers