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This project investigates whether real-world lottery draws deviate from ideal uniform randomness due to physical implementation effects such as ball weight, wear, machine mechanics…
Fourier transformation remains a core primitive in scientific computing, signal processing, and ML systems, but practical performance and accuracy depend heavily on algorithm and h…
Assess whether quantum reservoirs (with PCA‑encoded inputs) can outperform classical ones and how entanglement changes feature mapping.
Robust dynamic operating envelopes (RDOEs) solve the problem of secure allocation of latent network capacity to flexible distributed energy resources (DER) in unbalanced distributi…
Quantum reservoir computing for image classification is currently constrained by a reproducibility problem: many reported improvements can be explained by uneven preprocessing, rea…
Quantum reservoir computing (QRC) is often evaluated with heterogeneous comparator strength, making it difficult to determine whether reported gains are genuinely quantum-mechanist…
Quantum reservoir computing has recently reported encouraging image-classification performance, yet many claims remain sensitive to fairness controls, measurement-policy confounds,…
Quantum reservoir computing is frequently evaluated with point-estimate accuracy gains that confound representation effects, readout parity, and computational cost. We present a hy…
