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A simple two-qubit reservoir is constructed that performs temporal recall exactly, while every fixed-window predictor faces the same positive worst-case error over unbounded delays, regardless of model capacity.
This work analyzes the effect of encoding discontinuities on diversity-driven discovery and introduces two representation refinements: a smooth, continuous mechanism for gate selection and a factorized representation that separates structural discovery from continuous parameter optimization.
In the Quantum Approximate Optimization Algorithm (QAOA), the entanglement topology, where qubit pairs are connected by two-qubit gates, is conventionally set equal to the edge set of the problem graph. This coupling ties circuit design to explicit problem knowledge and may not yield the most trainable circuit under li...
We propose a compact NISQ-compatible quantum transformer architecture for synthetic QNLP sequence modelling. The model preserves the autoregressive next-token interface of a classical transformer, but replaces attention and feed-forward sublayers with variational quantum encoder blocks, connector circuits, decoder bloc...
The natural-language-based genetic algorithm (NaLaGA) shows that a generic, problem-independent genetic algorithm (GA) can function by utilizing large language models (LLMs) for all interactions with the solution candidates without ever running any LLM-generated code. We analyze inherent biases in the function of a NaL...
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