Dimension Reduction for Quantum Adaptive Agents

• URL: http://arxiv.org/abs/2607.19156v1
• Date: Tue, 21 Jul 2026 14:54:55 GMT
• Title: Dimension Reduction for Quantum Adaptive Agents
• Abstract summary: We introduce a route-truncate-repair procedure that converts entropic quantum memory advantages into reductions in memory dimension.<n>A fidelity-divergence certificate quantifies the resulting trade-off between accuracy and memory dimension.<n>Results establish a route from entropic memory advantages to practical, dimension-reduced adaptive quantum agents.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Adaptive agents realise complex reactive behaviours by using a memory of past input stimuli and output actions to guide structured future responses. Quantum adaptive agents can operate while storing less information in memory than optimal classical counterparts; yet, this does not necessarily translate into a reduced dimension of the memory that must be physically realised. We introduce a route-truncate-repair procedure that converts entropic quantum memory advantages into reductions in memory dimension. Routing a reference input process through an agent yields a temporal matrix product state representation whose canonical bond is identified with the agent's memory. Truncating this bond and locally repairing the resulting dynamics produces a smaller, physically-valid agent that remains capable of responding to arbitrary input sequences. A fidelity-divergence certificate quantifies the resulting trade-off between accuracy and memory dimension. Benchmark adaptive processes exhibit substantial dimension reduction whilst preserving the underlying behaviour with high fidelity. These results establish a route from entropic memory advantages to practical, dimension-reduced adaptive quantum agents.

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