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Creating superpositions that correspond to efficiently integrable probability distributions
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We give a simple and efficient process for generating a quantum superposition of states which form a discrete approximation of any efficiently integrable (such as log concave) probability density functions.
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Cited by 35 Pith papers
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Spectral Gaps with Quantum Counting Queries and Oblivious State Preparation
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A simpler Gaussian state-preparation
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Domain-Aware Probability Sampling for Hybrid Quantum Systems using Bayesian Optimization
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Quantum Algorithm for Estimating Intrinsic Geometry
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Minimizing entanglement entropy for enhanced quantum state preparation
A two-step method minimizes entanglement entropy of target states before using matrix product state representations to achieve high-accuracy quantum state preparation on NISQ devices.
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Linearization Scheme of Shallow Water Equations for Quantum Algorithms
A Carleman linearization maps 1D shallow water equations to a linear system for quantum solvers, but validation is limited to small-amplitude test cases and the speedup remains conditional.
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New Quantum Algorithm for Principal Component Analysis
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Quantum iterative approach to the Traveling Salesman Problem
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Quantum Walks-Based Adaptive Distribution Generation with Efficient CUDA-Q Acceleration
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A Rigorous and Self--Contained Proof of the Grover--Rudolph State Preparation Algorithm
The Grover–Rudolph correctness proof is formally redone, but the claimed error bound and bit/shots rule are only in the abstract, and the Gray-code ladder proof has a false step.
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