Causal Architecture in Hidden Quantum Markov Models

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Hauptverfasser: Souissi, Abdessatar, Barhoumi, Abdessatar
Format: Preprint
Veröffentlicht: 2026
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author Souissi, Abdessatar
Barhoumi, Abdessatar
author_facet Souissi, Abdessatar
Barhoumi, Abdessatar
contents We introduce a class of causal hidden quantum Markov models (cHQMMs) that reverse the usual order of hidden updates and emissions compared to conventional HQMMs. Using a simple qubit model with a rotating hidden state and sharp measurements, we show that these two architectures-emission then transition versus transition then emission-generally produce different quantum processes. They can be distinguished by measurements at arbitrarily late times, no matter how the hidden system is initialized, and even when the two models start from different initial states. This means that the two orders of operations lead to genuinely different observable behaviors that cannot be reconciled by waiting longer or by choosing special initial conditions. At the same time, we prove that the two architectures become equivalent when they arise from entangled liftings of classical hidden Markov models, sharing the same classical statistics. This identifies a clear dividing line between classical and genuinely quantum hidden memory. Our findings highlight causal HQMMs as a useful tool for studying and distinguishing quantum memory effects in sequential processes.
format Preprint
id arxiv_https___arxiv_org_abs_2602_19120
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Causal Architecture in Hidden Quantum Markov Models
Souissi, Abdessatar
Barhoumi, Abdessatar
Mathematical Physics
We introduce a class of causal hidden quantum Markov models (cHQMMs) that reverse the usual order of hidden updates and emissions compared to conventional HQMMs. Using a simple qubit model with a rotating hidden state and sharp measurements, we show that these two architectures-emission then transition versus transition then emission-generally produce different quantum processes. They can be distinguished by measurements at arbitrarily late times, no matter how the hidden system is initialized, and even when the two models start from different initial states. This means that the two orders of operations lead to genuinely different observable behaviors that cannot be reconciled by waiting longer or by choosing special initial conditions. At the same time, we prove that the two architectures become equivalent when they arise from entangled liftings of classical hidden Markov models, sharing the same classical statistics. This identifies a clear dividing line between classical and genuinely quantum hidden memory. Our findings highlight causal HQMMs as a useful tool for studying and distinguishing quantum memory effects in sequential processes.
title Causal Architecture in Hidden Quantum Markov Models
topic Mathematical Physics
url https://arxiv.org/abs/2602.19120