Quantum memristor
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A quantum memristor is a nanoscale device that exhibits memristive behavior governed by quantum mechanics. First theorized in 2016,[1] it represents the quantum analogue of the classical memristor (memory resistor) proposed by Leon Chua in 1971. Unlike classical memristors whose resistance depends on the history of classical charge flow, quantum memristors exhibit non-Markovian dynamics where resistance emerges from quantum state evolution, enabling applications in quantum neuromorphic computing and quantum memory.[2]
Several types of quantum memristor have been proposed.[3][4][5] It has been proposed that photonic quantum memristors can be used for nonlinear quantum computing.[6]
History
The development of memristors traces back to the theoretical concept proposed by Leon Chua in 1971, who identified the memristor as the fourth fundamental passive circuit element, alongside resistors, capacitors, and inductors [7]. This concept was built on the premise that a memristor's resistance is not only dependent on its current state but also on its past input history, effectively giving it a memory function, hence the name "memory resistor”.[7]
In recent years, there has been significant progress in the field of memristors, particularly with the advent of quantum memristors. These devices are designed to replicate the memristive behaviors of classical memristors while integrating quantum mechanical principles, offering enhanced functionalities and applications.[8] The evolution of memristors has led to the classification of different types, including resistive random-access memories (ReRAM) and analog memristors that emulate the tunable weights of biological synapses, thus paving the way for advanced neuromorphic computing systems. Research on quantum memristors has accelerated, with various studies exploring their operational principles and potential applications in superconducting quantum computers and other sophisticated computing architectures.[9][10] The exploration of quantum memristors is seen as a vital advancement in the quest for more efficient memory and computation systems, highlighting their prospective role in the future of computing technology.
See also
References
- ↑ Pfeiffer, P.; Egusquiza, I. L.; Di Ventra, M.; Sanz, M.; Solano, E. (6 July 2016). "Quantum memristors". Scientific Reports. 6 (1). arXiv:1511.02192. Bibcode:2016NatSR...629507P. doi:10.1038/srep29507. PMC 4933948. PMID 27381511. Unknown parameter
|article-number=ignored (help) - ↑ Salmilehto, J.; Deppe, F.; Di Ventra, M.; Sanz, M.; Solano, E. (14 February 2017). "Quantum Memristors with Superconducting Circuits". Scientific Reports. 7 (1). arXiv:1603.04487. Bibcode:2017NatSR...742044S. doi:10.1038/srep42044. PMC 5307327. PMID 28195193. Unknown parameter
|article-number=ignored (help) - ↑ Norambuena, Ariel; Torres, Felipe; Di Ventra, Massimiliano; Coto, Raúl (22 February 2022). "Polariton-Based Quantum Memristors". Physical Review Applied. 17 (2). arXiv:2108.09382. Bibcode:2022PhRvP..17b4056N. doi:10.1103/PhysRevApplied.17.024056. Unknown parameter
|article-number=ignored (help) - ↑ Spagnolo, Michele; Morris, Joshua; Piacentini, Simone; Antesberger, Michael; Massa, Francesco; Crespi, Andrea; Ceccarelli, Francesco; Osellame, Roberto; Walther, Philip (April 2022). "Experimental photonic quantum memristor". Nature Photonics. 16 (4): 318–323. arXiv:2105.04867. Bibcode:2022NaPho..16..318S. doi:10.1038/s41566-022-00973-5.
- ↑ Stremoukhov, Sergey; Forsh, Pavel; Khabarova, Ksenia; Kolachevsky, Nikolay (28 July 2023). "Proposal for Trapped-Ion Quantum Memristor". Entropy. 25 (8): 1134. Bibcode:2023Entrp..25.1134S. doi:10.3390/e25081134. PMC 10453901 Check
|pmc=value (help). PMID 37628163 Check|pmid=value (help). - ↑ Ferrara, Alberto; Lo Franco, Rosario (13 January 2025). "Entanglement and coherence dynamics in photonic quantum memristors". Physical Review A. 111 (1). arXiv:2409.08979. Bibcode:2025PhRvA.111a2421F. doi:10.1103/PhysRevA.111.012421. Unknown parameter
|article-number=ignored (help) - ↑ 7.0 7.1 "Quantum Memristor". QUBO Technology (in Deutsch). Retrieved 2025-08-21.
- ↑ Hernani-Morales, Carlos; Alvarado, Gabriel; Albarrán-Arriagada, Francisco; Vives-Gilabert, Yolanda; Solano, Enrique; Martín-Guerrero, José D. (2024). "Machine Learning for Maximizing the Memristivity of Single and Coupled Quantum Memristors". Advanced Quantum Technologies. n/a (n/a). doi:10.1002/qute.202300294. ISSN 2511-9044. Unknown parameter
|article-number=ignored (help) - ↑ Spagnolo, Michele; Morris, Joshua; Piacentini, Simone; Antesberger, Michael; Massa, Francesco; Crespi, Andrea; Ceccarelli, Francesco; Osellame, Roberto; Walther, Philip (April 2022). "Experimental photonic quantum memristor". Nature Photonics. 16 (4): 318–323. arXiv:2105.04867. Bibcode:2022NaPho..16..318S. doi:10.1038/s41566-022-00973-5. ISSN 1749-4893.
- ↑ Guo, Y.-M.; Albarrán-Arriagada, F.; Alaeian, H.; Solano, E.; Barrios, G. Alvarado (2022-08-31). "Quantum Memristors with Quantum Computers". Physical Review Applied. 18 (2): 024082. arXiv:2112.14660. Bibcode:2022PhRvP..18b4082G. doi:10.1103/PhysRevApplied.18.024082.
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