Quantum error correction via quantum convolutional neural networks
ilustraciones, diagramas
- Autores:
-
Falla León, José Luis
- Tipo de recurso:
- Fecha de publicación:
- 2024
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/86209
- Palabra clave:
- 530 - Física::539 - Física moderna
Quantum error correction
Quantum convolutional neural network
Quantum computing
Quantum algorithms
Corrección de error cuántico
Redes neuronales convolucionales cuánticas
Computación cuántica
Algoritmos cuánticos
redes neuronales convolucionales
corrección de errores cuántica
quantum algorithm
convolutional neural network
quantum error correction
algoritmo cuántico
- Rights
- openAccess
- License
- Reconocimiento 4.0 Internacional
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Quantum error correction via quantum convolutional neural networks |
| dc.title.translated.spa.fl_str_mv |
Corrección de error cuántico mediante redes neuronales convolucionales cuánticas |
| title |
Quantum error correction via quantum convolutional neural networks |
| spellingShingle |
Quantum error correction via quantum convolutional neural networks 530 - Física::539 - Física moderna Quantum error correction Quantum convolutional neural network Quantum computing Quantum algorithms Corrección de error cuántico Redes neuronales convolucionales cuánticas Computación cuántica Algoritmos cuánticos redes neuronales convolucionales corrección de errores cuántica quantum algorithm convolutional neural network quantum error correction algoritmo cuántico |
| title_short |
Quantum error correction via quantum convolutional neural networks |
| title_full |
Quantum error correction via quantum convolutional neural networks |
| title_fullStr |
Quantum error correction via quantum convolutional neural networks |
| title_full_unstemmed |
Quantum error correction via quantum convolutional neural networks |
| title_sort |
Quantum error correction via quantum convolutional neural networks |
| dc.creator.fl_str_mv |
Falla León, José Luis |
| dc.contributor.advisor.spa.fl_str_mv |
Viviescas Ramírez, Carlos Leonardo |
| dc.contributor.author.spa.fl_str_mv |
Falla León, José Luis |
| dc.contributor.researchgroup.spa.fl_str_mv |
Caos y Complejidad |
| dc.contributor.orcid.spa.fl_str_mv |
Falla, Jose [0000-0001-9918-2198] |
| dc.subject.ddc.spa.fl_str_mv |
530 - Física::539 - Física moderna |
| topic |
530 - Física::539 - Física moderna Quantum error correction Quantum convolutional neural network Quantum computing Quantum algorithms Corrección de error cuántico Redes neuronales convolucionales cuánticas Computación cuántica Algoritmos cuánticos redes neuronales convolucionales corrección de errores cuántica quantum algorithm convolutional neural network quantum error correction algoritmo cuántico |
| dc.subject.proposal.eng.fl_str_mv |
Quantum error correction Quantum convolutional neural network Quantum computing Quantum algorithms |
| dc.subject.proposal.spa.fl_str_mv |
Corrección de error cuántico Redes neuronales convolucionales cuánticas Computación cuántica Algoritmos cuánticos |
| dc.subject.wikidata.spa.fl_str_mv |
redes neuronales convolucionales corrección de errores cuántica quantum algorithm |
| dc.subject.wikidata.eng.fl_str_mv |
convolutional neural network quantum error correction algoritmo cuántico |
| description |
ilustraciones, diagramas |
| publishDate |
2024 |
| dc.date.accessioned.none.fl_str_mv |
2024-06-05T20:53:10Z |
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2024-06-05T20:53:10Z |
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2024-04-05 |
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Trabajo de grado - Maestría |
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info:eu-repo/semantics/masterThesis |
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info:eu-repo/semantics/acceptedVersion |
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Text |
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Universidad Nacional de Colombia |
