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Tailoring Term Truncations for Electronic Structure Calculations Using a Linear Combination of Unitaries
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A highly anticipated use of quantum computers is the simulation of complex quantum systems including molecules and other many-body systems. One promising method involves directly applying a linear combination of unitaries (LCU) to approximate a Taylor series by truncating after some order. Here we present an adaptation of that method, optimized for Hamiltonians with terms of widely varying magnitude, as is commonly the case in electronic structure calculations. We show that it is more efficient to apply LCU using a truncation that retains larger magnitude terms as determined by an iterative procedure. We obtain bounds on the simulation error for this generalized truncated Taylor method, and for a range of molecular simulations, we report these bounds as well as exact numerical results. We find that our adaptive method can typically improve the simulation accuracy by an order of magnitude, for a given circuit depth.
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Cited by 1 Pith paper
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Fixing Divergence in Carleman Linearization via Analytical Continuation
A Möbius conformal map and regularized incomplete beta function fix the long-time divergence of Carleman linearization for logistic, KPP-Fisher, and phase-field equations.
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