Trotter error cancellation in nanographene simulations reduces circuit depth by about 10x for quantum phase estimation of energy gaps to chemical accuracy in the Pariser-Parr-Pople model.
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Element-Weighted KANs achieve state-of-the-art accuracy on formation energy, band gap, and work function while revealing periodic-table-aligned chemical trends through their learnable activation functions.
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Quantum simulation of nanographenes and Trotter error cancellation
Trotter error cancellation in nanographene simulations reduces circuit depth by about 10x for quantum phase estimation of energy gaps to chemical accuracy in the Pariser-Parr-Pople model.
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Interpretation of Crystal Energy Landscapes with Kolmogorov-Arnold Networks
Element-Weighted KANs achieve state-of-the-art accuracy on formation energy, band gap, and work function while revealing periodic-table-aligned chemical trends through their learnable activation functions.