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Repositorio Institucional Universidad Nacional de Colombia |
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https://repositorio.unal.edu.co/ |
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Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia |
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eng |
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eng |
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John Preskill. Quantum Computing in the NISQ era and beyond. Quantum, 2:79, August 2018. arXiv: 1801.00862. Jacob Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, and Seth Lloyd. Quantum machine learning. Nature, 549(7671):195{202, September 2017. Arute, et al. Quantum supremacy using a programmable superconducting processor. Nature, 574(7779):505-510, October 2019. Xiao Liang, Sheng Liu, Yan Li, and Yong-Sheng Zhang. Generation of Bose-Einstein Condensates' Ground State Through Machine Learning. arXiv:1712.10093 [quant-ph], December 2017. G. Vidal. Class of Quantum Many-Body States That Can Be Efficiently Simulated. Physical Review Letters, 101(11):110501, September 2008. Nobuyuki Yoshioka and Ryusuke Hamazaki. Constructing neural stationary states for open quantum many-body systems. Physical Review B, 99(21):214306, June 2019. Iris Cong, Soonwon Choi, and Mikhail D. Lukin. Quantum convolutional neural networks. Nature Physics, 15(12):1273-1278, December 2019. Raymond Laflamme, Cesar Miquel, Juan Pablo Paz, and Wojciech Hubert Zurek. Perfect Quantum Error Correcting Code. Physical Review Letters, 77(1):198-201, July 1996. Peter W. Shor. Scheme for reducing decoherence in quantum computer memory. Physical Review A, 52(4):R2493-R2496, October 1995. A. M. Steane. Error Correcting Codes in Quantum Theory. Physical Review Letters, 77(5):793-797, July 1996. A. R. Calderbank and Peter W. Shor. Good quantum error-correcting codes exist. Physical Review A, 54(2):1098-1105, August 1996. M. D. Reed, L. DiCarlo, S. E. Nigg, L. Sun, L. Frunzio, S. M. Girvin, and R. J. Schoelkopf. Realization of three-qubit quantum error correction with superconducting circuits. Nature, 482(7385):382-385, February 2012. P. Schindler, J. T. Barreiro, T. Monz, V. Nebendahl, D. Nigg, M. Chwalla, M. Hennrich, and R. Blatt. Experimental Repetitive Quantum Error Correction. Science, 332(6033):1059-1061, May 2011. Charles D. Hill, Eldad Peretz, Samuel J. Hile, Matthew G. House, Martin Fuechsle, Sven Rogge, Michelle Y. Simmons, and Lloyd C. L. Hollenberg. A surface code quantum computer in silicon. Science Advances, 1(9):e1500707, October 2015. Wright, et al. Benchmarking an 11-qubit quantum computer. Nature Communications, 10(1):5464, November 2019. Kosuke Fukui, Akihisa Tomita, and Atsushi Okamoto. Tracking quantum error correction. Physical Review A, 98(2):022326, August 2018. Kjaergaard et al. Superconducting Qubits: Current State of Play. arXiv:1905.13641, May 2019. Bharti et al. Noisy intermediate-scale quantum (NISQ) algorithms. Reviews of Modern Physics, 94(1):015004, February 2022. arXiv:2101.08448 [cond-mat, physics:quant-ph]. F. Vatan, V. P. Roychowdhury, and M. P. Anantram. Spatially Correlated Qubit Errors and Burst-Correcting Quantum Codes. arXiv:quant-ph/9704019, April 1997. Chi-Kwong Li, Mikio Nakahara, Yiu-Tung Poon, Nung-Sing Sze, and Hiroyuki Tomita. Efficient Quantum Error Correction for Fully Correlated Noise. Physics Letters A, 375(37):3255-3258, August 2011. Emanuel Knill, Raymond Laflamme, and Lorenza Viola. Theory of Quantum Error Correction for General Noise. arXiv:quant-ph/9908066, August 1999. M. Cerezo, Andrew Arrasmith, Ryan Babbush, Simon C. Benjamin, Suguru Endo, Keisuke Fujii, Jarrod R. McClean, Kosuke Mitarai, Xiao Yuan, Lukasz Cincio, and Patrick J. Coles. Variational quantum algorithms. Nature Reviews Physics, 3(9):625{644, August 2021. Michael A. Nielsen and Isaac L. Chuang. Quantum Computation and Quantum Information. Cambridge University Press, 2000. Ramamurti Shankar. Principles of quantum mechanics. Plenum, New York, NY, 1980. Simon J. Devitt, Kae Nemoto, and William J. Munro. Quantum Error Correction for Beginners. Reports on Progress in Physics, 76(7):076001, July 2013. T. Brun, I. Devetak, and M.