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Learn quantum simulation techniques for chemistry, materials, and high energy physics through this comprehensive conference talk from QDC 2025. Explore the sample-based quantum diagonalization (SQD) algorithm with Mario Motta, who demonstrates how quantum processors can sample important electronic configurations while classical solvers approximate ground states, showcasing recent improvements that bridge the gap to high-accuracy classical methods through partner results on binding energies, reaction pathways, and spin models. Follow along with Kevin Sung's hands-on tutorial using open source Qiskit add-ons to build molecular Hamiltonians, construct and optimize LUCJ ansatz circuits for SQD implementation, and execute the diagonalize_fermionic_hamiltonian routine. Discover AQC Tensor, an innovative approach that leverages tensor networks to compress deep trotterized time evolution circuits into significantly shallower approximate circuits, effectively reducing circuit depth and noise while maintaining high fidelity on current quantum hardware platforms.
