Dissipation Alters Modes of Information Encoding in Small Quantum Reservoirs near Criticality
Quantum reservoir computing (QRC) has emerged as a promising paradigm for harnessing near-term quantum devices to tackle temporal machine learning tasks. Yet, identifying the mechanisms that underlie enhanced performance remains challenging, particularly in many-body open systems where nonlinear int...
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MDPI AG
2025-01-01
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| Online Access: | https://www.mdpi.com/1099-4300/27/1/88 |
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| author | Krai Cheamsawat Thiparat Chotibut |
| author_facet | Krai Cheamsawat Thiparat Chotibut |
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| description | Quantum reservoir computing (QRC) has emerged as a promising paradigm for harnessing near-term quantum devices to tackle temporal machine learning tasks. Yet, identifying the mechanisms that underlie enhanced performance remains challenging, particularly in many-body open systems where nonlinear interactions and dissipation intertwine in complex ways. Here, we investigate a minimal model of a driven-dissipative quantum reservoir described by two coupled Kerr-nonlinear oscillators, an experimentally realizable platform that features controllable coupling, intrinsic nonlinearity, and tunable photon loss. Using Partial Information Decomposition (PID), we examine how different dynamical regimes encode input drive signals in terms of <i>redundancy</i> (information shared by each oscillator) and <i>synergy</i> (information accessible only through their joint observation). Our key results show that, near a critical point marking a dynamical bifurcation, the system transitions from predominantly redundant to synergistic encoding. We further demonstrate that synergy amplifies short-term responsiveness, thereby enhancing immediate memory retention, whereas strong dissipation leads to more redundant encoding that supports long-term memory retention. These findings elucidate how the interplay of instability and dissipation shapes information processing in small quantum systems, providing a fine-grained, information-theoretic perspective for analyzing and designing QRC platforms. |
| format | Article |
| id | doaj-art-09f63d91c175427a9d75a50ba27f7ca7 |
| institution | Kabale University |
| issn | 1099-4300 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
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| series | Entropy |
| spelling | doaj-art-09f63d91c175427a9d75a50ba27f7ca72025-01-24T13:31:58ZengMDPI AGEntropy1099-43002025-01-012718810.3390/e27010088Dissipation Alters Modes of Information Encoding in Small Quantum Reservoirs near CriticalityKrai Cheamsawat0Thiparat Chotibut1Chula Intelligent and Complex Systems Lab, Department of Physics, Faculty of Science, Chulalongkorn University, Bangkok 10330, ThailandChula Intelligent and Complex Systems Lab, Department of Physics, Faculty of Science, Chulalongkorn University, Bangkok 10330, ThailandQuantum reservoir computing (QRC) has emerged as a promising paradigm for harnessing near-term quantum devices to tackle temporal machine learning tasks. Yet, identifying the mechanisms that underlie enhanced performance remains challenging, particularly in many-body open systems where nonlinear interactions and dissipation intertwine in complex ways. Here, we investigate a minimal model of a driven-dissipative quantum reservoir described by two coupled Kerr-nonlinear oscillators, an experimentally realizable platform that features controllable coupling, intrinsic nonlinearity, and tunable photon loss. Using Partial Information Decomposition (PID), we examine how different dynamical regimes encode input drive signals in terms of <i>redundancy</i> (information shared by each oscillator) and <i>synergy</i> (information accessible only through their joint observation). Our key results show that, near a critical point marking a dynamical bifurcation, the system transitions from predominantly redundant to synergistic encoding. We further demonstrate that synergy amplifies short-term responsiveness, thereby enhancing immediate memory retention, whereas strong dissipation leads to more redundant encoding that supports long-term memory retention. These findings elucidate how the interplay of instability and dissipation shapes information processing in small quantum systems, providing a fine-grained, information-theoretic perspective for analyzing and designing QRC platforms.https://www.mdpi.com/1099-4300/27/1/88quantum reservoirsdriven-dissipative dynamicspartial information decompositiondynamic instabilitymemory capacity |
| spellingShingle | Krai Cheamsawat Thiparat Chotibut Dissipation Alters Modes of Information Encoding in Small Quantum Reservoirs near Criticality Entropy quantum reservoirs driven-dissipative dynamics partial information decomposition dynamic instability memory capacity |
| title | Dissipation Alters Modes of Information Encoding in Small Quantum Reservoirs near Criticality |
| title_full | Dissipation Alters Modes of Information Encoding in Small Quantum Reservoirs near Criticality |
| title_fullStr | Dissipation Alters Modes of Information Encoding in Small Quantum Reservoirs near Criticality |
| title_full_unstemmed | Dissipation Alters Modes of Information Encoding in Small Quantum Reservoirs near Criticality |
| title_short | Dissipation Alters Modes of Information Encoding in Small Quantum Reservoirs near Criticality |
| title_sort | dissipation alters modes of information encoding in small quantum reservoirs near criticality |
| topic | quantum reservoirs driven-dissipative dynamics partial information decomposition dynamic instability memory capacity |
| url | https://www.mdpi.com/1099-4300/27/1/88 |
| work_keys_str_mv | AT kraicheamsawat dissipationaltersmodesofinformationencodinginsmallquantumreservoirsnearcriticality AT thiparatchotibut dissipationaltersmodesofinformationencodinginsmallquantumreservoirsnearcriticality |