-H. Hsieh. Correcting Quantum Errors with Entanglement. Science, 314(5798):436{439, October 2006. P.G. Kwiat and D.F.V. James. Quantum optics -- entanglement and quantum information. In Robert D. Guenther, editor, Encyclopedia of Modern Optics, pages 256-264. Elsevier, Oxford, 2005. J. Chiaverini, D. Leibfried, T. Schaetz, M. D. Barrett, R. B. Blakestad, J. Britton, W. M. Itano, J. D. Jost, E. Knill, C. Langer, R. Ozeri, and D. J. Wineland. Realization of quantum error correction. Nature, 432(7017):602-605, December 2004. A. R. Calderbank, E. M. Rains, P. W. Shor, and N. J. A. Sloane. Quantum Error Correction and Orthogonal Geometry. Physical Review Letters, 78(3):405-408, January 1997. Daniel Gottesman. Stabilizer Codes and Quantum Error Correction. arXiv:quant-ph/9705052, May 1997. H. Barnum and E. Knill. Reversing quantum dynamics with near-optimal quantum and classical fidelity. Journal of Mathematical Physics, 43(5):2097, 2002. Philipp Schindler, Thomas Monz, Daniel Nigg, Julio T. Barreiro, Esteban, A. Martinez, Matthias F. Brandl, Michael Chwalla, Markus Hennrich, and Rainer Blatt. Undoing a Quantum Measurement. Physical Review Letters, 110(7):070403, February 2013. D. Riste, S. Poletto, M.-Z. Huang, A. Bruno, V. Vesterinen, O.-P. Saira, and L. DiCarlo. Detecting bit-flip errors in a logical qubit using stabilizer measurements. Nature Communications, 6(1):6983, November 2015. Kristan Temme, Sergey Bravyi, and Jay M. Gambetta. Error Mitigation for Short-Depth Quantum Circuits. Physical Review Letters, 119(18):180509, November 2017. Ying Li and Simon C. Benjamin. Efficient Variational Quantum Simulator Incorporating Active Error Minimization. Physical Review X, 7(2):021050, June 2017. Alberto Peruzzo, Jarrod McClean, Peter Shadbolt, Man-Hong Yung, Xiao-Qi Zhou, Peter J. Love, Alan Aspuru-Guzik, and Jeremy L. O'Brien. A variational eigenvalue solver on a photonic quantum processor. Nature Communications, 5(1):4213, July 2014. Dave Wecker, Matthew B. Hastings, and Matthias Troyer. Progress towards practical quantum variational algorithms. Physical Review A, 92(4):042303, October 2015. Jarrod R McClean, Jonathan Romero, Ryan Babbush, and Alan Aspuru-Guzik. The theory of variational hybrid quantum-classical algorithms. New Journal of Physics, 18(2):023023, February 2016. David Fumo. Types of machine learning algorithms you should know [blog]. https://www.scientificstyleandformat.org/Tools/SSF-Citation-Quick-Guide.html. Accessed: 2021-11-22. Ashish Sukhadeve. Understanding neural networks: A beginner's guide [blog]. https://www.datasciencecentral.com/profiles/blogs/understanding-neural-network-a-beginner-s-guide. Accessed: 2021-11-22. Denny Novikov. Machine Learning: The Ultimate Beginners Guide to Efficiently Learn and Understand Machine Learning, Artificial Neural Network and Data Mining. Independently Published, 2019. G. I. Diaz, A. Fokoue-Nkoutche, G. Nannicini, and H. Samulowitz. An effective algorithm for hyperparameter optimization of neural networks. IBM Journal of Research and Development, 61(4/5):9:1-9:11, 2017. Kevin Gurney. Introduction to Neural Networks. Taylor & Francis, Oxford, 1997. OCLC: 892785047. Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. Deep learning. Nature, 521(7553):436{444, May 2015. Alexandra Nagy and Vincenzo Savona. Variational Quantum Monte Carlo Method with a Neural-Network Ansatz for Open Quantum Systems. Physical Review Letters, 122(25):250501, June 2019. Michael J. Hartmann and Giuseppe Carleo. Neural-Network Approach to Dissipative Quantum Many-Body Dynamics. Physical Review Letters, 122(25):250502, June 2019. Filippo Vicentini, Alberto Biella, Nicolas Regnault, and Cristiano Ciuti. Variational Neural-Network Ansatz for Steady States in Open Quantum Systems. Physical Review Letters, 122(25):250503, June 2019. Richard P Feynman. Simulating physics with computers. International Journal of Theoretical Physics, page 22, 1982. Roman Orus. A Practical Introduction to Tensor Networks: Matrix Product States and Projected Entangled Pair States. Annals of Physics, 349:117-158, October 2014. Peter D. Johnson, Jonathan Romero, Jonathan Olson, Yudong Cao, and Alan Aspuru-Guzik. QVECTOR: an algorithm for device-tailored quantum error correction, November 2017. arXiv:1711.02249 [quant-ph]. Austin G. Fowler, Matteo Mariantoni, John M. Martinis, and Andrew N. Cleland. Surface codes: Towards practical large-scale quantum computation. Physical Review A, 86(3):032324, September 2012. G. Vidal. Entanglement Renormalization. Physical Review Letters, 99(22):220405, November 2007. Geoffrey Hinton. Lecture Notes for CSC2515: Lecture 6, 2007. |
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Reconocimiento 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Viviescas Ramírez, Carlos Leonardo5b30aa603ec28676fe215dfba86e3d61Falla León, José Luisf9899ad4b60afef07309d718db6e74c4Caos y ComplejidadFalla, Jose [0000-0001-9918-2198]2024-06-05T20:53:10Z2024-06-05T20:53:10Z2024-04-05https://repositorio.unal.edu.co/handle/unal/86209Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, diagramasA sub-class of variational quantum algorithms (VQAs), the quantum convolutional neural network (QCNN), has emerged as an efficient quantum error correction (QEC) algorithm and full quantum error-correcting code. Through hybrid quantum-classical optimization of a QCNN architecture for a particular error model, it is possible to "train" a neural network to decrease the logical error rates for specific error models. Going into the noisy intermediate-scale quantum (NISQ) technology era, effective quantum error correction is necessary for accurate quantum computing with noisy qubits, and VQAs can bring about near-term, intermediate-scale, reliable quantum computing.Como una subclase de algoritmos cuánticos variacionales (VQAs), la red neuronal convolucional cuántica (QCNN), ha surgido como un algoritmo eficiente de corrección de errores cuánticos (QEC) y un código de corrección de errores cuánticos completo. A través de la optimización híbrida cuántico-clásica de una arquitectura QCNN para un modelo de error particular, es posible "entrenar" una red neuronal para reducir las tasas de error lógico para modelos de errores específicos. Entrando en la era de la tecnología cuántica de escala intermedia ruidosa (NISQ), la corrección de errores cuánticos efectiva es necesaria para la computación cuántica precisa con qubits ruidosos, y los VQAs pueden propiciar una computación cuántica confiable a corto plazo y a escala intermedia. (Texto tomado de la fuente).MaestríaMagíster en Ciencias - FísicaComputación cuántica52 páginasapplication/pdfengUniversidad Nacional de ColombiaBogotá - Ciencias - Maestría en Ciencias - FísicaFacultad de CienciasBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá530 - Física::539 - Física modernaQuantum error correctionQuantum convolutional neural networkQuantum computingQuantum algorithmsCorrección de error cuánticoRedes neuronales convolucionales cuánticasComputación cuánticaAlgoritmos cuánticosredes neuronales convolucionalescorrección de errores cuánticaquantum algorithmconvolutional neural networkquantum error correctionalgoritmo cuánticoQuantum error correction via quantum convolutional neural networksCorrección de error cuántico mediante redes neuronales convolucionales cuánticasTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMJohn Preskill. Quantum Computing in the NISQ era and beyond. Quantum, 2:79, August 2018. arXiv: 1801.00862.Jacob Biamonte, Peter Wittek, Nicola Pancotti, Patrick Rebentrost, Nathan Wiebe, and Seth Lloyd. Quantum machine learning. Nature, 549(7671):195{202, September 2017.Arute, et al. Quantum supremacy using a programmable superconducting processor. Nature, 574(7779):505-510, October 2019.Xiao Liang, Sheng Liu, Yan Li, and Yong-Sheng Zhang. Generation of Bose-Einstein Condensates' Ground State Through Machine Learning. arXiv:1712.10093 [quant-ph], December 2017.G. Vidal. Class of Quantum Many-Body States That Can Be Efficiently Simulated. Physical Review Letters, 101(11):110501, September 2008.Nobuyuki Yoshioka and Ryusuke Hamazaki. Constructing neural stationary states for open quantum many-body systems. Physical Review B, 99(21):214306, June 2019.Iris Cong, Soonwon Choi, and Mikhail D. Lukin. Quantum convolutional neural networks. Nature Physics, 15(12):1273-1278, December 2019.Raymond Laflamme, Cesar Miquel, Juan Pablo Paz, and Wojciech Hubert Zurek. Perfect Quantum Error Correcting Code. Physical Review Letters, 77(1):198-201, July 1996.Peter W. Shor. Scheme for reducing decoherence in quantum computer memory. Physical Review A, 52(4):R2493-R2496, October 1995.A. M. Steane. Error Correcting Codes in Quantum Theory. Physical Review Letters, 77(5):793-797, July 1996.A. R. Calderbank and Peter W. Shor. Good quantum error-correcting codes exist. Physical Review A, 54(2):1098-1105, August 1996.M. D. Reed, L. DiCarlo, S. E. Nigg, L. Sun, L. Frunzio, S. M. Girvin, and R. J. Schoelkopf. Realization of three-qubit quantum error correction with superconducting circuits. Nature, 482(7385):382-385, February 2012.P. Schindler, J. T. Barreiro, T. Monz, V. Nebendahl, D. Nigg, M. Chwalla, M. Hennrich, and R. Blatt. Experimental Repetitive Quantum Error Correction. Science, 332(6033):1059-1061, May 2011.Charles D. Hill, Eldad Peretz, Samuel J. Hile, Matthew G. House, Martin Fuechsle, Sven Rogge, Michelle Y. Simmons, and Lloyd C. L. Hollenberg. A surface code quantum computer in silicon. Science Advances, 1(9):e1500707, October 2015.Wright, et al. Benchmarking an 11-qubit quantum computer. Nature Communications, 10(1):5464, November 2019.Kosuke Fukui, Akihisa Tomita, and Atsushi Okamoto. Tracking quantum error correction. Physical Review A, 98(2):022326, August 2018.Kjaergaard et al. Superconducting Qubits: Current State of Play. arXiv:1905.13641, May 2019.Bharti et al. Noisy intermediate-scale quantum (NISQ) algorithms. Reviews of Modern Physics, 94(1):015004, February 2022. arXiv:2101.08448 [cond-mat, physics:quant-ph].F. Vatan, V. P. Roychowdhury, and M. P. Anantram. Spatially Correlated Qubit Errors and Burst-Correcting Quantum Codes. arXiv:quant-ph/9704019, April 1997.Chi-Kwong Li, Mikio Nakahara, Yiu-Tung Poon, Nung-Sing Sze, and Hiroyuki Tomita. Efficient Quantum Error Correction for Fully Correlated Noise. Physics Letters A, 375(37):3255-3258, August 2011.Emanuel Knill, Raymond Laflamme, and Lorenza Viola. Theory of Quantum Error Correction for General Noise. arXiv:quant-ph/9908066, August 1999.M. Cerezo, Andrew Arrasmith, Ryan Babbush, Simon C. Benjamin, Suguru Endo, Keisuke Fujii, Jarrod R. McClean, Kosuke Mitarai, Xiao Yuan, Lukasz Cincio, and Patrick J. Coles. Variational quantum algorithms. Nature Reviews Physics, 3(9):625{644, August 2021.Michael A. Nielsen and Isaac L. Chuang. Quantum Computation and Quantum Information. Cambridge University Press, 2000.Ramamurti Shankar. Principles of quantum mechanics. Plenum, New York, NY, 1980.Simon J. Devitt, Kae Nemoto, and William J. Munro. Quantum Error Correction for Beginners. Reports on Progress in Physics, 76(7):076001, July 2013.T. Brun, I. Devetak, and M.-H. Hsieh. Correcting Quantum Errors with Entanglement. Science, 314(5798):436{439, October 2006.P.G. Kwiat and D.F.V. James. Quantum optics -- entanglement and quantum information. In Robert D. Guenther, editor, Encyclopedia of Modern Optics, pages 256-264. Elsevier, Oxford, 2005.J. Chiaverini, D. Leibfried, T. Schaetz, M. D. Barrett, R. B. Blakestad, J. Britton, W. M. Itano, J. D. Jost, E. Knill, C. Langer, R. Ozeri, and D. J. Wineland. Realization of quantum error correction. Nature, 432(7017):602-605, December 2004.A. R. Calderbank, E. M. Rains, P. W. Shor, and N. J. A. Sloane. Quantum Error Correction and Orthogonal Geometry. Physical Review Letters, 78(3):405-408, January 1997.Daniel Gottesman. Stabilizer Codes and Quantum Error Correction. arXiv:quant-ph/9705052, May 1997.H. Barnum and E. Knill. Reversing quantum dynamics with near-optimal quantum and classical fidelity. Journal of Mathematical Physics, 43(5):2097, 2002.Philipp Schindler, Thomas Monz, Daniel Nigg, Julio T. Barreiro, Esteban, A. Martinez, Matthias F. Brandl, Michael Chwalla, Markus Hennrich, and Rainer Blatt. Undoing a Quantum Measurement. Physical Review Letters, 110(7):070403, February 2013.D. Riste, S. Poletto, M.-Z. Huang, A. Bruno, V. Vesterinen, O.-P. Saira, and L. DiCarlo. Detecting bit-flip errors in a logical qubit using stabilizer measurements. Nature Communications, 6(1):6983, November 2015.Kristan Temme, Sergey Bravyi, and Jay M. Gambetta. Error Mitigation for Short-Depth Quantum Circuits. Physical Review Letters, 119(18):180509, November 2017.Ying Li and Simon C. Benjamin. Efficient Variational Quantum Simulator Incorporating Active Error Minimization. Physical Review X, 7(2):021050, June 2017.Alberto Peruzzo, Jarrod McClean, Peter Shadbolt, Man-Hong Yung, Xiao-Qi Zhou, Peter J. Love, Alan Aspuru-Guzik, and Jeremy L. O'Brien. A variational eigenvalue solver on a photonic quantum processor. Nature Communications, 5(1):4213, July 2014.Dave Wecker, Matthew B. Hastings, and Matthias Troyer. Progress towards practical quantum variational algorithms. Physical Review A, 92(4):042303, October 2015.Jarrod R McClean, Jonathan Romero, Ryan Babbush, and Alan Aspuru-Guzik. The theory of variational hybrid quantum-classical algorithms. New Journal of Physics, 18(2):023023, February 2016.David Fumo. Types of machine learning algorithms you should know [blog]. https://www.scientificstyleandformat.org/Tools/SSF-Citation-Quick-Guide.html. Accessed: 2021-11-22.Ashish Sukhadeve. Understanding neural networks: A beginner's guide [blog]. https://www.datasciencecentral.com/profiles/blogs/understanding-neural-network-a-beginner-s-guide. Accessed: 2021-11-22.Denny Novikov. Machine Learning: The Ultimate Beginners Guide to Efficiently Learn and Understand Machine Learning, Artificial Neural Network and Data Mining. Independently Published, 2019.G. I. Diaz, A. Fokoue-Nkoutche, G. Nannicini, and H. Samulowitz. An effective algorithm for hyperparameter optimization of neural networks. IBM Journal of Research and Development, 61(4/5):9:1-9:11, 2017.Kevin Gurney. Introduction to Neural Networks. Taylor & Francis, Oxford, 1997. OCLC: 892785047.Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. Deep learning. Nature, 521(7553):436{444, May 2015.Alexandra Nagy and Vincenzo Savona. Variational Quantum Monte Carlo Method with a Neural-Network Ansatz for Open Quantum Systems. Physical Review Letters, 122(25):250501, June 2019.Michael J. Hartmann and Giuseppe Carleo. Neural-Network Approach to Dissipative Quantum Many-Body Dynamics. Physical Review Letters, 122(25):250502, June 2019.Filippo Vicentini, Alberto Biella, Nicolas Regnault, and Cristiano Ciuti. Variational Neural-Network Ansatz for Steady States in Open Quantum Systems. Physical Review Letters, 122(25):250503, June 2019.Richard P Feynman. Simulating physics with computers. International Journal of Theoretical Physics, page 22, 1982.Roman Orus. A Practical Introduction to Tensor Networks: Matrix Product States and Projected Entangled Pair States. Annals of Physics, 349:117-158, October 2014.Peter D. Johnson, Jonathan Romero, Jonathan Olson, Yudong Cao, and Alan Aspuru-Guzik. QVECTOR: an algorithm for device-tailored quantum error correction, November 2017. arXiv:1711.02249 [quant-ph].Austin G. Fowler, Matteo Mariantoni, John M. Martinis, and Andrew N. Cleland. Surface codes: Towards practical large-scale quantum computation. Physical Review A, 86(3):032324, September 2012.G. Vidal. Entanglement Renormalization. Physical Review Letters, 99(22):220405, November 2007.Geoffrey Hinton. 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